Evidence map›Paper›PMID 33568204›Full record

ArticleVirology journal2021

Pneumonia scoring systems for severe COVID-19: which one is better.

PengFei Cheng, Hao Wu, JunZhe Yang, XiaoYang Song, MengDa Xu, BiXi Li, JunJun Zhang, MingZhe Qin, Cheng Zhou, Xiang Zhou

Abstract read
In one paragraph

Article in Virology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
–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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  11. [Hematological indices associated with mortality in critically ill patients with COVID-19].Revista medica del Instituto Mexicano del Seguro Social · 2023
    Observational
  12. [COVID-19 mortality prediction. Comparison between two scales].Revista medica del Instituto Mexicano del Seguro Social · 2022
    Article
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  18. Analysis of mitochondrial function in lymphocytes obtained from COVID-19 patients.International journal of immunopathology and pharmacology
    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

10 authors.

PengFei Cheng *Department of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
Hao Wu *Department of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
JunZhe Yang *Department of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
XiaoYang SongDepartment of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
MengDa XuDepartment of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
BiXi LiDepartment of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
JunJun ZhangDepartment of Gastroenterology, General Hospital of Central Theater Command of PLA, Wuhan, China.
MingZhe QinDepartment of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China.
Cheng ZhouDepartment of Radiation Oncology, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Xiang ZhouDepartment of Anesthesiology, General Hospital of Central Theater Command of PLA, Wuhan, China. zhouxiang188483@126.com.ORCID 0000-0001-9635-8741

Funding

National Natural Science Foundation of China 81901932
6 · The paper itself

Abstract

purposeTo investigate the predictive significance of different pneumonia scoring systems in clinical severity and mortality risk of patients with severe novel coronavirus pneumonia. MATERIALS AND

methodsA total of 53 cases of severe novel coronavirus pneumonia were confirmed. The APACHE II, MuLBSTA and CURB-65 scores of different treatment methods were calculated, and the predictive power of each score on clinical respiratory support treatment and mortality risk was compared.

resultsThe APACHE II score showed the largest area under ROC curve in both noninvasive and invasive respiratory support treatment assessments, which is significantly different from that of CURB-65. Further, the MuLBSTA score had the largest area under ROC curve in terms of death risk assessment, which is also significantly different from that of CURB-65; however, no difference was noted with the APACHE II score.

conclusionFor patients with COVID, the APACHE II score is an effective predictor of the disease severity and mortality risk. Further, the MuLBSTA score is a good predictor only in terms of mortality risk.

Indexed as

AdultAgedAged, 80 and overAPACHECOVID-19FemaleHumansMaleMiddle AgedPneumoniaPrognosisRisk AssessmentROC CurveSARS-CoV-2Severity of Illness IndexYoung AdultAPACHE II scoreCURB-65 scoreDisease assessmentMuLBSTA scoreNovel coronavirus pneumonia

Identifiers

PMID33568204
PMCPMC7874994

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.