Evidence map›Paper›PMID 42291309›Full record

ArticleFrontiers in cellular and infection microbiology2026

Single and combined use of the platelet-lymphocyte ratio and neutrophil-lymphocyte ratio in hemorrhagic fever with renal syndrome.

Ting Wang, Kai Qi, Yaoni Li, Qiujian Zhao, Yazhou Yao, Lilan Zheng, Xingxing Zheng, Haodong Shi

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Article in Frontiers in cellular and infection microbiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Ting WangClinical Laboratory, Baoji Central Hospital, Baoji, Shaanxi, China.
Kai QiClinical Laboratory, Baoji Central Hospital, Baoji, Shaanxi, China.
Yaoni LiClinical Laboratory, Baoji Central Hospital, Baoji, Shaanxi, China.
Qiujian ZhaoClinical Laboratory, Baoji Central Hospital, Baoji, Shaanxi, China.
Yazhou YaoClinical Laboratory, Baoji Central Hospital, Baoji, Shaanxi, China.
Lilan ZhengClinical Laboratory, Fujian Provincial Hospital South Branch, Fuzhou, Fujian, China.
Xingxing ZhengRadiology Department, Baoji Central Hospital, Baoji, Shaanxi, China.
Haodong ShiOrthopedics Department, Baoji Central Hospital, Baoji, Shaanxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to evaluate the diagnostic performance of the platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) in hemorrhagic fever with renal syndrome (HFRS). Methods: This retrospective study included 215 patients with HFRS (HFRS group) and 256 healthy controls (HC group). Peripheral blood samples were collected to measure platelet counts (PLT), and PLR and NLR were subsequently calculated. Multivariate logistic regression was used to adjust for the confounding effects of age and gender. Receiver operating characteristic (ROC) curves, net reclassification improvement (NRI) and integrated discrimination improvement (IDI) assessed their predictive performance. Results: For HFRS diagnosis, the AUC of PLR (0.8141; 95% CI 0.7682-0.8600) was higher than that of NLR (0.6412; 95% CI 0.5882-0.6942). PLT count achieved the highest AUC (0.8729; 95% CI 0.8356-0.9102), specificity (94.92%) and sensitivity (76.74%). The combined PLT, PLR, and NLR achieved a significantly greater AUC (0.9029, NRI 0.234, IDI 0.002, all P < 0.05) than individual indicators. After adjusting for age and gender, PLT, PLR, and NLR remained significant independent predictors of HFRS. NLR showed a significant age - dependent increase, with older patients exhibiting the highest values. Conclusion: PLT, PLR, and NLR especially their combination, may be valuable and accessible biomarkers for the adjunctive diagnosis of HFRS.

Indexed as

Blood PlateletsHemorrhagic Fever with Renal SyndromeLymphocytesNeutrophilsAdultBiomarkersFemaleHumansLymphocyte CountMaleMiddle AgedPlatelet CountRetrospective StudiesROC CurveSensitivity and SpecificityBiomarkersdiagnosishemorrhagic fever with renal syndromeneutrophil-lymphocyte ratioplatelet countsplatelet-lymphocyte ratio

Identifiers

PMID42291309
PMCPMC13259994

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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.