Evidence map›Paper›PMID 38180953›Full record

ArticlePLOS global public health2024

Risk factors for COVID-19 in-hospital mortality in Argentina: A competing risk survival analysis.

Sebastian Calonico, Juan Cruz Lopez Del Valle, Rafael Di Tella

Abstract read
In one paragraph

Article in PLOS global public health, 2024. 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

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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

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

3 authors.

Sebastian CalonicoDepartment of Health Policy and Management, Mailman School of Public Health, ColumbiaUniversity, NYC, New York, United States of America.ORCID https://orcid.org/0000-0002-9736-8949
Juan Cruz Lopez Del ValleBoston University, Boston, Massachusetts, United States of America.ORCID https://orcid.org/0000-0001-9356-2931
Rafael Di TellaHarvard Business School, Harvard University, Cambridge, Massachusetts, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 poses dire threats for low and middle-income countries (LMICs). Yet, there remains limited rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs, and often the evidence was based on small samples and/or unicentric. The objective of this study was to examine risk factors of COVID-19 mortality in Argentina, a hard-hit middle-income Latin American country. We analyze data on 5,146 COVID-19 patients from 11 centers across 10 cities in Argentina, making this one of the largest multi-centric retrospective observational descriptive studies in the LMICs. Information on demographics and co-morbidities was extracted from medical records. Outcomes of relevance consisted of whether the patient was discharged or deceased (as established in medical records), along with date of each event. We use survival models that account for competing risks. Median age was 60 years (IQR: 48-72), there were fewer women (40.8%) hospitalized than men (59.2%), and the most prevalent comorbidities were hypertension (40.9%), diabetes (20.0%) and obesity (19.1%). Patients were hospitalized for a median duration of 8 days (IQR: 5-13), and in-hospital mortality was 18.1%, though it varied substantially across health centers (95%CI: 17.1%-19.2%). Baseline characteristics most associated with in-hospital mortality were respiratory rate (adjusted HR = 3.6, 95%CI: 2.5-5.4 for ≥ 26 breathes/min), older age (adjusted HR = 2.5, 95%CI: 2.0-3.3 for the 80+ age group), and chronic kidney disease (adjusted HR = 2.2, 95%CI: 1.8-2.8). Associations were attenuated when survival models did not account for the competing risk of being discharged. We document lower mortality rates than those in prior studies, likely due to a lower prevalence of comorbidities amongst patients in our sample. Compared with standard Cox models, we find that, when using competing risk models, risk factors have a larger role in explaining COVID-19 mortality. Overall, we provide rigorous evidence describing the characteristics and outcomes of hospitalized patients for LMICs. Thus, our findings are useful to conduct a more accurate in-hospital monitoring of patient subgroups who may be at greater risk. They also provide valuable guidance for public health and policy efforts in Argentina and other developing countries.

Identifiers

PMID38180953
PMCPMC10769012

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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.