J Psychosom Res. 2024 Dec 17;189:112018. doi: 10.1016/j.jpsychores.2024.112018. Online ahead of print.
ABSTRACT
OBJECTIVE: Osteoarthritis (OA) is a prevalent degenerative joint condition. Among OA patients, depressive symptoms are the most frequent psychiatric disorder, negatively impacting both prognosis and quality of life. This study analyzed the independent factors associated with the development of depressive symptoms in patients with OA and constructed a nomogram to assess the risk of developing depressive symptoms.
METHODS: An analysis was conducted on data from 2093 OA patients in the NHANES database, covering 2007 to 2014. A training set and a validation set were randomly assigned to participants in a 7:3 ratio. Variables significantly associated with depressive symptoms in OA patients were identified using the least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression analyses and nomograms were constructed. Its performance and clinical relevance were assessed using receiver operating characteristic (ROC) curves, C indices, calibration curves, and decision curves.
RESULTS: Among the 2093 OA patients, 357 were assessed as having depressive symptoms. There are eight independent relevant factors, which are gender, age, poverty-to-income ratio (PIR), race, educational attainment, smoking status, diabetes, and sleep disorder. The AUC values of the training and validation sets were 0.718 (95 %CI: 0.683-0.752) and 0.733 (95 %CI: 0.678-0.788). Calibration and decision curve analyses showed that this nomogram exhibits high accuracy, good discrimination, and potential clinical benefits on both training and validation sets.
CONCLUSIONS: We screened to obtain factors associated with depressive symptoms in patients with OA. Dynamic nomograms enable the combination of individual relevant factors for better assessing and managing high-risk OA groups.
PMID:39721308 | DOI:10.1016/j.jpsychores.2024.112018