Evidence map›Paper›PMID 40928611›Full record

ArticleJournal of neuro-oncology2025

Utility and performance of cerebrospinal fluid cytology in discriminating central nervous system infections and brain tumors.

Miao Su, Huiqian Duan, Qian Lei, Zhimei Tan, Yuxin Shi, Jia Liu, Liqun Xu, Qiuxiang Li, Jing Li, Zhaohui Luo

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In one paragraph

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

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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

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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

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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.

Miao SuDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Huiqian DuanDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Qian LeiDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Zhimei TanDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Yuxin ShiDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Jia LiuDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Liqun XuDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Qiuxiang LiDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China.
Jing LiDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China. lijing.neurology@aliyun.com.
Zhaohui LuoDepartment of Neurology, Xiangya Hospital, Central South University, No.87 Xiangya Road, Kaifu District, Changsha, 410008, Hunan Province, China. luozhaohui_xy@csu.edu.cn.

Funding

Hunan Provincial Special Project for the Construction of Innovative Province 2023SK2025Innovative Construction Foundation of Hunan Province 2021SK4001National Key Research and Development Program of China 2022YFC2503802National Natural Science Foundation of China 82371412National Natural Science Foundation of Hunan province, China 2023JJ30924Scientific research project of Health Commission of Hunan Province B202303076019
6 · The paper itself

Abstract

BACKGROUND AND

objectiveDifferentiating central nervous system infections (CNSIs) from brain tumors (BTs) is difficult due to overlapping features and the limited individual indicators, and cerebrospinal fluid (CSF) cytology remains underutilized. To improve differential diagnosis, we developed a model based on 9 early, cost-effective cerebrospinal fluid parameters, including CSF cytology.

methodsPatients diagnosed with CNSIs or BTs at Xiangya Hospital of Central South University between October 1st, 2017 and March 31st, 2024 were enrolled and divided into the training set and the test set. Lasso analysis, random forest, and multivariable logistic regression were used to construct a diagnostic model to distinguish CNSIs from BTs by utilizing differences in basic CSF parameters and CSF cytology results. And its diagnostic efficacy was evaluated using the receiver operating characteristic (ROC) curve. A nomogram was used for model visualization.

resultsA total of 783 patients were included in this study. 9 important CSF parameters significantly contribute to the differentiation between CNSIs and BTs, including CSF pressure, protein, glucose, adenosine deaminase, chloride, and the counts of lymphocytes, monocytes, plasma cells and phagocytes. CSF phagocytes and monocytes were elevated in BTs, whereas lymphocytes and plasma cells were higher in CNSIs. The model demonstrated strong diagnostic performance, achieving an area under the ROC curve (AUC) of 0.889 in the training set and 0.900 in the test set.

conclusionsWe developed a diagnostic model based on 9 CSF indicators. In our study, CSF phagocytes and monocytes were associated with BTs, while lymphocytes and plasma cells indicated CNSIs.

Indexed as

Brain NeoplasmsCentral Nervous System InfectionsCerebrospinal FluidAdolescentAdultAgedChildCytodiagnosisDiagnosis, DifferentialFemaleHumansMaleMiddle AgedNomogramsRetrospective StudiesROC CurveBrain tumorCentral nervous system infectionCerebrospinal fluidDiagnostic modelDifferential diagnosis

Identifiers

PMID40928611

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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.