Evidence map›Paper›PMID 23133591›Full record

ArticlePloS one2012

The effect of chance variability in blood pressure readings on the decision making of general practitioners: an internet-based case vignette study.

Mohammed A Mohammed, Tom Marshall, Paramjit Gill

Abstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–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

1 citing paper in PubMed.

  1. Trial
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

3 authors.

Mohammed A MohammedPrimary Care Clinical Sciences, University of Birmingham, Edgbaston, Birmingham, United Kingdom.
Tom Marshall
Paramjit Gill

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGuidelines for the management of blood pressure (BP) in primary care generally suggest that decisions be made on the basis of specific threshold values (e.g. BP 140/90 mmHg); but this fails to adequately accommodate a common cause of variation--the play of chance.

objectiveTo determine the impact of chance variability in BP readings on the clinical decision making of general practitioners (GPs) regarding anti-hypertensive treatment and cardiovascular risk management.

methodWe used an internet based study design, where 109 GPs were assigned to manage one of eight case vignettes (guidelines would recommend treatment for only one of the eight) and presented with blood pressure readings that were randomly selected from an underlying population.

resultsSeventeen (15.6%, 17/109) GPs consulted the vignette for whom treatment was recommended, but only 7/17 (41.2%) GPs prescribed treatment, whereas 14/92 (15.2%) GPs prescribed medication to the other vignettes. When deciding to follow-up a vignette GPs were influenced by threshold values for systolic and diastolic BP, but not by the overall cardiovascular risk. If the first reading was a low BP (systolic <140, diastolic <90) GPs were highly likely to discharge the vignette and follow-up a high BP reading (diastolic >90 or systolic BP≥140). Similar factors predicted the decision to prescribe a drug, although the vignette's cardiovascular risk (>20%) was now statistically significant (p = 0.03).

conclusionsGP decision making, whilst generally consistent with guidelines, appears to be compromised by chance variation leading to under and over treatment. Interventions to adequately accommodate chance variability into clinical decision making are required.

Indexed as

AdultAgedAntihypertensive AgentsBlood PressureBlood Pressure DeterminationCardiovascular DiseasesDecision MakingDecision Support Systems, ClinicalFemaleGeneral PractitionersHumansHypertensionInternetMaleMiddle AgedPractice Patterns, Physicians'Antihypertensive Agents

Identifiers

PMID23133591
PMCPMC3487729

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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.