Influencing factors of Sleep Disorders in Amyotrophic Lateral Sclerosis: A Cross-sectional Study

Influencing factors of Sleep Disorders in Amyotrophic Lateral Sclerosis: A Cross-sectional Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Influencing factors of Sleep Disorders in Amyotrophic Lateral Sclerosis: A Cross-sectional Study Qianping Jiang, Dan Yang, Rui Jiang, Shilei Wan, Miao Wu, Dandan Xu, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7024421/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Sep, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background Amyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disease frequently accompanied by sleep disorders. Conventional insomnia interventions are often unsuitable for ALS patients due to cognitive and respiratory impairments. There is a lack of targeted studies addressing sleep-related issues using multifactorial analyses specific to this group. Participants and Methods: This cross-sectional study included 266 ALS patients at the Motor Neuron Disease Rehabilitation and Treatment Center of Hubei Provincial Hospital of Traditional Chinese Medicine. Participants were evaluated using tools like the Pittsburgh Sleep Quality Index (PSQI) and ALS Functional Rating Scale-Revised (ALSFRS-R). Regression models identified factors affecting sleep disorders and quality. Results Patients with sleep disorders were more likely to have non-motor symptoms like anxiety, depression, pain, and excessive daytime sleepiness compared to those without. Fatigue severity and anxiety levels were identified as independent influencing factors of sleep disorders. Additionally, fatigue, anxiety, pain intensity, and disease progression rate were significantly linked to sleep quality. Conclusions This study is the first comprehensive analysis of sleep-related factors in Chinese ALS patients, highlighting the crucial roles of fatigue, anxiety, pain, and disease progression rate. It provides a basis for future personalized, non-pharmacological interventions tailored to the specific needs of ALS patients. Health sciences/Diseases Health sciences/Neurology Biological sciences/Neuroscience sleep disorders amyotrophic lateral sclerosis ALS influencing factors correlation 1. Introduction Amyotrophic lateral sclerosis (ALS) is a rare and fatal neurodegenerative disease characterized primarily by muscle atrophy, motor dysfunction, and a range of non-motor symptoms. The pathological hallmark of ALS is the selective degeneration of upper and lower motor neurons, which ultimately leads to death, most commonly due to respiratory failure [ 1 – 3 ]. Despite significant advances in understanding its pathogenesis in recent years, no curative treatment is currently available. Current therapeutic strategies are primarily supportive, focusing on symptom management to alleviate discomfort, slow disease progression, and improve patients' quality of life [ 2 ]. Sleep disorders represent some of the most prevalent non-motor symptoms associated with ALS, occurring at a markedly higher frequency than in the general population [ 4 ]. Research indicates that approximately 63% of individuals with ALS experience sleep disorders, in contrast to 37% of healthy controls [ 5 ]. These disturbances not only detrimentally affect subjective well-being and quality of life but may also expedite disease progression and complicate comprehensive disease management. A study by Li et al. demonstrated that patients with poor sleep quality exhibited more rapid respiratory decline at the time of diagnosis [ 6 ]. Consequently, the early identification and management of sleep disorders may contribute to decelerating ALS progression and enhancing patients' quality of life [ 6 – 8 ]. However, due to the unique characteristics of ALS, conventional treatments for insomnia are often not widely applicable in this population. In the general population, the primary treatments for insomnia include cognitive behavioral therapy for insomnia (CBT-I) and pharmacotherapy. CBT-I improves sleep quality by modifying maladaptive sleep habits and alleviating anxiety. Common pharmacological agents include benzodiazepines, non-benzodiazepine hypnotics, and antidepressants [ 9 , 10 ]. However, for ALS patients, the implementation of CBT-I is hindered by impairments in speech communication and cognitive comprehension. Moreover, respiratory muscle atrophy leads to compromised respiratory function, making the use of sedative medications substantially riskier due to the heightened potential for respiratory depression or exacerbation of respiratory failure. Therefore, thoroughly investigating the factors that contribute to sleep disorders in ALS patients is essential for developing safe and feasible individualized intervention strategies. This study aimed to identify the key variables affecting sleep quality in individuals with ALS, thereby providing a theoretical foundation and strategic direction for future development of non-pharmacological treatment approaches adapted to the context of respiratory and communication dysfunction. Ultimately, these findings may expand intervention options and improve overall quality of life and disease management for ALS patients. 2. Methods The study protocol was reviewed and approved by the Ethics Committee of Hubei Provincial Hospital of Traditional Chinese Medicine (Ethics approval number: HBZY2024-C38-01). All methods were performed in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants or their legal guardians. The study was conducted in full compliance with the principles outlined in the Declaration of Helsinki. 2.1 Study Participants 2.1.1 Inclusion Criteria Between January 2022 and January 2025, a cohort of consecutive patients diagnosed with ALS and receiving treatment at the Motor Neuron Disease Rehabilitation and Treatment Center of Hubei Provincial Hospital of Traditional Chinese Medicine were enrolled in the study. The inclusion criteria were as follows: (1) a confirmed diagnosis of ALS in accordance with the 2020 International Gold Coast Criteria; (2) clinical staging between stages 1 and 3 as per the London criteria, with no prior history of gastrostomy, continuous 24-hour non-invasive ventilation (NIV), or tracheostomy; (3) voluntary participation with the provision of signed informed consent. 2.1.2 Exclusion Criteria (1) A history of severe sleep disorders; (2) Coexisting severe chronic respiratory or cardiac diseases; (3) Use of psychoactive medications within the past six weeks; (4) Cognitive impairments preventing accurate comprehension of questionnaire items. 2.2 General data Assessment Demographic data included age, sex, smoking history, alcohol consumption, site of disease onset, disease duration, years of education (high school or below, junior college, university or above), marital status (married, divorced, or single), employment status (full-time employed or retired), and monthly household income (5,000 RMB or ≥ 5,000 RMB). 2.3 Clinical Data Assessment All scale-based assessments were conducted by trained physicians from the Motor Neuron Disease Rehabilitation and Treatment Center at Hubei Provincial Hospital of Traditional Chinese Medicine. Disease progression rate was calculated as:[(48 − baseline ALSFRS-R score) / 48 × 100%] [ 11 ]. Sleep disorders assessment : Sleep disorders were assessed using the Pittsburgh Sleep Quality Index (PSQI), which provides a comprehensive evaluation of sleep quality in ALS patients. The PSQI is a self-reported questionnaire that evaluates sleep over the past month across seven domains: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disorder, use of sleep medication, and daytime dysfunction [ 12 ]. It consists of 19 self-rated items, each domain scored from 0 to 3, for a total score ranging from 0 to 21. This standardized tool has demonstrated adequate validity and reliability in various populations, including ALS patients, and can be used for longitudinal assessment of sleep quality [ 13 ]. A total score greater than 5 indicates poor sleep quality. Disease severity assessment Disease severity was assessed using the revised ALS Functional Rating Scale (ALSFRS-R), which evaluates physical function and disease progression in ALS patients [ 14 , 15 ]. This instrument includes 12 items covering bulbar function, limb mobility, respiratory function, and activities of daily living. Each item is scored based on functional performance, with total scores ranging from 0 to 48; higher scores indicate better physical function and daily living ability. Daytime sleepiness assessment Daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS), a widely used instrument to evaluate excessive daytime sleepiness in ALS patients [ 16 ]. The ESS consists of eight items, each scored from 0 to 3, with a total score ranging from 0 to 24. A total ESS score ≥ 10 suggests significant daytime sleepiness, while a score ≥ 15 indicates severe somnolence. Fatigue condition assessment Fatigue was evaluated using the Fatigue Severity Scale (FSS) [ 17 ], which includes nine items rated on a 7-point Likert scale (1 = strongly disagree; 7 = strongly agree), with total scores ranging from 9 to 63. Scores ≥ 36 indicate clinically significant fatigue requiring intervention Anxiety and depression assessment Anxiety and depression are critical factors affecting the quality of life in ALS patients [ 18 , 19 ]. Therefore, anxiety and depressive symptoms were evaluated using the Hamilton Anxiety Rating Scale (HARS) and the Hamilton Depression Rating Scale (HDRS) [ 18 , 19 ]. The HARS comprises 14 items, each scored from 0 to 4; a total score > 7 indicates the presence of anxiety symptoms. The HDRS includes 17 items, each scored from 0 to 4, with a total score > 7 suggesting depressive symptoms. Pain assessment Pain intensity over the past 30 days was evaluated using the Visual Analog Scale (VAS) [ 20 ]. The VAS is a self-reported tool in which respondents are presented with a numeric rating scale and asked to indicate their pain level on a continuum from 0 to 10, where 0 represents no pain and 10 represents the worst imaginable pain. A VAS score of ≥ 4 was considered indicative of moderate to severe pain, while a score < 4 indicated mild pain. 2.4 Data analysis Data analysis was conducted using R version 4.3.3. The Kolmogorov-Smirnov test was used to assess the normality of basic information and clinical indicators. Continuous variables that followed a normal distribution were described using the mean and standard deviation (SD). Continuous variables that did not follow a normal distribution were expressed as median and interquartile range (IQR). Categorical variables were summarized using patient counts and percentages. The independent samples t-test was used to compare continuous variables with normal distribution between two groups; the Mann-Whitney U test was used for non-normally distributed continuous variables; the chi-square test was used to analyze differences between categorical variables in the two groups. Initially, to investigate the influencing factors of sleep disorders, the presence or absence of such disorders was treated as a binary dependent variable. A univariate logistic regression analysis was conducted to compute the odds ratio (OR) along with its 95% confidence interval (CI). Variables that demonstrated a P-value of less than 0.05 in the univariate analysis were subsequently included in a multivariate logistic regression model to ascertain independent risk factors. All statistical tests were two-tailed, with a significance threshold set at P < 0.05. The model's fit was validated, and multicollinearity was evaluated using the variance inflation factor (VIF). Subsequently, to further examine the factors affecting sleep quality, the total score of the Pittsburgh Sleep Quality Index (PSQI) was used as a continuous dependent variable. An initial univariate linear regression analysis was performed, and variables with a P-value < 0.05 were incorporated into a multivariate stepwise linear regression model. The model underwent rigorous testing for linearity, independence of residuals, homoscedasticity, and normality to ensure analytical accuracy. A two-tailed P-value < 0.05 was deemed statistically significant. 3. Results 3.1 Baseline data characteristics A total of 266 patients with ALS were enrolled in this study, of whom 163 were male and 103 were female, with a mean age of 54 years and a mean disease duration of 17.44 months. Among them, 176 patients (66.16%) reported sleep disorders, including 103 males (58.52%) and 73 females (41.48%). No significant differences were observed between ALS patients with and without sleep disorders in terms of ALSFRS-R Bulbar (ALSFRS-RB), ESS, FVC, disease duration, education level, caregiver status, working status, region of onset, smoking history, drinking history, or sex (p > 0.05) (refer to Table 1 ). Table 1 Comparison of general data between the two groups of ALS patients Variables Total (n = 266) ALS patients without sleep disorder (n = 90) ALS patients with sleep disorder (n = 176) Statistic P Age, M (Q₁, Q₃) 54.00 (47.00, 60.00) 50.00 (43.25, 57.75) 55.00 (49.00, 61.00) Z=-2.95 0.003 Education Level, n (%) χ²=0.40 0.818 High school and below 146 (54.89) 47 (52.22) 99 (56.25) junior college 51 (19.17) 18 (20.00) 33 (18.75) University and above 69 (25.94) 25 (27.78) 44 (25.00) working status, n (%) χ²=3.73 0.155 Full-time work 107 (40.23) 42 (46.67) 65 (36.93) jobless 98 (36.84) 33 (36.67) 65 (36.93) retire 61 (22.93) 15 (16.67) 46 (26.14) Marital Status, n (%) - 1.000 divorce 3 (1.13) 1 (1.11) 2 (1.14) married 260 (97.74) 88 (97.78) 172 (97.73) single 3 (1.13) 1 (1.11) 2 (1.14) Income, n (%) χ²=2.40 0.493 10000 99 (37.22) 35 (38.89) 64 (36.36) 3000—4999 43 (16.17) 15 (16.67) 28 (15.91) 5000–10000 85 (31.95) 31 (34.44) 54 (30.68) Caregiver, n (%) χ²=0.70 0.404 self-care 46 (17.29) 18 (20.00) 28 (15.91) Taking care of others 220 (82.71) 72 (80.00) 148 (84.09) Region Of Onset, n (%) χ²=0.00 0.963 Bulbar 41 (15.41) 14 (15.56) 27 (15.34) limb 225 (84.59) 76 (84.44) 149 (84.66) Smoking History, n (%) χ²=0.19 0.660 0 182 (68.42) 60 (66.67) 122 (69.32) 1 84 (31.58) 30 (33.33) 54 (30.68) Drinking History, n (%) χ²=0.27 0.604 0 177 (66.54) 58 (64.44) 119 (67.61) 1 89 (33.46) 32 (35.56) 57 (32.39) Sexuality, n (%) χ²=1.66 0.197 Female 103 (38.72) 30 (33.33) 73 (41.48) Male 163 (61.28) 60 (66.67) 103 (58.52) t: t-test, Z: Mann-Whitney test, χ²: Chi-square test, -: Fisher exact SD: standard deviation, M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile The Student's t-test (with Mann-Whitney U test when necessary) was used to compare continuous variables and the chi-squared test was used to analyze categorical variables. The meaning of the bold values represented statistically significant values in the statistical analysis. The meaning of the bold values represented statistically significant values in the statistical analysis. However, compared to ALS patients without sleep disorders, those with sleep disorders demonstrated lower scores on the on the ALSFRS-R Limb (ALSFRS-RL), ALSFRS-R Respiratory (ALSFRS-RR), and overall ALSFRS-R, while exhibiting higher scores on the FSS, VAS, HARS, and HDRS scores. Additionally, patients with sleep disorders exhibited more rapid disease progression and were of an older age (refer to Table 2 ). Table 2 Comparison of baseline clinical characteristics between the two groups of ALS patients Variables Total (n = 266) ALS patients without sleep disorder (n = 90) ALS patients with sleep disorder (n = 176) Statistic P FSS, Mean ± SD 33.36 ± 14.12 27.80 ± 13.72 36.21 ± 13.49 t=-4.78 < .001 VAS, Mean ± SD 1.95 ± 1.54 1.66 ± 1.30 2.10 ± 1.63 t=-2.43 0.016 HARS, Mean ± SD 11.96 ± 7.86 7.51 ± 4.83 14.24 ± 8.15 t=-8.43 < .001 HDRS, Mean ± SD 11.83 ± 7.27 8.91 ± 4.67 13.33 ± 7.89 t=-5.72 < .001 ESS, Mean ± SD 3.22 ± 1.73 3.07 ± 1.73 3.30 ± 1.73 t=-1.05 0.297 ALSFRS-RB, Mean ± SD 10.06 ± 2.39 10.46 ± 2.25 9.85 ± 2.45 t = 1.96 0.052 ALSFRS-RL, Mean ± SD 14.74 ± 5.88 16.02 ± 5.34 14.09 ± 6.04 t = 2.57 0.011 ALSFRS-RR, Mean ± SD 10.86 ± 2.11 11.43 ± 1.51 10.57 ± 2.31 t = 3.64 < .001 ALSFRS-R, Mean ± SD 35.66 ± 8.50 37.91 ± 7.26 34.51 ± 8.87 t = 3.35 < .001 Disease Progression Rate, Mean ± SD 1.71 ± 1.83 1.34 ± 1.27 1.90 ± 2.03 t=-2.40 0.017 Disease duration, Mean ± SD 17.44 ± 8.34 17.58 ± 7.92 17.37 ± 8.57 t = 0.20 0.842 FVC, M (Q₁, Q₃) 76.76 (63.80, 90.50) 74.81 (62.31, 89.70) 79.08 (69.56, 92.31) Z=-1.64 0.100 t: t-test, Z: Mann-Whitney test, χ²: Chi-square test, -: Fisher exact SD: standard deviation, M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile FSS,Fatigue Severity Scale; VAS,Visual Analog Scale; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ESS,Epworth Sleepiness Scale;ALSFRS-RB,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Bulbar Function;ALSFRS-RL, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; ALSFRS-R, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised;FVC,Forced Lung Function; The Student's t-test (with Mann-Whitney U test when necessary) was used to compare continuous variables and the chi-squared test was used to analyze categorical variables. The meaning of the bold values represented statistically significant values in the statistical analysis.The meaning of the bold values represented statistically significant values in the statistical analysis. 3.2 Logistic regression analysis of sleep disorders in patients with ALS Using the presence of sleep disorders (PSQI > 5) as the dependent variable, this study included variables such as the FSS, VAS, HARS, HDRS, ALSFRS-RL, ALSFRS-RR, Age and disease progression rate in univariate binary logistic regression analyses, with univariate binary logistic regression results detailed in Supplementary Table 1. Variables that achieved a significance level of P < 0.05 in the univariate analyses were subsequently included in a multivariate logistic regression model. Predictor variables were selected using a bidirectional stepwise regression method. The findings revealed that anxiety levels (as measured by the HARS score) and fatigue severity (as measured by the FSS score) were independent risk factors for sleep disorders in patients with ALS (refer to Table 3 ). Table 3 Multivariate binary logistic regression analysis of factors associated with sleep disorders. Variables β S.E Z P OR (95%CI) FSS 0.03 0.01 2.27 0.023 1.03 (1.01 ~ 1.05) VAS HARS 0.12 0.03 4.81 < .001 1.13 (1.08 ~ 1.19) HDRS ALSFRS-RL ALSFRS-RR -0.15 0.09 -1.76 0.078 0.86 (0.72 ~ 1.02) Age 0.02 0.01 1.56 0.119 1.02 (0.99 ~ 1.05) Progression Rate 0.18 0.12 1.53 0.126 1.20 (0.95 ~ 1.52) FSS, Fatigue Severity Scale;VAS,Visual Analog Scale;Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ALSFRS-RL, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; OR, odds ratio. The binary logistic stepwise regression analysis (Two-way stepwise method) was used. The meaning of the bold values represented statistically significant values in the statistical analysis. 3.3 Linear regression analysis of sleep quality Utilizing the total PSQI score as a continuous dependent variable, further univariate linear regression analyses were conducted to explore potential clinical correlates of sleep quality. The variables included ALSFRS-RB, ESS score, disease duration and FVC in addition to the previously described factors. Detailed results of the univariate regression are presented in Supplementary Table 2. Variables with P-values < 0.05 in the univariate analysis were entered into a multivariate stepwise linear regression model. The results indicated that FSS score, VAS score, HARS score and disease progression rate were the primary factors influencing sleep quality in patients with ALS, as presented in Table 4 . Collinearity analysis indicated that all VIFs were below 10, as shown in Supplementary Table 3. Table 4 Factors related to sleep quality in multiple linear regression analysis. Variables β S.E t P β (95%CI) FSS 0.06 0.02 3.44 < .001 0.06 (0.02 ~ 0.09) VAS 0.38 0.14 2.67 0.008 0.38 (0.10 ~ 0.66) HARS 0.21 0.03 6.95 < .001 0.21 (0.15 ~ 0.26) HDRS ESS ALSFRS-RB ALSFRS-RL ALSFRS-RR Age 0.03 0.02 1.53 0.128 0.03 (-0.01 ~ 0.08) Progression Rate 0.31 0.12 2.63 0.009 0.31 (0.08 ~ 0.55) Disease duration FVC FSS, Fatigue Severity Scale;VAS,Visual Analog Scale;Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ESS,Epworth Sleepiness Scale;ALSFRS-RB,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Bulbar Function;ALSFRS-RL,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function;FVC,Forced Lung Function;A multiple linear stepwise regression model was used. The meaning of the bold values represented statistically significant values in the statistical analysis. 4. Discussion This study aimed to investigate factors associated with sleep disorders in patients with ALS. The findings revealed that, compared with patients without sleep disorders, those with such issues were more likely to present with non-motor symptoms such as anxiety, depression, pain, and excessive daytime sleepiness. Multivariate logistic and linear regression analyses indicated that fatigue severity and anxiety levels were independent predictors of both the occurrence of sleep disorders and overall sleep quality in ALS patients. Additionally, linear regression analysis demonstrated that pain intensity and disease progression rate were significantly associated with the severity of sleep disorders. Anxiety may impact sleep in ALS patients through multiple mechanisms. First, the progressive and incurable nature of ALS may induce persistent anxiety, which in turn activates the brain's fear and salience networks [ 21 ], leading to hyperarousal, difficulty relaxing, and impaired sleep initiation [ 22 ]. Second, anxiety may alter the levels of several neurotransmitters involved in sleep regulation, including adenosine, gamma-aminobutyric acid, dopamine, and serotonin, thereby disrupting sleep architecture [ 23 ]. Additionally, anxiety may elevate cortisol levels and activate the hypothalamic–pituitary–adrenal axis, which disrupts the normal circadian rhythm and makes it more difficult for patients to initiate or maintain deep sleep [ 24 , 25 ]. Fatigue is a common symptom in patients with ALS and is significantly associated with sleep disorders. Fatigue in ALS can be categorized into physical and mental components. Physically, fatigue arises primarily from muscle weakness and increased energy expenditure due to the degeneration of motor neurons, manifesting as progressive muscular decline that severely limits daily activity. Impaired motor function often prevents ALS patients from adjusting their posture or finding a comfortable sleeping position, leading to persistent physical discomfort that significantly impairs sleep quality [ 26 ]. Mentally, fatigue results from increased cognitive load and emotional stress, which may disrupt central nervous system function, reduce the occurrence of deep sleep stages, and further exacerbate sleep impairment [ 27 , 28 ]. Higher VAS scores indicate poorer sleep quality in ALS patients. ALS patients often experience muscle spasms, positional discomfort, and chronic pain, primarily arising from muscle cramps or prolonged static posture, especially in skeletal and joint regions. As the disease progresses, muscle atrophy renders these areas more susceptible to compression, thereby inducing persistent pain [ 29 ], which frequently triggers nocturnal awakenings and disrupts sleep continuity [ 20 ]. Furthermore, pain may activate central excitatory mechanisms, enhancing sympathetic activity and resulting in difficulty initiating sleep and reduced deep sleep duration [ 30 – 33 ]. A deeper understanding of the multifaceted nature of pain and its impact on sleep can inform more effective intervention strategies, thereby improving the quality of life for ALS patients. Disease progression rate in ALS is negatively correlated with sleep quality. Patients with more rapid disease progression are more prone to severe sleep disorders. Faster progression leads to greater diaphragmatic and intercostal muscle weakness, increasing both the incidence and severity of nocturnal hypoventilation and sleep-related breathing disorders, thereby markedly reducing overall sleep efficiency and quality [ 34 , 35 ]. Researchers have also found that faster progression is associated with more severe hypothalamic dysfunction; the hypothalamus, a key regulator of the sleep–wake cycle, has been shown to undergo atrophy and pathological changes in ALS [ 36 , 37 ]. During rapid disease progression, neurotoxic protein deposition may accelerate structural and functional damage in the hypothalamus, further impairing its role in sleep regulation and leading to ongoing deterioration of sleep quality [ 38 ]. This study has several strengths. First, 266 ALS patients treated at the Motor Neuron Disease Center of Hubei Provincial Hospital of Traditional Chinese Medicine were recruited. Given the rarity of ALS, this sample size provides adequate representativeness. All assessments were conducted by professionals using standardized scales, ensuring reliable and consistent data. Second, this is the first systematic study in China examining factors influencing sleep disorders in ALS patients. In addition to traditional variables (pain, respiratory function, disease severity), we included psychological and behavioral factors (anxiety, depression, fatigue, daytime sleepiness) to comprehensively assess potential mechanisms influencing sleep from a multidimensional perspective. However, this study also has limitations. First, the cross-sectional design reveals only associations; future longitudinal cohort studies are needed to verify the impact of risk factors such as fatigue and anxiety on ALS prognosis and sleep disorder progression, thereby providing more robust evidence. Second, only patients in clinical stages 1 to 3 were included, excluding those in advanced stages (stages 4–5). This may limit the applicability of findings to late-stage patients and may not fully reflect sleep disorder characteristics across all disease stages. Future studies should broaden inclusion criteria to enhance representativeness across all disease stages. Finally, reliance on patient-reported measures of sleep quality, anxiety, and fatigue may introduce recall bias and variability due to disease burden or emotional state, potentially affecting objectivity. Future research should incorporate objective measures, such as polysomnography, to improve result accuracy and reliability. This study identified several key factors associated with sleep disturbances in patients with ALS, including anxiety, fatigue, chronic pain, and disease progression rate. Future intervention strategies should be tailored to the unique functional limitations of ALS patients, with particular attention to those experiencing speech impairments and restricted motor abilities. Locally adaptable, feasible, and high-adherence interventions are needed. To address anxiety, simplified emotional regulation interventions should be developed to accommodate limitations in communication and cognitive function. Potential approaches include adapted CBT, emotional support groups, and mindfulness-based techniques, complemented by digital tools to enhance accessibility and adherence. For fatigue, standardized objective assessment criteria should be established. Interventions should integrate circadian rhythm optimization, energy management, and daily living modifications to mitigate its disruptive effects on sleep architecture. Chronic pain management should employ a comprehensive strategy, including positional adjustments, rehabilitation therapy, and non-pharmacological analgesia, focusing on optimizing nocturnal posture and individualized care. For patients with rapid disease progression, dynamic monitoring of respiratory function and the establishment of early-warning mechanisms should be prioritized. Attention should also be given to potential degeneration of central regulatory systems, such as hypothalamic function. The intervention pathway should be based on stratified assessments and multidisciplinary collaboration to advance ALS sleep management toward precision and personalization. Declarations Acknowledgments: This study was funded by the Hubei Provincial Natural Science Foundation (Joint Fund,2023AFD128, 2024AFD279) and Science and Technology Special Project of State Administration of Traditional Chinese Medicine (GZY-KJS-2025-008). Author contributions: All authors contributed substantially to the conception and design of the work. Jiang Qianping: Writing-original draft, Visualization, Methodology, Data curation, Conceptualization. Yang Dan: Methodology, Data curation, Conceptualization. Jiang Rui: Supervision, Data curation. Wan Shilei: Data curation. Wu Miao: Data curation. Xu Dandan: Supervision, Data curation. Zhou Jing: Writing-review & editing, Writing-original draft, Supervision, Funding acquisition. Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethical standard statement: This study was approved by the Ethics Committee of Hubei Provincial Hospital of Traditional Chinese Medicine (Wuhan, China, Ethics approval number: HBZY2024-C38-01). 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The ALSFRS-R: a revised ALS functional rating scale that incorporates assessments of respiratory function. BDNF ALS Study Group (Phase III)[J]. J Neurol Sci, 1999,169(1-2):13-21.DOI:10.1016/s0022-510x(99)00210-5. Sap-Anan N, Pascoe M, Wang L, et al. The Epworth Sleepiness Scale in epilepsy: Internal consistency and disease-related associations[J]. Epilepsy Behav, 2021,121(Pt A):108099.DOI:10.1016/j.yebeh.2021.108099. Wang M Y, Liu I C, Chiu C H, et al. Cultural adaptation and validation of the Chinese version of the Fatigue Severity Scale in patients with major depressive disorder and nondepressive people[J]. Qual Life Res, 2016,25(1):89-99.DOI:10.1007/s11136-015-1056-x. Rodriguez-Seijas C, Thompson J S, Diehl J M, et al. A comparison of the dimensionality of the Hamilton Rating Scale for anxiety and the DSM-5 Anxious-Distress Specifier Interview[J]. Psychiatry Res, 2020,284:112788.DOI:10.1016/j.psychres.2020.112788. HAMILTON M. A rating scale for depression[J]. J Neurol Neurosurg Psychiatry, 1960,23(1):56-62.DOI:10.1136/jnnp.23.1.56. An R, Li Y, He X, et al. The Evaluation of Pain with Nociceptive and Neuropathic Characteristics from Three Different Perspectives in Amyotrophic Lateral Sclerosis Patients: A Case Controlled Observational Study in Southwestern China[J]. Neural Plast, 2021,2021:5537892.DOI:10.1155/2021/5537892. Li C, Xia L, Ma J, et al. Dynamic functional abnormalities in generalized anxiety disorders and their increased network segregation of a hyperarousal brain state modulated by insomnia[J]. J Affect Disord, 2019,246:338-345.DOI:10.1016/j.jad.2018.12.079. Seo J, Pace-Schott E F, Milad M R, et al. Partial and Total Sleep Deprivation Interferes With Neural Correlates of Consolidation of Fear Extinction Memory[J]. Biol Psychiatry Cogn Neurosci Neuroimaging, 2021,6(3):299-309.DOI:10.1016/j.bpsc.2020.09.013. Elmenhorst D, Elmenhorst E M, Hennecke E, et al. Recovery sleep after extended wakefulness restores elevated A(1) adenosine receptor availability in the human brain[J]. Proc Natl Acad Sci U S A, 2017,114(16):4243-4248.DOI:10.1073/pnas.1614677114. Monachelli G G, Meyer M, Rodriguez G, et al. Progesterone and cortisol levels in sporadic amyotrophic lateral sclerosis (sALS): correlation with prognostic factors[J]. Horm Mol Biol Clin Investig, 2011,6(1):167-173.DOI:10.1515/HMBCI.2011.006. Spataro R, Volanti P, Vitale F, et al. Plasma cortisol level in amyotrophic lateral sclerosis[J]. J Neurol Sci, 2015,358(1-2):282-286.DOI:10.1016/j.jns.2015.09.011. Chen J H, Wu S C, Chen H J, et al. Risk of developing pressure sore in amyotrophic lateral sclerosis patients - a nationwide cohort study[J]. J Eur Acad Dermatol Venereol, 2018,32(9):1589-1596.DOI:10.1111/jdv.14911. Baglioni C, Battagliese G, Feige B, et al. Insomnia as a predictor of depression: a meta-analytic evaluation of longitudinal epidemiological studies[J]. J Affect Disord, 2011,135(1-3):10-19.DOI:10.1016/j.jad.2011.01.011. Skapinakis P, Rai D, Anagnostopoulos F, et al. Sleep disturbances and depressive symptoms: an investigation of their longitudinal association in a representative sample of the UK general population[J]. Psychol Med, 2013,43(2):329-339.DOI:10.1017/S0033291712001055. Akerblom Y, Zetterberg L, Larsson B J, et al. Pain, disease severity and associations with individual quality of life in patients with motor neuron diseases[J]. BMC Palliat Care, 2021,20(1):154.DOI:10.1186/s12904-021-00848-6. Hurwitz N, Radakovic R, Boyce E, et al. Prevalence of pain in amyotrophic lateral sclerosis: a systematic review and meta-analysis[J]. Amyotroph Lateral Scler Frontotemporal Degener, 2021,22(7-8):449-458.DOI:10.1080/21678421.2021.1892765. Rosa D, Ingrande L, Marcomini I, et al. Perceived Pain in People Living with Amyotrophic Lateral Sclerosis-A Scoping Review[J]. Nurs Rep, 2024,14(4):3023-3039.DOI:10.3390/nursrep14040220. Kwak S. Pain in amyotrophic lateral sclerosis: a narrative review[J]. J Yeungnam Med Sci, 2022,39(3):181-189.DOI:10.12701/jyms.2022.00332. Delpont B, Beauvais K, Jacquin-Piques A, et al. Clinical features of pain in amyotrophic lateral sclerosis: A clinical challenge[J]. Rev Neurol (Paris), 2019,175(1-2):11-15.DOI:10.1016/j.neurol.2017.11.009. Lechtzin N, Cudkowicz M E, de Carvalho M, et al. Respiratory measures in amyotrophic lateral sclerosis[J]. Amyotroph Lateral Scler Frontotemporal Degener, 2018,19(5-6):321-330.DOI:10.1080/21678421.2018.1452945. Yan J, Chen H, Zhang Y, et al. Fecal microbiota transplantation significantly improved respiratory failure of amyotrophic lateral sclerosis[J]. Gut Microbes, 2024,16(1):2353396.DOI:10.1080/19490976.2024.2353396. Hiller A J, Ishii M. Disorders of Body Weight, Sleep and Circadian Rhythm as Manifestations of Hypothalamic Dysfunction in Alzheimer's Disease[J]. Front Cell Neurosci, 2018,12:471.DOI:10.3389/fncel.2018.00471. Liu S, Ren Q, Gong G, et al. Hypothalamic subregion abnormalities are related to body mass index in patients with sporadic amyotrophic lateral sclerosis[J]. J Neurol, 2022,269(6):2980-2988.DOI:10.1007/s00415-021-10900-3. Gabery S, Ahmed R M, Caga J, et al. Loss of the metabolism and sleep regulating neuronal populations expressing orexin and oxytocin in the hypothalamus in amyotrophic lateral sclerosis[J]. Neuropathol Appl Neurobiol, 2021,47(7):979-989.DOI:10.1111/nan.12709. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7024421","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":486950839,"identity":"3dfcf2e4-6225-4f6d-b5e2-7b5f1efd4a70","order_by":0,"name":"Qianping Jiang","email":"","orcid":"","institution":"Affiliated Hospital of Hubei University of Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Qianping","middleName":"","lastName":"Jiang","suffix":""},{"id":486950840,"identity":"4114f0ee-2e70-4147-a5c5-eff6d7b06a3e","order_by":1,"name":"Dan Yang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYBACNmb2AwcSKtjs2OQfHyBOCx87T+KDB2f4kvkY0hKI0yLHz2Bs+LBFjnEeQ44BsQ5jSJNIbDBjZmM48/HGGwY7Od0GgloYj0kk7kjjY2Ps3Ww5hyHZ2OwAUbacOcbMxsy7TZqH4UDiNiK0mEkktv1nbGPjeUa0FmODxDY2xjYeHjZitQADOeEMWzKbBJux5RwDIvwi33/8wMEfwKiUn8H88MabCjs5glpQgAQPkVGDrIVUHaNgFIyCUTAiAAAXdTnAC2HN+gAAAABJRU5ErkJggg==","orcid":"","institution":"Affiliated Hospital of Hubei University of Chinese Medicine","correspondingAuthor":true,"prefix":"","firstName":"Dan","middleName":"","lastName":"Yang","suffix":""},{"id":486950841,"identity":"745a63a2-9252-4a1d-90b6-b82ef3694603","order_by":2,"name":"Rui Jiang","email":"","orcid":"","institution":"Affiliated Hospital of Hubei University of Chinese 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16:56:50","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":17109,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.S2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7024421/v1/25738dd551be55b7207fcf6a.docx"},{"id":87225715,"identity":"e1e09725-4113-4875-86ad-42ca54ae7b0b","added_by":"auto","created_at":"2025-07-21 17:12:50","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":15595,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTable.S3.docx","url":"https://assets-eu.researchsquare.com/files/rs-7024421/v1/7eae65bdfd211269408ce690.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Influencing factors of Sleep Disorders in Amyotrophic Lateral Sclerosis: A Cross-sectional Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eAmyotrophic lateral sclerosis (ALS) is a rare and fatal neurodegenerative disease characterized primarily by muscle atrophy, motor dysfunction, and a range of non-motor symptoms. The pathological hallmark of ALS is the selective degeneration of upper and lower motor neurons, which ultimately leads to death, most commonly due to respiratory failure [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Despite significant advances in understanding its pathogenesis in recent years, no curative treatment is currently available. Current therapeutic strategies are primarily supportive, focusing on symptom management to alleviate discomfort, slow disease progression, and improve patients' quality of life [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eSleep disorders represent some of the most prevalent non-motor symptoms associated with ALS, occurring at a markedly higher frequency than in the general population [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Research indicates that approximately 63% of individuals with ALS experience sleep disorders, in contrast to 37% of healthy controls [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. These disturbances not only detrimentally affect subjective well-being and quality of life but may also expedite disease progression and complicate comprehensive disease management. A study by Li et al. demonstrated that patients with poor sleep quality exhibited more rapid respiratory decline at the time of diagnosis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Consequently, the early identification and management of sleep disorders may contribute to decelerating ALS progression and enhancing patients' quality of life [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHowever, due to the unique characteristics of ALS, conventional treatments for insomnia are often not widely applicable in this population. In the general population, the primary treatments for insomnia include cognitive behavioral therapy for insomnia (CBT-I) and pharmacotherapy. CBT-I improves sleep quality by modifying maladaptive sleep habits and alleviating anxiety. Common pharmacological agents include benzodiazepines, non-benzodiazepine hypnotics, and antidepressants [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, for ALS patients, the implementation of CBT-I is hindered by impairments in speech communication and cognitive comprehension. Moreover, respiratory muscle atrophy leads to compromised respiratory function, making the use of sedative medications substantially riskier due to the heightened potential for respiratory depression or exacerbation of respiratory failure.\u003c/p\u003e\u003cp\u003eTherefore, thoroughly investigating the factors that contribute to sleep disorders in ALS patients is essential for developing safe and feasible individualized intervention strategies. This study aimed to identify the key variables affecting sleep quality in individuals with ALS, thereby providing a theoretical foundation and strategic direction for future development of non-pharmacological treatment approaches adapted to the context of respiratory and communication dysfunction. Ultimately, these findings may expand intervention options and improve overall quality of life and disease management for ALS patients.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e The study protocol was reviewed and approved by the Ethics Committee of Hubei Provincial Hospital of Traditional Chinese Medicine (Ethics approval number: HBZY2024-C38-01). All methods were performed in accordance with relevant guidelines and regulations. Informed consent was obtained from all participants or their legal guardians. The study was conducted in full compliance with the principles outlined in the Declaration of Helsinki.\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study Participants\u003c/h2\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e\u003ch2\u003e2.1.1 Inclusion Criteria\u003c/h2\u003e\u003cp\u003eBetween January 2022 and January 2025, a cohort of consecutive patients diagnosed with ALS and receiving treatment at the Motor Neuron Disease Rehabilitation and Treatment Center of Hubei Provincial Hospital of Traditional Chinese Medicine were enrolled in the study. The inclusion criteria were as follows: (1) a confirmed diagnosis of ALS in accordance with the 2020 International Gold Coast Criteria; (2) clinical staging between stages 1 and 3 as per the London criteria, with no prior history of gastrostomy, continuous 24-hour non-invasive ventilation (NIV), or tracheostomy; (3) voluntary participation with the provision of signed informed consent.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.1.2 Exclusion Criteria\u003c/h2\u003e\u003cp\u003e(1) A history of severe sleep disorders; (2) Coexisting severe chronic respiratory or cardiac diseases; (3) Use of psychoactive medications within the past six weeks; (4) Cognitive impairments preventing accurate comprehension of questionnaire items.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.2 General data Assessment\u003c/h2\u003e\u003cp\u003eDemographic data included age, sex, smoking history, alcohol consumption, site of disease onset, disease duration, years of education (high school or below, junior college, university or above), marital status (married, divorced, or single), employment status (full-time employed or retired), and monthly household income (5,000 RMB or \u0026ge;\u0026thinsp;5,000 RMB).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Clinical Data Assessment\u003c/h2\u003e\u003cp\u003eAll scale-based assessments were conducted by trained physicians from the Motor Neuron Disease Rehabilitation and Treatment Center at Hubei Provincial Hospital of Traditional Chinese Medicine. Disease progression rate was calculated as:[(48\u0026thinsp;\u0026minus;\u0026thinsp;baseline ALSFRS-R score) / 48 \u0026times; 100%] [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e\u003cb\u003eSleep disorders assessment\u003c/b\u003e: Sleep disorders were assessed using the Pittsburgh Sleep Quality Index (PSQI), which provides a comprehensive evaluation of sleep quality in ALS patients. The PSQI is a self-reported questionnaire that evaluates sleep over the past month across seven domains: subjective sleep quality, sleep latency, sleep duration, sleep efficiency, sleep disorder, use of sleep medication, and daytime dysfunction [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. It consists of 19 self-rated items, each domain scored from 0 to 3, for a total score ranging from 0 to 21. This standardized tool has demonstrated adequate validity and reliability in various populations, including ALS patients, and can be used for longitudinal assessment of sleep quality [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A total score greater than 5 indicates poor sleep quality.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDisease severity assessment\u003c/strong\u003e\u003cp\u003eDisease severity was assessed using the revised ALS Functional Rating Scale (ALSFRS-R), which evaluates physical function and disease progression in ALS patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This instrument includes 12 items covering bulbar function, limb mobility, respiratory function, and activities of daily living. Each item is scored based on functional performance, with total scores ranging from 0 to 48; higher scores indicate better physical function and daily living ability.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDaytime sleepiness assessment\u003c/strong\u003e\u003cp\u003eDaytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS), a widely used instrument to evaluate excessive daytime sleepiness in ALS patients [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The ESS consists of eight items, each scored from 0 to 3, with a total score ranging from 0 to 24. A total ESS score\u0026thinsp;\u0026ge;\u0026thinsp;10 suggests significant daytime sleepiness, while a score\u0026thinsp;\u0026ge;\u0026thinsp;15 indicates severe somnolence.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eFatigue condition assessment\u003c/strong\u003e\u003cp\u003eFatigue was evaluated using the Fatigue Severity Scale (FSS) [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], which includes nine items rated on a 7-point Likert scale (1\u0026thinsp;=\u0026thinsp;strongly disagree; 7\u0026thinsp;=\u0026thinsp;strongly agree), with total scores ranging from 9 to 63. Scores\u0026thinsp;\u0026ge;\u0026thinsp;36 indicate clinically significant fatigue requiring intervention\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eAnxiety and depression assessment\u003c/strong\u003e\u003cp\u003eAnxiety and depression are critical factors affecting the quality of life in ALS patients [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Therefore, anxiety and depressive symptoms were evaluated using the Hamilton Anxiety Rating Scale (HARS) and the Hamilton Depression Rating Scale (HDRS) [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The HARS comprises 14 items, each scored from 0 to 4; a total score\u0026thinsp;\u0026gt;\u0026thinsp;7 indicates the presence of anxiety symptoms. The HDRS includes 17 items, each scored from 0 to 4, with a total score\u0026thinsp;\u0026gt;\u0026thinsp;7 suggesting depressive symptoms.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003ePain assessment\u003c/strong\u003e\u003cp\u003ePain intensity over the past 30 days was evaluated using the Visual Analog Scale (VAS) [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The VAS is a self-reported tool in which respondents are presented with a numeric rating scale and asked to indicate their pain level on a continuum from 0 to 10, where 0 represents no pain and 10 represents the worst imaginable pain. A VAS score of \u0026ge;\u0026thinsp;4 was considered indicative of moderate to severe pain, while a score\u0026thinsp;\u0026lt;\u0026thinsp;4 indicated mild pain.\u003c/p\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Data analysis\u003c/h2\u003e\u003cp\u003eData analysis was conducted using R version 4.3.3. The Kolmogorov-Smirnov test was used to assess the normality of basic information and clinical indicators. Continuous variables that followed a normal distribution were described using the mean and standard deviation (SD). Continuous variables that did not follow a normal distribution were expressed as median and interquartile range (IQR). Categorical variables were summarized using patient counts and percentages. The independent samples t-test was used to compare continuous variables with normal distribution between two groups; the Mann-Whitney U test was used for non-normally distributed continuous variables; the chi-square test was used to analyze differences between categorical variables in the two groups.\u003c/p\u003e\u003cp\u003eInitially, to investigate the influencing factors of sleep disorders, the presence or absence of such disorders was treated as a binary dependent variable. A univariate logistic regression analysis was conducted to compute the odds ratio (OR) along with its 95% confidence interval (CI). Variables that demonstrated a P-value of less than 0.05 in the univariate analysis were subsequently included in a multivariate logistic regression model to ascertain independent risk factors. All statistical tests were two-tailed, with a significance threshold set at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. The model's fit was validated, and multicollinearity was evaluated using the variance inflation factor (VIF).\u003c/p\u003e\u003cp\u003eSubsequently, to further examine the factors affecting sleep quality, the total score of the Pittsburgh Sleep Quality Index (PSQI) was used as a continuous dependent variable. An initial univariate linear regression analysis was performed, and variables with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were incorporated into a multivariate stepwise linear regression model. The model underwent rigorous testing for linearity, independence of residuals, homoscedasticity, and normality to ensure analytical accuracy. A two-tailed P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was deemed statistically significant.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Baseline data characteristics\u003c/h2\u003e\u003cp\u003eA total of 266 patients with ALS were enrolled in this study, of whom 163 were male and 103 were female, with a mean age of 54 years and a mean disease duration of 17.44 months. Among them, 176 patients (66.16%) reported sleep disorders, including 103 males (58.52%) and 73 females (41.48%). No significant differences were observed between ALS patients with and without sleep disorders in terms of ALSFRS-R Bulbar (ALSFRS-RB), ESS, FVC, disease duration, education level, caregiver status, working status, region of onset, smoking history, drinking history, or sex (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (refer to Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of general data between the two groups of ALS patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eALS patients without sleep disorder (n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALS patients with sleep disorder\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;176)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e54.00 (47.00, 60.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e50.00 (43.25, 57.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e55.00 (49.00, 61.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZ=-2.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.003\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation Level, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.818\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigh school and below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e146 (54.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (52.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e99 (56.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ejunior college\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e51 (19.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (20.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (18.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUniversity and above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e69 (25.94)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25 (27.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44 (25.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eworking status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=3.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.155\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFull-time work\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e107 (40.23)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (46.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (36.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ejobless\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e98 (36.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (36.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (36.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eretire\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e61 (22.93)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (16.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (26.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarital Status, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003edivorce\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003emarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e260 (97.74)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 (97.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e172 (97.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003esingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (1.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (1.14)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIncome, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.493\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;3000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (14.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (10.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (17.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e99 (37.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (38.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e64 (36.36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3000\u0026mdash;4999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (16.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (16.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (15.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5000\u0026ndash;10000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85 (31.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31 (34.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (30.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCaregiver, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=0.70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.404\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eself-care\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (17.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (20.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (15.91)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTaking care of others\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e220 (82.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e72 (80.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e148 (84.09)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRegion Of Onset, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=0.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.963\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBulbar\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (15.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14 (15.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (15.34)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003elimb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e225 (84.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76 (84.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e149 (84.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSmoking History, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.660\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182 (68.42)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e122 (69.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84 (31.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (33.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (30.68)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDrinking History, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.604\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e177 (66.54)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58 (64.44)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e119 (67.61)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89 (33.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e32 (35.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e57 (32.39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSexuality, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eχ\u0026sup2;=1.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.197\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e103 (38.72)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30 (33.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73 (41.48)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e163 (61.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (66.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e103 (58.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003et: t-test, Z: Mann-Whitney test, χ\u0026sup2;: Chi-square test, -: Fisher exact\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSD: standard deviation, M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eThe Student's t-test (with Mann-Whitney U test when necessary) was used to compare continuous variables and the chi-squared test was used to analyze categorical variables. The meaning of the bold values represented statistically significant values in the statistical analysis. The meaning of the bold values represented statistically significant values in the statistical analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eHowever, compared to ALS patients without sleep disorders, those with sleep disorders demonstrated lower scores on the on the ALSFRS-R Limb (ALSFRS-RL), ALSFRS-R Respiratory (ALSFRS-RR), and overall ALSFRS-R, while exhibiting higher scores on the FSS, VAS, HARS, and HDRS scores. Additionally, patients with sleep disorders exhibited more rapid disease progression and were of an older age (refer to Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of baseline clinical characteristics between the two groups of ALS patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;266)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eALS patients without sleep disorder (n\u0026thinsp;=\u0026thinsp;90)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eALS patients with sleep disorder\u003c/p\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;176)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eStatistic\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33.36\u0026thinsp;\u0026plusmn;\u0026thinsp;14.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.80\u0026thinsp;\u0026plusmn;\u0026thinsp;13.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.21\u0026thinsp;\u0026plusmn;\u0026thinsp;13.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-4.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVAS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.95\u0026thinsp;\u0026plusmn;\u0026thinsp;1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-2.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.016\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHARS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.96\u0026thinsp;\u0026plusmn;\u0026thinsp;7.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.51\u0026thinsp;\u0026plusmn;\u0026thinsp;4.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.24\u0026thinsp;\u0026plusmn;\u0026thinsp;8.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-8.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDRS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11.83\u0026thinsp;\u0026plusmn;\u0026thinsp;7.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.91\u0026thinsp;\u0026plusmn;\u0026thinsp;4.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.33\u0026thinsp;\u0026plusmn;\u0026thinsp;7.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-5.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESS, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.22\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.07\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-1.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.297\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RB, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.06\u0026thinsp;\u0026plusmn;\u0026thinsp;2.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.46\u0026thinsp;\u0026plusmn;\u0026thinsp;2.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.85\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;1.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RL, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.74\u0026thinsp;\u0026plusmn;\u0026thinsp;5.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.02\u0026thinsp;\u0026plusmn;\u0026thinsp;5.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.09\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.011\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RR, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.86\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.43\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.57\u0026thinsp;\u0026plusmn;\u0026thinsp;2.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;3.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-R, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.66\u0026thinsp;\u0026plusmn;\u0026thinsp;8.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.91\u0026thinsp;\u0026plusmn;\u0026thinsp;7.26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.51\u0026thinsp;\u0026plusmn;\u0026thinsp;8.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;3.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease Progression Rate, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.71\u0026thinsp;\u0026plusmn;\u0026thinsp;1.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.34\u0026thinsp;\u0026plusmn;\u0026thinsp;1.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.90\u0026thinsp;\u0026plusmn;\u0026thinsp;2.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et=-2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.017\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease duration, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17.44\u0026thinsp;\u0026plusmn;\u0026thinsp;8.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.58\u0026thinsp;\u0026plusmn;\u0026thinsp;7.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17.37\u0026thinsp;\u0026plusmn;\u0026thinsp;8.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u0026thinsp;=\u0026thinsp;0.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.842\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFVC, M (Q₁, Q₃)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e76.76 (63.80, 90.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e74.81 (62.31, 89.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e79.08 (69.56, 92.31)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eZ=-1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.100\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003et: t-test, Z: Mann-Whitney test, χ\u0026sup2;: Chi-square test, -: Fisher exact\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSD: standard deviation, M: Median, Q₁: 1st Quartile, Q₃: 3st Quartile\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eFSS,Fatigue Severity Scale; VAS,Visual Analog Scale; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ESS,Epworth Sleepiness Scale;ALSFRS-RB,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Bulbar Function;ALSFRS-RL, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; ALSFRS-R, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised;FVC,Forced Lung Function; The Student's t-test (with Mann-Whitney U test when necessary) was used to compare continuous variables and the chi-squared test was used to analyze categorical variables. The meaning of the bold values represented statistically significant values in the statistical analysis.The meaning of the bold values represented statistically significant values in the statistical analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Logistic regression analysis of sleep disorders in patients with ALS\u003c/h2\u003e\u003cp\u003eUsing the presence of sleep disorders (PSQI\u0026thinsp;\u0026gt;\u0026thinsp;5) as the dependent variable, this study included variables such as the FSS, VAS, HARS, HDRS, ALSFRS-RL, ALSFRS-RR, Age and disease progression rate in univariate binary logistic regression analyses, with univariate binary logistic regression results detailed in Supplementary Table\u0026nbsp;1. Variables that achieved a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analyses were subsequently included in a multivariate logistic regression model. Predictor variables were selected using a bidirectional stepwise regression method. The findings revealed that anxiety levels (as measured by the HARS score) and fatigue severity (as measured by the FSS score) were independent risk factors for sleep disorders in patients with ALS (refer to Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariate binary logistic regression analysis of factors associated with sleep disorders.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eS.E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eOR (95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e0.023\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.03 (1.01\u0026thinsp;~\u0026thinsp;1.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.81\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.13 (1.08\u0026thinsp;~\u0026thinsp;1.19)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e-0.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-1.76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.86 (0.72\u0026thinsp;~\u0026thinsp;1.02)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.119\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.02 (0.99\u0026thinsp;~\u0026thinsp;1.05)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProgression Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.20 (0.95\u0026thinsp;~\u0026thinsp;1.52)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003eFSS, Fatigue Severity Scale;VAS,Visual Analog Scale;Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ALSFRS-RL, Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; OR, odds ratio. The binary logistic stepwise regression analysis (Two-way stepwise method) was used. The meaning of the bold values represented statistically significant values in the statistical analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Linear regression analysis of sleep quality\u003c/h2\u003e\u003cp\u003eUtilizing the total PSQI score as a continuous dependent variable, further univariate linear regression analyses were conducted to explore potential clinical correlates of sleep quality. The variables included ALSFRS-RB, ESS score, disease duration and FVC in addition to the previously described factors. Detailed results of the univariate regression are presented in Supplementary Table\u0026nbsp;2. Variables with P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analysis were entered into a multivariate stepwise linear regression model. The results indicated that FSS score, VAS score, HARS score and disease progression rate were the primary factors influencing sleep quality in patients with ALS, as presented in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Collinearity analysis indicated that all VIFs were below 10, as shown in Supplementary Table\u0026nbsp;3.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFactors related to sleep quality in multiple linear regression analysis.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eβ\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eS.E\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003et\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eβ (95%CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFSS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.06 (0.02\u0026thinsp;~\u0026thinsp;0.09)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVAS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.38 (0.10\u0026thinsp;~\u0026thinsp;0.66)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHARS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;.001\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.21 (0.15\u0026thinsp;~\u0026thinsp;0.26)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eESS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RL\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALSFRS-RR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.03 (-0.01\u0026thinsp;~\u0026thinsp;0.08)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eProgression Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.009\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.31 (0.08\u0026thinsp;~\u0026thinsp;0.55)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDisease duration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFVC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"7\"\u003eFSS, Fatigue Severity Scale;VAS,Visual Analog Scale;Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function; HARS, Hamilton Anxiety Rating Scale; HDRS, Hamilton Depression Rating Scale; ESS,Epworth Sleepiness Scale;ALSFRS-RB,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Bulbar Function;ALSFRS-RL,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised limbs; ALSFRS-RR,Amyotrophic Lateral Sclerosis Functional Rating Scale-revised Respiratory Function;FVC,Forced Lung Function;A multiple linear stepwise regression model was used. The meaning of the bold values represented statistically significant values in the statistical analysis.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study aimed to investigate factors associated with sleep disorders in patients with ALS. The findings revealed that, compared with patients without sleep disorders, those with such issues were more likely to present with non-motor symptoms such as anxiety, depression, pain, and excessive daytime sleepiness. Multivariate logistic and linear regression analyses indicated that fatigue severity and anxiety levels were independent predictors of both the occurrence of sleep disorders and overall sleep quality in ALS patients. Additionally, linear regression analysis demonstrated that pain intensity and disease progression rate were significantly associated with the severity of sleep disorders.\u003c/p\u003e\u003cp\u003eAnxiety may impact sleep in ALS patients through multiple mechanisms. First, the progressive and incurable nature of ALS may induce persistent anxiety, which in turn activates the brain's fear and salience networks [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e], leading to hyperarousal, difficulty relaxing, and impaired sleep initiation [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Second, anxiety may alter the levels of several neurotransmitters involved in sleep regulation, including adenosine, gamma-aminobutyric acid, dopamine, and serotonin, thereby disrupting sleep architecture [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Additionally, anxiety may elevate cortisol levels and activate the hypothalamic\u0026ndash;pituitary\u0026ndash;adrenal axis, which disrupts the normal circadian rhythm and makes it more difficult for patients to initiate or maintain deep sleep [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFatigue is a common symptom in patients with ALS and is significantly associated with sleep disorders. Fatigue in ALS can be categorized into physical and mental components. Physically, fatigue arises primarily from muscle weakness and increased energy expenditure due to the degeneration of motor neurons, manifesting as progressive muscular decline that severely limits daily activity. Impaired motor function often prevents ALS patients from adjusting their posture or finding a comfortable sleeping position, leading to persistent physical discomfort that significantly impairs sleep quality [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Mentally, fatigue results from increased cognitive load and emotional stress, which may disrupt central nervous system function, reduce the occurrence of deep sleep stages, and further exacerbate sleep impairment [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eHigher VAS scores indicate poorer sleep quality in ALS patients. ALS patients often experience muscle spasms, positional discomfort, and chronic pain, primarily arising from muscle cramps or prolonged static posture, especially in skeletal and joint regions. As the disease progresses, muscle atrophy renders these areas more susceptible to compression, thereby inducing persistent pain [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e], which frequently triggers nocturnal awakenings and disrupts sleep continuity [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, pain may activate central excitatory mechanisms, enhancing sympathetic activity and resulting in difficulty initiating sleep and reduced deep sleep duration [\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. A deeper understanding of the multifaceted nature of pain and its impact on sleep can inform more effective intervention strategies, thereby improving the quality of life for ALS patients.\u003c/p\u003e\u003cp\u003eDisease progression rate in ALS is negatively correlated with sleep quality. Patients with more rapid disease progression are more prone to severe sleep disorders. Faster progression leads to greater diaphragmatic and intercostal muscle weakness, increasing both the incidence and severity of nocturnal hypoventilation and sleep-related breathing disorders, thereby markedly reducing overall sleep efficiency and quality [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Researchers have also found that faster progression is associated with more severe hypothalamic dysfunction; the hypothalamus, a key regulator of the sleep\u0026ndash;wake cycle, has been shown to undergo atrophy and pathological changes in ALS [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. During rapid disease progression, neurotoxic protein deposition may accelerate structural and functional damage in the hypothalamus, further impairing its role in sleep regulation and leading to ongoing deterioration of sleep quality [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study has several strengths. First, 266 ALS patients treated at the Motor Neuron Disease Center of Hubei Provincial Hospital of Traditional Chinese Medicine were recruited. Given the rarity of ALS, this sample size provides adequate representativeness. All assessments were conducted by professionals using standardized scales, ensuring reliable and consistent data. Second, this is the first systematic study in China examining factors influencing sleep disorders in ALS patients. In addition to traditional variables (pain, respiratory function, disease severity), we included psychological and behavioral factors (anxiety, depression, fatigue, daytime sleepiness) to comprehensively assess potential mechanisms influencing sleep from a multidimensional perspective.\u003c/p\u003e\u003cp\u003eHowever, this study also has limitations. First, the cross-sectional design reveals only associations; future longitudinal cohort studies are needed to verify the impact of risk factors such as fatigue and anxiety on ALS prognosis and sleep disorder progression, thereby providing more robust evidence. Second, only patients in clinical stages 1 to 3 were included, excluding those in advanced stages (stages 4\u0026ndash;5). This may limit the applicability of findings to late-stage patients and may not fully reflect sleep disorder characteristics across all disease stages. Future studies should broaden inclusion criteria to enhance representativeness across all disease stages. Finally, reliance on patient-reported measures of sleep quality, anxiety, and fatigue may introduce recall bias and variability due to disease burden or emotional state, potentially affecting objectivity. Future research should incorporate objective measures, such as polysomnography, to improve result accuracy and reliability.\u003c/p\u003e\u003cp\u003eThis study identified several key factors associated with sleep disturbances in patients with ALS, including anxiety, fatigue, chronic pain, and disease progression rate. Future intervention strategies should be tailored to the unique functional limitations of ALS patients, with particular attention to those experiencing speech impairments and restricted motor abilities. Locally adaptable, feasible, and high-adherence interventions are needed.\u003c/p\u003e\u003cp\u003eTo address anxiety, simplified emotional regulation interventions should be developed to accommodate limitations in communication and cognitive function. Potential approaches include adapted CBT, emotional support groups, and mindfulness-based techniques, complemented by digital tools to enhance accessibility and adherence. For fatigue, standardized objective assessment criteria should be established. Interventions should integrate circadian rhythm optimization, energy management, and daily living modifications to mitigate its disruptive effects on sleep architecture. Chronic pain management should employ a comprehensive strategy, including positional adjustments, rehabilitation therapy, and non-pharmacological analgesia, focusing on optimizing nocturnal posture and individualized care. For patients with rapid disease progression, dynamic monitoring of respiratory function and the establishment of early-warning mechanisms should be prioritized. Attention should also be given to potential degeneration of central regulatory systems, such as hypothalamic function. The intervention pathway should be based on stratified assessments and multidisciplinary collaboration to advance ALS sleep management toward precision and personalization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u0026nbsp;\u003c/strong\u003eThis study was funded by the Hubei Provincial Natural Science Foundation (Joint Fund,2023AFD128, 2024AFD279) and Science and Technology Special Project of State Administration of Traditional Chinese Medicine (GZY-KJS-2025-008).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u0026nbsp;\u003c/strong\u003eAll authors contributed substantially to the conception and design of the work. Jiang Qianping: Writing-original draft, Visualization, Methodology, Data curation, Conceptualization. Yang Dan: Methodology, Data curation, Conceptualization. Jiang Rui: Supervision, Data curation. Wan Shilei: Data curation. Wu Miao: Data curation. Xu Dandan: Supervision, Data curation. Zhou Jing: Writing-review \u0026amp; editing, Writing-original draft, Supervision, Funding acquisition.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest:\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical standard statement:\u0026nbsp;\u003c/strong\u003eThis study was approved by the Ethics Committee of Hubei Provincial Hospital of Traditional Chinese Medicine (Wuhan, China, Ethics approval number: HBZY2024-C38-01).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability:\u0026nbsp;\u003c/strong\u003eThe datasets used and analyzed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBrotman R G, Moreno-Escobar M C, Joseph J, et al. 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Neuropathol Appl Neurobiol, 2021,47(7):979-989.DOI:10.1111/nan.12709.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"sleep disorders, amyotrophic lateral sclerosis, ALS, influencing factors, correlation","lastPublishedDoi":"10.21203/rs.3.rs-7024421/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7024421/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAmyotrophic lateral sclerosis (ALS) is a progressive and fatal neurodegenerative disease frequently accompanied by sleep disorders. Conventional insomnia interventions are often unsuitable for ALS patients due to cognitive and respiratory impairments. There is a lack of targeted studies addressing sleep-related issues using multifactorial analyses specific to this group.\u003c/p\u003e\u003ch2\u003eParticipants and Methods:\u003c/h2\u003e\u003cp\u003eThis cross-sectional study included 266 ALS patients at the Motor Neuron Disease Rehabilitation and Treatment Center of Hubei Provincial Hospital of Traditional Chinese Medicine. Participants were evaluated using tools like the Pittsburgh Sleep Quality Index (PSQI) and ALS Functional Rating Scale-Revised (ALSFRS-R). Regression models identified factors affecting sleep disorders and quality.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003ePatients with sleep disorders were more likely to have non-motor symptoms like anxiety, depression, pain, and excessive daytime sleepiness compared to those without. Fatigue severity and anxiety levels were identified as independent influencing factors of sleep disorders. Additionally, fatigue, anxiety, pain intensity, and disease progression rate were significantly linked to sleep quality.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThis study is the first comprehensive analysis of sleep-related factors in Chinese ALS patients, highlighting the crucial roles of fatigue, anxiety, pain, and disease progression rate. It provides a basis for future personalized, non-pharmacological interventions tailored to the specific needs of ALS patients.\u003c/p\u003e","manuscriptTitle":"Influencing factors of Sleep Disorders in Amyotrophic Lateral Sclerosis: A Cross-sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-21 16:56:45","doi":"10.21203/rs.3.rs-7024421/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-12T04:20:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-08-10T19:14:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"203937671547969600670517552236396827077","date":"2025-07-31T20:14:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-29T12:41:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"312341726778152286684965243741976564667","date":"2025-07-17T14:12:08+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-17T09:55:00+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-07-17T09:53:35+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-07-03T17:44:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-07-03T04:11:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-07-02T02:30:48+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dfb3c600-97a5-4fe3-b4b6-17919a52069c","owner":[],"postedDate":"July 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":51699505,"name":"Health sciences/Diseases"},{"id":51699506,"name":"Health sciences/Neurology"},{"id":51699507,"name":"Biological sciences/Neuroscience"}],"tags":[],"updatedAt":"2025-10-06T16:07:59+00:00","versionOfRecord":{"articleIdentity":"rs-7024421","link":"https://doi.org/10.1038/s41598-025-20100-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-09-30 15:57:10","publishedOnDateReadable":"September 30th, 2025"},"versionCreatedAt":"2025-07-21 16:56:45","video":"","vorDoi":"10.1038/s41598-025-20100-y","vorDoiUrl":"https://doi.org/10.1038/s41598-025-20100-y","workflowStages":[]},"version":"v1","identity":"rs-7024421","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7024421","identity":"rs-7024421","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}