Evidence-Based Medicine in the EMR Era

Evidence-Based Medicine in the EMR Era

Jennifer Frankovich, M.D., Christopher A. Longhurst, M.D., and Scott M. Sutherland, M.D.

November 2, 2011 (10.1056/NEJMp1108726)

Many physicians take great pride in the practice of evidence-based medicine. Modern medical education emphasizes the value of the randomized, controlled trial, and we learn early on not to rely on anecdotal evidence. But the application of such superior evidence, however admirable the ambition, can be constrained by trials’ strict inclusion and exclusion criteria — or the complete absence of a relevant trial. For those of us practicing pediatric medicine, this reality is all too familiar. In such situations, we are used to relying on evidence at Levels III through V — expert opinion — or resorting to anecdotal evidence. What should we do, though, when there aren’t even meager data available and we don’t have a single anecdote on which to draw?

We recently found ourselves in such a situation as we admitted to our service a 13-year-old girl with systemic lupus erythematosus (SLE). Our patient‘s presentation was complicated by nephrotic-range proteinuria, antiphospholipid antibodies, and pancreatitis. Although anticoagulation is not standard practice for children with SLE even when they’re critically ill, these additional factors put our patient at potential risk for thrombosis, and we considered anticoagulation. However, we were unable to find studies pertaining to anticoagulation in our patient’s situation and were therefore reluctant to pursue that course, given the risk of bleeding. A survey of our pediatric rheumatology colleagues — a review of our collective Level V evidence, so to speak — was equally fruitless and failed to produce a consensus.

Without clear evidence to guide us and needing to make a decision swiftly, we turned to a new approach, using the data captured in our institution’s electronic medical record (EMR) and an innovative research data warehouse. The platform, called the Stanford Translational Research Integrated Database Environment (STRIDE), acquires and stores all patient data contained in the EMR at our hospital and provides immediate advanced text searching capability.1 Through STRIDE, we could rapidly review data on an SLE cohort that included pediatric patients with SLE cared for by clinicians in our division between October 2004 and July 2009. This “electronic cohort” was originally created for use in studying complications associated with pediatric SLE and exists under a protocol approved by our institutional review board.

Of the 98 patients in our pediatric lupus cohort, 10 patients developed thrombosis, documented in the EMR, while they were acutely ill. The prevalence was higher among patients who had persistent nephrotic-range proteinuria and pancreatitis (see table

Results of Electronic Search of Patient Medical Records (for a Cohort of 98 Pediatric Patients with Lupus) Focused on Risk Factors for Thrombosis Relevant to Our 13-Year-Old Patient with Systemic Lupus Erythematosus.). As compared with our patients with lupus who did not have these risk factors, the risk of thrombosis was 14.7 (95% confidence interval [CI], 3.3 to 96) among patients with persistent nephrosis and 11.8 (95% CI, 3.8 to 27) among those with pancreatitis. This automated cohort review was conducted in less than 4 hours by a single clinician. On the basis of this real-time, informatics-enabled data analysis, we made the decision to give our patient anticoagulants within 24 hours after admission.

Our case is but one example of a situation in which the existing literature is insufficient to guide the clinical care of a patient. But it illustrates a novel process that is likely to become much more standard with the widespread adoption of EMRs and more sophisticated informatics tools. Although many other groups have highlighted the secondary use of EMR data for clinical research,2,3 we have now seen how the same approach can be used to guide real-time clinical decisions. The rapid electronic chart review and analysis were not only feasible, but also more helpful and accurate than physician recollection and pooled colleague opinion. Such real-time availability of data to guide decision making has already transformed other industries,4 and the growing prevalence of EMRs along with the development of sophisticated tools for real-time analysis of deidentified data sets will no doubt advance the use of this data-driven approach to health care delivery. We look forward to a future in which health information systems help physicians learn from every patient at every visit and close the feedback loop for clinical decision making in real time.

Did we make the correct decision for our patient? Thrombosis did not develop, and the patient did not have any sequelae related to her anticoagulation; truthfully, though, we may never really know. We will, however, know that we made the decision on the basis of the best data available — acting, as the fictional detective Nero Wolfe would say, “in the light of experience as guided by intelligence.”5 In the practice of medicine, one can’t do better than that.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

This article (10.1056/NEJMp1108726) was published on November 2, 2011, at NEJM.org.

SOURCE INFORMATION

From the Division of Rheumatology (J.F.), the Division of Systems Medicine (C.A.L.), and the Division of Nephrology (S.M.S.), Department of Pediatrics, Stanford University School of Medicine, Palo Alto, CA.

REFERENCES

1

Lowe HJ, Ferris TA, Hernandez PM, Weber SC. STRIDE — an integrated standards-based translational research informatics platform. AMIA Annu Symp Proc 2009;14:391-395

2

Prokosch HU, Ganslandt T. Perspectives for medical informatics: reusing the electronic medical record for clinical research. Methods Inf Med 2009;48:38-44
Web of Science | Medline

3

Gunn PW, Hansen ML, Kaelber DC. Underdiagnosis of pediatric hypertension — an example of a new era of clinical research enabled by electronic medical records. AMIA Annu Symp Proc 2007;11:966-966

4

Halevy A, Norvig P, Pereira F. The Unreasonable Effectiveness of Data. IEEE Intelligent Systems, March/April 2009:8-12.

5

Stout R. In the best families. New York: Viking Press, 1950:71.

Why hospitals and physicians should get serious about patient-centered care

Image via Wikipedia

Source: Kevin MD

by STEVE WILKINS, MPH

Health care professionals are a cynical lot. We joke about the “fad or buzzword of the month,” usually some vague concept heralded by the powers on high. Our job is to promote the idea, knowing full well that the “next big thing” is probably right around the corner.

Take “patient-centered.” It sure feels like a buzz word. I suspect most hospital and physician executives, and their ad agency partners, would agree. But this time things are very different.

Here are reasons why hospitals and physicians should get serious about patient-centered care.

1. Patients are starting to discover that their doctors and hospitals are not nearly as good as they should be.

“Pay no attention to that man behind the curtain.” This line comes from the Wizard of Oz where little Toto rips the curtain back to show the great and powerful Oz is merely an old medicine show marketer from Kansas.

The analogy is a good one. Patients across the U.S., and other countries, are “doing a Toto” as they pull back the curtains on doctors and hospitals only to learn that they are often not getting the quality of care they expected.

People every day hear about some story that undermines their confidence in the health care system. Doctor Smith at XYZ hospital amputated the wrong limb again, Sally down the street was given the wrong medication, Mr. Patel’s opinion was ignored by his doctor, and so on. Unlike years past when such stories were infrequent and seemed to occur in some other city… stories now appear daily, occur in my city, and are instantly shared with people around the world via the internet.

2. Patient-centered care is the right thing to do, and it’s not that hard

I think most would agree that today’s health care system is still very provider-driven. That means that the care that is delivered, how it is delivered, who delivers it, and how outcomes are measured are all defined from the providers’ perspective (physicians, hospitals and payers ). Patient-centered care simply means looking at these same issues but from the perspective of individual patients. Notice nowhere here did I equate patient-centered care with smile training, customer service training or pianos in attractive lobbies. Patient-centered care means involving patients in the planning, delivery and evaluation of health care where it really counts in terms of outcomes, patient adherence, cost reduction and fewer re-hospitalizations.

Being patient-centered is like doing a market research study and then implementing the findings. Patient-centered care does not give absolute control to patients, it simply invites them into the party and gives them a place at the table. As providers, we don’t do a good job of listening to patients. We do an even worse job when it comes to acting on what patients tell us they want.

3. Patient-centered care will make any hospital or doctor stand out from the crowd.

Like a beautiful rainbow, patients and providers will recognize patient-centered care when they see it. Like rainbows, example of patient-centered care are few and far between, but here are some tell-tale signs:

Providers and patients know each others’ names
Patients’ opinions are actively sought, listened to and honored where possible (no, a suggestion box, patient satisfaction survey or mission statement constitute being patient-centered — if you think they are then you aren’t patient-centered)
Patients tell you that their doctors and other team members really listened to what they had to say (again if you think satisfaction surveys qualify you aren’t there yet)
Patients are treated as the most important member of their health care team and taught how they can best contribute to the team’s success
Providers feel that their patients are actively involved in their own care
You see a significant improvement in patient health status, adherence, engagement, level of utilization and patient/provider experience

If these aren’t good enough reasons to give patient-centered care another look at your organization then just think about this. Beginning in 2013, 30% of hospital Medicare reimbursement will be determined based upon patient experience. Eventually commercial payers will follow suit.

Steve Wilkins is a former hospital executive and consumer health behavior researcher who blogs atMind The Gap.

Top ten medical blogs

Image via Wikipedia

Source: Medical Island

Of course, the post deals only with english written blogs.

Blogging has of late become a regular past-time among various professionals and the medical profession is no exception. Medical Blogging requires serious consideration of the audience and the topics to be covered. Medical Professionals across the globe keep themselves updated through various electronic media and the internet has become the ultimate source of medical information for most of them.

Medical blogs make up a major chunk of the information available on the internet. They cover a range of topics from providing regular medical updates to the peculiar blog that talks about mundane medical terms and nuances. Medical Blogs are either started by individuals, run by some companies and organisations or an amalgamation of both. The vast number of medical blogs made the task of finding the “BEST” a serious business.

It is only true that no single blog could be the same for the entire audience, hence the ranking provided here is arbitrary based on my personal preferences. Without much ado, here is my list of the “TOP 10 MEDICAL BLOGS”

1. KevinMD Blog

2. Science Roll

3. GeriPal

4. Practical Bioethics

5. The Health Care Blog

6. Life in the Fast Lane

7. Creativity in Healthcare

8. Doc Gurley

9. Academic Life in Emergency Medicine

10. CasesBlog – Medical and Health Blog

I enjoyed reading many other medical blogs, but the ones mentioned here really caught my attention. I hope you too enjoy reading and following these blogs.

You will have suggestions to make about the selection or your own collection of favourite medical blogs. If so, post them in the comments section so that I can create another list of “The Best 100 Medical Blogs”.

Estimating treatment effects for individual patients based on the results of randomised clinical trials

BMJ 2011; 343:d5888 doi: 10.1136/bmj.d5888 (Published 3 October 2011)

Cite this as: BMJ 2011; 343:d5888

Research

Estimating treatment effects for individual patients based on the results of randomised clinical trials

OPEN ACCESS

Johannes A N Dorresteijn, epidemiologist and medical doctor1,

Frank L J Visseren, professor of vascular medicine, epidemiologist, and internist1,

Paul M Ridker, Eugene Braunwald professor of medicine, epidemiologist, and cardiologist2,

Annemarie M J Wassink, internist and postdoctoral researcher1,

Nina P Paynter, assistant professor of epidemiology2,

Ewout W Steyerberg, professor of medical decision making, and methodologist3,

Yolanda van der Graaf, professor of epidemiology and imaging4,

Nancy R Cook, associate professor of biostatistics and epidemiology2

Author Affiliations

¹Department of Vascular Medicine, University Medical Center Utrecht, PO Box 85500, 3508 GA Utrecht, Netherlands
²Division of Preventive Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
³Department of Public Health, Erasmus Medical Center, Rotterdam, Netherlands
⁴Julius Center for Health Sciences and Primary Care, Utrecht, Netherlands

Correspondence to: F L J Visseren F.L.J.Visseren@umcutrecht.nl

Accepted 12 August 2011

Abstract

Objectives To predict treatment effects for individual patients based on data from randomised trials, taking rosuvastatin treatment in the primary prevention of cardiovascular disease as an example, and to evaluate the net benefit of making treatment decisions for individual patients based on a predicted absolute treatment effect.

Setting As an example, data were used from the Justification for the Use of Statins in Prevention (JUPITER) trial, a randomised controlled trial evaluating the effect of rosuvastatin 20 mg daily versus placebo on the occurrence of cardiovascular events (myocardial infarction, stroke, arterial revascularisation, admission to hospital for unstable angina, or death from cardiovascular causes).

Population 17 802 healthy men and women who had low density lipoprotein cholesterol levels of less than 3.4 mmol/L and high sensitivity C reactive protein levels of 2.0 mg/L or more.

Methods Data from the Justification for the Use of Statins in Prevention trial were used to predict rosuvastatin treatment effect for individual patients based on existing risk scores (Framingham and Reynolds) and on a newly developed prediction model. We compared the net benefit of prediction based rosuvastatin treatment (selective treatment of patients whose predicted treatment effect exceeds a decision threshold) with the net benefit of treating either everyone or no one.

Results The median predicted 10 year absolute risk reduction for cardiovascular events was 4.4% (interquartile range 2.6-7.0%) based on the Framingham risk score, 4.2% (2.5-7.1%) based on the Reynolds score, and 3.9% (2.5-6.1%) based on the newly developed model (optimal fit model). Prediction based treatment was associated with more net benefit than treating everyone or no one, provided that the decision threshold was between 2% and 7%, and thus that the number willing to treat (NWT) to prevent one cardiovascular event over 10 years was between 15 and 50.

Conclusions Data from randomised trials can be used to predict treatment effect in terms of absolute risk reduction for individual patients, based on a newly developed model or, if available, existing risk scores. The value of such prediction of treatment effect for medical decision making is conditional on the NWT to prevent one outcome event.

Trial registration number Clinicaltrials.gov NCT00239681.

The New Language of Medicine

Pamela Hartzband, M.D., and Jerome Groopman, M.D.

N Engl J Med 2011; 365:1372-1373October 13, 2011

During our first year of medical school, we spent countless hours learning new words, memorizing vocabulary as if we were studying a foreign language. We discovered that some words that sounded foreign actually represented the familiar: rubeola was measles, pruritus meant itching. Now, we find ourselves learning a new language of medicine filled with words that seem familiar yet feel foreign. Patients are no longer patients, but rather “customers” or “consumers.”1 Doctors and nurses have been transmuted into “providers.” These descriptors have been widely adopted in the media, medical journals, and even on clinical rounds. Yet the terms are not synonymous. The word “patient” comes from patiens, meaning suffering or bearing an affliction. Doctor is derived from docere, meaning to teach, and nurse from nutrire, to nurture. These terms have been used for more than three centuries.

What precipitated the increasing usage of this new vocabulary in medicine? We are in the midst of an economic crisis, and efforts to reform the health care system have centered on controlling spiraling costs. To that end, many economists and policy planners have proposed that patient care should be industrialized and standardized.2 Hospitals and clinics should run like modern factories, and archaic terms such as doctor, nurse, and patient must therefore be replaced with terminology that fits this new order.

The words we use to explain our roles are powerful. They set expectations and shape behavior. This change in the language of medicine has important and deleterious consequences. The relationships between doctors, nurses, or any other medical professionals and the patients they care for are now cast primarily in terms of a commercial transaction. The consumer or customer is the buyer, and the provider is the vendor or seller. To be sure, there is a financial aspect to clinical care. But that is only a small part of a much larger whole, and to people who are sick, it’s the least important part. The words “consumer” and “provider” are reductionist; they ignore the essential psychological, spiritual, and humanistic dimensions of the relationship — the aspects that traditionally made medicine a “calling,” in which altruism overshadowed personal gain. Furthermore, the term “provider” is deliberately and strikingly generic, designating no specific role or type or level of expertise. Each medical professional — doctor, nurse, physical therapist, social worker, and more — has specialized training and skills that are not recognized by the all-purpose term “provider,” which carries no resonance of professionalism. There is no hint of the role of doctor as teacher with special knowledge to help the patient understand the reasons for his or her malady and the possible ways of remedying it, no honoring of the work of the nurse as a nurturer with unique expertise whose close care is essential to healing. Rather, the generic term “provider” suggests that doctors and nurses and all other medical professionals are interchangeable. “Provider” also signals that care is fundamentally a prepackaged commodity on a shelf that is “provided” to the “consumer,” rather than something personalized and dynamic, crafted by skilled professionals and tailored to the individual patient.

Business is geared toward the bottom line: making money. A customer or consumer is guided by “caveat emptor” — “let the buyer beware” — an adversarial injunction and hardly a sentiment that fosters the atmosphere of trust so central to the relationship between doctor or nurse and patient. Reducing medicine to economics makes a mockery of the bond between the healer and the sick. For centuries, doctors who were mercenary were publicly and appropriately castigated, the subjects of caustic characterization in plays by Moliere and stories by Turgenev. Such doctors betrayed their calling. Should we now be celebrating the doctor whose practice, like a successful business, maximizes profits from “customers”?

Beyond introducing new words, the movement toward industrializing and standardizing all of medicine (rather than just safety and emergency protocols) has caused certain terms that were critical to our medical education to all but disappear. “Clinical judgment,” for instance, is a phrase that has fallen into disgrace, replaced by “evidence-based practice,” the practice of medicine based on scientific data. But evidence is not new; throughout our medical education beginning more than three decades ago, we regularly examined the scientific evidence for our clinical practices. On rounds or in clinical conferences, doctors debated the design and results of numerous research studies. But the exercise of clinical judgment, which permitted assessment of those data and the application of study results to an individual patient, was seen as the acme of professional practice. Now some prominent health policy planners and even physicians contend that clinical care should essentially be a matter of following operating manuals containing preset guidelines, like factory blueprints, written by experts.2 These guidelines for care are touted as strictly scientific and objective. In contrast, clinical judgment is cast as subjective, unreliable, and unscientific. But there is a fundamental fallacy in this conception. Whereas data per se may be objective, their application to clinical care by the experts who formulate guidelines is not. This truth, that evidence-based practice codified in clinical guidelines has an inescapable subjective core, is highlighted by the fact that working with the same scientific data, different groups of experts write different guidelines for conditions as common as hypertension and elevated cholesterol levels3 or for the use of screening tests for prostate and breast cancers.4 The specified cutoffs for treatment or no treatment, testing or no testing, the weighing of risk versus benefit — all necessarily reflect the values and preferences of the experts who write the recommendations. And these values and preferences are subjective, not scientific.5

What impact will this new vocabulary have on the next generation of doctors and nurses? Recasting their roles as those of providers who merely implement prefabricated practices diminishes their professionalism. Reconfiguring medicine in economic and industrial terms is unlikely to attract creative and independent thinkers with not only expertise in science and biology but also an authentic focus on humanism and caring.

When we ourselves are ill, we want someone to care about us as people, not as paying customers, and to individualize our treatment according to our values. Despite the lip service paid to “patient-centered care” by the forces promulgating the new language of medicine, their discourse shifts the focus from the good of the individual to the exigencies of the system and its costs. Marketplace and industrial terms may be useful to economists, but this vocabulary should not redefine our profession. “Customer,” “consumer,” and “provider” are words that do not belong in teaching rounds and the clinic. We believe doctors, nurses, and others engaged in care should eschew the use of such terms that demean patient and professional alike and dangerously neglect the essence of medicine.

Disclosure forms provided by the authors are available with the full text of this article at NEJM.org.

SOURCE INFORMATION

From Beth Israel Deaconess Medical Center and Harvard Medical School — both in Boston.

Can We Trust Cardiovascular Practice Guidelines?

Out of compliance in cardiology when you read a clinical guide. From the list SBMFC sent by Juan Gérvas.

Conflicto de intereses en cardiologia 1 http://www.scribd.com/embeds/67948910/content?start_page=1&view_mode=list&access_key=key-1v67lnaw9jhqtk6z6n3r(function() { var scribd = document.createElement(“script”); scribd.type = “text/javascript”; scribd.async = true; scribd.src = “http://www.scribd.com/javascripts/embed_code/inject.js”; var s = document.getElementsByTagName(“script”)[0]; s.parentNode.insertBefore(scribd, s); })();

Conflicto de intereses en cardiologia 2 http://www.scribd.com/embeds/67949024/content?start_page=1&view_mode=list&access_key=key-28axg40wt4om4s8ae1mk(function() { var scribd = document.createElement(“script”); scribd.type = “text/javascript”; scribd.async = true; scribd.src = “http://www.scribd.com/javascripts/embed_code/inject.js”; var s = document.getElementsByTagName(“script”)[0]; s.parentNode.insertBefore(scribd, s); })();

I just want permission to be ill’: towards a sociology of medically unexplained symptoms

Image via Wikipedia

Soc Sci Med. 2006 Mar;62(5):1167-78. Epub 2005 Aug 30.

‘I just want permission to be ill’: towards a sociology of medically unexplained symptoms.

Nettleton S.

Source

University of York, York, UK. sjn2@york.ac.uk

Abstract

A significant proportion of symptoms are medically unexplained. People experience illness but no pathological basis for the symptoms can be discerned by the medical profession. Living without a clinical diagnosis or medical explanation has consequences for such patients. This paper reports on a small qualitative interview-based study of 18 neurology outpatients in England who live with such medically unexplained symptoms (MUS). The findings broadly concur with those identified in the related literatures on medically unexplained syndromes and unexplained pain: the difficulties of living with uncertainty; dealing with legitimacy; and a resistance to psychological explanations of their suffering. From a thematic analysis of the interview data we identify and elaborate on three related issues, which we refer to as: ‘morality’; ‘chaos’; and ‘ambivalence’. Although this article presents empirical data its aim is primarily conceptual; it integrates the findings of the empirical analysis with the existing literature in order to try to make some sociological sense of the emergent themes by drawing on sociological and cultural analyses of risk and the body. We draw on Bauman‘s concept of ambivalence to suggest that the very processes associated with more precise ‘problem solving’ and ‘classification’ do, in fact, generate even more uncertainty and anxiety. On the one hand, we seek closure and certainty and yet this leaves no means of living with uncertainty. Indeed, society does not readily grant permission to be ill in the absence of disease. We conclude by suggesting that an appreciation of the experience of such embodied doubt articulated by people who live with MUS may have a more general applicability to the analysis of social life under conditions of late modernity.

PMID:: 16135395; [PubMed – indexed for MEDLINE]

Investigating over-the-counter oral analgesics

There is good evidence supporting the efficacy of standard doses of aspirin, paracetamol, ibuprofen, naproxen, and diclofenac, all of which are available as over-the-counter (OTC) medicines in some part of the world. There is no good evidence for most branded combination products, though it is likely that additional analgesic effect is produced by codeine. Combinations of ibuprofen and paracetamol appear to be particularly effective.

Background

A wide variety of over-the-counter (OTC) analgesics are available to buy, but the amount of high quality information about these treatments is limited. We set out to find evidence for the efficacy of a range of OTC analgesics, available in various parts of the world, in standard acute pain trials. Specifically we were looking for single dose data from 4-6 hour trials in post-operative pain models, and reporting standard outcomes.

Clinical trials measuring the efficacy of analgesics in acute pain have been standardised over many years. Trials have to be randomised and double blind. Typically, in the first few hours or days after an operation, patients develop pain that is moderate to severe in intensity, and will then be given the test analgesic or placebo. Pain is measured using standard pain intensity scales immediately before the intervention, and then using pain intensity and pain relief scales over the following 4 to 6 hours for shorter acting drugs. Pain relief of half the maximum possible pain relief or better (at least 50% pain relief) is typically regarded as a clinically useful outcome. For patients given rescue medication it is usual for no additional pain measurements to be made, and for all subsequent measures to be recorded as initial pain intensity or baseline (zero) pain relief (baseline observation carried forward). This process ensures that analgesia from the rescue medication is not wrongly ascribed to the test intervention. In some trials the last observation is carried forward, which gives an inflated response for the test intervention compared to placebo, but the effect has been shown to be negligible over four to six hours.

Single dose trials in acute pain are commonly short in duration, rarely lasting longer than 12 hours, allowing no reliable conclusions to be drawn about safety. To show that the analgesic is working it is necessary to use placebo. There are clear ethical considerations in doing this. These ethical considerations are answered by using acute pain situations where the pain is expected to go away, and by providing additional analgesia, commonly called rescue analgesia, if the pain has not diminished after about an hour. This is reasonable, because not all participants given an analgesic will have significant pain relief. Approximately 18% of participants given placebo will have significant pain relief, and up to 50% may have inadequate analgesia with active medicines.

Systematic review and methods

For references to methods used, refer to Moore et al., Bandolier’s Little Book of Pain, Oxford University Press, 2006.

We searched PubMed, Cochrane Central Library, and our own in-house databases in pain research for any double-blind, randomised controlled trials reporting pain relief, pain intensity, or patient global evaluation of efficacy as outcomes over 4-6 hours for single dose analgesic versus placebo. The search terms used included both trade names and generic names of the individual analgesic constituents, including combinations where appropriate. It is not likely that all OTC analgesics have been included, since sources for OTC analgesic names and availability are not easy to come by, and may change from time to time. OTC analgesic combinations, in particular, may change. The approach, therefore, was to work with combinations of drugs and doses of the combinations that appeared to be current in 2009.

From these trials we extracted outcome data, including pain relief measured as a TOTPAR (total pain relief) at 4 or 6 hours, and pain intensity measured as a SPID (summed pain intensity difference) at 4 or 6 hours. Mean TOTPAR or SPID values, for both the active analgesic and placebo, were then converted to %maxTOTPAR or %maxSPID by division into the calculated maximum value. The proportion of participants in each treatment group who achieved at least 50%maxTOTPAR was calculated using verified equations, and these proportions converted into the number of participants achieving at least 50%maxTOTPAR by multiplying by the total number of participants in the treatment group. Information on the number of participants with at least 50%maxTOTPAR for active treatment and placebo was then used to calculate relative benefit (RB) and number-needed-to-treat-to-benefit (NNT).

Results

One hundred and twenty five RCTs were retrieved that matched the search criteria. After closer scrutiny, six head-to-head comparative trials were excluded due to lack of a placebo control, and two trials were excluded due to lack of analysable data. The remaining one hundred and seventeen trials were randomised, double blind and placebo controlled and were included in the efficacy analysis. The studies involved a mixture of dental pain and episiotomy pain.

The overall standard and quantity of data available was poor, particularly for studies specifically using the trade name over-the-counter analgesics. To compensate for this we have included data on the equivalent dose generic named analgesics and their combinations. For some of the test analgesics (Anadin Extra, Askit, Codis, Dispirin, Dispirin Extra, Panadeine 15, Paracodol, Paramol, Pentalgin H, Sedalgin-neo, Solpadeine Max) no useable data could be found. In many cases, particularly those combination analgesics including codeine, this was due to differences in the doses of the constituent analgesics used in the available trials as compared with the over-the-counter versions. In general, over-the-counter analgesics containing codeine tended to use significantly lower doses of codeine and higher doses of other constituents; presumably to minimise codeine-related side effects. Information on combinations of paracetamol and ibuprofen is included since these newer combinations are likely to appear as OTC analgesics in several parts of the world. Table 1 gives information about the included studies.

Table 1: Details of available data

Drug	Details of available data	References of included studies
Anadin Extra	We found no trials comparing Anadin Extra (or a generic combination analgesic containing paracetamol, aspirin and caffeine in similar doses) to placebo	N/A
Askit	We found no trials comparing Askit (or a generic combination analgesic containing aspirin, caffeine and aloxiprin in similar doses) to placebo	N/A
Aspirine	We found two trials: Forbes et al. 1990 and Rubin et al. 1984 comparing a generic combination of aspirin and caffeine (ASA 650mg/caffeine 65mg in Forbes et al. and ASA 800mg/caffeine 65mg in Rubin et al.) against placebo. Both trials were relatively small and used different pain types: Forbes et al. (n=141) in dental and Rubin et al. (n=230) in episiotomy. The results reflect this with Forbes et al. reporting the % of patients achieving 50% pain relief on the active treatment as 27% and on the placebo as 1%; while Rubin et al. report 86% on the active treatment and 48% on the placebo	Forbes JA. Pharmacotherapy. 1990; 10(6):387-93 Rubin A. J Int Med Res. 1984; 12(6):338-45
Aspro Clear	We found seven trials in a Cochrane review of single dose oral aspirin for acute pain (Edwards et al. 2000 – currently undergoing in-house update) comparing aspirin in any formulation (ASA 1000mg) against placebo	Edwards JE. Cochrane Database Syst Rev. 2000;(2):CD002067
Codis	We found no trials comparing Codis (or a generic combination analgesic containing aspirin and codeine in similar doses) to placebo	N/A
Cuprofen Plus	We found two trials: Cater et al. 1985 and Norman et al. 1985 comparing a generic combination of ibuprofen and caffeine (IBU 400mg/COD 30mg) against placebo. Both trials reported pain following episiotomy with similar results	Cater M. Clin Ther. 1985; 7(4):442-7 Norman SL. Clin Ther. 1985; 7(5):549-54
Disprin	We found no trials comparing Dispirin (or a generic formulation of aspirin in a similar dose) to placebo	N/A
Disprin Extra	We found no trials comparing Dispirin Extra (or a generic combination of aspirin and paracetamol in similar doses) to placebo	N/A
Feminax Ultra	We found five trials in an up-to-date Cochrane review of single dose oral naproxen for acute pain (Derry et al. 2009) comparing naproxen or naproxen sodium (NAPROX 500mg or NAPROX SODIUM 550mg) against placebo	Derry C. Cochrane Database Syst Rev. 2009 Jan 21;(1);CD004234
Mersyndol	We found one trial: Margarone et al. 1995 comparing Mersyndol against placebo. The trial reported pain following dental surgery	Margarone JE. Clin Pharmacol Ther. 1995 Oct; 58(4):453-8
Nurofen	We found 61 trials in an up-to-date Cochrane review of single dose oral ibuprofen for acute pain (Derry et al. 2009) comparing a generic formulation of ibuprofen (IBU 400mg) against placebo	Derry C. Cochrane Database Syst Rev. 2009 Jul 8;(3):CD001548
Panadeine 15	We found no trials comparing Panadeine 15 (or a generic combination of paracetamol and codeine in similar doses) to placebo	N/A
Panadol	We found 28 trials in an up-to-date Cochrane review of single dose oral paracetamol for acute pain (Toms et al. 2008) comparing a generic formulation of paracetamol (PARA 1000mg) against placebo	Toms L. Cochrane Database Syst Rev. 2008 Oct 8;(4):CD004602
Panadol Extra	We found one trial: Winter et al. 1983 comparing a generic combination of paracetamol and caffeine (PARA 1000mg/CAF 130mg) against placebo. The trial reported pain following dental surgery	Winter L Jr. Current Therapeutic Research. 1983 Jan; 33(1):115-122
Paracodol	We found no trials comparing Paracodol (or a generic combination of paracetamol and codeine in similar doses) to placebo	N/A
Paramol	We found no trials comparing Paramol (or a generic combination of paracetamol and dihydrocodeine tartrate in similar doses) to placebo	N/A
Pentalgin H	We found no trials comparing Pentalgin H (or a generic combination of naproxen, codeine, caffeine, dipyrone and phenobarbitol in similar doses) to placebo	N/A
Saridon	We found one trial: Kiersch et al. 2002 comparing Saridon against placebo. The trial reported pain following dental surgery	Kiersch TA. Curr Med Res Opin. 2002; 18(1):18-25
Sedalgin-neo	We found no trials comparing Sedalgin-neo (or a generic combination of paracetamol, caffeine, codeine, dipyrone and phenobarbitol in similar doses) to placebo	N/A
Solpadeine Max	We found no trials comparing Solpadeine Max (or a generic combination of paracetamol and codeine in similar doses) to placebo	N/A
Solpadeine Plus	We found one trial: Cooper et al. 1986 comparing a generic combination of paracetamol, codeine and caffeine (PARA 1000mg/COD 16mg/CAF 30mg) against placebo. The trial reported pain following dental surgery	Cooper SA. Anesth Prog. 1986 May-Jun; 33(3):139-42
Voltarol	We found four trials in an up-to-date Cochrane review of single dose oral diclofenac for acute pain (Derry et al. 2009) comparing all generic formulations of diclofenac (DICLO 25mg) against placebo	Derry P. Cochrane Database Syst Rev. 2009 Apr 15;(2):CD004768

Table 2 summarises data available for each of the analgesics along with its calculated relative benefit (RB) and number-needed-to-treat-to-benefit (NNT). Para = paracetamol, Asa – aspirin, Caf = caffeine, Cod = codeine, Naprox = naproxen, Diclo = diclofenac, Ibu = ibuprofen

Drug	Constituents	Number of Trials	Number of Patients	Percent with Active	Percent with Control	RB (95% CI)	NNT (95% CI)
Anadin Extra	Para400 + Asa600 + Caf90	0
Askit	Asa530 + Caf110 + Aloxiprin140	0
Aspirine	Asa650 + Caf65	2	371	65	28	2.3 (1.8 – 3.0)	2.7 (2.2 – 3.7)
		Forbes 1990	141	17	0	39.8 (2.4 – 648)	3.9 (2.7 – 6.7)
		Rubin 1984	230	86	48	1.8 (1.5 – 2.2)	2.6 (2.0 – 3.7)
Aspro Clear	Asa1000	7	679	43	16	2.6 (2.0 – 3.5)	3.7 (3.0 – 5.0)
Codis	Asa1000 + Cod base 16	0
Cuprofen Plus	Ibu400 + Cod base 20	2	167	55	31	1.8 (1.2 – 2.6)	4.1 (2.6 – 10.3)
Disprin	Asa900	0
Disprin Extra	Asa600 + Para400	0
		Margarone 1995	76	21	8	2.7 (0.8 – 9.3)	7.6
Feminax Ultra	Naprox500	9	784	52	15	3.4 (2.7 – 4.4)	2.7 (2.3 – 3.2)
		Winter 1983	81	48	22	2.2 (1.1 – 4.2)	3.9 (2.2 – 18.0)
Mersyndol	Para1000 + Cod base15 + Doxylamine succinate10	1	76	21	8	2.7 (0.8 – 9.3)	Not Calculated
Nurofen	Ibu400	61	6475	54	14	4.0 (3.6 – 4.4)	2.5 (2.4 – 2.6)
Panadeine 15	Para1000 + Cod base23	0
Panadol	Para1000	28	3232	46	18	2.5 (2.2 – 2.9)	3.6 (3.2 – 4.0)
		Cooper 1986	61	29	4	6.2 (0.9 – 45.0)	4.2 (2.5 – 14.2)
Panadol Extra	Para1000 + Caf130	1	81	48	22	2.2 (1.1 – 4.2)	3.9 (2.2 – 18.0)
Paracodol	Para1000 + Cod base13	0
Paramol	Para1000 + Dihydrocodeine tartarate15	0
Pentalgin H	Naprox100 + Cod base8 + Caf50 + Dipyrone300 + Phenobarbitol15	0
Saridon	Para500 + Caf100 + Propifenazone300	1	301	23	2	9.2 (1.3 – 64.5)	4.9 (3.6 – 7.4)
Sedalgin-neo	Para600 + Caf100 + Cod base20 + Dipyrone300 + Phenobarbitol30	0
		Norman 1985	74	53	29	1.8 (1.0 – 3.3)	4.2 (2.2 – 48.5)
		Cater 1985	93	57	32	1.8 (1.1 – 2.9)	4.1 (2.3 – 19.8)
Solpadeine Max	Para1000 + Cod base20	0
Solpadeine Plus	Para1000 + Caf60 + Cod base13	1	61	29	4	6.2 (0.9 – 45.0)	4.2 (2.5 – 14.2)
Voltarol	Diclo25	4	502	53	15	3.6 (2.6 – 5.0)	2.6 (2.2 – 3.3)
None	Ibu100 + Para 250	2	175	73	10	7.6 (4.2 -14)	1.6 (1.3 – 1.9)
None	Ibu200 + Para 500	2	280	74	10	7.7 (2.2 – 14	1.6 (1.4 – 1.8)
None	Ibu400 + Para 1000	2	320	75	10	7.9 (4.3 – 14)	1.5 (1.4 – 1.7)

Table 3 shows a sub-analysis of only those trials involving dental pain.

Drug	Constituents	Number of Trials	Number of Patients	Percent with Active	Percent with Control	RB (95% CI)	NNT (95% CI)
Anadin Extra	Para400 + Asa600 + Caf90	0
Askit	Asa530 + Caf110 + Aloxiprin140	0
Aspirine	Asa650 + Caf65	1	141	17	0	39.8 (2.4 – 648)	3.9 (2.7 – 6.7)
Aspro Clear	Asa1000	3	345	32	11	2.9 (1.8 – 4.8)	4.7 (3.4 – 7.6)
Codis	Asa1000 + Cod base 16	0
Cuprofen Plus	Ibu400 + Cod base 20	0
Disprin	Asa900	0
Disprin Extra	Asa600 + Para400	0
Feminax Ultra	Naprox500	5	402	62	7	8.9 (5.3 – 14.9)	1.8 (1.6 – 2.1)
Mersyndol	Para1000 + Cod base15 + Doxylamine succinate10	1	76	21	8	2.7 (0.8 – 9.3)	Not Calculated
Nurofen	Ibu400	49	5428	55	12	4.7 (4.2 – 5.2)	2.3 (2.2 – 2.4)
Panadeine 15	Para1000 + Cod base23	0
Panadol	Para1000	18	2171	40	9	4.4 (3.5 – 5.5)	3.3 (3.0 – 3.7)
Panadol Extra	Para1000 + Caf130	1	81	48	22	2.2 (1.1 – 4.2)	3.9 (2.2 – 18.0)
Paracodol	Para1000 + Cod base13	0
Paramol	Para1000 + Dihydrocodeine tartarate15	0
Pentalgin H	Naprox100 + Cod base8 + Caf50 + Dipyrone300 + Phenobarbitol15	0
Saridon	Para500 + Caf100 + Propifenazone300	1	301	23	2	9.2 (1.3 – 64.5)	4.9 (3.6 – 7.4)
Sedalgin-neo	Para600 + Caf100 + Cod base20 + Dipyrone300 + Phenobarbitol30	0
Solpadeine Max	Para1000 + Cod base20	0
Solpadeine Plus	Para1000 + Caf60 + Cod base13	1	61	29	4	6.2 (0.9 – 45.0)	4.2 (2.5 – 14.2)
Voltarol	Diclo25	3	398	51	11	4.6 (3.1 – 7.1)	2.5 (2.1 – 3.2)
None	Ibu100 + Para 250	2	175	73	10	7.6 (4.2 -14)	1.6 (1.3 – 1.9)
None	Ibu200 + Para 500	2	280	74	10	7.7 (2.2 – 14	1.6 (1.4 – 1.8)
None	Ibu400 + Para 1000	2	320	75	10	7.9 (4.3 – 14)	1.5 (1.4 – 1.7)

To summarise the findings of our investigation we produced comparative figures (Figures 1 and 2 for all data and just dental studies, respectively) showing the NNTs and their 95% confidence intervals for each analgesic where calculable.

Figure 1: NNTs for all available data

Figure 2: NNTs for dental studies only

Comment

There are two main issues when looking at the evidence of acute pain efficacy of OTC analgesics. The first is the dearth of evidence in the public domain for some of these products. The second is what we are able to make of what evidence we have.

Dearth of evidence

Most of the OTC analgesics, including combination analgesics, were developed decades ago, as long ago as the 1950s, in times when trials were performed for registration purposes. Publication was infrequent. A good example is a review of 30 trials involving about 10,000 patients examining the analgesic efficacy of caffeine in combination with analgesics published in JAMA in 1984 [1]. Most of the data was unpublished then, and has remained unpublished subsequently. We know more about OTC drugs like paracetamol and ibuprofen from trials in which they have been used as active comparators than trials in which they themselves have been tested [2].

The dearth of evidence is not, therefore, surprising. It is, however, frustrating. For several OTC analgesics we have no reliable data, and for others the data available are inadequate – leading to very wide confidence intervals in Figures 1 and 2. This is a shame, because OTC analgesics, properly used, are effective for many people.

It is also the case that the case for analgesic combinations can be developed using evidence from closely related studies. A case in point is the combination of paracetamol and codeine, where relatively small amounts of information for some dose combinations is bolstered with evidence from other dose combinations [3].

What can we make of the evidence we have

The best evidence we have is from ibuprofen 400 mg (Nurofen), paracetamol 10000 mg (Panadol), naproxen 500 mg (Feminax Ultra), diclofenac 25 mg (Voltarol), aspirin 1000 mg (Aspro), and from ibuprofen +paracetamol in combination, though the evidence is likely not to have come from testing of any particular product. All of these analgesics have usefully low NNTs in the range of about 2-4, or somewhat lower for ibuprofen/paracetamol combination.

The evidence for combination analgesics is less clear, with predominantly no trials, or too few trials and patients available to make any judgement. This is a shame, because there is evidence elsewhere [3, for example] that combinations of analgesics can produce very good results, as seen here with combinations of ibuprofen and paracetamol.

Consumers can make up their own minds whether the expense of branded analgesics is worth it compared to the often much lower cost of unbranded – though that is a UK view, and certainly analgesics like paracetamol and ibuprofen are available in quantity and at low cost in the USA.

References

Laska EM, Sunshine A, Mueller F, Elvers WB, Siegel C, Rubin A. Caffeine as an analgesic adjuvant. JAMA 1984 251:1711-8.
Barden J, Derry S, McQuay HJ, Moore RA. Bias from industry trial funding? A framework, a suggested approach, and a negative result. Pain 2006 121:207-18.
Smith LA, Moore RA, McQuay HJ, Gavaghan D. Using evidence from different sources: an example using paracetamol 1000 mg plus codeine 60 mg. BMC Med Res Methodol. 2001 Jan 10;1:1.

Knowledge Library

Tratamientos psicológicos que dañan

Image via Wikipedia

O de cuando “primum non nocere” no sólo es aplicable a los aspectos biológicos de las consultas.

Lilienfeld Psychological Treatments That Cause Harm http://www.scribd.com/embeds/60561644/content?start_page=1&view_mode=list&access_key=key-2otp3hakkrx7gl5ub7w3(function() { var scribd = document.createElement(“script”); scribd.type = “text/javascript”; scribd.async = true; scribd.src = “http://www.scribd.com/javascripts/embed_code/inject.js”; var s = document.getElementsByTagName(“script”)[0]; s.parentNode.insertBefore(scribd, s); })();

Designing a Smarter Patient

Source: Wall Street Journal – Via Juan Gérvas (list of Seminario Internacional de Atención Primaria: Prevención Cuaternaria) . Barcelona. Octubre 2011

By JEROME GROOPMAN and PAMELA HARTZBAND

Edel Rodriguez

When given clearer information, patients weigh risks and benefits differently from their doctors.

“I’m comfortable with that,” or “No, it wouldn’t be comfortable for me.”

That’s what our patients often tell us when faced with a choice about taking a medication or undergoing a procedure. And the discussion usually stops there.

But what makes someone comfortable or uncomfortable with one treatment or another, or with no treatment at all? Where do these views come from? And how can patients make better decisions?

For answers, we spent four years interviewing scores of patients of different ages. We found that a host of powerful and often hidden influences, inside and outside the patient’s mind, can sway thinking and distort judgment. We also discovered that, by unmasking those influences, it is possible for patients to gain greater confidence and control over their medical decisions.

Consider the case of Susan Powell (not her real name), a nurse’s assistant now in her 50s. She had been healthy all her life, but when she turned 45, she decided to see a primary-care doctor. Susan ate healthy foods and was physically active, but she was a bit overweight, and her blood tests showed that she had high cholesterol. Her doctor prescribed a statin drug and asked her to come back in a month.

Statins are among the most commonly prescribed medications in the world. In the U.S. alone, more than 25 million people take the drugs to lower their cholesterol, which is a key factor leading to heart attack and stroke.

Soon after seeing her doctor, Susan spoke with an acquaintance at church who had developed muscle pain after starting to take a statin. Susan also thought of her father, who had high cholesterol and never took any medication for it. “People take too many pills,” he often told his children. He lived a long, full and active life.

Susan decided not to take the statin.

Many people decline treatment because they know someone who suffered from side effects or someone who lived well into old age without treatment. Stories deeply affect all of us, and they can make real the risks and benefits that might otherwise seem abstract—but they can also distort our vision by making the rare appear routine.

Statistics can help to put lessons drawn from stories into a larger context, letting us make a more considered choice than we possibly could by using narratives alone.

At Susan’s follow-up appointment a month later, her doctor told her that “by taking a statin pill, you’ll reduce your risk of a heart attack over the next 10 years by as much as 30%.” The risk of side effects, she continued, was very small, and the benefits far outweighed the risk. Susan promised to give it serious thought.

She continued to search for information, reading everything she could about cholesterol. What caught her eye was a government-sponsored link to a “10-Year Heart Attack Risk Calculator.”

She entered her age, total cholesterol number of 240, and “good” cholesterol (HDL) of 37. She was not a smoker, her blood pressure was fine, and she was on no medications. The result: “Risk Score: 1%: Means 1 of 100 people with this level of risk will have a heart attack in the next 10 years.”

This means that 99 of 100 people like me won’t have a heart attack in the next 10 years, Susan told herself. She started to feel much better. She had found a key number in health literacy: her risk for disease without treatment.

Without treatment, Susan’s risk for a heart attack was 1 in 100. If 1 in 100 women has a heart attack, that means 2 in 200 do, or 3 in 300. The statin treatment reduces risk by 30%, or about one-third.

Let’s apply that benefit to a group of 300 women like Susan, where three would have a heart attack without taking statins. If we treat them all, we would prevent one heart attack—because we protect one-third of those three. The other two women would still have a heart attack despite taking the medicine. The remaining 297 would not have had a heart attack even without the medication, so they wouldn’t benefit from taking it.

This statistic comes as a surprise to many people. When you hear that a statin lowers Susan’s risk by 30%, it sounds as if she is at a 100% risk of suffering a heart attack if she doesn’t take the medication.

Another component of health literacy is understanding the risks of a therapy. Statins cause muscle pain in 1% to 10% of people who take them. However, if we “flip” the frame, the number without any side effects is 90 to 99 out of 100, a much more reassuring statistic.

Advertisements for drugs may include statistics, but fundamentally these ads are designed to communicate a compelling tale. Over the weeks that followed her appointment with her physician, Susan paid particular attention to ads for statins. Once she started looking for them, they seemed to be everywhere.

In 2007, a team of researchers from the UCLA Medical Center and other medical centers studied prescription drug ads broadcast on national networks. They found that the average American TV viewer sees over 1,000 prescription drug ads in the space of a year. That’s 16 hours all told—much more time than the average person spends with his or her primary-care physician.

The study concluded that the large majority of TV ads fail to fulfill an educational purpose. But they clearly work, at least from the point of view of sales: Every $1,000 spent on advertising translated into 24 new prescriptions, according to an analysis by the House Energy and Commerce Committee.

Another illuminating study, conducted by researchers at the Dartmouth Institute for Health Policy and Clinical Practice, examined the impact of printed drug ads on patient preferences. One group was given actual ads. A second group received the same ads, except that the brief summary at the end of the text was replaced by a “drug-facts box.” The box presented information in a clear, accessible fashion, similar to the way we recalculated the benefits and risks of a statin for Susan.

The results of the Dartmouth research are impressive. Nearly two-thirds of the group that saw the original ads overestimated the benefits of the treatment. They believed it was 10 times more effective than it actually was. But nearly three-quarters of the participants who saw the information in the drug-facts box correctly assessed the actual benefits of the treatment.

Even more striking was another finding. When people were given readily understandable information about the statin’s actual benefit in preventing future heart disease, nearly twice as many said they wouldn’t take the drug in light of its side effects. When given clearer information, the patients weighed the risks and benefits differently from their doctors and were less likely to take the medication.

Susan Powell’s decision was not simple. More than five years later, her doctor continues to encourage her to take the drug, and she continues to say no—but now, at least, she can more fully explain why.

—Dr. Groopman and Dr. Hartzband are on the faculty of Harvard Medical School and the staff of Beth Israel Deaconess Medical Center, both in Boston. This essay is adapted from their new book, “Your Medical Mind: How To Decide What Is Right for You.

A cure for the disease of hate

Image via Wikipedia

BMJ 2011; 343:d5715 doi: 10.1136/bmj.d5715 (Published 14 September 2011)

Cite this as: BMJ 2011; 343:d5715

Views & Reviews

Review of the Week

A cure for the disease of hate

Iain McClure, consultant child and adolescent psychiatrist, Royal Hospital for Sick Children, Edinburgh

imcclure@nhs.net

A Gazan doctor working in Israel describes his life and extraordinary tragedy, with a determination that good must come from bad. Iain McClure recommends his book to all doctors

On 16 January 2009 three Palestinian sisters were killed when an Israeli tank fired two shells into their bedroom. They were the daughters of Dr Izzeldin Abuelaish, a Palestinian gynaecologist, who, uniquely for a Gazan doctor, held a consultant post in an Israeli hospital. Abuelaish’s book, I Shall Not Hate, is an account of his life up to this momentous event and movingly explains his remarkable reaction. In essence, Abuelaish, who likens hate to disease and communication to cure, has drawn on his medical experience to seek a new approach to the resolution of apparently insoluble conflict.

For the three weeks prior to January 2009 the Israeli Defense Forces had been pursuing an incursion into the Gaza Strip to eradicate Quassam rocket attacks into Israel. The Israeli government had prevented Israeli or foreign journalists broadcasting from within Gaza during the operation. However, Abuelaish, a well known public figure in Gaza, had …

[Full text of this article]

Natural Rotavirus Infection in an Indian Birth Cohort: How Much Protection Does It Give?

By Jennifer Zeis

Rotaviruses cause more than half a million deaths each year, and approximately 23 percent of these deaths occur in India. There are two vaccines available for use to prevent rotavirus gastroenteritis in infants and children: RotaTeq and Rotarix. But RotaTeq was introduced in India only earlier this year, and access to it is limited.

Oral vaccines are notorious for having a low efficacy rate in India. The oral trivalent polio vaccine, for example, has not provided long term protection there despite a high effectiveness in developed countries. Seroconversion interference by other enteroviruses is one known culprit, an issue that is compounded in India by high population density and low sanitation.

Earlier research has shown that two infections of rotavirus confer natural protection to children in Mexico against subsequent infections. Does this natural protection occur in India, where rotavirus has the highest mortality in the world?

To find out, Beryl Gladstone et al. recruited 452 children from Chinnallapuram, Ramanaickanpalayam, and Kasba, three contiguous slums in Vellore, India, between March 2002 and August 2003. Field workers visited each child’s house twice a week and obtained a stool sample every two weeks. During these visits the mothers were asked about their children’s health since the last visit. Descriptions of symptoms were recorded, as well as descriptions of illness among other members of the household. All told, researchers made 121,005 home visits, they report in their study published in NEJM this week.

A blood sample was also collected at birth or during the first week of life and at least every 6 months for the 3 years of follow-up. These samples were analyzed for antirotavirus IgA and IgG antibodies. A diagnosis of rotavirus was made if the IgG antibody level rose by a factor of 4 or if IgA increased by a factor of 3.

Primary analyses were restricted to the 373 children who completed the full three years of follow-up. All surveillance and diarrheal stool samples – 26,902 in total, 91.8% of the scheduled collections – were screened for rotavirus using enzyme linked immunosorbent assay (ELISA).

If a test came back positive for rotavirus, it was screened again and then the strain was genotyped. Researchers genotyped 472 rotavirus strains. Infection with the most common type – G1P[8], which surfaced in 15.9% of infections – did not decrease the risk of overall or homotypic rotavirus infection or diarrhea.

These data provide a mixed result. Among the previously-reported Mexican cohort, three rotavirus infections resulted in complete protection against severe rotavirus, but among this Indian cohort, three infections provided 67% protection against rotavirus infection and 79% protection against moderate or severe diarrhea.

Researchers also found that reinfection rates were “much higher” than expected: 30% of all identified infections were primary, as compared with 52% and 81% in Mexico and Guinea-Bissau, respectively. Researchers found that rotavirus affected 53% of children by 6 months of age, a higher level at the same age than Mexico (34%) and Guinea-Bissau (26%).

The researchers conclude that early infection and frequent reinfection in this locale resulted in lower protection than has been reported elsewhere. They also comment that their study found no evidence of homotypic protection, even though the general belief is that protection from infections is initially homotypic and then broadens to heterotypic.

Lindsey Baden, MD, Deputy Editor at NEJM, notes “The findings in this report demonstrate the complex dynamics of rotaviruses in different parts of the world. Pubic health and vaccine deployment strategies will have to incorporate improvements in our understanding of rotavirus biology.”

While the study by Gladstone et al. does not provide a simple answer to the future of rotavirus vaccination in India, it supplies data that may inform vaccination strategies in this and other resource-poor settings.

“Taken together,” the authors write, “these data indicate that rotavirus-vaccination strategies for India and similar settings may need to be modified by increasing the dose or number of doses of vaccine and considering earlier vaccination, such as neonatal or maternal immunization.”

Factores de riesgo para el mal de Alzheimer

Diagnostic criteria are not only essential for the practice of clinical medicine, but also to reflect the current conceptualisation and understanding of the disease process. Landmark criteria for Alzheimer’s disease (AD) were published in 1984 (the NINCDS-ADRDA criteria)1 and have since constituted the benchmark for clinical diagnosis. Much of what we now understand about the cause, pathophysiology, course, and treatment of AD has been based on this diagnostic algorithm, which focuses principally on the exclusion of all other possible cerebral causes of progressive, acquired cognitive impairment.

Factores que provocan Alzheimer

Investigadores han encontrado los factores que provocan Alzheimer y estos pueden ser prevenidos para no desarrollar esta terrible enfermedad. Han encontrado siete padecimientos que producen Alzheimer en las personas mayores, estas pueden ser evitadas y tratas a tiempo.

El Alzheimer es una enfermedad que se produce en el cerebro, sobre todo en personas de edad adulta mayor, debido a ciertas circunstancias que se van desarrollando a través del tiempo, ya sea por el estilo de vida o hasta por ser hereditaria, pero aun así los científicos no han encontrado la causa general de este padecimiento.

Las siete causas que provocan Alzheimer son fumar, no hacer ejercicio, depresión, diabetes, alta presión y escasa actividad mental. Esta investigación encontró estos siete factores como los más importantes para desarrollar Alzheimer, el estudio fue publicado en la revista Lancet Neurology y explica que si hacemos cambios en nuestro estilo de vida podremos reducir los riesgos de desarrollar Alzheimer, según comentan en elmundo.

Los investigadores que desarrollaron el estudio encontraron que estas causas estaban asociadas al 51% de los casos de Alzheimer que revisaron, así que sin duda modificar estos hábitos o prevenir las enfermedades será de gran ayuda para no desarrollar esta enfermedad.

A pesar de esto, los investigadores han comentado que el estudio se apoyó en una revisión de datos que tienen que ver con los pacientes con Alzheimer, pero todavía falta mucho para determinar una causa general que produzca el Alzheimer.

No está de más hacer algunos cambios en nuestro estilo de vida, ya que será benéfico para nuestra salud física y mental.

¿Es fiable el cálculo del índice tobillo-brazo con un esfigmomanómetro digital?

Vega J, Romaní S, Garcipérez FJ, Vicente L, Pacheco N, Zamorano J et al. Enfermedad arterial periférica: eficacia del método oscilante. Rev Esp Cardiol 2011; 64: 619-621. TC PDF

Introducción

En los últimos años se ha propuesto la utilización del índice tobillo-brazo (ITB) mediante Doppler como método de detección de la arteriopatía periférica (AP). Sin embargo, es un método que requiere disponer de una sonda Doppler y de un entrenamiento apropiado. En cambio, es habitual disponer de esfigmomanómetros digitales de manejo sencillo.

Objetivo

Evaluar la eficacia para diagnosticar una AP del ITB calculado mediante una sonda Doppler y mediante un esfigmomanómetro digital automático convencional.

Perfil del estudio

Tipo de estudio: Estudio transversal

Área del estudio: Diagnóstico

Ámbito del estudio: Comunitario

Métodos

Se incluyeron en el estudio los pacientes derivados a un laboratorio de hemodinámica para la realización de una angiografía arterial periférica por claudicación intermitente o por sospecha de enfermedad arterial avanzada. A todos los participantes se les calculó el ITB mediante Doppler y un esfigmomanómetro automático digital convencional. Se excluyeron las mediciones de ITB >1,4. Cuando 3 mediciones sucesivas de la PA con el esfigmomanómetro daban una lectura de error (se presumía una PAS<60 mm Hg) se les asignaba un índice 0. Las exploraciones fueron llevadas a cabo por residentes tras un breve entrenamiento.

Paralelamente se les practicó una angioigrafía, que se utilizó como patrón oro, y se definió la AP hemodinámicamente significativa como la presencia de una estenosis >50%.

Resultados

Se incluyeron en el estudio a 85 pacientes. La edad media fue de 68 años y el 89% eran varones. Se analizaron los resultados de 158 piernas (se excluyeron 12 por amputaciones, presencia de úlceras dolorosas o ITB>1,4), de las cuales el 83% presentaba lesiones de AP hemodinámicamente significativas. En 70 piernas no se logró hacer ninguna medición de la PAS con el esfigmomanómetro. 69 de ellas tuvieron lesiones graves. Con el Doppler no se consiguió identificar el latido pedio o tibial posterior en 55 piernas con lesiones graves, pero tampoco en 12 sin lesiones angiográficas o con lesiones no significativas.

Los resultados fueron parecidos para el esfigmomanómetro convencional y para el Doppler (tabla 1).

Tabla 1. Índices de fiabiilidad diagnóstica del esfigmomanómetro y del Doppler (IC95%).
	Esfigmomanómetro	Doppler
Sensibilidad (%)	97 (93 a 99)	95 (89 a 97)
Especificidad (%)	89 (67 a 95)	56 (33 a 70)
Valor predictivo positivo (%)	97 (94 a 99)	91 (85 a 95)
Valor predictivo negativo (%)	86 (63 a 93)	68 (43 a 82)
Área bajo la curva	0,94 (0,85 a 1,03)	0,81 (0,67 a 0,94)
Falsos positivos (n)	3	12

Conclusiones

Los autores concluyen que el esfigmomanómetro automático tiene una mejor rentabilidad diagnóstica que el Doppler cuando el médico que lleva a cabo la exploración no está especialmente entrenado en el manejo de este dispositivo.

Conflictos de interés

Ninguno declarado.

Comentario

La AP afecta aproximadamente al 5% de las personas >40 años. Su presencia puede ser un indicio de enfermedad aterosclerótica generalizada y duplica el riesgo de muerte a medio plazo. La principal manifestación clínica de la enfermedad es la claudicación intermitente, pero sólo está presente en una minoría de los pacientes.

El ITB mediante Doppler se ha propuesto como un método sensible y muy específico de AP. Además presenta una buena correlación con la gravedad de la estenosis. Sin embargo, no todos los médicos disponen de una sonda Doppler y su medición tiene otros inconvenientes: requiere un entrenamiento mínimo, consume tiempo (algo menos de 15 min.) y la variabilidad interobservador es siginificativa.

Por contra, los medidores automáticos digitales de la PA están ampliamente extendidos en la consulta de atención primaria. Los resultados de este estudio sugieren que el cálculo del ITB mediante estos aparatos presenta resultados al menos tan válidos como los calculados mediante un dispositivo Doppler.

Una de las fortalezas de este estudio es que se ha comparado con el patrón oro ideal, que es la arteriografía. Sin embargo, se ha llevado a cabo en un número pequeño de pacientes con una elevada proporción de lesiones graves, por lo que sería conveniente validarlo en unas condiciones más similares a las de la atención primaria.

Bibliografía

Selvin E, Erlinger TP. Prevalence of and Risk Factors for Peripheral Arterial Disease in the United States: Results From the National Health and Nutrition Examination Survey, 1999–2000. Circulation 2004; 110: 738-743. R TC PDF
Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann TJ, Browner D. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med 1992; 326: 381-386. PDF
Mohler ER, Treat-Jacobson D, Reilly MP, Cunningham KE, Miani M, Criqui MH et al. Utility and barriers to performance of the ankle-brachial index in primary care practice. Vasc Med 2004; 9: 253-260. R PDF

Autor

Manuel Iglesias Rodal. Correo electrónico: mrodal@menta.net.

indice tobillo brazo

View more presentations from GETSA

Placebo , another point of view

Image via Wikipedia

The Rise of Placebo Medicine

Published by Steven Novella under Politics and Regulation,Science and Medicine
It is my contention that terms such as “complementary and alternative medicine” and “integrative medicine” exist for two primary purposes. The first is marketing – they are an attempt at rebranding methods that do not meet the usual standards of unqualified “medicine”. The second is a very deliberate and often calculating attempt at creating a double standard.

We already have a standard of care within medicine, and although its application is imperfect its principles are clear – the best available scientific evidence should be used to determine that medical interventions meet a minimum standard of safety and effectiveness. Regulations have largely (although also imperfectly) reflected that principle, as have academia, publishing standards, professional organizations, licensing boards, and product regulation.

With the creation of the new brand of medicine (CAM and integrative) came the opportunity to change the rules of science and medicine to create an alternative standard, one tailor made for those modalities that do not meet existing scientific and even ethical standards for medicine. This manifests in many ways – the NCCAM was created so that these modalities would have an alternate standard for garnering federal dollars for research. Many states now have “health care freedom laws” which create a separate standard of care (actually an elimination of the standard of care) for self-proclaimed “alternative” practices.

But perhaps the most insidious and damaging double-standard that is being advocated under the banner of CAM is a separate standard of scientific research itself. The normal rules of research that have evolved over the last few centuries are being subtly altered or discarded, with clever newspeak. It is a way for proponents to choose their evidence, rather than having the evidence decide what works and what does not work. We saw this strategy at play with the recent acupuncture study for back pain that clearly showed acupuncture was no more effective than placebo acupuncture. Proponents (propagated by an uncritical media) turned scientific logic on its head by interpreting this result as indicating that placebo acupuncture must work also (if only we could figure out how, they unconvincingly mused).

We see this strategy at work also with the use of so-called “pragmatic” studies – a rebranding of “unblinded” studies. This is a way to choose their evidence – in this case, poorly controlled unblinded studies that are more likely to reflect the bias of the researchers and therefore give them a result that they like. This is their reaction to well-designed placebo controlled trials that show their preferred modality does not work.

Another strategy is to change the meaning of the concept of placebo effects. This one was ready-made, and most people grossly misunderstand the nature of “the” placebo effect. One of my first articles for SBM was about the placebo effect because this concept is so criticial to science-based medicine. To summarize – the placebo effect is really many effects. It is everything other than a physiological response to the treatment. It is not all a real effect of mind-over-matter – it includes every bias and artifact of observation as well. It includes things like subjects reporting they feel better to the researcher because they want the treatment to work and they want to please the authority figure, who also wants the treatment to work and may be encouraging the perception of benefit.

It is most important to understand how the term “placebo effect” is used in the context of a controlled clinical trial. Scientific methodology is about controlling variables – because we want to know which variables work and which ones do not. In any clinical scenario there are a multitude of variables that may affect the outcome or the perception of the outcome. Therefore a well-designed study maximally controls all the variables – ideally so that the one variable of interest (the treatment) is completely isolated. This is accomplished in a number of ways. One method is randomization – randomly assigning subjects to the various treatment and placebo arms of a clinical trial. Randomization combined with sufficiently large trial size (number of subjects) results in all variables not specifically controlled for averaging out among the various arms. Another way to look at is that randomization prevents systematic biases in who gets treated and who gets a placebo from affecting the results.

Another method of controlling variables is the double-blind placebo control. Ideally one group of subjects will receive the treatment being studied while another group will receive a treatment that is identical in every way except that it is inert (i.e. it controls for all possible variables and isolated the one variable of interest – the treatment). Both the subject and the examiner are blinded to which is which to control for psychological effects. In order to conclude that the treatment “works” those subject receiving the active treatment must do statistically significantly better than those receiving the placebo. If the activity of the treatment was the only variable, then we can confidently conclude it was responsible for the improvement.

I know this is all very basic, but it is these very basic concepts that are being challenged by proponents of so-called CAM. They are trying to say the the effect measured in the placebo arm of such studies is a real effect, something valuable and alone is sufficient to justify the treatment. This philosophy has been termed by critics “placebo medicine” and is just the latest attempt at creating a double standard. But the claim is utterly ignorant of the scientific nature of the placebo effect. It is a method of controlling for biases, artifacts, and variables (known and unknown) – it is not a real effect.

There may be some non-specific therapeutic effects mixed into placebo effects. For example, people who are being studied tend to take better care of themselves and are more compliant with treatments (because they are being watched). They may also feel better as a result of the positive attention from a health care provider – old-fashioned good bedside manner. These are some of the variables being controlled for. But it is scientifically absurd to argue that they justify an ineffective treatment. But that is exactly what CAM proponents are doing.

The latest manifestation of this strategy is a report put out in the UK by The Kings Fund – a health policy charity. They put together a committee to examine how the UK can find evidence to support CAM therapies. They are not interested in figuring out “if” such treatments work, but rather how they can show “that” they work. They report:

Explaining the need for different types of research when assessing complementary practice, Professor Dame Carol Black said: ‘It has become widely accepted that a stronger evidence base is needed if we are to reach a better understanding of complementary practices and ensure greater confidence in their clinical and cost effectiveness. The challenge is to develop methods of research that allow us to assess the value of an approach that seeks to integrate the physical intervention, the personal context in which it is given, and non-specific effects that together comprise a particular therapy.’

Got that? We need new kinds of research (read “double standard”) in order to demonstrate the value of these special CAM practices. The reason that we need to find new ways to demonstrate their value is because they fail under the accepted scientific methods. The last sentence is just a fancy way of saying that placebo effects should count as real effects.

It further says:

‘As long as findings from research can provide confidence in the positive effect of the physical intervention at the heart of the treatment, then any added benefit brought by the therapeutic relationship and the context for treatment should count as part of the treatment effect,’ the report says.

‘For complementary therapies such a holistic approach to effectiveness should be adopted by bodies such as NICE, when comparing cost-effectiveness across a range of treatments.’

The “physical intervention at the heart of the treatment” is functionally the same thing as – non-specific placebo effects. They want to take a “holistic” approach to evidence (another useful marketing brand), meaning they get to decide what the evidence means. George Orwell would be proud.

As usual, Edzard Ernst (the go to expert for the media) gets it exactly right. He is quoted as saying:

‘This is the introduction of double standards through the back door.’

‘In this case we might as well allow an ineffective medication on the market, because it too will have a placebo effect.’

That latter point is a favorite of mine as well. Whenever CAM proponents try to change the rules of science to suit their needs, I invite my readers to imagine a pharmaceutical company getting away with the same thing (not that they wouldn’t want to if they could). Imagine a drug that works no better than placebo in well-designed clinical trials and the company trying to get FDA approval on the grounds that their drug has a valuable placebo effect, even if it is physiologically worthless.

Conclusion

The integrity of science-based medicine is critical to the health of the public, the legitimacy of modern medicine, and also the economic health of modern society (as is being forcefully argued recently). We need to have one scientific standard that is fair, rational, and scientifically sound. The creation of a double standard for proponents of modalities that do not meet the very reasonable standards of scientific medicine is eroding the standard of care and the integrity of modern medicine.

The public, the media, politicians, and regulators should not fall for the deceptive language that is being used to disguise the truth of these efforts to undermine science-based medicine. This is a brass attempt at changing the rules of science to meet their perceived needs. When you change the rules of science you no longer have science – you have pseudoscience or something even more nefarious.

Putting research into primary care practice

BMJ 2011; 343:d3922 doi: 10.1136/bmj.d3922 (Published 5 July 2011)

Cite this as: BMJ 2011; 343:d3922

Editorial

Putting research into primary care practice

Frede Olesen, professor

¹Research Unit for General Practice, Department of Public Health, Aarhus University, Bartholins Allé 2, DK-8000 Aarhus C, Denmark

fo@alm.au.dk

The European initiative is a good start, but excludes too many patients and crucial aspects of primary care

The European Medical Research Council and European Science Foundation recently published a strategic report in its series of “Current Forward Looks” entitled Implementation of Medical Research in Clinical Practice. 1 The collaboration has previously published two strategic reports on the ways forward for basic biological research and for investigator driven clinical trials. 1 By suggesting a strategy on the use of research in practice, it now intends to close the loop. The strategy holds much potential for improving the quality of clinical practice and clinically oriented health services research.

The report has three main strengths: firstly, it takes strategy and policy to the level of specific recommendations for improving the quality of clinical research; secondly, it presents a strong case for the implementation of good research; and, thirdly, it gives special attention to the particular problems encountered in general practice.

The report proposes that the quality of clinical research could be improved by closer national and European coordination of independent funding of larger projects, …

[Full text of this article]

Knee examination

http://www.dailymotion.com/embed/video/xfu405
Knee Examination por rubenroa

There’ s no free launch

Image via Wikipedia

This is the today’s editorial of BMJ, one of the most reliable medical journal all over the world. The title deals about …..”provision of health information for all”……….but I can’t explain it because I can not read it, because at the end of this abstract says “Full Text of this Article”……..of course, to read the full article I need to pay first. So it doesn’t matter what the editorial says, if you want information, in the information age……….you have to pay….at least for the famous British Medical Journal. Anyway, I think you can read more about this in another blog’s o newspaper like “guardian”, in related articles.
BMJ 2011; 342:d4151 doi: 10.1136/bmj.d4151 (Published 30 June 2011)

Cite this as: BMJ 2011; 342:d4151

Editorial

Provision of health information for all

Richard Smith, director1,

Tracey Pérez Koehlmoos, programme head2

+Author Affiliations

¹UnitedHealth Chronic Disease Initiative, London SW4 0LD, UK
²Health and Family Planning Systems Programme, ICDDR,B, Dhaka, Bangladesh

richardswsmith@yahoo.co.uk

A major organisation should support global efforts

High quality information is essential for good health, yet many individuals, practitioners, and health organisations—particularly in low and middle income countries—lack access to information. This problem has been highlighted many times, 1 2 3 4 and Health Information for All 2015 (HIFA2015) was founded in 2006 with the aim that “by 2015 every person worldwide will have access to an informed healthcare provider—lack of relevant, reliable healthcare information will no longer be a major contributor to avoidable death and suffering” (www.hifa2015.org/ ). It is unlikely that this ambitious goal will be achieved.

In HIFA2015’s definition, the term “healthcare providers” includes mothers and family caregivers, in recognition that their basic knowledge and decisions are crucial to survival. In many countries in Africa more than 80% of children die before they even reach a health facility. The term “healthcare information” refers to health knowledge for prevention and treatment of disease rather than routine statistical data.

HIFA2015 now has 5000 members from 2000 organisations in 158 countries, and it has four global forums—HIFA2015, CHILD2015, HIFA-Portuguese, and HIFA-EVIPNet. Most of those who contribute to the forums come from low and middle income countries. The organisation has a three pronged strategy of communication (bringing together a critical …

[Full text of this article]

tweetmeme_url='';

In Memorian: Barbara Starfield

Con profunda tristeza los médicos generales y de familia recibimos la noticia del fallecimiento de Barbara Starfield. Comprometida con la atención primaria, las palabras huelgan y copio aqui, para quienes no la conocieron, su pagina de profesora en John Hopkins, la misma Universidad donde nació el modelo flexneriano y que ella combatió. Tuve el honor de, si bien no conocerla personalmente, leerla en la lista de “Social Determinats of Health”, e intercambiar opiniones a través de e-mails. Hemos perdido a un simbolo de la Atención Primaria, pero su pensamiento seguirá vivo. Mi condolencia también a su amigo, quien me dió la noticia, Juan Gervas.

Barbara Starfield

Professor

Academic Degrees
MDMPH
Departmental Affiliation
Name:
Health Policy and Management
Affiliation Type:
Primary
Division:
Primary Care Policy Center
Name:
Population, Family and Reproductive Health
Affiliation Type:
Joint
Departmental Address
452 Hampton House
Contact Information
Email:
bstarfie+jhsph.edu
Phone:
410-955-3737
Fax:
410-614-9046
Link:
Personal Website
Research and Professional Experience
Determinants of health and equity in health; effectivenss and equity of health services; assessment of population health; co-morbidity and case mix; primary care and specialty care and their interrelationships; continuity (longitudinality) of care and its effects; comprehensiveness and coordination of care

Honors and Awards
David Luckman Memorial Award, State University of New York, Downstate Medical Center, 1958. The 1967 Award of The Enuresis Foundation for “significant contribution to knowledge and understanding of enuresis.” Research Scientist Development Award (K02 HS 46225) from the National Center for Health Services Research and Development, 1970-75. Member, Institute of Medicine, National Academy of Sciences. Elected 1977. The George Armstrong Award for Work in Advancing the Goals of Improved Patient Care, Teaching, and Research in Ambulatory Pediatrics. The Ambulatory Pediatric Association, May 1983. First Annual Research Award for Contributions to Research in Child Health. The Ambulatory Pediatric Association, May 1990. Residential Scholar, Bellagio Study Center, Rockefeller Foundation, June 9 – July 13, 1990. Special Recognition Award for the Secretary for Health and Human Services (Task Force to Develop Child Health Indicators, 1990), May 1991. First National Primary Care Achievement Award, Pew Charitable Trusts/Health Resources and Services Administration (DHHS), 1994. Distinguished Investigator Award, Association for Health Services Research, 1995. American Public Health Association‘s Martha May Eliot Award, 1995. AHSR (Association for Health Services Research) Distinguished Fellow, 1996. Maurice Wood Award for Lifetime Contribution to Primary Care Research, North American Primary Care Research Group (NAPCRG), 2000. Honorary Fellow, Royal College of General Practitioners (UK), 2000. Lifetime Achievement Award, Ambulatory Pediatric Association, 2002. Morehouse School of Medicine Excellence in Primary Care Award, 2002

Selected Publications
Gervas J, Starfield B, Heath I. Is clinical prevention better than cure? Lancet 2008; 372:1997-9. Starfield B. Refocusing the system. N Engl J Med 2008; 359(20): 2087, 2091. Lee TH, Bodenheimer T, Goroll AH, Starfield B, Treadway K. Perspective roundtable: redesigning primary care. N Engl J Med 2008; 359(20): e24. Starfield B. Commentary: Access, primary care, and the medical home: rights of passage. Med Care 2008; 46: 1015-16. Starfield B. The biggest bang for the buck: a conversation with Barbara Starfield, M.D., M.P.H. Interview by Sallie Rixey. Md Med 2008; 9(3): 11-3. Rawaf S; De Maeseneer J; Starfield B. From Alma-Ata to Almaty: a new start for primary health care. Lancet 2008; 372(9647): 1365-7. Starfield B. An evidence base for primary care. Managed Care 2008; 17(6): 33-26, 39. Starfield B, Hyde J, Gérvas J, Heath I. The concept of prevention: a good idea gone astray? J Epidemiol Community Health 2008; 62: 580-83. Alonso J, Urzola D, Serra-Sutton V, Tebe C, Starfield B, Riley AW, Rajmil L. Validity of the health profile-types of the Spanish Child Health and Illness Profile – Adolescent Edition (CHIP-AE). Value in Health 2008; 11: 440-9. Starfield B. Editorial: The importance of primary care in health systems. Hong Kong Practitioner 2008; 30: 1-2. Starfield B. Comment: Quality and outcomes framework: patient-centred. Lancet 2008; 372: 692-4. Starfield B. Commentary: Primary care in Canada: coming or going? Healthc Pap 2008; 8: 58-62; discussion 64-7. Starfield B. Social gradients and child health. In Heggenhougen HK, Quah SR (eds.). International Encyclopedia of Public Health, Vol 6, pp. 87-101. San Diego, CA: Academic Press, 2008. Gervas J, Starfield B, Violan C, Minue S. GPs with special interests: unanswered questions. Br J Gen Pract 2007; 57: 912-7. Starfield B, Fryer GE Jr. The primary care workforce: ethical and policy implications. Ann Fam Med 2007; 5: 486-91. Starfield B, Birn A-E. Income redistribution is not enough: income inequality, social welfare programs, and achieving equity in health. J Epidemiol Community Health 2007; 61: 1038-41. Starfield B. Global health, equity, and primary care. J Am Board Fam Med 2007; 20(6): 511-3. Gérvas J, Starfield B, Minué S, Violan C, Seminario de Innovacion en Atencion Primaria 2007. [Some Causes (and Solutions) of the Loss of Prestige of General Practitioners/Family Doctors. Against the Discrediting of Heroes.]. Aten Primaria 2007; 39(11): 615-8. Beasley JW, Starfield B, vanWeel C, Rosser WW, Haq CL. Global health and primary care research. J Am Board Fam Med 2007; 20(6):518-26. Pueyo M-J, Serra-Sutton V, Alonso J, Starfield B, Rajmil L. Self-reported social class in adolescents: validity and relationship with gradients in self-reported health. BMC Health Services Research 2007; 7:151. Pasarin MI, Berra S, Rajmil L, Solans M, Borrell C, Starfield B. [An instrument to evaluate primary health care from the population perspective]. Aten Primaria 2007; 39 (8): 395-401. Forrest CB, Shadmi E, Nutting PA, Starfield B. Specialty referral completion among primary care patients: results from the ASPN Referral Study. Ann Fam Med 2007; 5: 361-7. Starfield B, Horder J. Interpersonal continuity: old and new perspectives. Br J Gen Pract 2007; 57 (540): 527-9. Starfield B. Pathways of influence on equity in health. Soc Sci Med 2007; 64 (7): 1355-62. Macinko J, Starfield B, Shi L. Quantifying the health benefits of primary care physician supply in the United States. Int J Health Serv 2007; 37(1): 111-26. Starfield B, Gervas J. Family medicine should encourage its clinicians to specialize: negative position. Chapter 10 in Buetow SA and Kenealy TW. Ideological Debates in Family Medicine, pp. 107-119. New York, NY: Nova Science Publishers, 2007. Starfield B, Shi L. Commentary: Primary care and health outcomes: a health services research challenge. Health Serv Res 2007; 42(6 Pt 1): 2252-6. Valderas JM, Starfield B, Salisbury C. Definitions of chronic health conditions in childhood. JAMA 2007; 298: 1636. Valderas JM, Starfield B, Roland M. Multimorbidity’s many challenges: A research priority in the UK. BMJ 2007; 334(7604): 1128. Starfield B, Shi L. Commentary: The impact of primary care and what states can do. North Carolina Medical Journal 2007; 68: 204-7. Starfield B. Editorial: Co-morbidity and its challenges for quality of primary care. Rev Port Clin Geral 2007; 23:179-80. Starfield B. Pathways of influence on equity in health: A rejoinder to Braveman and Wilkinson. Soc Sci Med 2007; 64(7): 1371-2.

Reconocimiento a Julio Ceitlin

Un justo reconocimiento a la labor y la historia de Julio Ceitlin. Uno de los hombres fundadores de la medicina familiar en iberoamérica. Mis felicitaciones a Julio, y mi agradecimiento por todo lo que me enseñó. El es uno de mis pocos maestros.

Dear Julio

I hope this message finds you well.

On behalf of the leadership of The College of Family Physicians of Canada ( CFPC) , I am pleased to share the news with you that you have been selected to receive Honorary Membership in the CFPC. This is an honour bestowed each year to a small number of outstanding individuals who have contributed significantly to our College or the discipline of family medicine and family practice and/or the health and well- being of the population in Canada or internationally. Your leadership of the specialty of family medicine in South America and the impact of your work globally, including of course your interest in ,communication with and recognition of the challenges we face in family medicine in Canada have long earned the respect and admiration of your friends and colleagues in our College

The award will be presented during our Convocation and Awards presentations on the final evening of Family Medicine Forum 2011 being held at the Palais de Congres in Montreal Quebec on Saturday November 5th 2011.

The award includes complimentary registration to Family Medicine Forum 2011 being held from Nov 3-5 in Montreal as well as up to $1500.00 to offset travel and other expenses .Recipients of Honorary Membership may append the special designation MCFP (Hon) following their names .

My sincere congratulations, Julio on having being named to receive this award. We look forward to your being able to join us in Montreal for this special presentation.

Sincerely

Cal

Calvin Gutkin, MD, CCFP (EM), FCFP

Executive Director & Chief Executive Officer

The College of Family Physicians of Canada

Phone: 800-387-6197 x 237

905-629-0900 x 237

Fax: 905-629-0893

Email: cgutkin@cfpc.ca

Website: http://www.cfpc.ca

Evidence-Based Medicine in the EMR Era

SOURCE INFORMATION

REFERENCES

Related articles

Share this:

Like this:

Related articles

Share this:

Like this:

Related articles

Share this:

Like this:

Estimating treatment effects for individual patients based on the results of randomised clinical trials

Abstract

Related articles

Share this:

Like this:

SOURCE INFORMATION

Related articles

Share this:

Like this:

Related articles

Share this:

Like this:

‘I just want permission to be ill’: towards a sociology of medically unexplained symptoms.

Source

Abstract

Share this:

Like this:

Background

Systematic review and methods

Results

Table 1: Details of available data

Table 2 summarises data available for each of the analgesics along with its calculated relative benefit (RB) and number-needed-to-treat-to-benefit (NNT). Para = paracetamol, Asa – aspirin, Caf = caffeine, Cod = codeine, Naprox = naproxen, Diclo = diclofenac, Ibu = ibuprofen

Table 3 shows a sub-analysis of only those trials involving dental pain.

Figure 1: NNTs for all available data

Figure 2: NNTs for dental studies only

Comment

Dearth of evidence

What can we make of the evidence we have

References

Related articles

Share this:

Like this:

Related articles

Share this:

Like this:

Source: Wall Street Journal – Via Juan Gérvas (list of Seminario Internacional de Atención Primaria: Prevención Cuaternaria) . Barcelona. Octubre 2011

By JEROME GROOPMAN and PAMELA HARTZBAND

Related articles

Share this:

Like this:

A cure for the disease of hate

Related articles

Share this:

Like this:

Related articles

Share this:

Like this:

Factores que provocan Alzheimer

Related articles

Share this:

Like this:

Vega J, Romaní S, Garcipérez FJ, Vicente L, Pacheco N, Zamorano J et al. Enfermedad arterial periférica: eficacia del método oscilante. Rev Esp Cardiol 2011; 64: 619-621. TC PDF

Introducción

Objetivo

Perfil del estudio

Métodos

Resultados

Conclusiones

Conflictos de interés

Comentario

Bibliografía

Autor

Share this:

Like this:

Related articles

Share this:

Like this:

Putting research into primary care practice