Evidence map›Paper›PMID 37580157›Full record

SynthesisEuropean heart journal. Quality of care & clinical outcomes2024

Worldwide impact of COVID-19 on hospital admissions for non-ST-elevation acute coronary syndromes (NSTACS): a systematic review with meta-analysis of 553 038 cases.

Francesco Sofi, Monica Dinu, GianPaolo Reboldi, Sofia Lotti, Luca Genovese, Isabella Tritto, GianFranco Gensini, Charles Michael Gibson, Giuseppe Ambrosio

Open access · bronzeAbstract readSystematic ReviewMeta-Analysis
In one paragraph

Synthesis in European heart journal. Quality of care & clinical outcomes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.5field-weighted citation impact, top 10% of its field
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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Review
  2. Review
  3. Postpandemic Cardiac Mortality Rates.JAMA network open · 2025
    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

9 authors at 4 institutions in 2 countries.

Francesco SofiDepartment of Experimental and Clinical Medicine, University of Florence, Florence 50134, Italy.
Monica DinuDepartment of Experimental and Clinical Medicine, University of Florence, Florence 50134, Italy.
GianPaolo ReboldiDepartment of Medicine, University of Perugia School of Medicine, Perugia 06126, Italy.
Sofia LottiDepartment of Experimental and Clinical Medicine, University of Florence, Florence 50134, Italy.ORCID 0000-0001-9288-5683
Luca GenoveseDepartment of Cardiology, IRCCS MultiMedica, Milan 20138, Italy.
Isabella TrittoDivision of Cardiology, University of Perugia School of Medicine, Perugia 06126, Italy.
GianFranco GensiniDepartment of Cardiology, IRCCS MultiMedica, Milan 20138, Italy.
Charles Michael GibsonBaim Institute for Clinical Research, Harvard Medical School, Boston, MA 02215, USA.
Giuseppe AmbrosioCenter for Clinical and Translational Research-CERICLET, University of Perugia School of Medicine, Perugia 06126, Italy.ORCID 0000-0002-9677-980X
University of Florence · ITUniversity of Perugia · ITMultiMedica · ITHarvard University · US

Funding

IRCCS 2020-23670065Italian Ministry of Health
6 · The paper itself

Abstract

backgroundHow coronavirus disease 2019 (COVID-19) impacted non-ST-segment elevation acute coronary syndromes (NSTACS) is an object of controversial reports.

aimTo systematically review studies reporting NSTACS hospitalizations during the COVID-19 pandemic, and analyse whether differences in COVID-19 epidemiology, methodology of report, or public health-related factors could contribute to discrepant findings.

methodsComprehensive search (Medline, Embase, Scopus, Web of Science, Cochrane Register), of studies reporting NSTACS hospitalizations during the COVID-19 pandemic compared with a reference period, following Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. Data were independently extracted by multiple investigators and pooled using a random-effects model. Health-related metrics were from publicly available sources, and analysed through multiple meta-regression modelling.

resultsWe retrieved 102 articles (553 038 NSTACS cases, 40 countries). During peak COVID-19 pandemic, overall incidence rate ratio (IRR) of NSTACS hospitalizations over reference period decreased (0.70, 95% confidence interval (CI) 0.66-0.75; P < 0.00001). Significant heterogeneity was detected among studies (I2 = 98%; P < 0.00001). Importantly, wide variations were observed among, and within, countries. No significant differences were observed by study quality, whereas comparing different periods within 2020 resulted in greater decrease (IRR: 0.61; CI: 0.53-0.71) than comparing 2020 vs. previous years (IRR: 0.74; CI 0.69-0.79). Among many variables, major predictors of heterogeneity were severe acute respiratory syndrome coronavirus 2 reproduction rate/country, number of hospitals queried, and reference period length; country stringency index and socio-economical indicators did not contribute significantly.

conclusionsDuring the COVID-19 pandemic, NSTACS hospitalizations decreased significantly worldwide. However, substantial heterogeneity emerged among countries, and within the same country. Factors linked to public health management, but also to methodologies to collect results may have contributed to this heterogeneity.

trial registrationThe protocol was registered in the PROSPERO International Prospective Register of Systematic Reviews (ID: CRD42022308159).

Indexed as

Acute Coronary SyndromeCOVID-19Global HealthHospitalizationSARS-CoV-2HumansPandemicsAcute coronary syndromesCoronavirusCOVID-19Healthcare organizationMyocardial infarctionNSTEMI

Identifiers

PMID37580157
PMCPMC11112522
OpenAlexW4385827799

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

None linked

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.