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International Heart Journal 2024This study aimed to clarify (1) the association among the atrial fibrillation (AF) type, sleep-disordered breathing (SDB), heart failure (HF), and left atrial (LA)...
Bidirectional Association Among the Type of Atrial Fibrillation, Sleep-Disordered Breathing Severity, Heart Failure Progression, and Left Atrial Enlargement, in Patients with Atrial Fibrillation.
This study aimed to clarify (1) the association among the atrial fibrillation (AF) type, sleep-disordered breathing (SDB), heart failure (HF), and left atrial (LA) enlargement, (2) the independent predictors of LA enlargement, and (3) the effects of ablation on those conditions in patients with AF. The study's endpoint was LA enlargement (LA volume index [LAVI] ≥ 78 mL/m).Of 423 patients with nonvalvular AF, 236 were enrolled. We evaluated the role of the clinical parameters such as the AF type, SDB severity, and HF in LA enlargement. Among them, 141 patients exhibiting a 3% oxygen desaturation index (ODI) of ≥ 10 events/hour underwent polysomnography to evaluate the SDB severity measured by the apnea-hypopnea index (AHI). The LA enlargement and HF were characterized by the LA diameter/LAVI, an increase in the B-type natriuretic peptide level, and a lower left ventricular ejection fraction.This study showed that non-paroxysmal AF (NPAF) rather than paroxysmal AF (PAF), the SDB severity, LA enlargement, and HF progression had bidirectional associations and exacerbated each other, which generated a vicious cycle that contributed to the LA enlargement. NPAF (OR = 4.55, P < 0.001), an AHI of ≥ 25.10 events/hour (OR = 1.55, P = 0.003), and a 3% ODI of ≥ 15.43 events/hour (OR = 1.52, P = 0.003) were independent predictors of an acceleration of the LA enlargement. AF ablation improved the HF and LA enlargement.To break this vicious cycle, AF ablation may be the basis for suppressing the LA enlargement and HF progression subsequently eliminating the substrates for AF and SDB in patients with AF.
Topics: Humans; Atrial Fibrillation; Male; Female; Sleep Apnea Syndromes; Heart Failure; Disease Progression; Middle Aged; Aged; Heart Atria; Severity of Illness Index; Catheter Ablation; Polysomnography; Atrial Remodeling; Echocardiography
PubMed: 38825490
DOI: 10.1536/ihj.23-493 -
NPJ Digital Medicine Jun 2024Apnea and hypopnea are common sleep disorders characterized by the obstruction of the airways. Polysomnography (PSG) is a sleep study typically used to compute the...
Apnea and hypopnea are common sleep disorders characterized by the obstruction of the airways. Polysomnography (PSG) is a sleep study typically used to compute the Apnea-Hypopnea Index (AHI), the number of times a person has apnea or certain types of hypopnea per hour of sleep, and diagnose the severity of the sleep disorder. Early detection and treatment of apnea can significantly reduce morbidity and mortality. However, long-term PSG monitoring is unfeasible as it is costly and uncomfortable for patients. To address these issues, we propose a method, named DRIVEN, to estimate AHI at home from wearable devices and detect when apnea, hypopnea, and periods of wakefulness occur throughout the night. The method can therefore assist physicians in diagnosing the severity of apneas. Patients can wear a single sensor or a combination of sensors that can be easily measured at home: abdominal movement, thoracic movement, or pulse oximetry. For example, using only two sensors, DRIVEN correctly classifies 72.4% of all test patients into one of the four AHI classes, with 99.3% either correctly classified or placed one class away from the true one. This is a reasonable trade-off between the model's performance and the patient's comfort. We use publicly available data from three large sleep studies with a total of 14,370 recordings. DRIVEN consists of a combination of deep convolutional neural networks and a light-gradient-boost machine for classification. It can be implemented for automatic estimation of AHI in unsupervised long-term home monitoring systems, reducing costs to healthcare systems and improving patient care.
PubMed: 38824175
DOI: 10.1038/s41746-024-01139-z -
Frontiers in Big Data 2024To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely...
OBJECTIVE
To develop a robust machine learning prediction model for the automatic screening and diagnosis of obstructive sleep apnea (OSA) using five advanced algorithms, namely Extreme Gradient Boosting (XGBoost), Logistic Regression (LR), Support Vector Machine (SVM), Light Gradient Boosting Machine (LightGBM), and Random Forest (RF) to provide substantial support for early clinical diagnosis and intervention.
METHODS
We conducted a retrospective analysis of clinical data from 439 patients who underwent polysomnography at the Affiliated Hospital of Xuzhou Medical University between October 2019 and October 2022. Predictor variables such as demographic information [age, sex, height, weight, body mass index (BMI)], medical history, and Epworth Sleepiness Scale (ESS) were used. Univariate analysis was used to identify variables with significant differences, and the dataset was then divided into training and validation sets in a 4:1 ratio. The training set was established to predict OSA severity grading. The validation set was used to assess model performance using the area under the curve (AUC). Additionally, a separate analysis was conducted, categorizing the normal population as one group and patients with moderate-to-severe OSA as another. The same univariate analysis was applied, and the dataset was divided into training and validation sets in a 4:1 ratio. The training set was used to build a prediction model for screening moderate-to-severe OSA, while the validation set was used to verify the model's performance.
RESULTS
Among the four groups, the LightGBM model outperformed others, with the top five feature importance rankings of ESS total score, BMI, sex, hypertension, and gastroesophageal reflux (GERD), where Age, ESS total score and BMI played the most significant roles. In the dichotomous model, RF is the best performer of the five models respectively. The top five ranked feature importance of the best-performing RF models were ESS total score, BMI, GERD, age and Dry mouth, with ESS total score and BMI being particularly pivotal.
CONCLUSION
Machine learning-based prediction models for OSA disease grading and screening prove instrumental in the early identification of patients with moderate-to-severe OSA, revealing pertinent risk factors and facilitating timely interventions to counter pathological changes induced by OSA. Notably, ESS total score and BMI emerge as the most critical features for predicting OSA, emphasizing their significance in clinical assessments. The dataset will be publicly available on my Github.
PubMed: 38817683
DOI: 10.3389/fdata.2024.1353469 -
Chest May 2024Stroke is the second-leading cause of death worldwide. Obstructive sleep apnea (OSA) is an independent risk factor for stroke and is associated with multiple vascular... (Review)
Review
TOPIC IMPORTANCE
Stroke is the second-leading cause of death worldwide. Obstructive sleep apnea (OSA) is an independent risk factor for stroke and is associated with multiple vascular risk factors. Post-stroke OSA is prevalent and closely linked with various stroke subtypes including cardioembolic stroke and cerebral small vessel disease. Observational studies have demonstrated that untreated post-stroke OSA is associated with an increased risk of recurrent stroke, mortality, poorer functional recovery and longer hospitalizations.
REVIEW FINDINGS
Post-stroke OSA tends to be underdiagnosed and under-treated, possibly because stroke patients with OSA present atypically compared to the general population with OSA. Objective testing, such as the use of ambulatory sleep testing or in-laboratory polysomnography, is recommended for diagnosing OSA. The gold standard for treating OSA is continuous positive airway pressure (CPAP) therapy. Randomized controlled trials (RCTs) have shown that treatment of post-stroke OSA using CPAP improves non-vascular outcomes such as cognition and neurological recovery. However, RCTs that have evaluated the effect of CPAP on recurrent stroke risk and mortality have been largely negative.
SUMMARY
There is a need for high quality RCTs in post-stroke OSA that may provide evidence to support the utility of CPAP (and/or other treatment modalities) in reducing recurrent vascular events and mortality. This may be achieved by examining treatment strategies that have yet to be trialed in post-stroke OSA, tailoring interventions according to post-stroke OSA endotypes and phenotypes, selecting high risk populations, and using metrics that reflect the physiological abnormalities that underlie the harmful effects of OSA on cardiovascular outcomes.
PubMed: 38815623
DOI: 10.1016/j.chest.2024.04.028 -
Turkish Journal of Medical Sciences 2024Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder in children. Determination of risk factors for the development of OSA is essential for early...
BACKGROUND/AIM
Obstructive sleep apnea (OSA) is a common sleep-related breathing disorder in children. Determination of risk factors for the development of OSA is essential for early diagnosis and treatment of the disease and decreases the risk of negative consequences. This study aimed to investigate the predictive values of Mallampati score, tonsillar size, and BMI z-score in the presence and severity of OSA in children.
MATERIALS AND METHODS
This prospective cross-sectional study included 114 children with OSA symptoms. All children were assessed by BMI z-score, Mallampati score, and tonsillar size and underwent overnight polysomnography. They were consecutively selected and assigned to 4 groups as follows: Group 1 included normal-weight with a low Mallampati score; Group 2 involved normal-weight with a high Mallampati score; Group 3 included obese with a low Mallampati score; and Group 4 involved obese with a high Mallampati score.
RESULTS
Of the 114 included children, 58 were female and 56 were male, with a mean age of 13.1 ± 2.9 years. OSA frequency and apnea-hypopnea index were significantly higher in group 4 compared with other groups (p = 0.003 and p < 0.0001, respectively), whereas average and minimum spO were significantly lower (for both, p = 0.001). Mallampati score and BMI z-score were found to be significant for predicting OSA (odds ratio = 4.147, 95% CI: 1.440-11.944; p = 0.008 and odds ratio = 1.760, 95% CI: 1.039-2.980; p = 0.035, respectively). Among OSA patients, the Mallampati score, tonsillar size, and BMI z-score were found to be significant for predicting OSA severity (odds ratio = 4.520, 95% CI: 1.332-15.335, p = 0.015, odds ratio = 9.177, 95% CI: 2.513-33.514, p = 0.001, and odds ratio = 2.820, 95% CI: 1.444-5.508; p = 0.002, respectively).
CONCLUSION
The coexistence of the Mallampati score and BMI z-score significantly increases the presence of OSA in children. Mallampati score, tonsillar size, and BMI z-score are promising parameters for predicting OSA severity.
Topics: Humans; Sleep Apnea, Obstructive; Male; Female; Palatine Tonsil; Cross-Sectional Studies; Body Mass Index; Prospective Studies; Child; Adolescent; Severity of Illness Index; Polysomnography; Predictive Value of Tests; Risk Factors
PubMed: 38812649
DOI: 10.55730/1300-0144.5791 -
Archives of Cardiovascular Diseases 2024Sacubitril/valsartan has been demonstrated to significantly improve left ventricular performance and remodelling in patients with heart failure. However, its effects on... (Observational Study)
Observational Study
BACKGROUND
Sacubitril/valsartan has been demonstrated to significantly improve left ventricular performance and remodelling in patients with heart failure. However, its effects on the right ventricle in patients with chronic heart failure and sleep-disordered breathing (SDB) have not been studied.
AIM
To investigate the impact of sacubitril/valsartan treatment on right ventricular function in patients with SDB.
METHODS
This was a subanalysis of an observational prospective multicentre study involving 101 patients. At inclusion, patients were evaluated by echocardiography and nocturnal ventilatory polygraphy, which allowed patients to be divided into three groups: "central-SDB"; "obstructive-SDB"; and "no-SDB".
RESULTS
After 3 months of sacubitril/valsartan therapy, a positive impact on right ventricular function was observed. In the general population, tricuspid annular plane systolic excursion increased by +1.32±4.74mm (P=0.024) and systolic pulmonary artery pressure decreased by -3.1±10.91mmHg (P=0.048). The central-SDB group experienced the greatest echocardiographic improvement, with a significant increase in tricuspid annular plane systolic excursion of +2.1±4.9mm (P=0.045) and a significant reduction in systolic pulmonary artery pressure of -8.4±9.7mmHg (P=0.001).
CONCLUSIONS
Sacubitril/valsartan improved right ventricular function in patients with heart failure and SDB after only 3 months of treatment. The greatest improvement in right ventricular function was observed in the central-SDB group.
Topics: Humans; Valsartan; Drug Combinations; Male; Female; Aminobutyrates; Ventricular Function, Right; Prospective Studies; Biphenyl Compounds; Middle Aged; Treatment Outcome; Aged; Heart Failure; Time Factors; Recovery of Function; Sleep Apnea, Central; Angiotensin II Type 1 Receptor Blockers; Tetrazoles; Protease Inhibitors; Polysomnography; Neprilysin; Chronic Disease
PubMed: 38811278
DOI: 10.1016/j.acvd.2024.04.003 -
CoDAS 2024To investigate oropharyngeal structures and functions in a pediatric population with Down Syndrome (DS) and obstructive sleep apnea (OSA) and to correlate with the...
PURPOSE
To investigate oropharyngeal structures and functions in a pediatric population with Down Syndrome (DS) and obstructive sleep apnea (OSA) and to correlate with the apnea/hypopnea index (AHI) and sleep questionnaires.
METHODS
12 Children with DS and OSA, between the age of 4 and 12 years old, underwent polysomnography (PSG); sleep questionnaires, Pediatric Sleep Questionnaire (PSQ) and Obstructive Sleep Apnea-18 (OSA-18); and speech-language evaluation using the Short Evaluation of Orofacial Myofunctional Protocol (ShOM).
RESULTS
There was a positive correlation between ShoM higher scores and the apnea-hypopnea index (AHI) and between ShoM and the number of hypopneas. The orofacial myofunctional alterations observed in the studied group were: oral breathing, alteration in lip tonus and competence, tongue posture at rest and in swallowing, and occlusal alteration. There was also an increased risk for OSA according to the sleep questionnaires, as well as the presence of obesity and overweight, but without correlation with the severity of OSA.
CONCLUSION
All DS children show alterations in orofacial characteristics, higher scores being associated to severe OSA. Orofacial myofunctional evaluation may help to identify different phenotypes in Down syndrome children with Obstructive sleep Apnea, enhancing the need for a multidisciplinary approach.
Topics: Humans; Down Syndrome; Sleep Apnea, Obstructive; Child; Pilot Projects; Polysomnography; Male; Female; Child, Preschool; Surveys and Questionnaires; Severity of Illness Index; Mouth Breathing; Tongue; Facial Muscles; Cross-Sectional Studies
PubMed: 38808857
DOI: 10.1590/2317-1782/20242023119pt -
Otolaryngologia Polska = the Polish... Jun 2024Sleep is the physiological state of the body where proper morphology and duration are indispensable for human functions throughout both, physical and mental spheres....
INTRODUCTION
Sleep is the physiological state of the body where proper morphology and duration are indispensable for human functions throughout both, physical and mental spheres. Disordered breathing during sleep impairs its morphology and results in major disorders in any age group. Adverse effects of Obstructive Sleep Apnea Syndrome in children and poor availability of centers offering children's polysomnography call for a reliable and easily accessible screening method.
AIM
The aim of the study were to evaluate the usefulness of pulse transit time in the diagnostics of disordered sleep breathing in children and to attempt to employ the parameter in screening tests. Pulse transit time is a physiological parameter determining the time needed for the pulse wave to travel between two measurement points.
MATERIAL AND METHODS
Enrolled in the retrospective study were 153 patients (100 boys and 53 girls) suspected of obstructive sleep apnea syndrome who underwent polysomnography at I. Mościcki ENT Hospital in Chorzów.
RESULTS
Statistically significant relations between apnea/hypopnea index and pulse transit time were observed in both, individual age groups and all of the patients. Pulse transit time results proved a negative correlation with apnea/hypopnea index values commonly accepted as a parameter concluding the polysomnography procedures.
CONCLUSIONS
The results of the study indicate that pulse transit time measurements may find application in screening tests of sleep-disordered breathing in children.
Topics: Humans; Male; Female; Child; Retrospective Studies; Pulse Wave Analysis; Polysomnography; Child, Preschool; Sleep Apnea Syndromes; Sleep Apnea, Obstructive; Adolescent
PubMed: 38808637
DOI: No ID Found -
Cureus May 2024Obstructive sleep apnea syndrome (OSAS) is a severe condition that is characterized by recurrent partial or complete breathing interruptions during sleep, leading to...
INTRODUCTION
Obstructive sleep apnea syndrome (OSAS) is a severe condition that is characterized by recurrent partial or complete breathing interruptions during sleep, leading to insulin resistance, microvascular complications, and cardiovascular complications. It is of great importance to know the impact of type 2 diabetes mellitus (DM), which is prevalent in the world and in our country, Turkey, leads to significant mortality and morbidity, significantly affects the quality of life, and requires continuous follow-up, on sleep in patients with OSAS and to raise awareness on this issue. In this study, we aimed to determine the effects of diabetes on sleep duration and sleep architecture in patients with OSAS and to investigate the relationship between OSAS severity and DM control.
METHODS
Fifty diabetic and 42 non-diabetic patients diagnosed with OSAS at the Sleep Disorders Center of Süreyyapaşa Chest Diseases and Thoracic Surgery Training and Research Hospital, Istanbul, Turkey, between October 2022 and March 2023 were included in the study. Polysomnographic and biochemical parameters of the two groups were compared. The effect of OSAS severity and sleep architecture on diabetes control was investigated.
RESULTS
No significant difference was found between diabetic and non-diabetic patients in terms of total sleep duration, sleep efficiency, and sleep latency, whereas REM (rapid eye movement) latency was prolonged and REM sleep duration and percentage were significantly lower in diabetic patients. The severity of OSAS was found to be greater in diabetic patients and they spent significantly more time below 90% saturation during sleep. No correlation was found between the groups in the glycated hemoglobin (HbA1c) parameter, which we examined in terms of diabetes control, sleep architecture, and OSAS severity.
CONCLUSION
The presence of diabetes aggravates the severity of OSAS, prolongs the transition to REM sleep, and leads to a decrease in REM duration. Sleep is essential for both mental and physical well-being. In this regard, it is of utmost importance to examine diabetic patients for OSAS and to perform polysomnography in appropriate patients.
PubMed: 38807970
DOI: 10.7759/cureus.61215 -
Frontiers in Psychiatry 2024To examine serum concentrations of neurotensin, pannexin-1 and sestrin-2, and their correlations with subjective and objective sleep quality and cognitive function in...
OBJECTIVES
To examine serum concentrations of neurotensin, pannexin-1 and sestrin-2, and their correlations with subjective and objective sleep quality and cognitive function in the patients with chronic insomnia disorder (CID).
METHODS
Sixty-five CID patients were enrolled continuously and fifty-six good sleepers in the same period were served as healthy controls (HCs). Serum levels of neurotensin, pannexin-1 and sestrin-2 were measured by enzyme-linked immunosorbent assays. Sleep quality was assessed with the Pittsburgh Sleep Quality Index (PSQI) and polysomnography, and mood was evaluated by 17-item Hamilton Depression Rating Scale. General cognitive function was assessed with the Chinese-Beijing Version of Montreal Cognitive Assessment and spatial memory was evaluated by Blue Velvet Arena Test (BVAT).
RESULTS
Relative to the HCs, the CID sufferers had higher levels of neurotensin (=5.210, <0.001) and pannexin-1 (=-4.169, <0.001), and lower level of sestrin-2 (=-2.438, =0.015). In terms of objective sleep measures, pannexin-1 was positively associated with total sleep time (=0.562, =0.002) and sleep efficiency (=0.588, =0.001), and negatively with wake time after sleep onset (=-0.590, =0.001) and wake time (=-0.590, =0.001); sestrin-2 was positively associated with percentage of rapid eye movement sleep (=0.442, =0.016) and negatively with non-rapid eye movement sleep stage 2 in the percentage (=-0.394, =0.034). Adjusted for sex, age and HAMD, pannexin-1 was still associated with the above objective sleep measures, but sestrin-2 was only negatively with wake time (=-0.446, =0.022). However, these biomarkers showed no significant correlations with subjective sleep quality (PSQI score). Serum concentrations of neurotensin and pannexin-1 were positively associated with the mean erroneous distance in the BVAT. Adjusted for sex, age and depression, neurotensin was negatively associated with MoCA score (=-0.257, =0.044), pannexin-1 was positively associated with the mean erroneous distance in the BVAT (=0.270, =0.033).
CONCLUSIONS
The CID patients had increased neurotensin and pannexin-1 and decreased sestrin-2 in the serum levels, indicating neuron dysfunction, which could be related to poor sleep quality and cognitive dysfunction measured objectively.
PubMed: 38803679
DOI: 10.3389/fpsyt.2024.1360305