Evidence map›Paper›PMID 25126761›Full record

SynthesisPloS one2014

Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.

Natalie McCormick, Diane Lacaille, Vidula Bhole, J Antonio Avina-Zubieta

Abstract readMeta-AnalysisSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 150 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
150citing papers in PubMed, 5 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

150 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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  20. Cardiovascular Outcomes Associated with Cholinesterase Inhibitor Use in Individuals at High Cardiovascular Risk.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2025
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90 more citing papers are in PubMed but not listed here.

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

4 authors.

Natalie McCormickFaculty of Pharmaceutical Sciences, University of British Columbia, Vancouver, British Columbia, Canada; Arthritis Research Centre of Canada, Richmond, British Columbia, Canada.
Diane LacailleArthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Cardiovascular Committee of the Canadian Rheumatology Administrative Data Network, Richmond, British Columbia, Canada.
Vidula BholeArthritis Research Centre of Canada, Richmond, British Columbia, Canada; EpiSolutions Consultancy Services, Thane, India.
J Antonio Avina-ZubietaArthritis Research Centre of Canada, Richmond, British Columbia, Canada; Division of Rheumatology, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Cardiovascular Committee of the Canadian Rheumatology Administrative Data Network, Richmond, British Columbia, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveHeart failure (HF) is an important covariate and outcome in studies of elderly populations and cardiovascular disease cohorts, among others. Administrative data is increasingly being used for long-term clinical research in these populations. We aimed to conduct the first systematic review and meta-analysis of studies reporting on the validity of diagnostic codes for identifying HF in administrative data.

methodsMEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify HF; or (b) Evaluating the validity of HF codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value [PPV], negative predictive value, or Kappa scores) for HF, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Using a random-effects model, pooled sensitivity and specificity values were produced, along with estimates of the positive (LR+) and negative (LR-) likelihood ratios, and diagnostic odds ratios (DOR = LR+/LR-) of HF codes.

resultsNineteen studies published from 1999-2009 were included in the qualitative review. Specificity was ≥95% in all studies and PPV was ≥87% in the majority, but sensitivity was lower (≥69% in ≥50% of studies). In a meta-analysis of the 11 studies reporting sensitivity and specificity values, the pooled sensitivity was 75.3% (95% CI: 74.7-75.9) and specificity was 96.8% (95% CI: 96.8-96.9). The pooled LR+ was 51.9 (20.5-131.6), the LR- was 0.27 (0.20-0.37), and the DOR was 186.5 (96.8-359.2).

conclusionsWhile most HF diagnoses in administrative databases do correspond to true HF cases, about one-quarter of HF cases are not captured. The use of broader search parameters, along with laboratory and prescription medication data, may help identify more cases.

Indexed as

Clinical CodingAgedAged, 80 and overDatabases, FactualDiagnostic ErrorsHeart FailureHumansMyocardium

Identifiers

PMID25126761
PMCPMC4134216

What OpenQuestion holds

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Registered trials

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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.