Evidence map›Paper›PMID 41884344›Full record

ArticleFrontiers in neurology

Risk factors for pituitary apoplexy: a meta-analysis and development of a clinical prediction nomogram.

Haipeng Chen, Ning Huang, Rui Tang, Jin Chen, Guanjian Zhao

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

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1 · What the graph read from it

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Haipeng ChenDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Ning HuangDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Rui TangDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Jin ChenDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing, Medical University, Chongqing, China.
Guanjian ZhaoDepartment of Neurosurgery, The Second Affiliated Hospital of Chongqing, Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose: This study aimed to identify significant risk factors for pituitary apoplexy in patients with pituitary adenomas through a meta-analysis and to develop an individualized nomogram for clinical decision-making. Methods: A two-part investigation was conducted. First, a meta-analysis of published studies identified risk factors for pituitary apoplexy and calculated pooled odds ratios (ORs) and 95% confidence intervals (CIs). Second, a retrospective cohort of 234 patients was used to construct and validate a nomogram based on multivariate logistic regression. Results: The meta-analysis included six studies, revealing that non-functioning pituitary adenomas (OR = 1.93, 95% CI: 1.38-2.70), male sex (OR = 2.57, 95% CI: 1.85-3.58), and hypertension (OR = 2.53, 95% CI: 1.54-4.15) were significantly associated with pituitary apoplexy. The nomogram demonstrated excellent predictive performance with AUCs of 0.86 in the training set and 0.83 in the validation set. Calibration curves showed good agreement between predicted and observed probabilities. The Hosmer-Lemeshow test yielded P values of 1 and 0.272 in the training and validation cohorts, respectively. Decision curve analysis demonstrated significant net clinical benefit in both cohorts. Conclusion: This study identified key predictors of pituitary apoplexy and developed a nomogram that may help stratify risk and guide preventive and therapeutic strategies.

Indexed as

meta-analysisnomogrampituitary adenomapituitary apoplexyrisk prediction

Identifiers

PMID41884344
PMCPMC13008675

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