医学研究生抑郁症状的预测Nomogram:一项病例对照研究

Zewen Huang, Junyu Wang, Lejun Zhang, Lu Xu, Tingting Wang, Ming Guo, Xi Xu, Heli Lu
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引用次数: 1

摘要

目的:医学研究生抑郁症状的筛查与预测是一个关键问题。虽然许多因素被提出,相关的心理干预措施也在不断完善,但准确预测医学生的抑郁症状仍然是一个很大的挑战。本研究旨在建立一个准确预测医学生研究生阶段抑郁症状的nomogram,以期为早期识别高危人群及采取心理干预提供参考。方法:采用方便抽样法,选取南昌大学第二附属医院医学研究生937名。选取211名有抑郁症状的医研究生为病例组,689名年龄、性别、婚姻状况相同的医研究生为对照组,进行病例对照匹配。通过多变量logistic回归分析确定抑郁症状的影响因素,并建立nomogram,用nomogram对各因素进行评分。结果:家庭功能(OR= 0.87, 0.80-0.94, P< 0.01)、社会支持(OR= 0.95, 0.92-0.98, P< 0.01)、生活满意度(OR= 0.92, 0.88-0.96, P< 0.001)、主观幸福感(OR= 0.63, 0.47-0.84, P< 0.01)、烟酒使用情况(OR= 1.54, 1.00-2.35, P< 0.05)是医学研究生抑郁症状的显著相关因素,可以综合预测。通过使用这些因素,我们创建了一个抑郁症状的nomogram。曲线下面积为0.80(95%置信区间0.77 ~ 0.83)。结论:nomogram是一种准确预测医学生研究生阶段抑郁症状的有效测量工具,并能在早期识别出抑郁的高危人群。在预测抑郁症状潜在风险的基础上,尽早采取针对性的心理干预,减少抑郁症状对医研究生的负面影响至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Nomogram for Depressive Symptoms in Postgraduate Medical Students: A Case-Control Study
Purpose: The screening and prediction of depressive symptoms in postgraduate medical students is a key issue. Many factors have been suggested, and the relevant measures of psychological intervention have been continuously improved, nevertheless, it is still of great challenge to predict depressive symptoms of medical students precisely. This study sought to create a nomogram for precise prediction of depressive symptoms in medical students during the postgraduate stage in order to provide reference for early identification of high risk groups and taking psychological intervention. Methods: We chose 937 postgraduate medical students from The Second Affiliated Hospital of Nanchang University by using convenience sampling method. We selected 211 postgraduate medical students with depressive symptoms as the case group, and selected 689 postgraduate medical students of the same age, gender and marital status as the control group for case-control matching. Influencing factors for depressive symptoms were identified by multivariable logistic regression analysis and used to create a nomogram, and nomogram was used to score each factors. Results: Family function (OR= 0.87, 0.80-0.94, P< 0.01), social support (OR= 0.95, 0.92-0.98, P< 0.01), life satisfaction (OR= 0.92, 0.88-0.96, P< 0.001), subjective well-being (OR= 0.63, 0.47-0.84, P< 0.01) and alcohol and tobacco use (OR= 1.54, 1.00-2.35, P< 0.05) were identified as significantly associated factors that could be combined for accurate prediction of depressive symptoms among postgraduate medical students. We created a nomogram for depressive symptoms by using these factors. The area under the curve was 0.80 (95% confidence interval 0.77-0.83). Conclusions: The nomogram is a useful measurement tool for precise prediction of depressive symptoms among medical students during the postgraduate stage, and can also identify high-risk groups in early times. On the basis of predicting the potential risk of depressive symptoms, taking specific psychological intervention as soon as possible to reduce the negative impact of depressive symptoms on postgraduate medical students is vital.
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