基于睡眠期体动特征的无感睡眠监测床垫的应用效果评价  

Application effect of a non-contact sleep monitoring mattress based on body movement characteristics during sleep

作　　者：张燕春 刘艳 汪睿 王飞龙 赵悦 李飞 陈图南 鲜继淑 ZHANG Yanchun;LIU Yan;WANG Rui;WANG Feilong;ZHAO Yue;LI Fei;CHEN Tunan;XIAN Jishu(Department of Neurosurgery,First Affiliated Hospital,Army Medical University(Third Military Medical University),Chongqing,China)

机构地区：[1]陆军军医大学(第三军医大学)第一附属医院神经外科,重庆

出　　处：《陆军军医大学学报》2025年第4期326-334,共9页Journal of Army Medical University

摘　　要：目的验证基于睡眠期体动特征的无感睡眠监测床垫(non-contact sleep monitoring mattress,NCSMM)在神经外科术前患者睡眠质量评估中的准确性,旨在为临床医护人员提供更加便携有效的评估工具。方法采用单臂研究设计,便利抽样法抽取陆军军医大学(第三军医大学)第一附属医院神经外科住院患者114名,通过NCSMM、多导睡眠图(polysomnography,PSG)、患者报告结局测量信息系统(patient-reported outcomes measurement information system,PROMIS)睡眠障碍简表、理查兹-坎贝尔睡眠量表(Richards-Campbell sleep questionnaire,RCSQ)以及可穿戴设备手表共5种睡眠质量评估工具进行一晚的睡眠监测。以PSG监测的睡眠效率(≤85%)为诊断睡眠障碍的依据,计算NCSMM、PROMIS、ROSQ、可穿戴设备手表受试者工作特征(receiver operating characteristic,ROC)曲线下面积(area under the curve,AUC)、敏感度、特异度、阳性预测率、阴性预测率及Youden指数等指标,比较各工具的评估效果。结果NCSMM、PROMIS、RCSQ、可穿戴设备手表的AUC分别为0.788[95%CI(0.687,0.888),P<0.001]、0.664[95%CI(0.543,0.784),P=0.020]、0.723[95%CI(0.600,0.846),P=0.001]、0.750[95%CI(0.654,0.846),P<0.001],诊断准确率分别为0.774、0.559、0.742、0.602,Youden指数分别为0.488、0.321、0.456、0.459。NCSMM的AUC、诊断准确率、Youden指数均优于其他3种工具。结论NCSMM在神经外科术前住院患者睡眠质量评估中表现出一定的的准确性,可作为便携有效的评估工具。Objective To verify the accuracy of a Non-Contact Sleep Monitoring Mattress(NCSMM)based on body movement during sleep in assessing sleep quality of patients before neurosurgery in order to provide a more portable and efficient assessment tool for clinical staff.Methods A single-arm trial was conducted on 114 inpatients admitted in our department selected with convenience sampling.Sleep quality data of 1 night were collected through 5 sleep quality assessment tools,including NCSMM,polysomnography(PSG),Patient-Reported Outcome Measurement Information System(PROMIS)Sleep Disturbance scale,Richards-Campbell Sleep Scale(RCSQ),and a wearable device(smart watch for body movements and sleep quality monitoring).The sleep efficiency(≤85%)obtained by PSG was used as the diagnostic standard for sleep disorders.The area under the receiver operating characteristic curve(AUC),sensitivity,specificity,positive predictive value,negative predictive value,and Youden index were calculated for the other 4 tools to evaluate and compare their diagnostic effectiveness.Results The AUC value for NCSMM,PROMIS,RCSQ and smart watch was 0.788(95%CI:0.687~0.888,P<0.001),0.664(95%CI:0.543~0.784,P=0.02),0.723(95%CI:0.600~0.846,P=0.001)and 0.750(95%CI:0.654~0.846,P<0.001),respectively.The diagnostic accuracy rate was 0.774,0.559,0.742 and 0.602,with corresponding Youden index value of 0.488,0.321,0.456,and 0.459.NCSMM demonstrated the best AUC value,sensitivity and Youden index when compared with the other 3 tools.Conclusion NCSMM shows high accuracy in assessing sleep quality in pre-neurosurgery inpatients,and it is a viable portable and efficient assessment tool in clinical practice.

关 键 词：睡眠障碍 可穿戴设备 住院患者 护理评估 

分 类 号：R338.6[医药卫生—人体生理学] R473.74[医药卫生—基础医学] R741.041