Evidence map›Paper›PMID 39444292›Full record

ArticleAnnals of medicine2024

Study on the predictive value of laboratory inflammatory markers and blood count-derived inflammatory markers for disease severity and prognosis in COVID-19 patients: a study conducted at a university-affiliated infectious disease hospital.

Zhipeng Wu, Yu Cao, Zhao Liu, Nan Geng, Wen Pan, Yueke Zhu, Hongbo Shi, Qingkun Song, Bo Liu, Yingmin Ma

Abstract read
In one paragraph

Article in Annals of medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Longitudinal analysis of systemic inflammatory biomarkers in glioblastoma patients: an exploratory single‑center analysis.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026
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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

10 authors.

Zhipeng WuDepartment of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Yu CaoDepartment of Clinical Epidemiology, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Zhao LiuDepartment of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Nan GengDepartment of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Wen PanDepartment of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Yueke ZhuDepartment of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Hongbo ShiBeijing Institute of Hepatology, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Qingkun SongDepartment of Clinical Epidemiology, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Bo LiuDepartment of Emergency Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.
Yingmin MaDepartment of Respiratory and Critical Care Medicine, Beijing Youan Hospital, Capital Medical University, Beijing, People's Republic of China.ORCID 0000-0002-2311-9712

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSince the outbreak of coronavirus disease 2019 (COVID-19), studies have found correlations between blood cell count-derived inflammatory markers (BCDIMs) and disease severity and prognosis in COVID-19 patients. However, there is currently a lack of systematic comparisons between procalcitonin (PCT), C-reactive protein (CRP), C-reactive protein-to-albumin ratio (CAR) and BCDIMs for assessing the severity and prognosis of COVID-19 patients.

methodsA total of 1040 COVID-19 patients were included in the study. Demographics, comorbidities and laboratory results were analysed. BCDIMs refer to the following ratios: neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-C-reactive protein ratio (LCR), systemic inflammation response index (SIRI) and systemic inflammation index (SII). Disease severity and 28-day mortality are clinical outcomes of this study. Area under the curve (AUC) of receiver operating characteristic (ROC) curve was calculated for these markers, and DeLong's test compared their statistical differences. Cox regression analysis assessed their predictive value for the 28-day mortality rate.

resultsAmong the 1040 patients, 35.3% were severe/critical, 49.6% were moderate and 15.1% were mild cases. Within 28 days, 15.1% died. The NLR had the highest predictive value for disease severity (AUC: 0.790, 95% CI: 0.762-0.818). NLR differed significantly from other markers, except LCR. LCR best predicted 28-day mortality (AUC: 0.798, 95% CI: 0.766-0.829). Some markers showed significant differences in AUC with LCR. Multivariable Cox regression identified BCDIMs, PCT, CRP and CAR as significant risk factors for 28-day mortality.

conclusionsPCT, CRP, CAR and BCDIMs, easily obtained in clinical settings, are valuable predictors of disease severity and the 28-day mortality in COVID-19 patients. The NLR is particularly effective for disease severity, while the LCR is highly predictive of 28-day mortality. These markers provide guidance for stratified management of COVID-19 patients.

Indexed as

BiomarkersCOVID-19C-Reactive ProteinPredictive Value of TestsProcalcitoninSeverity of Illness IndexAdultAgedBlood Cell CountFemaleHumansInflammationMaleMiddle AgedNeutrophilsPrognosisBiomarkersC-Reactive ProteinProcalcitoninSerum Albumin28-day mortalityBCDIMsCOVID-19disease severitylaboratory inflammatory markers

Identifiers

PMID39444292
PMCPMC11504162

What Socratic holds

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LicenceCC BY-NC
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Registered trials

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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 Socratic graph.