Evidence map›Paper›PMID 22180684›Full record

ArticleThe Yale journal of biology and medicine2011

Medical reversal: why we must raise the bar before adopting new technologies.

Vinay Prasad, Adam Cifu

Abstract read
In one paragraph

Article in The Yale journal of biology and medicine, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
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  5. Review
  6. Low-value care in musculoskeletal health care: Is there a way forward?Pain practice : the official journal of World Institute of Pain · 2022
    Review
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  12. Exploring Novel Computable Knowledge in Structured Drug Product Labels.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2020
    Article
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  15. Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Vinay PrasadDepartment of Medicine, Northwestern University, Chicago, Illinois, USA.
Adam Cifu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Medical reversal occurs when a new clinical trial - superior to predecessors by virtue of better controls, design, size, or endpoints - contradicts current clinical practice. In recent years, we have witnessed several instances of medical reversal. Famous examples include the class 1C anti-arrhythmics post-myocardial infarction (contradicted by the CAST trial) or routine stenting for stable coronary disease (contradicted by the COURAGE trial). In this paper, we explore the phenomenon of medical reversal. The causes and consequences are discussed. Conflicts of interest among researchers and an unyielding faith in basic science are explored as root causes of reversal. Reversal harms patients who undergo the contradicted therapy during the years it was in favor and those patients who undergo the therapy in the lag time before a change in medical practice. Most importantly, it creates a loss of faith in the medical system by physicians and patients. The solution to reversal is upfront, randomized clinical trials for new clinical practices and a systematic method to evaluate practices already in existence.

Indexed as

Practice Patterns, Physicians'Biomedical TechnologyClinical Trials as TopicConflict of InterestContraindicationsEvidence-Based MedicineHumansResearch Designbasic sciencecontradicted findingsevidence-based medicinemedical reversalobservational studiesrandomized controlled trials

Identifiers

PMID22180684
PMCPMC3238324

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.