Department of Pediatric Surgery, Tongji Medical College, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Huazhong University of Science & Technology, 100 Hongkong Road, Wuhan, Hubei, China.
Departmentf Pediatric Orthopedics, Shengjing Hospital of China Medical University, Shenyang, 110000, Liaoning, China.
BMC Public Health. 2024 Aug 27;24(1):2328. doi: 10.1186/s12889-024-19696-z.
Depression represents a frequent mental health challenge in individuals with fractures, negatively impacting their recuperation and overall well-being. The purpose of this research was to formulate and corroborate a prognostic framework for pinpointing depression risk among fracture sufferers by utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2020 and a separate hospital-based group.
We analyzed records from 1,748 individuals with fractures documented in the NHANES database spanning 2005 to 2020, of which 362 were diagnosed with depression, as indicated by a Patient Health Questionnaire-9 (PHQ-9) score of 10 or higher. An additional validation group comprised 360 fracture patients sourced from a medical center. Considered variables for prediction encompassed demographic details, lifestyle habits, past medical conditions, and laboratory results. The method of least absolute shrinkage and selection operator (LASSO) regression facilitated the narrowing down of variables, while multivariate logistic regression was employed to pinpoint significant predictors. To assist in prediction, a nomogram was designed and subsequently validated.
Five independent predictors were identified: drinking, insomnia, poverty-to-income ratio, education level, and white blood cell count. The nomogram showed good discrimination in the NHANES cohorts (training area under the curve (AUC) 0.734, validation AUC 0.740) and hospital-based external validation (AUC 0.711). Calibration curves and decision analysis supported its predictive accuracy and clinical value.
The constructed nomogram offers a precise and clinically relevant instrument for forecasting depression risk in patients with fractures, facilitating the early detection of individuals at high risk and enabling prompt intervention.
抑郁症是骨折患者常见的心理健康挑战，会对他们的康复和整体健康产生负面影响。本研究旨在利用 2005 年至 2020 年国家健康和营养检查调查（NHANES）的数据以及一个独立的基于医院的小组，构建和验证一个针对骨折患者的抑郁风险预测框架。
我们分析了 NHANES 数据库中记录的 1748 名骨折患者的记录，其中 362 名患者的 PHQ-9 评分≥10 分，被诊断为患有抑郁症。另外一个验证组由 360 名来自医疗中心的骨折患者组成。预测变量包括人口统计学特征、生活方式习惯、既往病史和实验室结果。最小绝对收缩和选择算子（LASSO）回归方法有助于缩小变量范围，而多元逻辑回归则用于确定显著预测因子。为了辅助预测，设计并验证了一个列线图。
确定了五个独立的预测因子：饮酒、失眠、贫困收入比、教育水平和白细胞计数。该列线图在 NHANES 队列中表现出良好的区分度（训练区面积下曲线（AUC）0.734，验证 AUC 0.740）和基于医院的外部验证（AUC 0.711）。校准曲线和决策分析支持其预测准确性和临床价值。
构建的列线图为预测骨折患者的抑郁风险提供了一种精确且具有临床相关性的工具，有助于早期发现高风险个体，并能及时进行干预。
