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DOI 10.21037/atm-22-6511

Медицинская библиотека · Annals of translational medicine · 2023

Association between skin disease and anxiety: a logistic analysis and prediction.

Sun Chao, Ren Yali, Zhang Wanhong

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Аннотация

BACKGROUND

Dermatosis has symptoms of flushing, itching, pain, and burning, which causes psychological distress in patients.

METHODS

We collected the data of 214 patients from the Wuhan Institute of Dermatology and Venereology from January 2020 to January 2022, including age, gender, diagnosis, Hamilton Anxiety Rating Scale (HAMA), and anxiety. First, descriptive analysis and difference analysis of the included data were carried out. Second, a correlation matrix was used to exclude the confounding factors with strong collinearity. Finally, logistic regression was used to analyze and predict the risk factors of anxiety.

RESULTS

In the anxiety group and nonanxiety group, eczema and generalized eczema accounted for the largest proportion, and there was no difference in the composition of the diagnosis between the 2 groups. Several related analyses proved the accuracy of the logistic model. The results showed that age had a protective effect on the anxiety of patients with skin diseases [odds ratio (OR) =0.8606 with 95% confidence interval (CI): 0.7812, 0.8987]. Neurodermatitis (OR =1.0853 with 95% CI: 1.0115, 1.2512), eczema (OR =1.1358 with 95% CI: 1.0215, 1.2129), generalized eczema (OR =1.3346 with 95% CI: 1.1212, 1.5521), and psoriasis (OR =1.3685 with 95% CI: 1.1728, 1.6215) were associated with the anxiety of patients. Prediction analysis showed that with increase of patients' age, the likelihood of anxiety decreased.

CONCLUSIONS

This study demonstrated a strong correlation between skin diseases and anxiety and that the likelihood of anxiety decreases as age increases. Therefore, psychological intervention for patients with skin diseases, especially young patients, is essential.

Для цитирования: Sun Chao, Ren Yali, Zhang Wanhong. Association between skin disease and anxiety: a logistic analysis and prediction.. Annals of translational medicine. 2023. DOI: 10.21037/atm-22-6511.
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