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基于决策树和随机森林算法模型预测醛固酮瘤患者术后血压恢复情况

关兆娟 薛舒婷 谷婷钰 张岩波 王彦

山西医科大学学报2025,Vol.56Issue(2):127-133,7.
山西医科大学学报2025,Vol.56Issue(2):127-133,7.DOI:10.13753/j.issn.1007-6611.2025.02.003

基于决策树和随机森林算法模型预测醛固酮瘤患者术后血压恢复情况

Prediction of postoperative blood pressure recovery in aldosterone-producing adenoma patients based on decision tree and random forest models

关兆娟 1薛舒婷 1谷婷钰 2张岩波 1王彦3

作者信息

  • 1. 山西医科大学公共卫生学院卫生统计学教研室,太原 030001
  • 2. 山西医科大学第一临床医学院内分泌科
  • 3. 山西医科大学第一医院内分泌科
  • 折叠

摘要

Abstract

Objective To construct decision tree and random forest models for predicting the postoperative blood pressure recovery in patients with aldosterone-producing adenoma,evaluate their predictive performance,and identify key factors affecting postoperative blood pressure recovery.Methods Clinical data of 211 aldosterone-producing adenoma patients were collected,and the patients were divided into training set and testing set at a ratio of 7∶3.Decision tree and random forest models were built using the training set to predict the postoperative blood pressure recovery in aldosterone-producing adenoma patients,and the models were validated using the testing set.The performance of both models was compared to assess their effectiveness in predicting postoperative blood pressure re-covery.Results Among the 211 aldosterone-producing adenoma patients,79 patients achieved normal blood pressure postopera-tively,while 132 patients showed improvement but did not fully recover.The cure rate of postoperative blood pressure was 37.4%.There were significant differences between the two groups in terms of age,body mass index,duration of hypertension,and estimated glomerular filtration rate(P<0.05).The decision tree model achieved an accuracy of 0.75,a specificity of 0.82,a sensitivity of 0.64,AUC of 0.79,and an F1 score of 0.67.The random forest model achieved an accuracy of 0.81,a specificity of 0.87,a sensitivity of 0.72,AUC of 0.87,and an F1 score of 0.75.Therefore,the random forest model was better than the decision tree model in predictive performance.Conclusion The random forest model can more accurately predict the postoperative blood pressure recovery in aldoste-rone-producing adenoma patients and effectively identify key influencing factors such as age,BMI,duration of hypertension,and eGFR.This model can provide the scientific evidence for clinical treatment and personalized management of postoperative blood pres-sure in aldosterone-producing adenoma patients.

关键词

醛固酮瘤/肾上腺切除术/血压/预测模型/决策树模型/随机森林算法模型/影响因素

Key words

aldosterone-producing adenoma/adrenalectomy/blood pressure/predictive model/decision tree model/ran-dom forest model/influencing factors

分类

临床医学

引用本文复制引用

关兆娟,薛舒婷,谷婷钰,张岩波,王彦..基于决策树和随机森林算法模型预测醛固酮瘤患者术后血压恢复情况[J].山西医科大学学报,2025,56(2):127-133,7.

山西医科大学学报

1007-6611

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