Evidence map›Paper›PMID 41291519›Full record

Observational studyBMC infectious diseases2025

LDH to lymphocyte percentage ratio is a novel predictor of in-hospital mortality in PLWH - a retrospective study.

Xiaoting Xie, Jingzhen Lai, Zhiman Xie, Wudi Wei, Sufang Ai, Rongfeng Chen, Zongxiang Yuan, Sirun Meng, Li Ye, Junjun Jiang and 1 more

Abstract readObservational Study
In one paragraph

Observational study in BMC infectious diseases, 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

11 authors.

Xiaoting Xie *Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Jingzhen Lai *Guangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Zhiman Xie *Infectious Disease Department, No. 4th People's Hospital of Nanning, Nanning, Guangxi, 530021, China.
Wudi WeiGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Sufang AiInfectious Disease Department, No. 4th People's Hospital of Nanning, Nanning, Guangxi, 530021, China.
Rongfeng ChenGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Zongxiang YuanGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Sirun MengGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China.
Li YeGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China. yeli@gxmu.edu.cn.
Junjun JiangGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China. jiangjunjun@gxmu.edu.cn.
Hao LiangGuangxi Key Laboratory of AIDS Prevention and Treatment, School of Public Health, Guangxi Medical University, Nanning, Guangxi, 530021, China. lianghao@gxmu.edu.cn.

Funding

First-class discipline innovation-driven talent program of Guangxi Medical University to LJNational Natural Science Foundation of China 82304203Natural Science Foundation of Guangxi Province 2023GXNSFBA026093
6 · The paper itself

Abstract

backgroundHuman immunodeficiency virus (HIV) infection and acquired immune deficiency syndrome (AIDS) present significant global health challenges. Over time, the condition has evolved into a chronic disease, requiring continuous monitoring of inflammation and immune status to guide treatment strategies. This study aimed to evaluate various combinations of hematological, immunological, and biochemical parameters in PLWH with HIV/AIDS-related conditions to identify cost-effective biomarkers for predicting in-hospital mortality of people living with HIV(PLWH).

methodsThis retrospective, observational study included 7,855 PLWH with HIV/AIDS-related admissions between 2011 and 2019. We extracted medical records and laboratory test results from the subjects. Receiver Operating Characteristic (ROC) curve analysis was performed to assess the ability of all biochemical indicators to differentiate in-hospital mortality. Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and Backpropagation Neural Network (BP-NN) models were developed and evaluated, and the importance score of each feature was calculated in the optimal model. Additionally, multivariate Logistic Regression (LR) analysis and a SHAP-based (SHapley Additive exPlanations) LR model were used to compare selected indicators with key traditional variables, evaluating their predictive value for in-hospital mortality in PLWH hospitalized for HIV/AIDS-related conditions.

resultsThis study analyzed 46 basic biochemical parameters and 1,041 composite ratios. The Lactate Dehydrogenase to Lymphocyte Percentage Ratio (LDH to lymphocyte percentage ratio, L-LWR) achieved the highest area under the curve (AUC) of 0.716 (95% CI: 0.695–0.738, P < 0.001) in ROC analysis. In the XGBoost model, which performed best on the test set, L-LWR ranked fourth in feature importance, making it the highest-ranked biochemical indicator. Multivariate logistic regression identified clinical stage 3 (OR: 3.05, 95% CI: 1.44–6.45, P < 0.001) and high L-LWR (> 24.441) (OR: 2.55, 95% CI: 2.04–3.20, P < 0.001) as significant risk factors. In the SHAP-based LR model, high L-LWR had the most significant impact on the model’s output (P < 0.001).

conclusionL-LWR is a potential predictor of in-hospital mortality in PLWH hospitalized for HIV/AIDS-related conditions. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

HIV InfectionsHospital MortalityL-Lactate DehydrogenaseLymphocytesAdultBiomarkersBoosting Machine Learning AlgorithmsFemaleHumansLogistic ModelsLymphocyte CountMaleMiddle AgedRetrospective StudiesROC CurveSupport Vector MachineBiomarkersL-Lactate DehydrogenaseHIV/AIDSIn-hospital mortalityLDH to lymphocyte percentage ratioMachine learningPrognostic index

Identifiers

PMID41291519
PMCPMC12752228

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

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.