Patient Profiling Based on Spectral Clustering for an Enhanced Classification of Patients with Tension-Type Headache

Abstract

Profiling groups of patients in clusters can provide meaningful insights into the features of the population, thus helping to identify people at risk of chronification and the development of specific therapeutic strategies. Our aim was to determine if spectral clustering is able to distinguish subgroups (clusters) of tension-type headache (TTH) patients, identify the profile of each group, and argue about potential different therapeutic interventions. A total of 208 patients (n = 208) with TTH participated. Headache intensity, frequency, and duration were collected with a 4-week diary. Anxiety and depressive levels, headache-related burden, sleep quality, health-related quality of life, pressure pain thresholds (PPTs), dynamic pressure thresholds (DPT) and evoked-pain, and the number of trigger points (TrPs) were evaluated. Spectral clustering was used to identify clusters of patients without any previous assumption. A total of three clusters of patients based on a main difference on headache frequency were identified: one cluster including patients with chronic TTH (cluster 2) and two clusters including patients with episodic TTH (clusters 0–1). Patients in cluster 2 showed worse scores in all outcomes than those in clusters 0–1. A subgroup of patients with episodic TTH exhibited pressure pain hypersensitivity (cluster 0) similarly to those with chronic TTH (cluster 2). Spectral clustering was able to confirm subgrouping of patients with TTH by headache frequency and to identify a group of patients with episodic TTH with higher sensitization, which may need particular attention and specific therapeutic programs for avoiding potential chronification.

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