Evidence map›Paper›PMID 40684452›Full record

ArticleAnnals of medicine2025

The predictive value of hyaluronic acid for the severity and prognosis of COVID-19: a retrospective multicenter cohort study.

Genhua Mu, Yanjie Zhang, Jialong Zhang, Guangqing Cui, Xiaochun Yuan, Chun Pan, Jingyuan Xu

Abstract readMulticenter Study
In one paragraph

Article in Annals of medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Genhua MuDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Yanjie ZhangDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.
Jialong ZhangDepartment of Critical Care Medicine, Yancheng NO.1 People's Hospital, Yancheng, Jiangsu, China.
Guangqing CuiDepartment of Critical Care Medicine, Dongtai People's Hospital, Yancheng, Jiangsu, China.
Xiaochun YuanDepartment of Critical Care Medicine, Dafeng People's Hospital, Yancheng, Jiangsu, China.
Chun PanDepartment of Critical Care Medicine, Sichuan Academy of Medical Sciences and Sichuan People's Hospital, Chengdu, China.
Jingyuan XuDepartment of Critical Care Medicine, Zhongda Hospital, School of Medicine, Southeast University, Nanjing, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe aim of this study was to elucidate the relationship between HA levels and clinical outcomes, including disease severity and prognosis.

methodsA retrospective multicenter cohort analysis was conducted across three medical centers in China from September 2022 to February 2023. Patients with positive nucleic acid for the novel coronavirus were included in the study. The primary endpoint is 28-day mortality.The severity was assessed by the 'Diagnosis and Treatment Plan for Novel Coronavirus Pneumonia (Trial Version 9)'. Analyses assessed HA correlation with severity (Kendall), predictive value for mortality (logistic regression, ROC, Delong test), and survival differences (KM analysis using a Youden index-derived HA cutoff).

resultsA total of 862 patients (median age 72; 58.47% male) were included in the study, of whom 108 died. Non-survivors were older, more men, lower BMI, and more complicatinos. The overall median HA level was 121.65 ng/ml, significantly higher in non-survivors(

conclusionHA may potentially function as a biomarker for COVID-19 and could provide a vital reference for the clinical treatment.

Indexed as

COVID-19Hyaluronic AcidAgedAged, 80 and overBiomarkersChinaFemaleHumansMaleMiddle AgedPredictive Value of TestsPrognosisRetrospective StudiesSARS-CoV-2Severity of Illness IndexBiomarkersHyaluronic AcidbiomarkerCOVID-19Hyaluronic acidprognosisseverity

Identifiers

PMID40684452
PMCPMC12278463

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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.