A predictive model for postoperative compensatory hyperhidrosis in primary palmar hyperhidrosis: a retrospective...

Area of Science:

• Medical research
• Surgical outcomes
• Dermatology

Background:

• Sympathectomy is optimal for severe primary palmar hyperhidrosis (PPH).
• Compensatory hyperhidrosis (CH) significantly impacts patient satisfaction post-surgery.
• Identifying risk factors for moderate-to-severe CH (msCH) is crucial for managing patient expectations.

Purpose of the Study:

• To identify independent risk factors for developing moderate-to-severe compensatory hyperhidrosis (msCH) in patients with PPH.
• To develop a predictive model and nomogram for msCH.
• To improve preoperative counseling and patient selection for sympathectomy.

Main Methods:

• Retrospective analysis of 1,013 patients undergoing sympathectomy for PPH (2014-2024).
• Logistic regression modeling to determine risk factors for msCH.
• Development and validation of a predictive nomogram using identified risk factors.

Main Results:

• 182 out of 903 patients (20.2%) developed msCH.
• Independent risk factors for msCH included: age >25 years, smoking history, higher BMI, palmar-axillary hyperhidrosis, and T3 sympathectomy.
• The predictive nomogram demonstrated good predictive performance with an AUC of 0.839.

Conclusions:

• Age >25, smoking, higher BMI, palmar-axillary hyperhidrosis, and T3 sympathectomy are key predictors of msCH.
• A validated predictive model can accurately forecast the risk of msCH.
• This model can aid clinicians in patient counseling and surgical decision-making for PPH treatment.