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

Introduction

Primary palmar hyperhidrosis (PPH) is an autonomic dysfunction disorder characterized by pathological excessive sweating of the palms, which significantly impairs patients’ quality of life and psychological well-being, with a global prevalence of 0.6–5% (1,2). Endoscopic thoracic sympathectomy (ETS) remains an effective intervention for moderate-to-severe PPH (msPPH). However, compensatory hyperhidrosis (CH) occurs in 30–90% of postoperative patients, with 15–30% progressing to moderate-to-severe compensatory hyperhidrosis (msCH), which represents the most prevalent and clinically challenging adverse effect and may even lead to patients’ regret (3-6). While the pathophysiology of CH remains incompletely understood, it is hypothesized with the involvement of post-sympathectomy thermoregulatory dysregulation (7). Consequently, developing an accurate predictive model to identify high-risk patients is imperative for optimizing surgical decision-making and improving clinical outcomes.

Current research on post-ETS CH faces several limitations. Firstly, existing studies predominantly rely on univariate analyses rather than multifactorial predictive models. Prior investigations have focused on isolated variables such as the level of sympathectomy (T3 vs. T4), body mass index (BMI) (≥25 kg/m²), and smoking history (8-10). For instance, Kim et al. demonstrated that T3 sympathectomy carries a higher risk of severe CH compared to T4 sympathectomy (8). Dobosz et al. identified BMI ≥25 kg/m² as an independent risk factor for CH (9). Moreover, owing to the modest cohort sizes, most of the published literature is underpowered, exemplified by Adhami et al.’s Australian cohort (n=298) and Hyun et al.’s machine learning analysis (n=138) (11,12).

The development of a robust CH prediction model represents a critical unmet need in clinical practice, with large cohort study being the most pressing evidence gap. Leveraging our institution’s 10-year experience in minimally invasive ETS, the present study analyzed >1,000 consecutive PPH cases. This represents the largest CH prediction cohort to date, enabling identification of risk factors for msCH and construction of a clinically actionable prediction model. We present this article in accordance with the TRIPOD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1562/rc).

Methods

Study population

A total of 1,013 consecutive patients undergoing ETS for PPH at Xinqiao Hospital (March 2014–December 2024) were retrospectively enrolled. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Xinqiao Hospital (approval No. 2025-NO.038-01). The requirement for informed consent was waived because the present study was retrospective without disclosure of patient information. Inclusion criteria were: (I) clinical diagnosis of msPPH; (II) bilateral ETS treatment; and (III) complete clinical and follow-up data. All patients underwent ETS via electrocautery ablation of the sympathetic chain at either the T3 or T4 level.

Operative procedure

Under general anesthesia, positioned semi-supine with 30°–45° upper body elevation and arm abduction, all patients received bilateral axillary small incisions (approximately 0.5 to 1.0 cm in length) at the third intercostal space. The sympathetic chain was identified thoracoscopically at the T3 or T4 level and ablated with an electrocautery hook.

Statistical analysis

Patients were followed by outpatient clinic visits and telephone interviews at 1, 3, 6, and 12 months postoperatively, with survey questionnaires assessing improvement of primary symptoms, severity of CH, and postoperative satisfaction. All statistical analyses and nomogram construction were performed using R software (version 4.2.2). Categorical data were analyzed with χ² or Fisher’s exact tests. Significant univariate predictors (P<0.05) were included in the multivariable logistic regression model. Model validation was conducted through two approaches: (I) receiver operating characteristic (ROC) curve; and (II) calibration accuracy evaluation using slope analysis. Bootstrapping repetitions (n=300) were utilized for internal validation of the nomogram and to estimate the predictive accuracy.

Results

Baseline clinical characteristics

From March 2014 to December 2024, a total of 1,013 patients who underwent bilateral ETS for msPPH at Xinqiao Hospital were initially screened. After excluding 110 cases due to missing data or incomplete follow-up, 903 patients were included in the final analysis (Figure 1). Generally, 182 (20.2%) developed msCH. Meanwhile 721 (79.8%) had no CH or only mild CH. The most common sites for CH included the back (n=112, 61.5%), abdomen (n=86, 47.3%), anterior chest (n=54, 29.7%), thighs/buttocks (n=43, 23.6%) and perineal region (n=36, 19.8%). Details are listed in Table 1.

Figure 1 Research flowchart. CH, compensatory hyperhidrosis; PPH, primary palmar hyperhidrosis.

Females constituted the majority of participants (n=535, 59.2%). The median age of patients was 25 years (range, 14–56 years), and 488 patients (50.4%) were aged ≤25 years. The vast majority (n=793, 87.8%) were of Han ethnicity. A total of 307 patients (34.0%) were students (including high school, undergraduate, and postgraduate students). Family history of PPH was found in 187 patients (20.7%). The majority of patients (n=611, 67.7%) had no smoking history. The incidence of msCH increased progressively with higher BMI: 55 cases in the BMI <19.0 kg/m² group, 93 in the 19.0–24.0 kg/m² group, and 34 in the >24.0 kg/m² group . Surgical intervention was performed between 2014–2019 in 390 patients (43.2%). Three hundred and fifteen patients (34.9%) underwent surgery during summer. Isolated palmar hyperhidrosis and combined palmar-axillary hyperhidrosis were observed in 410 (45.4%) and 493 patients (54.6%), respectively. Preoperative assessment classified the majority (n=822, 91.0%) as severe CH. Seven hundred and thirty-three patients (81.2%) underwent bilateral T4 sympathectomy.

Risk factors for CH

In univariate logistic regression analysis, age, smoking history, BMI, site of hyperhidrosis, and level of sympathectomy showed statistically significant differences (P<0.01). Details were listed in Table 2. Furthermore, multivariate analysis identified these five factors as independent risk factors for msCH: age [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), BMI (OR 1.68, 95% CI: 1.10–2.56, P=0.02), site of hyperhidrosis (OR 2.37, 95% CI: 1.57–3.57, P<0.01), and level of sympathectomy (OR 3.14, 95% CI: 2.03–4.85, P<0.01). No statistical significance was observed for gender, ethnicity, occupation, family history, operative duration, surgical season, or hyperhidrosis severity (P>0.05).

Development and validation of the nomogram

Based on the above five independent risk factors, a nomogram to predict msCH was constructed (Figure 2). By calculating the total score of these five variables, the probability of msCH after surgery could be accurately predicted. According to ROC curve, the area under the curve (AUC) was 0.839, indicating good predictive performance of the model (Figure 3A). Additionally, the calibration curve demonstrated excellent agreement between predicted and observed outcomes (Figure 3B).

Figure 2 The nomogram for predicting the likelihood of moderate-to-severe compensatory hyperhidrosis after endoscopic thoracic sympathectomy. BMI, body mass index.

Figure 3 ROC (A) and calibration slope curve (B) of our model. AUC, area under the curve; ROC, receiving operating characteristic.

Discussion

Currently, the common surgical modalities for palmar hyperhidrosis encompass clipping, electrocautery, selective sympathectomy (ramicotomy), and radiofrequency thermocoagulation (10,13). According to the European Society of Thoracic Surgeons (ESTS) expert consensus, ETS is recommended as the optimal therapeutic strategy for PPH affecting the extremities, axillae, or face. Interruption of the sympathetic chain can be achieved via electrocautery or clipping techniques, with the highest success rates observed when the procedure is performed at the T3 or T4 level (14).

CH is a common complication following thoracic sympathectomy, with a reported incidence ranging from 30% to 90% (15-17). msCH not only significantly impairs patients’ quality of life but may also lead to dissatisfaction with surgical outcomes (18,19). Therefore, developing an effective predictive model for msCH is crucial for improving postoperative prognosis and patient satisfaction.

Previous studies predominantly investigated individual risk factors for CH (20,21), with only a limited number exploring predictive models (11,12). In a representative study by Adhami et al., a cohort of 298 patients was analyzed, yielding a predictive model with an AUC of 0.713 (11). Hyun et al. utilized a machine learning-based approach for CH prediction and achieved a higher AUC of 0.914. However, the generalizability of their findings might be constrained by the relatively small sample size (n=128) (12). Furthermore, most prior research focused on risk factors associated with overall CH, which primarily comprises mild cases (22). In contrast, msCH, a subtype more strongly linked to postoperative regret and patient dissatisfaction, has received considerably less attention (22-24). Given its greater clinical implications, further investigation into msCH is warranted.

As one of the largest studies to date on this topic, our investigation analyzed a single-center cohort of 903 patients. The observed incidence of msCH was 20.2% (n=182), consistent with previous reports (12,24). Univariate and multivariate logistic regression analyses revealed that age, smoking history, BMI, site of hyperhidrosis, and the level of sympathectomy were independent risk factors. Importantly, we developed a nomogram prediction model based on these variables, which demonstrated high predictive accuracy (AUC: 0.839). All incorporated variables were readily obtainable in clinical practice, enabling straightforward risk stratification by summing individual scores. Our findings provided clinically actionable insights and might contribute to improved decision-making in future practice.

In terms of age, our data demonstrated that advanced age served as an independent risk factor for msCH (OR 3.32, 95% CI: 2.23–4.95, P<0.01). These findings align with multiple prior studies (10,25,26). A meta-analysis encompassing 10 studies and 3,117 patients revealed that older age significantly increased the risk of CH (P=0.002) (10). Similarly, Kara et al. conducted a study of 74 patients and identified age >21 years as a significant predictor of CH (P=0.02) (25). Further supporting this association, a prospective cohort study (n=227) reported a positive correlation between advanced age and CH incidence (26). While the exact pathophysiological mechanisms remained unclear, age-related physiological and metabolic alterations might predispose older patients to CH (10).

Regarding smoking status, our analysis identified smoking as an independent risk factor for msCH (OR 6.46, 95% CI: 4.37–9.54, P<0.001). These findings also aligned with previously reported associations in the literature (10,21,27). Lin et al.’s meta-analysis demonstrated a robust correlation between smoking history and CH (10). A retrospective cohort study of 50 patients confirmed smoking history as a significant predictor of CH (27). These results were further corroborated by a larger cohort study (n=194), where 46% of participants developed CH within 30 postoperative days. Multivariable analysis in this study established smoking (prevalence 34%) as an independent risk factor for CH (21). Although existing studies consistently confirmed the association between smoking and CH, the underlying pathophysiological mechanisms remained poorly understood (10,21,27).

With respect to BMI, multiple studies indicated a potential association with CH (9,10,22). Lin et al. reported that elevated BMI levels positively correlated with CH, particularly demonstrating a significant association with severe CH (OR 1.20, 95% CI: 1.01–1.39, P<0.001) (10). A prospective study of 157 patients found that participants with BMI ≥25 kg/m² experienced more severe CH at 12-month follow-up based on both subjective and objective assessments (9). A retrospective single-center study involving 152 patients identified higher BMI as an independent risk factor for CH (OR 0.864, 95% CI: 0.755–0.989, P<0.05) (22). Our results consistently supported these observations, establishing elevated BMI as an independent risk factor for CH.

Multiple studies demonstrated that patients with multi-site hyperhidrosis had a higher risk of CH compared to those with single-site hyperhidrosis. In a cohort study of 95 patients, those with axillary hyperhidrosis (34.7%) showed significantly higher CH incidence than those without (76.0% vs. 46.3%, P=0.018) (28). A long-term follow-up study of 173 patients revealed that preoperative multi-site hyperhidrosis was strongly associated with CH (P=0.037) (2). A comparative study of single-site versus multi-site hyperhidrosis found that the palmar-axillary group exhibited more severe CH (74.9%) than the isolated palmar group (70.4%) (29). Our study yielded consistent findings, with significantly higher CH incidence observed in patients with combined palmar-axillary hyperhidrosis compared to those with isolated palmar involvement (OR 2.37, 95% CI: 1.57–3.57, P<0.01).

Multiple studies established that higher level of sympathectomy was associated with increased incidence of CH (28,30,31). A prospective study of 727 patients demonstrated that T2 sympathetic clipping resulted in significantly higher CH incidence and greater severity compared to T3/T4 interventions (30). Furthermore, consistent evidence indicated that T4 sympathectomy might represent an optimal approach for reducing both CH incidence and severity (28,31). A prospective evaluation of T4 sympathectomy in 66 patients revealed CH occurrence in 57.6% of cases, with mild, moderate, and severe CH reported in 39.4%, 16.7%, and 1.5% of patients, respectively (28). These outcomes compared favorably with studies employing higher-level sympathectomy. A randomized controlled trial of 163 PPH (78 undergoing T3 vs. 85 undergoing T4 sympathectomy) found significantly lower moderate CH incidence in the T4 group, with no severe cases reported (31). Our findings corroborated these observations, identifying higher-level (T3) sympathectomy as an independent risk factor for CH development (OR 3.14, 95% CI: 2.03–4.85, P<0.01).

Collectively, these results suggested that surgical strategy optimization, particularly selecting appropriate sympathectomy levels in patients with high-risk characteristics such as advanced age, smoking, elevated BMI, or multi-site hyperhidrosis, could potentially mitigate CH risk.

Although this study represents one of the largest sample-sized investigations in this field to date and we have developed a nomogram with satisfactory predictive performance, several limitations should be acknowledged. First, this is a single-center retrospective study, and future multicenter prospective studies are warranted. Second, to address the potential confounding influence of the surgical learning curve since our program inception in 2014, we contrasted outcomes between patients from the initial [2014–2019] and subsequent [2020–2024] 5-year periods. However, this analysis did not reveal any significant disparities. Last but not least, previous studies have reported the influence of psychological factors such as anxiety on CH. More potential influencing factors should be incorporated in future research to refine this predictive model, thereby enhancing its clinical applicability across broader populations.

Conclusions

Using one of the largest cohorts of PPH patients to date, we identified age >25 years, a history of smoking, higher BMI, palmar-axillary hyperhidrosis, and T3 sympathectomy as independent risk factors for msCH. Furthermore, we developed a nomogram with high predictive accuracy for msCH. We hope that this study will contribute to improving decision-making in clinical practice.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the TRIPOD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1562/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1562/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1562/prf

Funding: This work was supported by the Chongqing Science and Health Joint Medical Science and Technology Innovation and Key Project (No. 2025GGXM001) and Young PhD Talents cultivation Project (No. 2023YQB010).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2025-1562/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Institutional Review Board of Xinqiao Hospital (approval No. 2025-NO.038-01). The requirement for informed consent was waived because the present study was retrospective without disclosure of patient information.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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