Evidence map›Paper›PMID 34167463›Full record

ArticleBMC infectious diseases2021

Risk factors for mortality in critically ill patients with COVID-19: a multicenter retrospective case-control study.

Jinghua Gao, Li Zhong, Ming Wu, Jingjing Ji, Zheying Liu, Conglin Wang, Qifeng Xie, Zhifeng Liu

Abstract readMulticenter Study
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

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

14 citing papers in PubMed.

  1. Observational
  2. Article
  3. Prevalence and control of hypertension in COVID-19 positive cases.Journal of family medicine and primary care · 2024
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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

8 authors.

Jinghua Gao *The First School of Clinical Medicine, Southern Medical University, Guangzhou, 510010, China.
Li Zhong *Department of Critical Care Medicine, The First Affiliated Hospital, Guizhou University of Chinese Medicine, Guiyang, 550001, China.
Ming WuDepartment of Critical Care Medicine and Infection Prevention and Control, Health Science Center, The Second People's Hospital of Shenzhen & First Affiliated Hospital of Shenzhen University, Shenzhen, 518035, China.
Jingjing JiDepartment of Critical Care Medicine, General Hospital of Southern Theater Command of PLA, Guangzhou, 510010, China.
Zheying LiuDepartment of Critical Care Medicine, General Hospital of Southern Theater Command of PLA, Guangzhou, 510010, China.
Conglin WangDepartment of Critical Care Medicine, General Hospital of Southern Theater Command of PLA, Guangzhou, 510010, China.
Qifeng XieDepartment of Critical Care Medicine, General Hospital of Southern Theater Command of PLA, Guangzhou, 510010, China.
Zhifeng LiuThe First School of Clinical Medicine, Southern Medical University, Guangzhou, 510010, China. Zhifengliu7797@163.com.ORCID http://orcid.org/0000-0001-6273-1667

Funding

Clinical Research Project of Shenzhen municipal health commission SZLY2017007Sanming Project of Medicine in Shenzhen SZSM20162011the PLA Logistics Research Project of China 18CXZ030, CWH17L020, 17CXZ008
6 · The paper itself

Abstract

backgroundCoronavirus disease 2019 (COVID-19) has spread around the world, until now, the number of positive and death cases is still increasing. Therefore, it remains important to identify risk factors for death in critically patients.

methodsWe collected demographic and clinical data on all severe inpatients with COVID-19. We used univariable and multivariable Cox regression methods to determine the independent risk factors related to likelihood of 28-day and 60-day survival, performing survival curve analysis.

resultsOf 325 patients enrolled in the study, Multi-factor Cox analysis showed increasing odds of in-hospital death associated with basic illness (hazard ratio [HR] 6.455, 95% Confidence Interval [CI] 1.658-25.139, P = 0.007), lymphopenia (HR 0.373, 95% CI 0.148-0.944, P = 0.037), higher Sequential Organ Failure Assessment (SOFA) score on admission (HR 1.171, 95% CI 1.013-1.354, P = 0.033) and being critically ill (HR 0.191, 95% CI 0.053-0.687, P = 0.011). Increasing 28-day and 60-day mortality, declining survival time and more serious inflammation and organ failure were associated with lymphocyte count < 0.8 × 109/L, SOFA score > 3, Acute Physiology and Chronic Health Evaluation II (APACHE II) score > 7, PaO2/FiO2 < 200 mmHg, IL-6 > 120 pg/ml, and CRP > 52 mg/L.

conclusionsBeing critically ill and lymphocyte count, SOFA score, APACHE II score, PaO2/FiO2, IL-6, and CRP on admission were associated with poor prognosis in COVID-19 patients.

Indexed as

Critical IllnessSARS-CoV-2AdultAPACHECase-Control StudiesCOVID-19Hospital MortalityHumansInflammationLymphopeniaMaleMiddle AgedOrgan Dysfunction ScoresPrognosisRetrospective StudiesRisk FactorsCOVID-19MortalityRisk factorsSARS-COV-2

Identifiers

PMID34167463
PMCPMC8223178

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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.