1 Vita-Salute San Raffaele University, Department of Clinical Neurosciences, Neurology-Sleep Disorders Center, IRCCS San Raffaele Scientific Institute, Milan, Italy.
2 IRCCS San Raffaele Scientific Institute, Department of Clinical Neurosciences, Neurology-Sleep Disorders Center, Milan, Italy.
3 School of Psychology and Centre de Recherche CERVO, Université Laval, Québec, Quebec, Canada.
4 School of Health, Concordia University, Centre de recherches de l'Institut universitaire de gériatrie de Montréal (CRIUGM), CIUSSS Centre-Sud-de-l'île-de-Montréal, Montreal, Quebec, Canada.
5 Third Faculty of Medicine, Charles University, National Institute of Mental Health, Prague, Czech Republic.
6 National Institute of Mental Health, Klecany, Czech Republic.
7 College of Medicine, Penn State Health Milton S. Hershey Medical Center, Sleep Research &Treatment Center, Department of Psychiatry, Pennsylvania State University, Hershey, Pennsylvania, USA.
8 Department of Psychiatry and Psychotherapy, Medical Center, University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.
9 Human Sciences Department, University of Rome Guglielmo Marconi, Rome, Italy.

Investigating the mechanisms of action of cognitive-behavioural therapy for insomnia (CBT-I), the first-line treatment for chronic insomnia disorder (ID), can contribute to the overall understanding of insomnia and its treatment. To date, no study has examined the relationship between K-complexes (KC) and CBT-I, despite the known homeostatic and protective function of this relevant sleep brainwave. This retrospective multicentre study aims to explore the relationship between electroencephalographic (EEG) indices and CBT-I, with a particular focus on evaluating an index of sleep homeostasis identified by KC. This research is designed to assess the predictive value of this index for treatment outcomes and to examine its variations before and after intervention. Ninety eight patients with ID underwent a 6-8 week in-person CBT-I programme, with pre-and post-treatment evaluation conducted using polysomnography (PSG) and the Insomnia Severity Index (ISI). The main outcome was determined by calculating the slope of the linear equation indexing the KC density (number of KC/minutes of N2) in each non-artifacted NREM stage 2 epoch throughout the night (KCSlope). Furthermore, the sample was categorised into Responders (ISIdecrease =8) and non-Responders (ISIdecrease <8). The results indicate that the KC Slope is effective not only to predict treatment response (one-way ANOVA, F = 7.831 p = 0.007; Responders = -2.954*10^-5 ± 3.346*10^-5, non-Responders = -5.583*10^-5 ± 5.305*10^-5; adjusted for PSG wake after sleep onset at the baseline), but also to detect a statistically significant improvement in sleep pressure following CBT-I (Wilcoxon signed-rank test W = 3074.000 p = 0.022; KCSlope pre-treatment = -4.054*10^-5 ± 4.446*10^-5, KCSlope post-treatment = -4.797*10^-5 ± 5.710*10^-5). These findings suggest that CBT-I increases sleep pressure in patients with chronic insomnia, highlighting a novel and relevant biomarker in this context.