Objective sTo investigate how the different components of sleep dysfunction described in SLE patients combine together in sleep clusters. Methods We conducted a cross-sectional study on a perspective cohort of 79 SLE patients (mean age 8.2 +/- 14.3 years). Sleep was evaluated using Pittsburgh Sleep Quality Index (PSQI). Clusters were defined using the single components of PSQI in a hierarchical clustering model. We used Beck Depression Inventory, Hamilton Anxiety Rating Scale, and Medical Outcomes Study Short Form 36 (SF36) to measure depressive symptoms, anxiety, and quality of life, respectively. Results Three sleep clusters were identified. The cluster 1 (N=47) is characterized by the lowest values of PSQI total score. The cluster 2 (N=21) presents higher values of sleep latency, but sleep duration similar to cluster 1. In cluster 3 (N=11), we found sleep latency increased as in cluster 2, but the highest values of PSQI total score and reduced sleep duration. Scores of anxiety and sedentary time were higher in clusters 2 and 3 than in cluster 1. Cluster 3 presented the highest scores of depression and reduced mental and physical components of SF36. Conclusions The combination of different sleep components in SLE patients allowed us to identify three patterns of dysfunction: a first cluster with better sleep latency and duration, a second with increased sleep latency but conserved duration, and a third with impairment of both latency and duration. The stratification of sleep disorders in clusters might be useful for the personalization of therapy in relation to sleep cluster membership.
Pattern of sleep dysfunction in systemic lupus erythematosus: a cluster analysis
Laudisio A;Navarini L
;Angeletti S;Ciccozzi M;Antonelli Incalzi R;Afeltra A
2019-01-01
Abstract
Objective sTo investigate how the different components of sleep dysfunction described in SLE patients combine together in sleep clusters. Methods We conducted a cross-sectional study on a perspective cohort of 79 SLE patients (mean age 8.2 +/- 14.3 years). Sleep was evaluated using Pittsburgh Sleep Quality Index (PSQI). Clusters were defined using the single components of PSQI in a hierarchical clustering model. We used Beck Depression Inventory, Hamilton Anxiety Rating Scale, and Medical Outcomes Study Short Form 36 (SF36) to measure depressive symptoms, anxiety, and quality of life, respectively. Results Three sleep clusters were identified. The cluster 1 (N=47) is characterized by the lowest values of PSQI total score. The cluster 2 (N=21) presents higher values of sleep latency, but sleep duration similar to cluster 1. In cluster 3 (N=11), we found sleep latency increased as in cluster 2, but the highest values of PSQI total score and reduced sleep duration. Scores of anxiety and sedentary time were higher in clusters 2 and 3 than in cluster 1. Cluster 3 presented the highest scores of depression and reduced mental and physical components of SF36. Conclusions The combination of different sleep components in SLE patients allowed us to identify three patterns of dysfunction: a first cluster with better sleep latency and duration, a second with increased sleep latency but conserved duration, and a third with impairment of both latency and duration. The stratification of sleep disorders in clusters might be useful for the personalization of therapy in relation to sleep cluster membership.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.