DOI: 10.1097/ajp.0000000000001411 ISSN: 1536-5409

Pain Phenotyping in Carpal Tunnel Syndrome Based on IASP Criteria

Emrah Afsar, Zeynep Sena Namaz, Ismail Saracoglu, Merve Akdeniz Leblebicier

Objectives:

The primary aim of this study is to determine the pain phenotype in carpal tunnel sydrome (CTS) using an algorithm to support clinical reasoning processes. A secondary aim entails examining whether symptom severity, functional status, health related quality of life (HRQoL) and electrodiagnostic findings differs between the pain phenotypes in CTS.

Methods:

This cross-sectional study included 113 patients with CTS. Following the electrodiagnostic assessments, participants completed the Margolis pain diagram, Numeric Pain Rating Scale, Boston Carpal Tunnel Questionnaire, and Short Form-36 (SF-36). Clinical sensory examinations were performed, and pain phenotypes were classified using an IASP-aligned clinical phenotyping approach. Between-group differences were analyzed using covariate-adjusted multivariate models (MANCOVA), controlling for age, sex, pain intensity, and symptom duration.

Results:

Of the participants, 53 (46.9%) were classified as having a neuropathic pain phenotype and 60 (53.1%) as having a mixed pain phenotype. Significant differences were observed between groups in symptom severity ( P =0.035), functional status ( P =0.0001), selected SF-36 domains ( P =0.043–0.002), and electrodiagnostic parameters, including motor latency ( P <0.001), motor amplitude ( P =0.019), sensory amplitude ( P <0.001) and sensory conduction velocity ( P =0.001). The neuropathic pain group demonstrated more favorable electrophysiological findings, as well as better symptom severity, functional status and HRQoL scores.

Discussion:

In this study, approximately half of the patients were classified as neuropathic pain phenotype and the other half as mixed pain phenotype. Patients with a mixed pain phenotype exhibited worse clinical, functional, and electrodiagnostic profiles compared to those with neuropathic pain. Pain phenotyping may support improved clinical characterization and patient stratification in CTS.

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