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| Nomogram model and decision curve analysis of depression risk in diabetic retinopathy patients |
| JING Silu SHEN Han WANG Xiaofeng |
| Ward Two, Department of Ophthalmology, the First Affiliated Hospital of Nanjing Medical University, Jiangsu Province, Nanjing 210000, China |
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Abstract Objective To analyze the factors influencing the depression risk in diabetic retinopathy (DR) patients and construct and evaluate a Nomogram model. Methods A total of 329 patients with DR admitted to the First Affiliated Hospital of Nanjing Medical University from October 2018 to October 2021 were selected and divided into depressed group (132 cases) and non-depressed group (197 cases) according to the detection of depressive mood. The clinical data of the two groups were compared, and the influencing factors of depression in DR patients were analyzed by logistic regression model. The Nomogram model was further constructed and the performance of the model was verified by internal data. The clinical net benefit of the model was evaluated by decision curve. Results The incidence of depression in DR patients in this study was 40.1%. The proportion of smokers, the proportion of regular exercise, the proportion of good sleep quality, the proportion of people who do not use mobile phones, and the platelet count in the depressed group were all lower than those in the non-depressed group, the proportion of alcohol drinkers, proportion of hypertension, cholesterol, high-density lipoprotein, platelet distribution width, platelet-large cell ratio, and mean platelet volume were higher than those in the non-depression group, and the differences were statistically significant (P＜0.05). Exercise, sleep quality, mobile phone use, cholesterol, mean platelet volume, and glycosylated hemoglobin level were all influencing factors for depression in DR patients (P＜0.05). Internal verification results showed that C-index was 0.880 (95%CI: 0.843-0.917), and there was no significant difference between the predicted value and the observed value (P＞0.05). The results of decision curve analysis showed that the Nomogram model provided additional clinical benefits when the threshold was greater than 0.04. Conclusion The Nomogram model constructed in this study has good performance, which can predict the risk of depression in patients with DR with certain accuracy, and can provide strategies for medical staff to manage patients.
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