Evidence map›Paper›PMID 33384422›Full record

ArticleScientific reports2020

Development and validation of prognostic model for predicting mortality of COVID-19 patients in Wuhan, China.

Qi Mei, Amanda Y Wang, Amy Bryant, Yang Yang, Ming Li, Fei Wang, Jia Wei Zhao, Ke Ma, Liang Wu, Huawen Chen and 8 more

Open access · goldAbstract readMulticenter StudyValidation Study
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 24% 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Clinical significance of prognostic nutrition index in hospitalized patients with COVID-19: Results from single-center experience with systematic review and meta-analysis.Nutrition in clinical practice : official publication of the American Society for Parenteral and Enteral Nutrition · 2021
    Pooled it
  2. The Liver-Bone Axis in Steatotic Liver Disease.Calcified tissue international · 2026
    Review
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  4. A simple linear sweep voltammetric method for the detection of glucose using an Ag-Au/MWCNT nanocomposite-modified glassy carbon electrode.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2026
    Article
  5. Article
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  7. Sterically hindered phenolic azomethine dyes derived from aliphatic amines: solvatochromism, DFT studies and antioxidant activity.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2025
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
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  16. Article
  17. Predictors of COVID-19 severity among pregnant patients.Bosnian journal of basic medical sciences · 2022
    Article
  18. Article
  19. Article
  20. ABCInternational journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2021
    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

18 authors at 9 institutions in 4 countries.

Qi MeiTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Amanda Y WangThe Renal and Metabolic Division, The George Institute for Global Health, University of New South Wales, Sydney, Australia.
Amy BryantDepartment of Biomedical and Pharmaceutical Sciences, College of Pharmacy, Idaho State University, Meridian, ID, USA.
Yang YangRenmin Hospital of Wuhan University, Wuhan, Hubei, People's Republic of China.
Ming LiDepartment of Respiratory and Critical Care Medicine, Wuhan Pulmonary Hospital, Wuhan, Hubei, People's Republic of China.
Fei WangDepartment of Chinese Medicine, Wuhan No.1 Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Jia Wei ZhaoThe Faculty of Pharmacy, The University of Sydney, Sydney, Australia.
Ke MaDepartment and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Liang WuDepartment and Institute of Infectious Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Huawen ChenDepartment of Emergency Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Jinlong LuoDepartment of Emergency Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Shangming DuInstitute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany.
Kathrin HalfterInstitute for Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-University Munich, Munich, Germany.
Yong LiDepartment of Respiratory and Critical Care Medicine, National Clinical Research Center of Respiratory Disease, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China.
Christian KurtsInstitute of Experimental Immunology, University Clinic of Rheinische Friedrich-Wilhelms-University, Bonn, Germany.
Guangyuan HuTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China. h.g.y.121@163.com.
Xianglin YuanTongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, People's Republic of China. yuanxianglin@hust.edu.cn.
Jian LiInstitute of Experimental Immunology, University Clinic of Rheinische Friedrich-Wilhelms-University, Bonn, Germany.
Huazhong University of Science and Technology · CNTongji Hospital · CNLudwig-Maximilians-Universität München · DEIdaho State University · USRenmin Hospital of Wuhan University · CNThe George Institute for Global Health · AUUniversity of Sydney · AUWuhan No.1 Hospital · CNWuhan Pulmonary Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Novel coronavirus 2019 (COVID-19) infection is a global public health issue, that has now affected more than 200 countries worldwide and caused a second wave of pandemic. Severe adult respiratory syndrome-CoV-2 (SARS-CoV-2) pneumonia is associated with a high risk of mortality. However, prognostic factors predicting poor clinical outcomes of individual patients with SARS-CoV-2 pneumonia remain under intensive investigation. We conducted a retrospective, multicenter study of patients with SARS-CoV-2 who were admitted to four hospitals in Wuhan, China from December 2019 to February 2020. Mortality at the end of the follow up period was the primary outcome. Factors predicting mortality were also assessed and a prognostic model was developed, calibrated and validated. The study included 492 patients with SARS-CoV-2 who were divided into three cohorts: the training cohort (n = 237), the validation cohort 1 (n = 120), and the validation cohort 2 (n = 135). Multivariate analysis showed that five clinical parameters were predictive of mortality at the end of follow up period, including advanced age [odds ratio (OR), 1.1/years increase (p < 0.001)], increased neutrophil-to-lymphocyte ratio [(NLR) OR, 1.14/increase (p < 0.001)], elevated body temperature on admission [OR, 1.53/°C increase (p = 0.005)], increased aspartate transaminase [OR, 2.47 (p = 0.019)], and decreased total protein [OR, 1.69 (p = 0.018)]. Furthermore, the prognostic model drawn from the training cohort was validated with validation cohorts 1 and 2 with comparable area under curves (AUC) at 0.912, 0.928, and 0.883, respectively. While individual survival probabilities were assessed, the model yielded a Harrell's C index of 0.758 for the training cohort, 0.762 for the validation cohort 1, and 0.711 for the validation cohort 2, which were comparable among each other. A validated prognostic model was developed to assist in determining the clinical prognosis for SARS-CoV-2 pneumonia. Using this established model, individual patients categorized in the high risk group were associated with an increased risk of mortality, whereas patients predicted to be in the low risk group had a higher probability of survival.

Indexed as

Models, StatisticalMortalityAgedChinaCOVID-19FemaleHospitalizationHumansLymphopeniaMaleMiddle AgedMultivariate AnalysisPrognosisRetrospective StudiesRisk AssessmentRisk Factors

Identifiers

PMID33384422
PMCPMC7775455
OpenAlexW3113738142

What OpenQuestion holds

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LicenceCC BY
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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.