Sleep and Breathing最新文献

Purpose: Sleep dysfunction is often reported post-stroke, but its impact on short-term outcomes and caregiver burden remains less studied. Here, we studied the prevalence of sleep dysfunction and its relationship with self-reported depression, caregiver burden, and functional outcome after stroke.

Methods: Prospective observational study where consecutive patients with acute ischemic stroke were recruited at 3 months follow-up visit from stroke outpatient clinic from January 2022-March 2023. After informed consent, all the recruited patients were administered 5 questionnaires[Epworth Sleepiness Scale, Insomnia Severity Index, and Pittsburgh Sleep Quality Index for sleep, Patient Health Quality 9 for depression, and Zarit's Caregiver Burden Scale]. 20% of patients underwent overnight ambulatory level 3 polysomnography. Clinical and sleep characteristics were correlated with functional outcome and caregiver burden scores at 3 and 6 months follow-up.

Results: Of 100 patients, with a mean age of 62.2 ± 11.2 years, 67% had moderate to severe strokes at admission with mean National Institute of Health Stroke Scale [NIHSS] 8.3 ± 6.24.63% reporting one or more sleep disturbances post-stroke. 20% had hypersomnolence,35% had insomnia and 40% had poor sleep quality at 3 months after stroke.45% reported depression and 22% caregivers reported significant burden. Caregiver burden had a strong correlation with patient-reported hypersomnolence and poor sleep quality. Sleep dysfunction showed a significant association with poor functional outcomes at 6 months after stroke.

Conclusion: Sleep dysfunction is present in a significant number of ischemic stroke survivors 3 months after stroke and can contribute to poor functional outcomes and caregiver stress. The impact of early recognition and timely treatment of sleep dysfunction post-stroke needs to be studied in larger populations.

Purpose: Obstructive sleep apnea (OSA) and rapid eye movement (REM) sleep fragmentation are associated with increased fatigue, sleepiness, anxiety and depressive symptoms. However, the clinical significance of REM-predominant OSA (REM-OSA) remains less clear.

Aim: To determine any differences in symptom-burden between REM-OSA and non-REM (NREM) OSA.

Methods: Patients diagnosed with OSA at a University Hospital in Brussels between 25-11-2019 and 19-09-2020 were eligible. REM-OSA was defined as an apnea hypopnea index REM/NREM ratio of at least 2 with a minimum REM-time of 30 min. Severe OSA was excluded due to the expectedly lower prevalence of REM-OSA in this group. All patients completed the Hospital Anxiety and Depression Scale, Big Five Inventory-2, DS-14 questionnaire, SF-36 Health Survey Questionnaire, Pittsburgh Sleep Quality Index, Insomnia Severity Index, Fatigue Assessment Scale, Checklist Individual Strength, Epworth Sleepiness Scale and Stanford Sleepiness Scale at diagnosis.

Results: 209 patients with REM-OSA (112 mild and 97 moderate) and 132 with NREM-OSA (48 mild and 84 moderate) were included. Patients with mild REM-OSA were twice as likely to have a SSS score of 3 or more (defined as excessive daytime sleepiness) compared to NREM-OSA (odds ratio 2.1591, p-value 0.0359). There was no significant difference in anxiety, depression, personality traits, fatigue or sleep quality.

Conclusion: For mild OSA, a predominance of obstructive respiratory events during the REM phase results in a greater impact on excessive daytime sleepiness. To address this symptom, a lower treatment threshold to include symptomatic mild REM-OSA patients may be warranted.

Purpose: Obstructive sleep apnea (OSA) is prevalent in patients with cardiovascular disease (CVD), and is linked to worsened outcomes. Screening tools are essential for early detection and intervention. We aimed to investigate the role of ascending aorta diameter (AAD) obtained from echocardiography in identifying OSA in CVD patients.

Methods: We examined the correlation between AAD and sleep apnea test parameters in 721 hospitalized CVD (including hypertension, coronary artery disease, chronic heart failure, atrial fibrillation, and pulmonary hypertension) patients. Multivariate analyses were performed on all findings. Receiver operator characteristic curve (ROC) analyses were used to determine the role of AAD in detecting OSA.

Results: AAD was significantly higher in patients with OSA than those without OSA. AAD significantly correlated with apnea-hypopnea index (AHI) and saturation-related parameters. In comparison, pulmonary artery diameter did not correlate with AHI but had significant negative correlations with the saturation-related parameters. The area under the ROC of AAD for detecting OSA in CVD patients was 0.70 (95% CI, 0.65-0.74; p < 0.001). In the chronic heart failure subgroup, the area under the curve for AAD was 0.75 (95% CI 0.67-0.82, p < 0.001). The optimal cut-off value of AAD was 31.5 mm, resulting in a sensitivity of 73%, a specificity of 55% in CVD patients, and 29.5 mm with a sensitivity of 82% and a specificity of 64% in chronic heart failure patients.

Conclusions: AAD was associated with the severity of OSA. AAD could be a valuable tool for identifying OSA in CVD patients, particularly in patients with chronic heart failure.

Purpose: This exploratory study introduces a portable, wearable device using a single accelerometer to monitor twelve sleep positions. Targeted for home use, the device aims to assist patients with mild conditions such as gastroesophageal reflux disease (GERD) by tracking sleep postures, promoting healthier habits, and improving both reflux symptoms and sleep quality without requiring hospital-based monitoring.

Methods: The study developed AnpoNet, a lightweight deep learning model combining 1D-CNN and LSTM, optimized with BN and Dropout. The 1D-CNN captures short-term movement features, while the LSTM identifies long-term temporal dependencies. Experiments were conducted on data from 15 participants performing twelve sleep positions, with each position recorded for one minute at a sampling frequency of 50 Hz. The model was evaluated using 5-Fold cross-validation and unseen participant data to assess generalization.

Results: AnpoNet achieved a classification accuracy of 94.67% ± 0.80% and an F1-score of 92.94% ± 1.35%, outperforming baseline models. Accuracy was computed as the mean of accuracies obtained for three participants in the test set, averaged over five independent random seeds. This evaluation approach ensures robustness by accounting for variability in both individual participant performance and model initialization, underscoring its potential for real-world, home-based applications.

Conclusion: This study provides a foundation for a portable system enabling continuous, non-invasive sleep posture monitoring at home. By addressing the needs of GERD patients, the device holds promise for improving sleep quality and supporting positional therapy. Future research will focus on larger cohorts, extended monitoring durations, and user-friendly interfaces for broader adoption.

Purpose: To assess sinonasal function after preservation maxillomandibular advancement (MMA), as initial reports have shown it may decrease postoperatively.

Methods: This prospective study was performed at a tertiary referral center starting January 2023. MMA was performed with previously published nasal modifications to help mitigate negative sinonasal outcomes. Sino-nasal Outcome Test (SNOT-22) and Nasal Obstruction Symptom Evaluation Survey (NOSE) were collected preoperatively, and one and three months postoperatively. Repeated measures ANOVAs with a Bonferroni adjustment were performed for total score, total sinonasal score (sum of questions 1-12), and each symptom. Both p-values and partial eta squared (n_p²) were reported.

Results: Twenty patients were included. Median age was 50.7 years (range 31-65), with 20.0% being female. Preoperative AHI (65.1 ± 28.9) and SpO2 Nadir (78.0% [69.0-82.0]) improved to 12.1 ± 12.1 and 86.0 ± 3.2%. NOSE significantly decreased at one month (55.9 ± 28.4 vs. 8.11 ± 12.0, p < 0.001). Total score and total sinonasal scores significantly decreased postoperatively (49.0 ± 21.6 vs. 18.1 ± 17.4 vs. 12.5 ± 14.1, p < 0.001; 17.3 ± 12.5 vs. 9.2 ± 9.3 vs. 6.3 ± 7.3, p = 0.003) with MMA having large effects on both variables (n_p²=0.72 and 0.35, respectively). MMA had large significant effects on improvement in need to blow nose, nasal blockage, sneezing, runny nose, cough, post-nasal discharge, dizziness, and ear pain at one and three months postoperatively. Facial pain/pressure significantly worsened at one-month but then improved to baseline at three months postoperatively ((1.2 ± 1.4 vs. 1.9 ± 1.5 vs. 1.2 ± 1.4, p = 0.026).

Conclusion: Patients who underwent preservation MMA did not show evidence of worsening sinonasal function, with some evidence that sinonasal function may improve after MMA at three months postoperatively. Long-term follow-up with more patients is needed to support these findings.

Background: Narcolepsy impacts quality of life (QoL) with its symptomatology in hobbies and everyday activities, work and productivity and has social and economic consequences. The aim of this review is to map and synthesize evidence about QoL in narcolepsy patients and to focus on research strategies and publications in the matter.

Methods: A scoping review of articles published between 2014-2025. The initial search of WoS resulted in 7748 articles and 2583 in PubMed being screened for eligibility. Intervention, comorbidity, non-narcolepsy, prevalence and medical trials studies were excluded. We extracted data on bibliometric characteristics, research questions, sample and recruitment method, design, concepts and measures, and the main findings. Two independent reviewers did the screening and analyses. The analyzed data were consulted on with stakeholders to settle gaps, possibilities and directions for future research. This study followed the PRISMA-ScR guidelines.

Results: Twenty papers were included in this study. There is an increasing trend in publishing studies focused on QoL in narcolepsy patients, but its spread is very limited across various audiences. Most of the studies assess the association of narcolepsy symptoms, treatment, mental health or nutritional status and QoL in narcolepsy patients. Most used was a questionnaire-based cross-sectional design comparing a control group vs narcolepsy patients recruited through regular follow up at a sleep clinic or national reference centers or patients' organization.

Conclusion: There is a need to spread knowledge beyond the neurology audience, to widen the scope of research beyond the burden of the symptoms and to employ explorative qualitative designs.

Purpose: Despite increased awareness of sleep hygiene, over 80% of sleep apnea cases remain undiagnosed, underscoring the need for accessible screening methods. This study presents a method for detecting sleep apnea using data from the Apple Watch's inertial measurement unit (IMU).

Methods: An algorithm was developed to extract seismocardiographic and respiratory signals from IMU data, analyzing features such as breathing and heart rate variability, respiratory dips, and body movements. In a cohort of 61 adults undergoing polysomnography, we analyzed 52,337 30-second epochs, with 12,373 (23.6%) identified as apnea/hypopnea episodes. Machine learning models using five classifiers (Logistic Regression, Random Forest, Gradient Boosting, k-Nearest Neighbors, and Multi-layer Perceptron) were trained on data from 41 subjects and validated on 20 subjects.

Results: The Random Forest classifier performed best in per-epoch respiratory event detection, achieving an AUC of 0.827 and an F1 score of 0.572 in the training group, and an AUC of 0.831 and an F1 score of 0.602 in the test group. The model's per-subject predictions strongly correlated with the apnea-hypopnea index (AHI) from polysomnography (r = 0.93) and identified subjects with AHI ≥ 15 with 100% sensitivity and 90% specificity.

Conclusion: Utilizing the widespread availability of the Apple Watch and the low power requirements of the IMU, this approach has the potential to significantly improve sleep apnea screening accessibility.

Background: Obstructive sleep apnoea (OSA) may lead to heart rhythm abnormalities including bradycardia. Our aim was to ascertain clinical and echocardiographic parameters in patients with OSA in whom severe bradycardia was detected in an outpatient setting, as well as to evaluate the efficacy of CPAP therapy on heart rate normalization at the early stages of treatment.

Methods: Fifteen patients mild, moderate or severe OSA and concomitant bradycardia were enrolled. A standard non-invasive diagnostic assessment protocol was followed, including blood tests and echocardiography. The 24-hour Holter ECG was performed to confirm the presence of bradycardia and determine its subtype. Then CPAP therapy was commenced. Throughout the hospitalisation, continued cardiac monitoring was used in all patients, and 3-4 days following CPAP therapy commencement, a follow-up 24-hour Holter ECG was performed.

Results: Out of 15 patients observed, 3 patients did not consent to CPAP therapy, and one patient had to undergo emergency pacemaker implantation before he was started on CPAP. A complete resolution of bradycardia and cardiac conduction abnormalities was achieved in the remaining 11 patients by day 4. of treatment. The mean lowest recorded HR was 52.7 bpm as compared to 33.9 bpm before CPAP therapy commencement (p < 0.0002). Sinus pauses exceeding 2.5s were not detected in any of those patients.

Conclusion: OSA may be comorbid with and precipitate severe bradycardia. CPAP therapy enabled rapid resolution of bradycardia in more than 80% of our cohort, which may potentially prevent pacemaker implantation provided they remain compliant.

Purpose: Obstructive sleep apnea (OSA) affects up to 936 million adults globally and is linked to significant health risks, including neurocognitive impairment, cardiovascular diseases, and metabolic conditions. Despite its prevalence, OSA remains largely underdiagnosed. This study aimed to enhance OSA awareness and risk assessment using the STOP-Bang questionnaire in a telemedicine format.

Methods: During a six-week campaign on a popular Latin American news portal, 5,966 adults completed the STOP-Bang questionnaire. Participants reporting moderate or severe OSA risk were advised to seek clinical evaluation.

Results: Among respondents, 44.7% were identified as having a moderate-to-high risk for OSA. Key risk factors included snoring, witnessed apneas, hypertension, male gender, older age, high BMI, and larger neck circumference. Statistical analyses showed significant associations between these variables and OSA risk.

Conclusions: This study highlights the importance of increasing OSA visibility and early detection in the general population. Despite limitations such as selection bias and potential false negatives/positives with the STOP-Bang tool, the findings demonstrate the potential of media campaigns to raise awareness and prompt early medical consultation. Future efforts should include follow-up assessments to evaluate healthcare-seeking behavior and confirm OSA diagnoses, contributing to improved public health outcomes.

Purpose: Children with achondroplasia (ACH) are at risk for sudden death in infancy due to sleep disordered breathing (SDB) and foramen magnum stenosis (FMS). Sleep studies and neuroimaging are performed in infants with ACH, but interpretation of infant studies is challenging. We sought to describe baseline data on polysomnography (PSG) indices in infants with achondroplasia as well as effects of age and surgery on these parameters.

Methods: Retrospective data were abstracted from the multisite CLARITY ACH database from years 2008-2017. Both obstructive apnea hypopnea index (OAHI) and central apnea index (CAI) were extracted, and effects of age and surgical intervention (adenoidectomy [AD] or cervicomedullary decompression [CMD]) were analyzed.

Results: 172 PSGs from 86 infants were analyzed. In surgically naive children, OAHI decreased over the first year but then increased in the second year, while CAI was mostly stagnant over the first two years. There were no significant differences between age at first PSG or PSG indices for surgically naive infants versus those who underwent AD or CMD. OAHI decreased after AD and CAI decreased after CMD.

Conclusion: Similar to average stature infants, our results demonstrate the need to interpret sleep study findings of children with ACH in the context of age, particularly for obstructive indices. Neither OAHI nor CAI differentiated those infants who subsequently underwent surgery, suggesting that there were other important clinical factors in the surgical decision-making process. Independent of age, AD resulted in improvement in OSA and CMD with improvement in central sleep apnea.