妊娠晚期孕妇发生睡眠障碍的危险因素分析及预测模型的构建

Analysis of risk factors for sleep disorders in pregnant women in the third trimester and establishment of prediction model

  • 摘要: 目的 探讨妊娠晚期孕妇发生睡眠障碍的危险因素,并构建预测列线图。方法 选取319例妊娠晚期孕妇,依据妊娠晚期睡眠障碍发生情况分为睡眠障碍组(n=131)与无睡眠障碍组(n=188)。采用Logistic回归分析筛选妊娠晚期孕妇发生睡眠障碍的危险因素; 采用R软件建立预测妊娠晚期孕妇发生睡眠障碍的列线图; 采用受试者工作特征(ROC)曲线、校准曲线、Hosmer-Lemeshow拟合优度检验评价列线图预测妊娠晚期孕妇发生睡眠障碍的效能。结果 319例妊娠晚期孕妇中, 131例(41.07%)有睡眠障碍。Logistic回归分析结果显示,有自然流产史(95%CI: 2.120~8.703, P<0.001)、有焦虑(95%CI: 1.644~5.313, P<0.001)、有抑郁(95%CI: 2.169~7.477, P<0.001)、有孕前半年主动饮酒(95%CI: 1.690~5.828, P<0.001)、有妊娠合并症或并发症(95%CI: 1.610~4.851, P<0.001)、临睡前视屏时间>0.5 h(95%CI: 1.069~3.192, P=0.028)是妊娠晚期孕妇发生睡眠障碍的独立危险因素。ROC曲线的曲线下面积为0.788(95%CI: 0.739~0.838); 校准曲线斜率接近1, 且Hosmer-Lemeshow拟合优度检验χ2=6.055, P=0.417。结论 妊娠晚期孕妇有较高的睡眠障碍发生率。有自然流产史、有焦虑、有抑郁、有孕前半年主动饮酒、有妊娠合并症或并发症、临睡前视屏时间>0.5 h是发生睡眠障碍的独立危险因素。基于这6项独立危险因素建立的列线图模型有助于预测妊娠晚期孕妇睡眠障碍的发生。

     

    Abstract: Objective To explore the risk factors for sleep disorders in late pregnancy pregnant women, and establish predictive nomogram. Methods A total of 319 pregnant women in late pregnancy were selected, and were divided into sleep disorder group (n=131) and non-sleep disorder group (n=188) based on whether they experienced sleep disorders in late pregnancy. Logistic regression analysis was applied to screen for risk factors of sleep disorders in late pregnancy pregnant women; R software was applied to establish a nomogram for predicting sleep disorders in late pregnancy pregnant women. Receiver operating characteristic (ROC) curve, calibration curve and Hosmer-Lemeshow goodness of fit test were used to evaluate the efficacy of the nomogram in predicting sleep disorders in third trimester pregnant women. Results Out of 319 late pregnancy pregnant women, 131 had sleep disorders, accounting for 41.07%. Logistic regression analysis showed that history of spontaneous abortion (95%CI, 2.120 to 8.703, P<0.001), anxiety (95%CI, 1.644 to 5.313, P<0.001), depression (95%CI, 2.169 to 7.477, P<0.001), alcohol consumption in the first six months of pregnancy (95%CI, 1.690 to 5.828, P<0.001), pregnancy complications or complications (95%CI, 1.610 to 4.851, P<0.001), video time at bed before sleep >0.5 h (95%CI, 1.069 to 3.192, P=0.028) were independent risk factors for sleep disorders in third trimester pregnant women. The area under the ROC curve was 0.788(95%CI, 0.739 to 0.838). The slope of the calibration curve was close to 1, and the Hosmer-Lemeshow goodness of fit test showed a better results (χ2=6.055, P=0.417). Conclusion Pregnant women in late pregnancy have a higher incidence of sleep disorders. Patients with a history of natural abortion, anxiety, depression, drinking alcohol within six months before pregnancy, pregnancy comorbidities or complications, and video time >0.5 h at bed before sleep are independent risk factors. The nomogram model based on these 6 independent risk factors can help predict the occurrence of sleep disorders in pregnant women in the third trimester.

     

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