首页|期刊导航|护理研究|急性胰腺炎病人应激性高血糖持续时间的影响因素及其预测模型的构建

急性胰腺炎病人应激性高血糖持续时间的影响因素及其预测模型的构建OA

Influencing factors of the duration of stress hyperglycemia in patients with acute pancreatitis and the construction of its prediction model

中文摘要英文摘要

目的:分析急性胰腺炎病人应激性高血糖持续时间的影响因素,并构建其预测模型.方法:采用便利抽样法,选取2022年3月—2024年11月江苏省人民医院宿迁医院收治的急性胰腺炎病人206例为研究对象.收集病人临床资料,根据应激性高血糖持续时间分为应激性高血糖≥48 h组和应激性高血糖<48 h组.采用单因素及多因素Logistic回归分析探讨急性胰腺炎病人应激性高血糖持续时间的影响因素,基于决策树算法构建病人应激性高血糖≥48 h的风险预测模型.采用受试者工作特征曲线(ROC)评估Logistic回归模型与决策树模型的预测效能.结果:206例急性胰腺炎病人中,应激性高血糖≥48 h者41例(19.90%).应激性高血糖≥48 h组与应激性高血糖<48 h组病人的高血压、入院血糖水平、急性生理和慢性健康状况Ⅱ(APACHEⅡ)评分、全身炎症反应综合征(SIRS)、疼痛、营养风险情况比较,差异有统计学意义(P<0.05).多因素 Logistic回归分析显示,病人入院血糖水平、APACHEⅡ评分、SIRS、疼痛、有营养风险是急性胰腺炎病人应激性高血糖≥48 h的影响因素(P<0.05).决策树模型筛选出4个影响因素(疼痛、入院血糖水平、APACHEⅡ评分、营养风险),预测正确率为86.4%;疼痛与急性胰腺炎病人应激性高血糖≥48 h的相关性较强,当疼痛评分>2分、入院血糖水平>13.07 mmol/L且APACHEⅡ评分>7分时,急性胰腺炎病人发生应激性高血糖≥48 h的风险概率最高(88.2%).Logistic回归模型的ROC曲线下面积(AUC)为0.824,敏感度为82.9%,特异度为68.5%.决策树模型预测的 AUC 为 0.828,敏感度为 78.0%,特异度为 77.6%.两种模型预测效能比较,差异无统计学意义(Z=0.075,P=0.940).结论:急性胰腺炎病人应激性高血糖持续时间受多种因素影响,决策树模型与Logistic回归模型均具有良好预测价值,但决策树模型展现了各因素的交互影响作用,可联合使用两种模型,从不同层面促进护理干预策略的针对性及具体化.

Objective:To analyze the influencing factors of the duration of stress hyperglycemia in patients with acute pancreatitis,and to construct its predictive model.Methods:By using the convenience sampling method,a total of 206 patients with acute pancreatitis admitted to Suqian Hospital of Jiangsu Provincial People's Hospital from March 2022 to November 2024 were selected as the research subjects.The clinical data of the patients were collected.They were divided into the stress hyperglycemia≥48 hours group and the stress hyperglycemia<48 hours group according to the duration.Univariate and multivariate Logistic regression analysis were used to explore the influencing factors of the duration of stress hyperglycemia in patients.A risk prediction model for stress hyperglycemia of patients≥48 hours was constructed based on the decision tree algorithm.The predictive efficacy of the Logistic regression model and the decision tree model was evaluated by using the receiver operating characteristic curve(ROC).Results:Among 206 patients with acute pancreatitis,41 cases(19.90%)had stress hyperglycemia for≥48 hours.There were statistically significant differences in hypertension,admission blood glucose level,Acute Physiology and Chronic Health EvaluationⅡ(APACHEⅡ)scores,systemic inflammatory response syndrome(SIRS),pain,and nutritional risk between the stress hyperglycemia≥48 hours group and the stress hyperglycemia<48 hours group(P<0.05).Multivariate Logistic regression analysis showed that the patients'admission blood glucose level,APACHEⅡ scores,SIRS,pain,and nutritional risk were the influencing factors of stress hyperglycemia≥48 hours in patients with acute pancreatitis(P<0.05).The decision tree model screened out four influencing factors(pain,blood glucose level at admission,APACHE Ⅱ scores,and nutritional risk),with a prediction accuracy rate of 86.4%.The correlation between pain and stress hyperglycemia≥48 hours in patients with acute pancreatitis was relatively stronger.When the pain score was>2 points,the admission blood glucose level was>13.07 mmol/L.The APACHEⅡ score was>7.The risk probability of stress hyperglycemia≥48 hours in patients with acute pancreatitis was the highest(88.2%).The area under curve(AUC)of the Logistic regression model was 0.824,with a sensitivity of 82.9%and a specificity of 68.5%.The AUC predicted by the decision tree model was 0.828,with a sensitivity of 78.0%and a specificity of 77.6%.There was no statistically significant difference in terms of the predictive efficacy between the two models(Z=0.075,P=0.940).Conclusions:The duration of stress hyperglycemia in patients with acute pancreatitis was influenced by multiple factors.Both the decision tree model and the Logistic regression model have good predictive value.However,the decision tree model demonstrates the interactive influence of various factors.Therefore,the two models could be used in combination to promote the targeted and specific natures of nursing intervention strategies from different levels.

王雪健;陈雪茹;汤娜娜

江苏省人民医院宿迁医院(宿迁市第一人民医院),江苏 223800江苏省人民医院宿迁医院(宿迁市第一人民医院),江苏 223800江苏省人民医院宿迁医院(宿迁市第一人民医院),江苏 223800

急性胰腺炎应激性高血糖持续时间影响因素决策树预测模型

acute pancreatitisstress hyperglycemiadurationinfluencing factorsdecision treepredictive model

《护理研究》 2026 (8)

1265-1273,9

宿迁市科学技术局科研项目,编号:SY202219

10.12102/j.issn.1009-6493.2026.08.004

评论