Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan

Jing-rong DAI; Jie LI; Xu HE; Yang LI; Yan LI

doi:10.12259/j.issn.2095-610X.S20211104

Volume 42 Issue 11

Nov. 2021

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Jing-rong DAI, Jie LI, Xu HE, Yang LI, Yan LI. Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan[J]. Journal of Kunming Medical University, 2021, 42(11): 20-26. doi: 10.12259/j.issn.2095-610X.S20211104

Citation:

Jing-rong DAI, Jie LI, Xu HE, Yang LI, Yan LI. Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan[J]. Journal of Kunming Medical University, 2021, 42(11): 20-26. doi: 10.12259/j.issn.2095-610X.S20211104

Citation:

Jing-rong DAI, Jie LI, Xu HE, Yang LI, Yan LI. Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan[J]. Journal of Kunming Medical University, 2021, 42(11): 20-26. doi: 10.12259/j.issn.2095-610X.S20211104

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Risk Factors Analysis and Risk Prediction Model Construction of Depression in Inpatients of Geriatrics Department of a Hospital in Yunnan

doi: 10.12259/j.issn.2095-610X.S20211104

Jing-rong DAI^{1, 2},
Jie LI^{1, 2},
Xu HE^{1, 2},
Yang LI²,
Yan LI^{1, 2
,
,}

1.
Medical School，Kunming University of Science and Technology，Kunming Yunan 650500
2.
Dept. of Geriatrics，The First People’s Hospital of Yunnan Province，Kunming Yunan 650032，China

Received Date: 2021-09-11
Available Online: 2021-11-15
Publish Date: 2021-11-30

Abstract

Abstract

Objective To study the risk factors of depression in elderly inpatients and build a risk prediction model. Methods From September 2017 to July 2020, 525 elderly patients （≥60 years old） in the Department of Geriatrics of the First People’s Hospital of Yunnan Province were selected as the research objects. The comprehensive geriatric assessment system software independently developed by the geriatric medical department of the First People’s Hospital of Yunnan province was used for the comprehensive geriatric assessment, and the SDS scale in it was used to evaluate the depressive state of hospitalized patients. Binary Logistic regression analysis was used to explore the influencing factors of depression in the elderly, and a risk prediction model was established. The area under the ROC curve and the Hosmer-Lemeshow test were used to evaluate the prediction effect of the model. Results Among 525 newly admitted patients, there were 418 cases （79.6%） in the non-depressed group and 107 cases （20.4%） in the depressed group. There were statistically significant differences in age, gender, number of chronic diseases, MNA-SF, SAS, MMSE, BADL, ALS, MORSE and RomaⅢ scales between the two groups （P < 0.05）. The number of chronic diseases （OR = 1.473, 95%CI: 1.050 ～ 2.067, P = 0.025）, daily dysfunction （OR = 1.450, 95%CI: 1.073 ～ 1.958, P = 0.015）, anxiety （OR = 2.442, 95%CI: 1.829 ～ 3.259, P < 0.001）, cognitive dysfunction （OR = 1.488, 95%CI: 1.072～2.066, P = 0.018）, insomnia （OR = 1.620, 95%CI: 1.147～2.288, P = 0.006）, social support disorder （OR = 2.544, 95%, CI: 1.165～5.555, P = 0.019） were independent risk factors for depression in elderly inpatients. In addition, the ROC curve was drawn by using the prediction probability of the model as a new variable, the results showed that the AUC was 0.859, with a critical value of 0.595 （CI: 0.822～0.897, P < 0.001）, and the sensitivity and specificity of the prediction model were 0.818 and 0.782. Conclusion The state of senile depression is closely related to a variety of risk factors, and the risk prediction model based on the risk factors also has high accuracy.
- Geriatric symptoms,
- Depression,
- Prediction model,
- Inpatient

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References(28)

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