Evidence map›Paper›PMID 39716260›Full record

SynthesisSystematic reviews2024

Diagnostic accuracy of case-identification algorithms for heart failure in the general population using routinely collected health data: a systematic review.

Anita Andreano, Vito Lepore, Pietro Magnoni, Alberto Milanese, Caterina Fanizza, Deborah Testa, Alessandro Musa, Adele Zanfino, Paola Rebora, Lucia Bisceglia and 2 more

Abstract readSystematic Review
In one paragraph

Synthesis in Systematic reviews, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

12 authors.

Anita AndreanoSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy.
Vito LeporeArea Epidemiologia E Care Intelligence, Agenzia Regionale Strategica Per La Salute Ed Il Sociale (AReSS) Puglia, Lungomare Nazario Sauro 33, Bari, 70121, Italy.
Pietro MagnoniSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy. pmagnoni@ats-milano.it.ORCID 0000-0002-6431-6261
Alberto MilaneseSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy.
Caterina FanizzaArea Epidemiologia E Care Intelligence, Agenzia Regionale Strategica Per La Salute Ed Il Sociale (AReSS) Puglia, Lungomare Nazario Sauro 33, Bari, 70121, Italy.
Deborah TestaSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy.
Alessandro MusaArea Epidemiologia E Care Intelligence, Agenzia Regionale Strategica Per La Salute Ed Il Sociale (AReSS) Puglia, Lungomare Nazario Sauro 33, Bari, 70121, Italy.
Adele ZanfinoSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy.
Paola ReboraDipartimento Di Medicina E Chirurgia E Centro Interdipartimentale Bicocca Bioinformatics Biostatistics and Bioimaging Centre (B4), Università Milano Bicocca, Via Cadore 48, Monza, 20900, Italy.
Lucia BiscegliaArea Epidemiologia E Care Intelligence, Agenzia Regionale Strategica Per La Salute Ed Il Sociale (AReSS) Puglia, Lungomare Nazario Sauro 33, Bari, 70121, Italy.
Antonio Giampiero RussoSC Unità Di Epidemiologia, Agenzia Di Tutela Della Salute Della Città Metropolitana Di Milano, Via Conca del Naviglio 45, Milan, 20123, Italy.
PROPHET-I study group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHeart failure (HF), affecting 1-4% of adults in industrialized countries, is a major public health priority. Several algorithms based on administrative health data (HAD) have been developed to detect patients with HF in a timely and inexpensive manner, in order to perform real-world studies at the population level. However, their reported diagnostic accuracy is highly variable.

objectiveTo assess the diagnostic accuracy of validated HAD-based algorithms for detecting HF, compared to clinical diagnosis, and to investigate causes of heterogeneity.

methodsWe included all diagnostic accuracy studies that utilized HAD for the diagnosis of congestive HF in the general adult population, using clinical examination or chart review as the reference standard. A systematic search of MEDLINE (1946-2023) and Embase (1947-2023) was conducted, without restrictions. The QUADAS-2 tool was employed to assess the risk of bias and concerns regarding applicability. Due to low-quality issues of the primary studies, associated with both the index test and the reference standard definition and conduct, and to the high level of clinical heterogeneity, a quantitative synthesis was not performed. Measures of diagnostic accuracy of the included algorithms were summarized narratively and presented graphically, by population subgroups.

resultsWe included 24 studies (161,524 patients) and extracted 36 algorithms. Algorithm selection was based on type of administrative data and DOR. Six studies (103,018 patients, 14 algorithms) were performed in the general outpatient population, with sensitivities ranging from 24.8 to 97.3% and specificities ranging from 35.6 to 99.5%. Eight studies (14,957 patients, 10 algorithms) included hospitalized patients with sensitivities ranging from 29.0 to 96.0% and specificities ranging from 65.8 to 99.2%. The remaining studies included subgroups of the general population or hospitalized patients with cardiologic conditions and were analyzed separately. Fourteen studies had one or more domains at high risk of bias, and there were concerns regarding applicability in 9 studies. DISCUSSION: The considerable percentage of studies with a high risk of bias, together with the high clinical heterogeneity among different studies, did not allow to generate a pooled estimate of diagnostic accuracy for HAD-based algorithms to be used in an unselected general adult population. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42023487565.

Indexed as

AlgorithmsHeart FailureHumansSensitivity and SpecificityAdministrative health dataCase-detection algorithmsDiagnostic accuracy systematic reviewHealth claimsHeart failure

Identifiers

PMID39716260
PMCPMC11668106

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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.