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A predictive model for postoperative compensatory hyperhidrosis in primary palmar hyperhidrosis: a retrospective
Peng Luo1, Jingsi Wang1, Qingshan Chen1
1Department of Thoracic Surgery, Xinqiao Hospital, Third Military Medical University (Army Medical University), Chongqing, China.
Background:
While sympathectomy remains the optimal surgical intervention for severe primary palmar hyperhidrosis (PPH), compensatory hyperhidrosis (CH) has emerged as the most significant factor contributing to postoperative patient regret. This retrospective study aimed to identify risk factors and develop a predictive model for moderate-to-severe compensatory hyperhidrosis (msCH) in patients with PPH.
Methods:
A total of 1,013 patients were retrieved from the institutional database between 2014 and 2024. Logistic regression modeling was utilized to identify risk factors for msCH. A nomogram for predicting msCH was developed accordingly.
Results:
Of the initial cohort, there were 903 patients included in the final analysis, among whom 182 (20.2%) developed msCH. The following factors were identified as independent risk factors for msCH: age >25 years [odds ratio (OR) 3.32, 95% confidence interval (CI): 2.23-4.95, P<0.01], smoking history (OR 6.46, 95% CI: 4.37-9.54, P<0.01), higher body mass index (BMI) (OR 1.68, 95% CI: 1.10-2.56, P=0.02), palmar-axillary hyperhidrosis (OR 2.37, 95% CI: 1.57-3.57, P<0.01), and T3 sympathectomy (OR 3.14, 95% CI: 2.03-4.85, P<0.01). A predictive nomogram for msCH was developed based on these factors. Receiver operating characteristic (ROC) curve analysis demonstrated an area under the curve (AUC) of 0.839, indicating good predictive performance.
Conclusions:
Age >25 years, smoking history, higher BMI, palmar-axillary hyperhidrosis, and T3 sympathectomy were independent risk factors for msCH. Based on these factors, a predictive model for msCH was developed and showed high predictive accuracy.
