ICU经鼻高流量氧疗患者机械通气风险预测模型的建立

Establishment of a prediction model for mechanical ventilation in ICU patients with nasal high-flow oxygen therapy

目的建立重症监护室经鼻高流量氧疗患者最终行机械通气风险的预测模型,为临床提供便捷有效的预测方法及准确的治疗时机,提高ICU患者的预后。方法回顾性收集2019年1月至2021年12月本院重症监护室收治的经鼻高流量氧疗患者为研究对象。收集患者的一般临床资料,包括入院24 h内生命体征、血气生化指标、炎症指标、急性合并症、APACHEⅡ评分、ICU住院时长及总住院时长等,对上述指标进行统计学分析并构建列线图。结果本研究最终纳入362例患者,根据最终是否行机械通气分为经鼻高流量氧疗组(HFNC组)及氧疗失败行无创正压机械通气组(noninvasive positive pressure ventilation,NIPPV组)。将两组患者基线资料进行单因素及二元Logistic多因素回归分析后,结果表明APACHEⅡ评分(OR=1.323,95%CI:1.818~1.483)、ROX指数(OR=0.371,95%CI:0.226~0.609)、总住院时长(OR=1.097,95%CI:1.003~1.200)及合并急性呼吸衰竭(OR=2.456,95%CI:1.368~4.506)是决定患者是否行机械通气的独立影响因素。基于上述独立影响因素构建列线图,通过评估及验证模型显示,该模型的拟合优度R2为0.892,C-index为0.985;模型的校准曲线与理想曲线拟合较好,列线图与各独立影响因素的ROC曲线下面积分别为0.985、0.959、0.899、0.656和0.576,表明该模型比单独指标预测风险效能更高;决策曲线分析也显示出该列线图具有极高的临床获益性。结论影响经鼻高流量氧疗患者是否行机械通相关因素较多,本文通过单因素及多因素分析后将最具有价值的指标联合,建立了预测性能较好的评估患者风险的列线图,可进一步为临床医生提供简单有效的预测方法,提高患者的预后。

Objective To establish the prediction model of the ultimate risk of mechanical ventilation for patients undergoing nasal high-flow oxygen therapy in the intensive care unit(ICU),provide clinicians with a convenient and effective prediction method and accurate treatment timing,and improve the prognosis of ICU patients.Methods Patients admitted to the ICU of our hospital from January 2019 to December 2021 were retrospectively enrolled.General clinical data of the patients were collected,including vital signs,biochemical indices of blood gas,inflammatory indices,acute comorbidities,APACHEⅡscore,length of stay in ICU and total length of stay,within 24 h after admission.Statistical analysis was performed on the above indicators and a chart was constructed.Results Finally,362 patients were enrolled in this study,and were divided into the transnasal high flow oxygen therapy group(HFNC group)and noninvasive positive pressure ventilation group(NIPPV group)according to whether mechanical ventilation was finally performed.The univariate and binary Logistic multivariate regression analysis showed that APACHEⅡscore(OR=1.323,95%CI:1.818-1.483),ROX index(OR=0.371,95%CI:0.226-0.609),total length of stay(OR=1.097,95%CI:1.003-1.200)and complicating acute respiratory failure(OR=2.456,95%CI:1.368-4.506)were independent influencing factors for determining whether patients underwent mechanical ventilation.Based on the above independent influencing factors,the lipopograms were constructed.The goodness of fit R2 and C-index of the model were 0.892 and 0.985,respectively through evaluation and verification model.The calibration curve of the model fitted well with the ideal curve,and the areas under the ROC curve of the rosettes and independent factors were 0.985,0.959,0.899,0.656 and 0.576,respectively,indicating that the model was more effective than the independent index in predicting risk.Decision curve analysis also showed that the rosette had high clinical benefit.Conclusions There are many related factors affecting whether patients undergo mechanical ventilation after nasal high-flow oxygen therapy.In this paper,after univariate and multivariate analysis,the most valuable indicators are combined to establish a line chart with better predictive performance to assess patients'risk,which can further provide clinicians with simple and effective prediction methods and improve the prognosis of patients.