首页|糖尿病足患者并发脓毒症列线图预测模型的建立与评价

糖尿病足患者并发脓毒症列线图预测模型的建立与评价

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目的 建立预测糖尿病足患者并发脓毒症风险的列线图预测模型,为临床防治提供参考.方法 回顾并收集2022年1月至2023年3月在天津医科大学朱宪彝纪念医院住院的430例糖尿病足患者的临床资料,包括患者的年龄、性别、既往史、吸烟饮酒史、家族史、糖尿病病程、糖尿病足Texas分级及入院 24h内实验室指标.根据患者住院期间是否并发脓毒症分为脓毒症组和非脓毒症组;比较两组患者临床资料的差异;采用多因素Logistic回归分析筛选糖尿病足患者住院期间并发脓毒症的影响因素,并建立列线图预测模型;通过受试者工作特征曲线(ROC曲线)、校准曲线和决策曲线分析(DCA)对预测模型的效能进行评价;使用Bootstrap法进行内部验证.结果 430 例患者均纳入最终分析,其中 90 例患者在住院期间并发脓毒症,340 例未并发脓毒症.两组患者糖尿病病程、糖尿病足Texas分级、白细胞计数(WBC)、中性粒细胞计数(NEU)、淋巴细胞计数(LYM)、中性粒细胞与淋巴细胞比值(NLR)、血红蛋白(Hb)、白蛋白(Alb)、糖化血红蛋白(HbA1c)、C-反应蛋白(CRP)、血尿素氮(BUN)差异均有统计学意义.多因素Logistic回归分析显示,糖尿病病程[优势比(OR)=2.774,95%可信区间(95%CI)为 1.053~7.308,P=0.039]、糖尿病足Texas分级(OR=2.312,95%CI为 1.014~5.273,P=0.046)、WBC(OR=1.160,95%CI为 1.042~1.291,P=0.007)、HbA1c(OR=1.510,95%CI为 1.278~1.784,P<0.001)、CRP(OR=1.007,95%CI为 1.000~1.014,P=0.036)是糖尿病足患者住院期间并发脓毒症的独立危险因素,而Alb为保护因素(OR=0.885,95%CI为 0.805~0.972,P=0.011);基于以上 6 个指标构建列线图预测模型.ROC曲线分析显示,列线图预测模型识别脓毒症患者的ROC曲线下面积(AUC)为 0.919(95%CI为0.889~0.948);内部验证显示,该预测模型的AUC为 0.918(95%CI为 0.887~0.946).Hosmer-Lemeshow检验显示,χ2=2.978,P=0.936,说明预测模型的校准度较好;校准曲线显示,该模型对脓毒症的预测概率与实际概率一致性较好.DCA曲线提示该模型具有良好的临床有效性.结论 基于糖尿病病程、糖尿病足Texas分级、WBC、HbA1c、CRP、Alb 6 个影响因素构建的列线图预测模型对于糖尿病足患者住院期间脓毒症的发生具有良好的预测价值,有助于临床医师筛查糖尿病足患者进展为脓毒症的可能性,及时针对不同患者进行个体化干预.
Establishment and evaluation of a nomogram model for predicting the risk of sepsis in diabetic foot patients
Objective To establish a nomogram model for predicting the risk of sepsis in diabetic foot patients,and to provide reference for clinical prevention and treatment.Methods The clinical data of 430 patients with diabetic foot who were hospitalized in Chu Hsien-I Memorial Hospital of Tianjin Medical University from January 2022 to March 2023 were reviewed and collected,including age,gender,past medical history,smoking and drinking history,family history,diabetes course,Texas grade of diabetic foot and laboratory indicators within 24 hours after admission.Patients were divided into sepsis group and non-sepsis group according to the presence or absence of sepsis during hospitalization.The differences in clinical data between the two groups were compared.Multivariate Logistic regression analysis was used to screen the influencing factors of sepsis in patients with diabetic foot during hospitalization,and a nomogram predictive model was established.The performance of the prediction model was evaluated by receiver operator characteristic curve(ROC curve),calibration curve and decision curve analysis(DCA).Internal validation was performed by using Bootstrap method.Results A total of 430 patients were enrolled,among which 90 patients developed sepsis during hospitalization and 340 patients did not.There were statistically significant differences in diabetes course,Texas grade of diabetic foot,white blood cell count(WBC),neutrophil count(NEU),lymphocyte count(LYM),neutrophil to lymphocyte ratio(NLR),hemoglobin(Hb),albumin(Alb),glycosylated hemoglobin(HbA1c),C-reactive protein(CRP),and blood urea nitrogen(BUN)between the two groups.Multivariate Logistic regression analysis showed that diabetes course[odds ratio(OR)=2.774,95%confidence interval(95%CI)was 1.053-7.308,P=0.039],Texas grade of diabetic foot(OR=2.312,95%CI was 1.014-5.273,P=0.046),WBC(OR=1.160,95%CI was 1.042-1.291,P=0.007),HbA1c(OR=1.510,95%CI was 1.278-1.784,P<0.001),CRP(OR=1.007,95%CI was 1.000-1.014,P=0.036)were independent risk factors for sepsis in patients with diabetic foot during hospitalization,while Alb was a protective factor(OR=0.885,95%CI was 0.805-0.972,P=0.011).A nomogram predictive model was constructed based on the above 6 indicators.The ROC curve showed that the area under ROC curve(AUC)of the nomogram predictive model for identifying the sepsis patients was 0.919(95%CI was 0.889-0.948).The AUC of the nomogram predictive model after internal verification was 0.918(95%CI was 0.887-0.946).Hosmer-Lemeshow test showedχ2=2.978,P=0.936,indicating that the calibration degree of the predictive model was good.Calibration curve showed that the predicted probability of sepsis was in good agreement with the actual probability.DCA curve showed that the nomogram predictive model had good clinical usefulness.Conclusion The nomogram predictive model based on the risk factors of diabetes course,Texas grade of diabetic foot,WBC,HbA1c,CRP and Alb has good predictive value for the occurrence of sepsis in patients with diabetic foot during hospitalization,which is helpful for clinical screening of the possibility of diabetic foot patients progressing to sepsis,and timely personalized intervention for different patients.

Diabetic footFoot ulcerSepsisPredictive modelNomogram

林令君、王俊伟、万永丽、高杨

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国家卫健委激素与发育重点实验室,天津市代谢性疾病重点实验室,天津市内分泌研究所,天津医科大学朱宪彝纪念医院感染管理科,天津 300134

国家卫健委激素与发育重点实验室,天津市代谢性疾病重点实验室,天津市内分泌研究所,天津医科大学朱宪彝纪念医院ICU,天津 300134

国家卫健委激素与发育重点实验室,天津市代谢性疾病重点实验室,天津市内分泌研究所,天津医科大学朱宪彝纪念医院糖尿病足科,天津 300134

糖尿病足 足溃疡 脓毒症 预测模型 列线图

天津市医学重点学科建设项目

TJYXZDXK-032A

2024

中华危重病急救医学
中华医学会

中华危重病急救医学

CSTPCD北大核心
影响因子:3.049
ISSN:2095-4352
年,卷(期):2024.36(7)
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