Evidence map›Paper›PMID 37250632›Full record

ArticleFrontiers in medicine2023

Development and validation of an electronic database-based frailty index to predict mortality and hospitalization in a population-based study of adults with SARS-CoV-2.

Paola Rebora, Carlo Alberto Scirè, Giuseppe Occhino, Francesco Bortolan, Olivia Leoni, Francesco Cideni, Alberto Zucchelli, Emanuele Focà, Alessandra Marengoni, Giuseppe Bellelli and 1 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  3. Article
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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

11 authors.

Paola ReboraBicocca Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Carlo Alberto ScirèSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Giuseppe OcchinoBicocca Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Francesco BortolanRegione Lombardia, General Directorate for Welfare, Regional Epidemiological Observatory Organizational Unit, Directorate General for Health, Milan, Italy.
Olivia LeoniRegione Lombardia, General Directorate for Welfare, Regional Epidemiological Observatory Organizational Unit, Directorate General for Health, Milan, Italy.
Francesco CideniRegione Lombardia, General Directorate for Welfare, Regional Epidemiological Observatory Organizational Unit, Directorate General for Health, Milan, Italy.
Alberto ZucchelliDepartment of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
Emanuele FocàDivision of Infectious and Tropical Diseases, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
Alessandra MarengoniDepartment of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy.
Giuseppe BellelliSchool of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.
Maria Grazia ValsecchiBicocca Center of Bioinformatics, Biostatistics and Bioimaging, School of Medicine and Surgery, University of Milano-Bicocca, Monza, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Electronic health databases are used to identify people at risk of poor outcomes. Using electronic regional health databases (e-RHD), we aimed to develop and validate a frailty index (FI), compare it with a clinically based FI, and assess its association with health outcomes in community-dwellers with SARS-CoV-2. Methods: Data retrieved from the Lombardy e-RHD were used to develop a 40-item FI (e-RHD-FI) in adults (i.e., aged ≥18 years) with a positive nasopharyngeal swab polymerase chain reaction test for SARS-CoV-2 by May 20, 2021. The considered deficits referred to the health status before SARS-CoV-2. The e-RHD-FI was validated against a clinically based FI (c-FI) obtained from a cohort of people hospitalized with COVID-19 and in-hospital mortality was evaluated. e-RHD-FI performance was evaluated to predict 30-day mortality, hospitalization, and 60-day COVID-19 WHO clinical progression scale, in Regional Health System beneficiaries with SARS-CoV-2. Results: We calculated the e-RHD-FI in 689,197 adults (51.9% females, median age 52 years). On the clinical cohort, e-RHD-FI correlated with c-FI and was significantly associated with in-hospital mortality. In a multivariable Cox model, adjusted for confounders, each 0.1-point increment of e-RHD-FI was associated with increased 30-day mortality (Hazard Ratio, HR 1.45, 99% Confidence Intervals, CI: 1.42-1.47), 30-day hospitalization (HR per 0.1-point increment = 1.47, 99%CI: 1.46-1.49), and WHO clinical progression scale (Odds Ratio = 1.84 of deteriorating by one category, 99%CI 1.80-1.87). Conclusion: The e-RHD-FI can predict 30-day mortality, 30-day hospitalization, and WHO clinical progression scale in a large population of community-dwellers with SARS-CoV-2 test positivity. Our findings support the need to assess frailty with e-RHD.

Indexed as

care transitionscommunityCOVID-19health serviceshospitalpublic health

Identifiers

PMID37250632
PMCPMC10213394

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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.