Prediction of acupuncture treatment failure in patients with postherpetic neuralgia: a retrospective observational cohort analysis.
Source: PubMed, NCBI / U.S. National Library of Medicine
Postherpetic neuralgia (PHN) is a prevalent and painful complication following herpes zoster infection, impacting patient quality of life and posing significant treatment challenges. Current pharmacological approaches often result in adverse effects. The aim of this study was to develop a clinical prediction model for selecting PHN patients for electroacupuncture (EA) treatment and to determine the prognostic outcomes after two sessions. We conducted a retrospective observational cohort analysis on adults diagnosed with PHN between 2010 and 2017. All participants had undergone at least two acupuncture sessions. Data analysis included demographic, clinical and treatment variables to identify predictors of treatment outcomes. Treatment success was defined using the numeric rating scale (NRS), with failure characterized by an NRS score >3. Predictive modeling and internal validation employed bootstrap resampling. Among 243 patients included in the study, the treatment failure rate was 20.6%. Key predictive factors for treatment outcome were the presence of diabetes mellitus, use of carbamazepine and high initial NRS scores. The accuracy of the prediction model was reflected by an area under the receiver operating characteristic (ROC) curve of 0.80 after the first session and 0.88 following the third session, indicating a robust predictive capability. In this study, we successfully developed and internally validated a clinical prediction model for EA in PHN patients. We anticipat
Abstract
Postherpetic neuralgia (PHN) is a prevalent and painful complication following herpes zoster infection, impacting patient quality of life and posing significant treatment challenges. Current pharmacological approaches often result in adverse effects. The aim of this study was to develop a clinical prediction model for selecting PHN patients for electroacupuncture (EA) treatment and to determine the prognostic outcomes after two sessions. We conducted a retrospective observational cohort analysis on adults diagnosed with PHN between 2010 and 2017. All participants had undergone at least two acupuncture sessions. Data analysis included demographic, clinical and treatment variables to identify predictors of treatment outcomes. Treatment success was defined using the numeric rating scale (NRS), with failure characterized by an NRS score >3. Predictive modeling and internal validation employed bootstrap resampling. Among 243 patients included in the study, the treatment failure rate was 20.6%. Key predictive factors for treatment outcome were the presence of diabetes mellitus, use of carbamazepine and high initial NRS scores. The accuracy of the prediction model was reflected by an area under the receiver operating characteristic (ROC) curve of 0.80 after the first session and 0.88 following the third session, indicating a robust predictive capability. In this study, we successfully developed and internally validated a clinical prediction model for EA in PHN patients. We anticipate that this model may guide clinicians in personalized patient care, optimizing the selection process for EA treatment, and predicting treatment response early in the treatment cycle.