Evidence map›Paper›PMID 38467760›Full record

Observational studyScientific reports2024

NT-proBNP ratio is a potential predictor for COVID-19 outcomes in adult Chinese patients: a retrospective study.

Dan Li, Wu He, Bo Yu, Dao Wen Wang, Li Ni

Registry-linked trialAbstract readObservational Study
In one paragraph

Observational study in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05615792 (Observational Cohort of The Effects of Clinical Indicators, Drug Use and Genotypes on The Clinical Prognosis of COVID-19 Patients in Hubei Province), which is not on this map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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.

NCT05615792 completednot on this map

Observational Cohort of The Effects of Clinical Indicators, Drug Use and Genotypes on The Clinical Prognosis of COVID-19 Patients in Hubei Province

TypeobservationalSponsorDao Wen WangRan2020 to 2024Enrolled68,000Conditions2019 Novel Coronavirus DiseaseArmsNo intervention
3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Observational
  2. Review
  3. 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

5 authors.

Dan Li *Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China.
Wu He *Division of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China.
Bo YuDivision of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China.
Dao Wen WangDivision of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China.
Li NiDivision of Cardiology, Department of Internal Medicine and Hubei Key Laboratory of Genetics and Molecular Mechanisms of Cardiological Disorders, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, 1095# Jiefang Ave., Wuhan, 430030, China. nili@tjh.tjmu.edu.cn.

Funding

National Natural Science Foundation of China 81470519National Natural Science Foundation of China 82070354National Natural Science Foundation of China 82100526National Natural Science Foundation of China No. 82241034National Natural Science Foundation of China No. 82330010
6 · The paper itself

Abstract

Despite the progressive decline in the virulence of the novel coronavirus, there has been no corresponding reduction in its associated hospital mortality. Our aim was to redefine an accurate predictor of mortality risk in COVID-19 patients, enabling effective management and resource allocation. We conducted a retrospective analysis of 2917 adult Chinese patients diagnosed with COVID-19 who were admitted to our hospital during two waves of epidemics, involving the Beta and Omicron variants. Upon admission, NT-proBNP levels were measured, and we collected demographic, clinical, and laboratory data. We introduced a new concept called the NT-proBNP ratio, which measures the NT-proBNP level relative to age-specific maximum normal values. The primary outcome was all-cause in-hospital mortality. Our analysis revealed a higher in-hospital mortality rate in 2022, as shown by the Kaplan-Meier Survival Curve. To assess the predictive value of the NT-proBNP ratio, we employed the time-dependent receiver operating characteristic (ROC) curve. Notably, the NT-proBNP ratio emerged as the strongest predictor of mortality in adult Chinese hospitalized COVID-19 patients (area under the curve, AUC = 0.826; adjusted hazard ratio [HR], 3.959; 95% confidence interval [CI] 3.001-5.221; P < 0.001). This finding consistently held true for both the 2020 and 2022 subgroups. The NT-proBNP ratio demonstrates potential predictive capability compared to several established risk factors, including NT-proBNP, hsCRP, and neutrophil-to-lymphocyte ratio, when it comes to forecasting in-hospital mortality among adult Chinese patients with COVID-19.Trial registration Clinical Trial Registration: www.clinicaltrials.gov NCT05615792.

Indexed as

COVID-19AdultBiomarkersChinaHumansNatriuretic Peptide, BrainPeptide FragmentsPrognosisRetrospective StudiesROC CurveSARS-CoV-2BiomarkersNatriuretic Peptide, BrainPeptide Fragmentspro-brain natriuretic peptide (1-76)COVID-19In-hospital mortalityNT-proBNP ratioTime-dependent ROC curve

Identifiers

PMID38467760
PMCPMC10928211

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Registered trials

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.