新型重症监护室患者转出率关联规则预测模型创建与预测效能比较  

Study on the construction of a association rule prediction model for transfer rate of intensive care unit patients and the comparison of the predictive performance

作　　者：张彩凤 温鸿毅 田龙[1] Zhang Caifeng;Wen Hongyi;Tian Long(Department of Intensive Care Unit,the First Affiliated Hospital of Hebei North University,Zhangjiakou 075000,China)

机构地区：[1]河北北方学院附属第一医院重症监护室,河北张家口075000

出　　处：《中国急救医学》2025年第2期122-128,共7页Chinese Journal of Critical Care Medicine

基　　金：河北省医学科学研究课题计划(20220589)。

摘　　要：目的创建新型模型预测重症监护室(ICU)患者转出率。以传统医学统计学模型为参考,评价和比较新型模型的预测效能。方法收集2011年2月至2023年2月河北北方学院附属第一医院ICU 4000例患者进行回顾性研究。经筛选后将其随机分为建模组(n=2370)和验证组(n=1630)。基于建模组基线资料和FP-Growth算法创建新型ICU患者转出率关联规则预测模型。新型模型内、外部验证分别采用校准曲线、临床决策曲线和受试者工作特征(ROC)曲线。基于建模组基线资料和多元Logistic回归分析创建传统医学统计学预测模型。以传统医学统计学模型为参考,评价和比较新型模型的预测效能。结果新型ICU患者转出率关联规则预测模型显示,患者基线资料组合符合1周内、1~2周、2~3周、3~4周转出标准时,转出率分别为70%、41%、19%、12%。新型模型内、外部验证结果显示,模型一致性良好且能够提供临床净收益;新型模型预测建模组和验证组患者特定时间内转出率ROC曲线下面积(AUC)差异无统计学意义(均P>0.05)。相比传统医学统计学预测模型的独立危险因素组成,新型模型前项组成更复杂,预测建模组患者特定时间内转出率的AUC更高(均P<0.05)。结论新型ICU患者转出率关联规则模型预测效能可满足临床要求,更适用于ICU患者的管理和资源配置的优化。Objective To create a new model to predict the transfer rate of the intensive care unit(ICU)patients and to evaluate and compare the predictive performance of the new model based on the traditional medical statistical model as the reference.Methods A retrospective study was conducted on the ICU patients(n=4000)in the First Affiliated Hospital of Hebei North University from February 2011 to February 2023.After screening,they were randomly divided into a modeling group(n=2370)and a validation group(n=1630).A new association rule prediction model for transfer rate of the ICU patients was created based on the baseline data from the modeling group and FP-Growth algorithm.The new model was validated internally and externally by using calibration curve,clinical decision curve and receiver operating characteristic(ROC)curve,respectively.A traditional medical statistical prediction model was created based on the baseline data from the modeling group and multiple Logistic regression analysis.The predictive performance of the new model was evaluated and compared based on the traditional medical statistical model as the reference.Results The new association rule prediction model for transfer rate of the ICU patients showed that when the baseline data combination of the patients met the transfer criteria within 1 week,1-2 weeks,2-3 weeks and 3-4 weeks,the transfer rates were 70%,41%,19%and 12%,respectively.The internal and external validation results of the new model showed good consistency and could provide clinical net benefits.There was no statistically significant difference in the area under ROC curve(AUC)for the transfer rate predicted by the new model at specific time between the patients from modeling group and the validation group(P>0.05).Compared with the independent risk factors of the traditional medical statistical prediction model,the composition of preceding item of the new model was more complex,and its AUC for the transfer rate of the patients from the modeling group at specific time was higher(all P<0.05).Co

关 键 词：重症监护室 关联规则分析 多元LOGISTIC回归分析 转出 管理 资料配置 

分 类 号：R47[医药卫生—护理学]