Evidence mapPaperPMID 40910541Full record

ArticleJournal of global health2025

Health risk assessment for severe COVID-19 in Taiwan: a multi-centre electronic health record study.

Yu-Hui Chang, Whitney Burton, Phung-Anh Nguyen, Do Duy Khang, Chang-I Chen, Chung-Chien Huang, Carlos Shu-Kei Lam, Wen-Kuang Lin, Fu-Der Wang, Phan Thanh Phuc and 8 more

Abstract readMulticenter Study
In one paragraph

Article in Journal of global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing 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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Yu-Hui Chang *School of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Whitney Burton *International Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.
Phung-Anh NguyenGraduate Institute of Data Science, College of Management, Taipei Medical University, Taipei City, Taiwan.
Do Duy KhangPh.D. Program in Global Health and Health Security, School of Public Health, Taipei Medical University, Taipei, Taiwan.
Chang-I ChenDepartment of Healthcare Administration, School of Management, Taipei Medical University, Taipei, Taiwan.
Chung-Chien HuangInternational Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.
Carlos Shu-Kei LamEmergency Department, Department of Emergency and Critical Care Medicine, Wan Fang Hospital, Taipei Medical University, Taipei, Taiwan.
Wen-Kuang LinSchool of Pharmacy, College of Pharmacy, Taipei Medical University, Taipei, Taiwan.
Fu-Der WangDivision of Infectious Diseases, Department of Internal Medicine, Taipei Medical University Hospital, Taipei, Taiwan.
Phan Thanh PhucInternational Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.
Christine Y LuKolling Institute, Faculty of Medicine and Health, The University of Sydney and the Northern Sydney Local Health District, Sydney, NSW, Australia.
Hsin-Lun LeeDepartment of Radiology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
Min-Huei HsuGraduate Institute of Data Science, College of Management, Taipei Medical University, Taipei City, Taiwan.
Chih-Wei HuangClinical Big Data Research Center, Taipei Medical University Hospital, Taipei Medical University, Taipei, Taiwan.
Hsuan-Chia YangDepartment of Healthcare Administration, School of Management, Taipei Medical University, Taipei, Taiwan.
Shiue-Ming LinResearch Center of Data Science on Health Care Industry, College of Management, Taipei Medical University, Taipei, Taiwan.
Chieh YangResearch Center of Data Science on Health Care Industry, College of Management, Taipei Medical University, Taipei, Taiwan.
Jason C HsuInternational Ph.D. Program in Biotech and Healthcare Management, College of Management, Taipei Medical University, Taipei, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As the global battle against COVID-19 continues, understanding the factors contributing to severe outcomes remains critical for public health strategies. We aim to identify the determinants significantly influencing severe COVID-19 infection and mortality among the general population in Taiwan. Methods: We conducted a retrospective cohort study using data extracted from the Taipei Medical University Clinical Research Database from 1 January 2022 to 31 December 2022. We defined the primary outcomes as severe COVID-19 infection, including hospitalisation, ventilator use, intubation, and mortality. We performed logistic regression analyses to explore the association of various factors, including demographic characteristics, body mass index (BMI), Charlson Comorbidity Index score, and multiple comorbidities. Results: Among 96 489 confirmed COVID-19 cases, 44 996 (46.6%) were classified as high-risk patients. Compared to females, male patients had significantly higher risks of ventilator use (odds ratio (OR) = 1.245; 95% confidence interval (CI) = 1.147-1.352, P < 0.0001), intubation (OR = 1.115; 95% CI = 1.011-1.230, P = 0.03), and mortality (OR = 1.510; 95% CI = 1.332-1.713, P < 0.0001). Patients with lower BMI had significantly increased risks of ventilator use (OR = 0.972; 95% CI = 0.964-0.981, P < 0.0001) and mortality (OR = 0.92; 95% CI = 0.908-0.935, P < 0.0001), compared to patients with higher BMI. Patients with chronic comorbidities such as heart disease, moderate to severe kidney disease, diabetes, cancer, hypertension, anaemia, and Parkinson disease had significantly higher risks of severe COVID-19 or mortality compared to those without these conditions. Conversely, patients with peptic ulcer disease or hyperlipidaemia seem to have lower risks of severity and mortality compared to those without these conditions. Conclusions: We found that being male, having a lower BMI, and having certain chronic conditions increased the risk of severe COVID-19 outcomes, while peptic ulcer disease and hyperlipidaemia were linked to reduced risks. These findings highlight the need for targeted public health strategies for high-risk groups.

Indexed as

COVID-19AdultAgedAged, 80 and overBody Mass IndexComorbidityElectronic Health RecordsFemaleHospitalizationHumansMaleMiddle AgedRespiration, ArtificialRetrospective StudiesRisk AssessmentRisk Factors

Identifiers

PMID40910541
PMCPMC12412269

What Socratic 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 Socratic graph.