Obstructive Sleep Apnea-hypopnea Syndrome Patients Research Articles

Automatically detecting OSAHS patients based on transfer learning and model fusion

Abstract Snoring is the most typical symptom of obstructive sleep apnea hypopnea syndrome (OSAHS) that can be used to develop a non-invasive approach for automatically detecting OSAHS patients. In this work, a model based on transfer learning and model fusion was applied to classify simple snorers and OSAHS patients. Three kinds of basic models were constructed based on pretrained Visual Geometry Group-16 (VGG16), Pretrained Audio Neural Networks (PANN), and Mel-frequency Cepstral Coefficient (MFCC). The XGBoost was used to select features based on feature importance, the max voting strategy was applied to fuse these basic models and leave-one-subject-out cross validation was used to evaluate the proposed model. The results show that the fused model embedded with top-5 VGG16 features and top-5 PANN features can correctly identify OSAHS patients (AHI>5) with 100% accuracy. The proposed fused model provides a good classification performance with lower computational cost and higher robustness that makes detecting OSAHS patients at home possible.

Ultrasonographic changes and impact factors of diaphragmatic function in patients with obstructive sleep apnea-hypopnea syndrome.

Diaphragmatic impairment has been reported in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients. However, the risk factors of diaphragmatic dysfunction are unclear. This study was conducted to evaluate the diaphragmatic function and to investigate impact factors of ultrasonographic changes of the diaphragm in OSAHS patients. This cross-sectional study recruited 150 snoring patients. All patients were divided into the control group (AHI < 5/h, n = 20), the mild-to-moderate OSAHS group (5/h ≤ AHI ≤ 30/h, n = 61), and the severe OSAHS group (AHI > 30/h, n = 69). Diaphragmatic thickness at function residual capacity (TFRC) and total lung capacity (TTLC) were measured by two-dimensional ultrasound, and the diaphragmatic excursion during tidal and deep breath was measured by M-mode ultrasound. The diaphragmatic thickening fraction (TF) was calculated. Spearman analysis and multiple linear stepwise regression analysis were conducted to analyze the impact factors of diaphragmatic function. TFRC in the control group, mild-to-moderate OSAHS group, and severe OSAHS group was 1.23 (1.10, 1.39) mm, 1.60 (1.43, 1.85) mm, and 1.90 (1.70, 2.25) mm; TTLC was 2.75 (2.53, 2.93) mm, 3.25 (2.90, 3.55) mm, and 3.60 (3.33, 3.90) mm, and TF was 119.23% (102.94, 155.97), 96.55% (74.34, 119.11), and 85.29% (60.68,101.22). There were across-group significant differences in TFRC, TTLC, and TF (P < 0.05). The oxygen desaturation index was the influencing factor of TFRC, TTLC, and TF (P < 0.05). The diaphragm is thickened and diaphragmatic contractility is decreased in OSAHS patients. Nocturnal intermittent hypoxia is a risk factor for diaphragmatic hypertrophy and impaired diaphragmatic contractility.

Clinical efficacy and mechanism study of mid-frequency anti-snoring device in treating moderate obstructive sleep apnea-hypopnea syndrome.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is primarily caused by airway obstruction due to narrowing and blockage in the nasal and nasopharyngeal, oropharyngeal, soft palate, and tongue base areas. The mid-frequency anti-snoring device is a new technology based on sublingual nerve stimulation. Its principle is to improve the degree of oropharyngeal airway stenosis in OSAHS patients under mid-frequency wave stimulation. Nevertheless, there is a lack of clinical application and imaging evidence. To investigate the clinical efficacy and mechanisms of a mid-frequency anti-snoring device in treating moderate OSAHS. We selected 50 patients diagnosed with moderate OSAHS in our hospital between July 2022 and August 2023. They underwent a 4-wk treatment regimen involving the mid-frequency anti-snoring device during nighttime sleep. Following the treatment, we monitored and assessed the sleep apnea quality of life index and Epworth Sleepiness Scale scores. Additionally, we performed computed tomography scans of the oropharynx in the awake state, during snoring, and while using the mid-frequency anti-snoring device. Cross-sectional area measurements in different states were taken at the narrowest airway point in the soft palate posterior and retrolingual areas. Compared to pretreatment measurements, patients exhibited a significant reduction in the apnea-hypopnea index, the percentage of time with oxygen saturation below 90%, snoring frequency, and the duration of the most prolonged apnea event. The lowest oxygen saturation showed a notable increase, and both sleep apnea quality of life index and Epworth Sleepiness Scale scores improved. Oropharyngeal computed tomography scans revealed that in OSAHS patients cross-sectional areas of the oropharyngeal airway in the soft palate posterior area and retrolingual area decreased during snoring compared to the awake state. Conversely, during mid-frequency anti-snoring device treatment, these areas increased compared to snoring. The mid-frequency anti-snoring device demonstrates the potential to enhance various sleep parameters in patients with moderate OSAHS, thereby improving their quality of life and reducing daytime sleepiness. These therapeutic effects are attributed to the device's ability to ameliorate the narrowing of the oropharynx in OSAHS patients.

Evaluation of nocturnal apnea and airflow limitation as indicators for cognitive dysfunction in patients with chronic obstructive pulmonary disease/obstructive sleep apnea hypopnea syndrome overlap syndrome.

The aim of this study is to investigate how much intermittent hypoxemia and airflow limitation contribute to cognitive impairment in overlap syndrome (OS), which is the coexistence of two common diseases, obstructive sleep apnea hypopnea syndrome (OSAHS) and chronic obstructive pulmonary disease (COPD). We conducted a cross-sectional study of patients with OSAHS, COPD or OS, compared with normal controls, to determine the association between sleep apnea/pulmonary function-related indicators and cognitive dysfunction in individuals with OSAHS, COPD or OS. A total of 157 participants were recruited. Both OSAHS and OS presented lower adjusted Montreal cognitive assessment (MoCA) scores compared with COPD group. In addition, the MoCA score was significantly lower in COPD group compared with control group. The incidence of cognitive impairment was 57.4% in OSAHS group, and 78% in OS group, which were significantly higher than COPD group (29%) and control group (8.8%). Furthermore, a broader range of cognitive domains were affected in OS group compared with OSAHS group. Elevated levels of oxygen desaturation index (ODI) and/or apnea hypopnea index (AHI) were positively correlated with increased Epworth sleeping scale (ESS) in OSAHS and OS. Forced vital capacity (FVC), forced expiratory volume in 1s (FEV1) and peak expiratory flow (PEF) were positively correlated with cognitive scores in OSAHS but not in OS. Serum level of hypoxia-inducible factor-1α (HIF-1α) was significantly higher in OS. Logistic regression identified ODI as an independent risk factor for cognitive impairment in OS, while severity of snoring and PEF were independent risk factors in OSAHS. This study revealed significant cognitive impairment in OS, OSAHS and COPD. Sleep-related indicators are warranted in OS patients for detection, differentiation and grading of cognitive impairment, whereas pulmonary functions are warranted in OSAHS patients for detection and early intervention of cognitive impairment.

A machine learning model to predict the risk of depression in US adults with obstructive sleep apnea hypopnea syndrome: a cross-sectional study.

Depression is very common and harmful in patients with obstructive sleep apnea hypopnea syndrome (OSAHS). It is necessary to screen OSAHS patients for depression early. However, there are no validated tools to assess the likelihood of depression in patients with OSAHS. This study used data from the National Health and Nutrition Examination Survey (NHANES) database and machine learning (ML) methods to construct a risk prediction model for depression, aiming to predict the probability of depression in the OSAHS population. Relevant features were analyzed and a nomogram was drawn to visually predict and easily estimate the risk of depression according to the best performing model. This is a cross-sectional study. Data from three cycles (2005-2006, 2007-2008, and 2015-2016) were selected from the NHANES database, and 16 influencing factors were screened and included. Three prediction models were established by the logistic regression algorithm, least absolute shrinkage and selection operator (LASSO) algorithm, and random forest algorithm, respectively. The receiver operating characteristic (ROC) area under the curve (AUC), specificity, sensitivity, and decision curve analysis (DCA) were used to assess evaluate and compare the different ML models. The logistic regression model had lower sensitivity than the lasso model, while the specificity and AUC area were higher than the random forest and lasso models. Moreover, when the threshold probability range was 0.19-0.25 and 0.45-0.82, the net benefit of the logistic regression model was the largest. The logistic regression model clarified the factors contributing to depression, including gender, general health condition, body mass index (BMI), smoking, OSAHS severity, age, education level, ratio of family income to poverty (PIR), and asthma. This study developed three machine learning (ML) models (logistic regression model, lasso model, and random forest model) using the NHANES database to predict depression and identify influencing factors among OSAHS patients. Among them, the logistic regression model was superior to the lasso and random forest models in overall prediction performance. By drawing the nomogram and applying it to the sleep testing center or sleep clinic, sleep technicians and medical staff can quickly and easily identify whether OSAHS patients have depression to carry out the necessary referral and psychological treatment.

Assessing the contribution of mild high-altitude exposure to obstructive sleep apnea-hypopnea syndrome comorbidities.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a common sleep disorder. The lower atmospheric pressure and decreased oxygen levels of high-altitude areas can exacerbate the severity of OSAHS, but research into OSAHS in high-altitude areas remains limited. This study, from June 2015 to January 2020, involved 4,667 patients with suspected OSAHS and 38 healthy volunteers. The non-OSAHS group (AHI <5/h) had 395 patients, while the larger OSAHS group (AHI ≥5/h) comprised 4,272 patients. The significant size difference between the groups emphasized the study's focus on OSAHS, using the non-OSAHS mainly for comparison. Sleep technicians monitored the OSAHS patient group overnight by polysomnography (PSG), the apnea-hypopnea index (AHI), the mean oxygen saturation (MSpO2), lowest oxygen saturation (LSpO2), the oxygen desaturation index (ODI) and the total sleep time with oxygen saturation less than 90% (TST-SpO2 <90%). Healthy volunteers self-monitored sleep patterns at home, using the CONTEC RS01 respiration sleep monitor with a wristwatch sleep apnea screen meter. The RSO1 wristwatch-style device has already been studied for consistency and sensitivity with the Alice-6 standard multi-lead sleep monitor and can be used for OSAHS screening in this region. LSpO2 recordings from healthy volunteers (86.36 ± 3.57%) and non-OSAHS (AHI <5/h) cohort (78.59 ± 11.99%) were much lower than previously reported normal values. Regression analysis identified no correlations between AHI levels and MSpO2 or TST-SpO2 <90%, weak correlations between AHI levels and LSpO2 or MSpO2, and a strongly significant correlation between AHI levels and the ODI (r = 0.76, p < 0.05). The data also indicated that the appropriate clinical thresholds for OSAHS patients living at mild high altitude are classified as mild, moderate, or severe based on LSpO2 saturation criteria of 0.85-0.90, 0.65-0.84, or <0.65, respectively. The study findings suggest that individuals with an AHI score below 5 in OSAHS, who reside in high-altitude areas, also require closer monitoring due to the elevated risk of nocturnal hypoxia. Furthermore, the significant correlation between ODI values and the severity of OSAHS emphasizes the importance of considering treatment options. Additionally, the assessment of hypoxemia severity thresholds in OSAHS patients living in high-altitude regions provides valuable insights for refining diagnostic guidelines.

Lack of associations between thyroid dysfunction and obstructive sleep apnea-hypopnea syndrome: A meta-analysis.

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a comprehensive syndrome with endocrine and metabolic complications. This review aims to explore the correlation between thyroid hormone levels and the severity of OSAHS in patients. The protocol for this meta-analysis has been registered on PROSPERO. Searches were carried out from the inception of the databases to July 18, 2023, utilizing 6 databases (PubMed, CNKI, EMBASE, Web of Science, Cochrane Library, China Biology Medicine, and Wanfang). Standardized mean difference (SMD) and correlation coefficients were used as the effect size measures. Additionally, random effects or fixed effects models were used for pooled analysis. Moreover, data were statistically evaluated with the help of STATA 11.0 and R 4.1.3. This study included 23 articles that satisfied the pre-defined criteria. The prevalence of hypothyroidism and subclinical hypothyroidism in OSAHS patients was 6% and 8%, whereas hyperthyroidism had a prevalence of 2%. Moreover, thyroid hormone levels in OSAHS individuals exhibited no significant difference relative to healthy subjects. Subgroup analysis based on disease severity also established no significant changes in thyroid hormone levels between OSAHS individuals and controls. There was no significant correlation between the Apnea-Hypopnea Index (AHI) and free triiodothyronine (FT3), serum thyroid stimulating hormone (TSH), and free thyroxine (FT4) levels. The prevalence of thyroid dysfunction is relatively low in OSAHS individuals. Thyroid hormone levels show no significant difference between OSAHS patients and healthy subjects. Furthermore, there is no significant correlation between AHI and serum TSH, FT3, and FT4 levels. Based on existing data, the relationship between OSAHS and thyroid function remains controversial, and further in-depth research is warranted to validate the connection and elucidate the underlying mechanisms.

Modified oropharyngeal muscle training and scientific vocalization are effective in treating mild-to-moderate obstructive sleep apnea hypoventilation syndrome in adults

Background Obstructive Sleep Apnea-hypopnea Syndrome (OSAHS) has become a major public health challenge globally. Most patients have a concomitant voice disorder. The existing treatment methods have problems.Aims/Objectives: This study investigates the therapeutic effect of adding scientific vocalization to oropharyngeal muscle training on OSAHS patients. Material and methods A total of 30 patients were selected from September 2020 to October 2022. They underwent overnight polysomnography (PSG) and were identified as having mild to moderate obstructive sleep apnea hypoventilation syndrome. They were then chosen for a three-month period of modified oropharyngeal muscle training combined with scientific vocalization. Results Out of the 30 selected patients, 26 patients completed the training. Results showed a significant changes in multiple sleep-related indicators. he clinical outcomes were as follows: 7 cases were cured, 13 cases were effective, and 6 cases were ineffective. The overall effective rate was 76.92%. Conclusions and significance The combination of oropharyngeal muscle training and scientific vocalization for the treatment of mild to moderate OSAHS in adults significantly improves several measures used in the treatment of the condition. The method is easy to learn, effective, safe to use, and affordable. It provides more options for the treatment of OSAHS.

Identification of OSAHS patients based on ReliefF-mRMR feature selection.

Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a serious chronic sleep disorder. Snoring is a common and easily observable symptom of OSAHS patients. The purpose of this work is to identify OSAHS patients by analyzing the acoustic characteristics of snoring sounds throughout the entire night. Ten types of acoustic features, such as Mel-frequency cepstral coefficients (MFCC), linear prediction coefficients (LPC) and spectral entropy among others, were extracted from the snoring sounds. A fused feature selection algorithm based on ReliefF and Max-Relevance and Min-Redundancy (mRMR) was proposed for optimal feature set selection. Four types of machine learning models were then applied to validate the effectiveness of OSAHS patient identification. The results show that the proposed feature selection algorithm can effectively select features with high contribution, including MFCC and LPC. Based on the selected top-20 features and using a support vector machine model, the accuracies in identifying OSAHS patients under the thresholds of AHI = 5,15, and 30, were 100%, 100%, and 98.94%, respectively. This indicates that the proposed model can effectively identify OSAHS patients.

Interleukin-10 is not associated with obstructive sleep apnea hypopnea syndrome: A meta-analysis and meta-regression.

This study was conducted to explore the potential relationship between interleukin-10 (IL-10) and obstructive sleep apnea hypopnea syndrome (OSAHS). All the related research articles published before October 2022 were retrieved through the online database (EMBASE, VIP, Wan Fang, Web of Science, PubMed, and CNKI). Stata 11.0 software was used to calculate the standard mean difference (SMD) of the continuous variable and 95% confidence interval (CI). Expression profiles GSE38792 and GSE135917 were acquired from Gene Expression Omnibus (GEO) database, respectively. The expression of IL-10 mRNA in subcutaneous adipose tissue and visceral adipose tissue of OSAHS patients and healthy subjects was extracted by R software to verify the difference in IL-10 between the 2 groups. The IL-10 level in the plasma of people with and without OSAHS (STD Mean Difference (SMD) = -0.68, 95% CI = -1.58 to 0.21, I2 = 94.3%, P = .136) was the same. There was also no difference in IL-10 levels in serum between people with and without OSAHS (SMD = -0.12, 95% CI = -0.55 to 0.32, I2 = 94.4%, P = .591). In addition, the subjects were divided into different subgroups for meta-analysis according to race, body mass index, age, study type, and disease severity. Based on the outcomes, no notable difference was observed in the plasma/serum IL-10 level between the OSAHS subgroups and the control group. The results of bioinformatics analysis indicated that there was no significant difference in the expression of IL-10 mRNA in subcutaneous adipose tissue and visceral adipose tissue between patients with OSAHS and those in the control group. The current meta-analysis highlighted that IL-10 levels between patients with OSAHS and healthy people had no difference.

A Classification Method Related to Respiratory Disorder Events Based on Acoustical Analysis of Snoring

Acoustical analysis of snoring provides a new approach for the diagnosis of obstructive sleep apnea hypopnea syndrome (OSAHS). A classification method is presented based on respiratory disorder events to predict the apnea-hypopnea index (AHI) of OSAHS patients. The acoustical features of snoring were extracted from a full night’s recording of 6 OSAHS patients, and regular snoring sounds and snoring sounds related to respiratory disorder events were classified using a support vector machine (SVM) method. The mean recognition rate for simple snoring sounds and snoring sounds related to respiratory disorder events is more than 91.14% by using the grid search, a genetic algorithm and particle swarm optimization methods. The predicted AHI from the present study has a high correlation with the AHI from polysomnography and the correlation coefficient is 0.976. These results demonstrate that the proposed method can classify the snoring sounds of OSAHS patients and can be used to provide guidance for diagnosis of OSAHS.

[Effect of mouth breathing on upper airway structure in patients with obstructive sleep apnea].

Objective:To compare the changes of morphology of pharynx in patients with obstructive sleep apnea hypopnea syndrome （OSAHS） and healthy individuals during oral or nasal breathing, and explore the relevant influencing factors. Methods:Twenty-nine adult patients with OSAHS and 20 non-snoring controls underwent MRI to obtain upper airway structural measurements while the subjects were awake and during mouth breathing with a nasal clip.The following were analyzed. ①The changes of upper airway structure of oral and nasal respiration in non-snoring control/OSAHS patients were observed; ②The differences and influencing factors of upper airway structure changes between OSAHS patients and controls were compared during breathing. Results:The control group consisted of 15 males and 5 females, with an apnea-hypopnea index （AHI）<5 events/h, while the OSAHS group comprised 26 males and 3 females with an AHI of 40.4±23.1 events/h and the mean lowest arterial oxygen saturation （LSaO2） was 79.5% ±10.0%. In the both groups, the vertical distance between the mandible and the posterior pharyngeal wall decreased （P<0.05）; The long axis of tongue body decreased （P<0.05）, and the contact area between tongue and palate decreased. There was no significant change in the total volume of the retropalatine（RP） and retroglossal（RG） airway in the control group （P>0.05）. However, the minimum cross-sectional area and volume of the RP airway in OSAHS decreased （P<0.001）. The lateral diameters of uvula plane in OSAHS decreased during mouth breathing, which was contrary to the trend in the control group （P=0.017）. The AHI of patients was positively correlated with the reduction of the volume of the RP airway during oral breathing （P=0.001）; The reduction of the distance between the mandible and the posterior pharyngeal wall was positively correlated with the length of the airway （P<0.001）. Conclusion:Mouth breathing leads to the shortening of the long axis of the tongue, the reduction of the contact area between the soft palate and the tongue, vertical distance between the mandible and the posterior pharyngeal wall, and the cross-sectional area of the epiglottis plane. These changes vary between OSAHS patients and controls. During mouth breathing, the diameters, areas and volumes of the RP area decreased, and were more significant in severe cases.

AHI estimation of OSAHS patients based on snoring classification and fusion model

Obstructive sleep apnea-hypopnea syndrome (OSAHS) is a chronic and common sleep-breathing disease that could negatively influence lives of patients and cause serious concomitant diseases. Polysomnography(PSG) is the gold standard for diagnosing OSAHS, but it is expensive and requires overnight hospitalization. Snoring is a typical symptom of OSAHS. This study proposes an effective OSAHS screening method based on snoring sound analysis. Snores were labeled as OSAHS related snoring sounds and simple snoring sounds according to real-time PSG records. Three models were used, including acoustic features combined with XGBoost, Mel-spectrum combined with convolution neural network (CNN), and Mel-spectrum combined with residual neural network (ResNet). Further, the three models were fused by soft voting to detect these two types of snoring sounds. The subject's apnea-hypopnea index (AHI) was estimated according to these recognized snoring sounds. The accuracy and recall of the proposed fusion model achieved 83.44% and 85.27% respectively, and the predicted AHI has a Pearson correlation coefficient of 0.913 (R2 = 0.834, p < 0.001) with PSG. The results demonstrate the validity of predicting AHI based on analysis of snoring sound and show great potential for monitoring OSAHS at home.

Convolutional neural network for screening of obstructive sleep apnea using snoring sounds

Screening and assessment for obstructive sleep apnea hypopnea syndrome (OSAHS) has attracted growing attention to improve the life of patients with sleep apnea. The gold standard for diagnosing OSAHS is an overnight polysomnography (PSG) in a dedicated sleep laboratory. Yet, the PSG test is professional, expensive and unsuitable for mass screening of the population. OSAH affects about 10 % of population in the world, and there are about 80 % suffers remaining undiagnosed. The automatic and cheap OSAHS patients screening methods are urgently needed. As a major sign of undiagnosed OSAHS, snoring has been used for diagnosis of OSAHS. An automated snore detection method would allow a faster diagnosis and more patients to be analyzed. In this paper, we build a database including more than 80 thousand of snoring sound episodes from 124 subjects. These sounds are recorded by non-contact microphone in the subject’s private room, and labeled by trained sleep clinicians. And then the visibility graph method is modified as a novel framework for encoding these snoring time series into images to fully take advantage of two-dimension convolutional neural networks (CNN) in computer vision tasks. At last, a CNN model based on visibility graph method (VG) is applied to automatically extract features and recognize severity of OSAHS based on these snoring sounds. The experimental results show that our approach achieves an accuracy of 92.5 %, sensitivity of 93.9 %, and specificity of 91.2 % for OSAHS recognition. Our research provides an alternative method for rapid and massive screening and diagnosis of OSAHS.

Automatic identifying OSAHS patients and simple snorers based on Gaussian mixture models

Objective. Snoring is a typical symptom of Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS). In this study, an effective OSAHS patient detection system based on snoring sounds is presented.Approach. The Gaussian mixture model (GMM) is proposed to explore the acoustic characteristics of snoring sounds throughout the whole night to classify simple snores and OSAHS patients respectively. A series of acoustic features of snoring sounds of are selected based on the Fisher ratio and learned by GMM. Leave-one-subject-out cross validation experiment based on 30 subjects is conducted to validation the proposed model. There are 6 simple snorers (4 male and 2 female) and 24 OSAHS patients (15 male and 9 female) investigated in this work. Results indicates that snoring sounds of simple snorers and OSAHS patients have different distribution characteristics. Main results. The proposed model achieves average accuracy and precision with values of 90.0% and 95.7% using selected features with a dimension of 100 respectively. The average prediction time of the proposed model is 0.134 ± 0.005 s. Significance. The promising results demonstrate the effectiveness and low computational cost of diagnosing OSAHS patients using snoring sounds at home.

Effects of acupuncture on obstructive sleep apnea-hypopnea syndrome: A meta-analysis.

Our study aimed to systematically evaluate the effect of acupuncture in patients with obstructive sleep apnea-hypopnea syndrome (OSAHS). Literature search of four Chinese databases and six English databases for studies published from the inception of each database to March 1, 2022 and identify relevant studies published in Chinese or English. Related randomized controlled trials of acupuncture for the treatment of OSAHS were included to analyze the efficacy of acupuncture. Two researchers independently reviewed all of the retrieved studies to screen for eligible studies and extract the required relevant data. Included studies were subjected to a methodological quality assessment using the Cochrane Manual 5.1.0, and to a meta-analysis using Cochrane Review Manager version 5.4. A total of 19 studies with 1365 participants were examined. Compared with the control group, the apnea-hypopnea index, lowest oxygen saturation, Epworth Sleepiness Scale, interleukin-6, tumor necrosis factor α, and nuclear factor κ-B indicators all exhibited statistically significant changes. Thus, acupuncture was effective in alleviating the state of hypoxia and sleepiness and reduced the inflammatory response and disease severity among reported patients with OSAHS. Therefore, acupuncture could be widely used in the clinical treatment of OSAHS patients as a complementary strategy and warrants further study.

Assessment of Muscular Weakness in Severe Sleep Apnea Patients: A Prospective Study.

There are no official diagnostic tools to evaluate the weakness of the genioglossus muscle. We have developed a protocol for muscular assessment in patients with severe obstructive sleep apnea-hypopnea syndrome (OSAHS) and evaluated its effectiveness. Case and controls prospective study. Sleep Unit Hospital Quironsalud Marbella (Spain). Twenty-nine cases and 20 controls were recruited. Patients were examined by a phonoaudiologist that performed biometric measurements and the Orofacial Myofunctional Evaluation With Scores (OMES), Friedman, and Epworth Sleepiness Scale(ESS). In addition, upper airway muscle strength measures were performed using the Iowa Oral Performance Instrument (IOPI) and Tongue Digital Spoon (TDS). The final cohort consisted of 49 subjects, including 29 cases and 20 controls. According to the univariate and multivariate logistic regression analyses, ESS, OMES protocol, IOPI score, and TDS were associated with severe OSAHS. Multivariate regression revealed an IOPI score below 48 kps with an adjusted odds ratio (OR) of 9.96 (95% confidence interval [CI] 2.5-39.1, p = .001), and a 0.72 specificity (Spe), a 0.79 sensitivity (Sens), and a 0.82 area under the curve (AUC). Similarly, an OMES score lower than 200 had an adjusted risk ratioof 4.02 (95% CI 2-7, p < .001), 1 Spe, 0.79 Sens, and 0.98 AUC; and finally, TDS scores lower than 201 g/cm2 showed an adjusted OR of 27 (95% CI 4.74-153.6, p = .0001), 0.66 Spe, a 0.93 Sens, and a 0.86 AUC. Our findings suggest that severe OSAHS patients present different muscle patterns than controls.

Residents' cognition and attitude towards obstructive sleep apnea hypopnea syndrome.

Obstructive sleep apnea hypopnea syndrome (OSAHS) may cause damage to many organs of the body and is a potentially fatal disease, which has a serious impact on health and quality of life for patients. Residents play an important role in the screening of OSAHS. This study aims to evaluate the cognition and attitude level of residents towards OSAHS, and to provide evidence for the intervention and diagnosis of the disease. A cross-sectional survey of residents at a teaching hospital was conducted from December 1, 2021 to December 1, 2022. A questionnaire was used to assess residents' knowledge, attitudes, and confidence in dealing with OSAHS patients. Of the 200 residents who responded to the questionnaire, 183(91.5%) completed it. The average score on the knowledge scale of Obstructive Sleep Apnea Knowledge and Attitudes Questionnaire (OSAKA) for all residents in this study was 13.12±2.46. The knowledge score of internal medicine residents was higher than that of non-internal medicine residents (13.46±2.22 vs 12.33±2.83, P<0.05), and the mean knowledge score of residents with respiratory rotation experience was higher than that of residents without respiratory rotation experience (13.46±2.35 vs 12.69±2.56, P<0.05). The average score of the attitude/confidence scale on the OSAKA questionnaire for all residents in this study was 3.64±0.62. Of the 183 residents, 60.7% of residents considered OSAHS to be extremely important as a clinical disorder, 72.7% of residents were confident in the identification of OSAHS patients, but only 50.3% were confident in the management of OSAHS patients, and only 42.6% were confident in the management of patients treated with continuous positive pressure ventilation. There was a weak positive correlation among levels of knowledge, attitude, and confidence. Most residents are aware of the clinical importance of OSAHS, but their knowledge and confidence for OSAHS diagnosis and management are still insufficient, and they need to be trained to manage OSAHS patients.

The role of platelet-related parameters for the prediction of NAFLD in OSAHS patients

PurposeAs the detection of non-alcoholic fatty liver disease (NAFLD) is imperative for the prevention of its complications, we aimed to explore the predictive value of platelet to lymphocyte count ratio (PLR) and white blood cell count to mean platelet volume ratio (WBC/MPV) in relation to the occurrence of NAFLD among patients with obstructive sleep apnea–hypopnea syndrome (OSAHS).MethodsThis was a cross-sectional study consisting of 351 patients with OSAHS (279 with and 72 without NAFLD). The logistic regression analysis was performed to estimate associations between PLR, WBC/MPV, and NAFLD. Finally, the receiver operating characteristic curve (ROC curve) was used to analyze the efficacy of PLR and WBC/MPV in NAFLD prediction.ResultsCompared to the OSAHS-only group, there was a rising trend in AHI and TS90% in the OSAHS + NAFLD group. And the logistic regression analysis identified average oxygen saturation (MaSO2), WBC/MPV and PLR as predicted factors (odds ratio [OR] = 1.134, P = 0.031; OR = 7.559, P = 0.018, OR = 0.980, P < 0.001, respectively) for NAFLD in OSAHS patients. Moreover, compared with WBC/MPV, PLR, FLI, and APRI, a combination of WBC/MPV and PLR presented the largest AUC for the detection of NAFLD in BMI < 28 kg/m2 (0.753, 95% CI 0.684–0.822), and in age ≥ 60 years subgroup (0.786, 95% CI 0.692–0.880) in ROC analysis. Meanwhile, a combination of WBC/MPV and PLR presented the second largest AUC for the detection of NAFLD in all subjects (0.743, 95% CI 0.708–0.831), as well as in the age < 60 years subgroup (0.729, 95% CI 0.652–0.806), only ranked after FLI, suggesting the combination of WBC/MPV and PLR has a good predictive value for NAFLD in OSAHS patients.ConclusionWe confirmed that the levels of WBC/MPV, PLR, and MaSO2 were closely related to the occurrence of NAFLD among OSAHS patients. Furthermore, our results highlighted the clinical combination of WBC/MPV and PLR levels could act as a simple and effective biomarker for screening NAFLD in patients with OSAHS.

Continuous positive airway pressure may improve hypertension in patients with obstructive sleep apnea-hypopnea syndrome by inhibiting inflammation and oxidative stress.

The work was designed to investigate the effect of continuous positive airway pressure (CPAP) on hypertension in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients and to elucidate the underlying mechanisms. We examined the effect of CPAP on blood pressure and biomarkers reflecting inflammation and oxidative stress, and investigated the correlation between changes in blood pressure and the biomarkers. CPAP significantly improved clinic, ambulatory and home blood pressure (p < 0.05). The hypotensive effect of CPAP was positively correlated with the decrease of interleukin-6, C-reactive protein, NADPH oxidase and malonaldehyde. CPAP has a significant antihypertensive effect on OSAHS patients, especially nocturnal hypertension, possibly by counteracting inflammation and oxidative stress.