Sleep Disturbances as a Potential Risk Factor for Deterioration of Respiratory Function in Patients with Amyotrophic Lateral Sclerosis.

Objectives: Sleep disturbances are common in amyotrophic lateral sclerosis (ALS). However, previous studies have explored sleep quality at the cross-sectional level and the longitudinal variability characteristics are currently unknown. Our study aimed to longitudinally explore the effect of sleep quality on disease progression in patients with ALS. Methods: All enrolled patients with ALS were first diagnosed and completed the 6- and 12-month follow-ups. Subjective sleep disturbance was assessed using the Pittsburgh Sleep Quality Index (PSQI). Based on the PSQI score at baseline, patients with ALS were classified as poor sleepers (PSQI >5) and good sleepers (PSQI ≤5). Disease progression was assessed using the rate of disease progression, the absolute change from baseline forced vital capacity (ΔFVC) and the percentage change from baseline FVC (ΔFVC%) over the follow-up period. Results: Sixty-three patients were included in the study, 24 (38.1%) were poor sleepers and 39 were good sleepers. The percentage of patients with poor sleep quality was 38.1% at baseline, increasing to 60.3% and 74.6% at 6- and 12-month, respectively. Compared to good sleepers, ΔFVC and ΔFVC% values were greater in poor sleepers (P < 0.001 and P = 0.001, respectively). Poor sleep quality at diagnosis is associated with rapid deterioration of respiratory function during disease progression. Conclusions: Sleep disturbances maybe a potential risk factor for deterioration of respiratory function in patients with ALS. The role of sleep disturbances in disease progression deserves attention, and early assessment and intervention may slow disease progression and improve life quality of patients with ALS.

Sleep disorders and white matter integrity in patients with sporadic amyotrophic lateral sclerosis.

This study aimed to explore the characteristics of sleep disorders and their relationship with abnormal white-matter integrity in patients with sporadic amyotrophic lateral sclerosis. One hundred and thirty-six patients and 80 healthy controls were screened consecutively, and 56 patients and 43 healthy controls were ultimately analyzed. Sleep disorders were confirmed using the Pittsburgh sleep quality index, the Epworth sleepiness scale, and polysomnography; patients were classified into those with poor and good sleep quality. White-matter integrity was assessed using diffusion tensor imaging and compared between groups to identify the white-matter tracts associated with sleep disorders. The relationship between scores on the Pittsburgh sleep quality index and impaired white-matter tracts was analyzed using multiple regression. Poor sleep quality was more common in patients (adjusted odds ratio, 4.26; p = 0.005). Compared to patients with good sleep quality (n = 30), patients with poor sleep quality (n = 26; 46.4%) showed decreased fractional anisotropy, increased mean diffusivity, and increased radial diffusivity of projection and commissural fibers, and increased radial diffusivity of the right thalamus. The Pittsburgh score showed the best fit with the mean fractional anisotropy of the right anterior limb of the internal capsule (r = - 0.355, p = 0.011) and the mean radial diffusivity of the right thalamus (r = 0.309, p = 0.028). We conclude that sleep disorders are common in patients with sporadic amyotrophic lateral sclerosis and are associated with reduced white-matter integrity. The pathophysiology of amyotrophic lateral sclerosis may contribute directly to sleep disorders.

Development and validation of a dynamic risk prediction system for constipation in patients with amyotrophic lateral sclerosis.

Introduction: Although constipation is a common non-motor symptom in patients with amyotrophic lateral sclerosis (ALS), it is poorly valued. Moreover, there is a bidirectional effect between constipation and neuropsychiatric and sleep disturbances. Thus, these symptoms are better treated simultaneously. Therefore, this study aimed to develop and validate a model for predicting the risk of constipation in ALS patients, to help clinicians identify and treat constipation early. Methods: Data of 118 ALS admissions from an observational prospective cohort, registered between March 2017 and December 2021, were analyzed. Demographic data were obtained. Constipation was assessed using the Knowles-Eccersley-Scott Symptom Questionnaire. The severity of ALS was assessed using the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R). Anxiety and depressive symptoms were measured using the Hospital Anxiety and Depression Scale (HADS). The Pittsburgh Sleep Quality Index (PSQI) was used to assess patients' sleep status. The least absolute shrinkage and selection operator (LASSO) regression model was used to select factors and construct a nomogram. Nomogram model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curve, decision curve analysis (DCA), and clinical impact curve (CIC). The model was internally validated using bootstrap validation in the current cohort. Results: Age, family history of constipation, total ALSFRS-R score, site of onset, total PSQI score, and depressed, were identified as significant predictors of the risk of constipation in ALS patients. The prediction model was validated to have good accuracy (Hosmer-Lemeshow test: χ2 = 11.11, P > 0.05) and discrimination (AUC = 0.856, 95% confidence interval: 0.784-0.928). DCA and CIC showed that the nomogram model had excellent clinical performance. Conclusions: A web-based ALS constipation risk calculator with good predictive performance was constructed to identify patients at high risk of constipation and to allow early intervention in a clinical context.