Evidence map›Paper›PMID 38613736›Full record

ArticleDiscover oncology2024

Application value of intraoperative electrophysiological monitoring in cerebral eloquent area glioma surgery: a retrospective cohort study.

Yuankun Liu, Songyun Zhao, Jin Huang, Pengpeng Zhang, Qi Wang, Zhuwen Chen, Lingjie Zhu, Wei Ji, Chao Cheng

Open access · goldAbstract read
In one paragraph

Article in Discover oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.6field-weighted citation impact, top 35% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

9 authors at 4 institutions in 1 country.

Yuankun Liu *Department of Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Songyun Zhao *Department of Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Jin Huang *Department of Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Pengpeng ZhangDepartment of Lung Cancer Surgery, Tianjin Medical University Cancer Institute and Hospital, Tianjin, China.
Qi WangDepartment of Gastroenterology, Affiliated Hospital of Jiangsu University, Zhenjiang, China.
Zhuwen ChenDepartment of Functional Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China.
Lingjie ZhuDepartment of Pathophysiology, School of Medicine, Nantong University, Nantong, China.
Wei JiDepartment of Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China. jiwei@njmu.edu.cn.
Chao ChengDepartment of Neurosurgery, The Affiliated Wuxi People's Hospital of Nanjing Medical University, Wuxi, China. Mr_chengchao@126.com.
Wuxi People's Hospital · CNJiangsu University · CNNantong University · CNTianjin Medical University Cancer Institute and Hospital · CN

Funding

Basic Research Project of Wuxi Science and Technology Bureau K20221024Cohort and Clinical Research Program of Wuxi Medical Center, Nanjing Medical University WMCC202321Wuxi Taihu Lake Talent Plan, Supports for Leading Talents in Medical and Health Profession 2020THRC-DJ-SNWYouth project of Wuxi commission of Health Q202133
6 · The paper itself

Abstract

introductionSurgery for gliomas involving eloquent areas is a very challenging microsurgical procedure. Maximizing both the extent of resection (EOR) and preservation of neurological function have always been the focus of attention. Intraoperative neurophysiological monitoring (IONM) is widely used in this kind of surgery. The purpose of this study was to evaluate the efficacy of IONM in eloquent area glioma surgery.

methodsSixty-eight glioma patients who underwent surgical treatment from 2014 to 2019 were included in this retrospective cohort study, which focused on eloquent areas. Clinical indicators and IONM data were analysed preoperatively, two weeks after surgery, and at the final follow-up. Logistic regression, Cox regression, and Kaplan‒Meier analyses were performed, and nomograms were then established for predicting prognosis. The diagnostic value of the IONM indicator was evaluated by the receiver operating characteristic (ROC) curve.

resultsIONM had no effect on the postoperative outcomes, including EOR, intraoperative bleeding volume, duration of surgery, length of hospital stay, and neurological function status. However, at the three-month follow-up, the percentage of patients who had deteriorated function in the monitored group was significantly lower than that in the unmonitored group (23.3% vs. 52.6%; P < 0.05). Logistic regression analysis showed that IONM was a significant factor in long-term neurological function (OR = 0.23, 95% CI (0.07-0.70). In the survival analysis, long-term neurological deterioration indicated worsened overall survival (OS) and progression-free survival (PFS). A prognostic nomogram was established through Cox regression model analysis, which could predict the probability 3-year survival rate. The concordance index was 0.761 (95% CI 0.734-0.788). The sensitivity and specificity of IONM evoked potential (SSEP and TCeMEP) were 0.875 and 0.909, respectively. In the ROC curve analysis, the area under the curve (AUC) for the SSEP and TCeMEP curves was 0.892 (P < 0.05).

conclusionsThe application of IONM could improve long-term neurological function, which is closely related to prognosis and can be used as an independent prognostic factor. IONM is practical and widely available for predicting postoperative functional deficits in patients with eloquent area glioma.

Indexed as

FunctionGliomaIntraoperative neurophysiological monitoringRetrospective analysisSurvival

Identifiers

PMID38613736
PMCPMC11016029
OpenAlexW4394784586

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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.