Evidence map›Paper›PMID 33902676›Full record

ArticleCritical care (London, England)2021

Implications of cardiac markers in risk-stratification and management for COVID-19 patients.

Pengping Li, Wei Wu, Tingting Zhang, Ziyu Wang, Jie Li, Mengyan Zhu, Yuan Liang, Wenhua You, Kening Li, Rong Ding and 13 more

Open access · goldAbstract read
In one paragraph

Article in Critical care (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
1.4field-weighted citation impact, top 16% 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

13 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.

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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

23 authors at 5 institutions in 2 countries.

Pengping Li *Department of Bioinformatics, Nanjing Medical University, Nanjing, China.
Wei Wu *Department of Bioinformatics, Nanjing Medical University, Nanjing, China.
Tingting Zhang *Department of Bioinformatics, Nanjing Medical University, Nanjing, China.
Ziyu Wang *Department of Bioinformatics, Nanjing Medical University, Nanjing, China.
Jie LiDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Mengyan ZhuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Yuan LiangDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Wenhua YouDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Kening LiDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Rong DingDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Bin HuangDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Lingxiang WuDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Weiwei DuanDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Yi HanDepartment of Geriatrics, First Affiliated Hospital of Nanjing Medical University, Nanjing, China.
Xuesong LiKey Laboratory of Cardiovascular and Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing, China.
Xin TangKey Laboratory of Cardiovascular and Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing, China.
Xin WangFaculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK.
Han ShenDepartment of Laboratory Medicine, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China.
Qianghu WangDepartment of Bioinformatics, Nanjing Medical University, Nanjing, China.
Hong YanLaboratory Medicine Center, the Second Affiliated Hospital, Nanjing Medical University, Nanjing, China. yanhong@njmu.edu.cn.
Xinyi XiaCOVID-19 Research Center, Institute of Laboratory Medicine, Jinling Hospital, Nanjing University School of Medicine, Nanjing, China. xiaxynju@163.com.
Yong JiKey Laboratory of Cardiovascular and Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing, China. yongji@njmu.edu.cn.
Hongshan ChenKey Laboratory of Cardiovascular and Cerebrovascular Medicine, School of Pharmacy, Nanjing Medical University, Nanjing, China. hongshanchen@njmu.edu.cn.
Nanjing Medical University · CNNanjing Drum Tower Hospital · CNNanjing General Hospital of Nanjing Military Command · CNSecond Affiliated Hospital of Nanjing Medical University · CNUniversity of Manchester · GB

Funding

Innovative Research Group Project of the National Natural Science Foundation of China (CN) 91649125Key Foundation of Wuhan Huoshenshan Hospital Grant No. 2020[18]National Nature Science Foundation of China 31771334
6 · The paper itself

Abstract

backgroundCOVID-19 has resulted in high mortality worldwide. Information regarding cardiac markers for precise risk-stratification is limited. We aim to discover sensitive and reliable early-warning biomarkers for optimizing management and improving the prognosis of COVID-19 patients.

methodsA total of 2954 consecutive COVID-19 patients who were receiving treatment from the Wuhan Huoshenshan Hospital in China from February 4 to April 10 were included in this retrospective cohort. Serum levels of cardiac markers were collected after admission. Coronary artery disease diagnosis and survival status were recorded. Single-cell RNA-sequencing and bulk RNA-sequencing from different cohorts of non-COVID-19 were performed to analyze SARS-CoV-2 receptor expression.

resultsAmong 2954 COVID-19 patients in the analysis, the median age was 60 years (50-68 years), 1461 (49.5%) were female, and 1515 (51.3%) were severe/critical. Compared to mild/moderate (1439, 48.7%) patients, severe/critical patients showed significantly higher levels of cardiac markers within the first week after admission. In severe/critical COVID-19 patients, those with abnormal serum levels of BNP (42 [24.6%] vs 7 [1.1%]), hs-TNI (38 [48.1%] vs 6 [1.0%]), α- HBDH (55 [10.4%] vs 2 [0.2%]), CK-MB (45 [36.3%] vs 12 [0.9%]), and LDH (56 [12.5%] vs 1 [0.1%]) had a significantly higher mortality rate compared to patients with normal levels. The same trend was observed in the ICU admission rate. Severe/critical COVID-19 patients with pre-existing coronary artery disease (165/1,155 [10.9%]) had more cases of BNP (52 [46.5%] vs 119 [16.5%]), hs-TNI (24 [26.7%] vs 9.6 [%], α- HBDH (86 [55.5%] vs 443 [34.4%]), CK-MB (27 [17.4%] vs 97 [7.5%]), and LDH (65 [41.9%] vs 382 [29.7%]), when compared with those without coronary artery disease. There was enhanced SARS-CoV-2 receptor expression in coronary artery disease compared with healthy controls. From regression analysis, patients with five elevated cardiac markers were at a higher risk of death (hazards ratio 3.4 [95% CI 2.4-4.8]).

conclusionsCOVID-19 patients with pre-existing coronary artery disease represented a higher abnormal percentage of cardiac markers, accompanied by high mortality and ICU admission rate. BNP together with hs-TNI, α- HBDH, CK-MB and LDH act as a prognostic biomarker in COVID-19 patients with or without pre-existing coronary artery disease.

Indexed as

AgedBiomarkersChinaCoronary Artery DiseaseCOVID-19FemaleHospitalizationHumansMaleMiddle AgedPrognosisRetrospective StudiesRisk AssessmentBiomarkersCardiac markersCOVID-19SARS-CoV-2 receptor

Identifiers

PMID33902676
PMCPMC8074282
OpenAlexW3107248803

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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.