Polysomnographic Phenotypes of Obstructive Sleep Apnea in a Real-Life Cohort: A Pathophysiological Approach

Introduction: Obstructive sleep apnea (OSA) is heterogeneous and complex, but its severity is still based on the apnea–hypoapnea index (AHI). The present study explores using cluster analysis (CA), the additional information provided from routine polysomnography (PSG) to optimize OSA categorization. Methods: Cross-sectional study of OSA subjects diagnosed by PSG in a tertiary hospital sleep unit during 2016–2020. PSG, demographical, clinical variables, and comorbidities were recorded. Phenotypes were constructed from PSG variables using CA. Results are shown as median (interquartile range). Results: 981 subjects were studied: 41% females, age 56 years (45–66), overall AHI 23events/h (13–42) and body mass index (BMI) 30kg/m2 (27–34). Three PSG clusters were identified: Cluster 1: “Supine and obstructive apnea predominance” (433 patients, 44%). Cluster 2: “Central, REM and shorter-hypopnea predominance” (374 patients, 38%). Cluster 3: “Severe hypoxemic burden and higher wake after sleep onset” (174 patients, 18%). Based on classical OSA severity classification, subjects are distributed among the PSG clusters as severe OSA patients (AHI≥30events/h): 46% in cluster 1, 17% in cluster 2 and 36% in cluster 3; moderate OSA (15≤AHI<30events/h): 57% in cluster 1, 34% in cluster 2 and 9% in cluster 3; mild OSA (5≤AHI<15events/h): 28% in cluster 1, 68% in cluster 2 and 4% in cluster 3. Conclusions: The CA identifies three specific PSG phenotypes that do not completely agree with classical OSA severity classification. This emphasized that using a simplistic AHI approach, the OSA severity is assessed by an incorrect or incomplete analysis of the heterogeneity of the disorder. (AU)

Polysomnographic Phenotypes of Obstructive Sleep Apnea in a Real-Life Cohort: A Pathophysiological Approach.

INTRODUCTION: Obstructive sleep apnea (OSA) is heterogeneous and complex, but its severity is still based on the apnea-hypoapnea index (AHI). The present study explores using cluster analysis (CA), the additional information provided from routine polysomnography (PSG) to optimize OSA categorization. METHODS: Cross-sectional study of OSA subjects diagnosed by PSG in a tertiary hospital sleep unit during 2016-2020. PSG, demographical, clinical variables, and comorbidities were recorded. Phenotypes were constructed from PSG variables using CA. Results are shown as median (interquartile range). RESULTS: 981 subjects were studied: 41% females, age 56 years (45-66), overall AHI 23events/h (13-42) and body mass index (BMI) 30kg/m2 (27-34). Three PSG clusters were identified: Cluster 1: "Supine and obstructive apnea predominance" (433 patients, 44%). Cluster 2: "Central, REM and shorter-hypopnea predominance" (374 patients, 38%). Cluster 3: "Severe hypoxemic burden and higher wake after sleep onset" (174 patients, 18%). Based on classical OSA severity classification, subjects are distributed among the PSG clusters as severe OSA patients (AHI≥30events/h): 46% in cluster 1, 17% in cluster 2 and 36% in cluster 3; moderate OSA (15≤AHI<30events/h): 57% in cluster 1, 34% in cluster 2 and 9% in cluster 3; mild OSA (5≤AHI<15events/h): 28% in cluster 1, 68% in cluster 2 and 4% in cluster 3. CONCLUSIONS: The CA identifies three specific PSG phenotypes that do not completely agree with classical OSA severity classification. This emphasized that using a simplistic AHI approach, the OSA severity is assessed by an incorrect or incomplete analysis of the heterogeneity of the disorder.

COVID-19 in patients with pulmonary alveolar proteinosis: a European multicentre study.

Adult PAP patients experience similar #COVID19 rates to the general population, and high rates of hospitalisation and deaths, underscoring their vulnerability and the need for measures to prevent infection. The impact of iGM-CSF must be considered. https://bit.ly/3M0wKnZ.

Outcomes of COVID-19 Patients Admitted to the Intermediate Respiratory Care Unit: Non-Invasive Respiratory Therapy in a Sequential Protocol.

The intermediate respiratory care units (IRCUs) have a pivotal role managing escalation and de-escalation between the general wards and the intensive care units (ICUs). Since the COVID-19 pandemic began, the early detection of patients that could improve on non-invasive respiratory therapies (NRTs) in IRCUs without invasive approaches is crucial to ensure proper medical management and optimize limiting ICU resources. The aim of this study was to assess factors associated with survival, ICU admission and intubation likelihood in COVID-19 patients admitted to IRCUs. Observational retrospective study in consecutive patients admitted to the IRCU of a tertiary hospital from March 2020 to April 2021. Inclusion criteria: hypoxemic respiratory failure (SpO2 ≤ 94% and/or respiratory rate ≥ 25 rpm with FiO2 > 50% supplementary oxygen) due to acute COVID-19 infection. Demographic, comorbidities, clinical and analytical data, and medical and NRT data were collected at IRCU admission. Multivariate logistic regression models assessed factors associated with survival, ICU admission, and intubation. From 679 patients, 79 patients (12%) had an order to not do intubation. From the remaining 600 (88%), 81% survived, 41% needed ICU admission and 37% required intubation. In the IRCU, 51% required non-invasive ventilation (NIV group) and 49% did not (non-NIV group). Older age and lack of corticosteroid treatment were associated with higher mortality and intubation risk in the scheme, which could be more beneficial in severe forms. Initial NIV does not always mean worse outcomes.

Evolving mortality and clinical outcomes of hospitalized subjects during successive COVID-19 waves in Catalonia, Spain.

BACKGROUND: The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak. METHODS: We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a 7-joinpoint regression analysis, we split admissions into four waves. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU). FINDINGS: The analysis included 17,027 subjects admitted during the first wave (6800; 39.9%), summer wave (1807; 10.6%), second wave (3804; 22.3%), and third wave (4616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main factors contributing to differences in 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms. INTERPRETATION: Although in-hospital COVID-19 mortality remains high, it decreased substantially after the first wave and is highly dependent of patient's characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress. FUNDING: This work did not receive specific funding.

Individual outcome prediction models for patients with COVID-19 based on their first day of admission to the intensive care unit.

BACKGROUND: Currently, good prognosis and management of critically ill patients with COVID-19 are crucial for developing disease management guidelines and providing a viable healthcare system. We aimed to propose individual outcome prediction models based on binary logistic regression (BLR) and artificial neural network (ANN) analyses of data collected in the first 24 h of intensive care unit (ICU) admission for patients with COVID-19 infection. We also analysed different variables for ICU patients who survived and those who died. METHODS: Data from 326 critically ill patients with COVID-19 were collected. Data were captured on laboratory variables, demographics, comorbidities, symptoms and hospital stay related information. These data were compared with patient outcomes (survivor and non-survivor patients). BLR was assessed using the Wald Forward Stepwise method, and the ANN model was constructed using multilayer perceptron architecture. RESULTS: The area under the receiver operating characteristic curve of the ANN model was significantly larger than the BLR model (0.917 vs 0.810; p < 0.001) for predicting individual outcomes. In addition, ANN model presented similar negative predictive value than the BLR model (95.9% vs 94.8%). Variables such as age, pH, potassium ion, partial pressure of oxygen, and chloride were present in both models and they were significant predictors of death in COVID-19 patients. CONCLUSIONS: Our study could provide helpful information for other hospitals to develop their own individual outcome prediction models based, mainly, on laboratory variables. Furthermore, it offers valuable information on which variables could predict a fatal outcome for ICU patients with COVID-19.

Clinical Outcomes of Severe COVID-19 Patients Admitted to an Intermediate Respiratory Care Unit.

Introduction: Many severe COVID-19 patients require respiratory support and monitoring. An intermediate respiratory care unit (IMCU) may be a valuable element for optimizing patient care and limited health-care resources management. We aim to assess the clinical outcomes of severe COVID-19 patients admitted to an IMCU. Methods: Observational, retrospective study including patients admitted to the IMCU due to COVID-19 pneumonia during the months of March and April 2020. Patients were stratified based on their requirement of transfer to the intensive care unit (ICU) and on survival status at the end of follow-up. A multivariable Cox proportional hazards method was used to assess risk factors associated with mortality. Results: A total of 253 patients were included. Of them, 68% were male and median age was 65 years (IQR 18 years). Ninety-two patients (36.4%) required ICU transfer. Patients transferred to the ICU had a higher mortality rate (44.6 vs. 24.2%; p < 0.001). Multivariable proportional hazards model showed that age ≥65 years (HR 4.14; 95%CI 2.31-7.42; p < 0.001); chronic respiratory conditions (HR 2.34; 95%CI 1.38-3.99; p = 0.002) and chronic kidney disease (HR 2.96; 95%CI 1.61-5.43; p < 0.001) were independently associated with mortality. High-dose systemic corticosteroids followed by progressive dose tapering showed a lower risk of death (HR 0.15; 95%CI 0.06-0.40; p < 0.001). Conclusions: IMCU may be a useful tool for the multidisciplinary management of severe COVID-19 patients requiring respiratory support and non-invasive monitoring, therefore reducing ICU burden. Older age and chronic respiratory or renal conditions are associated with worse clinical outcomes, while treatment with systemic corticosteroids may have a protective effect on mortality.

Beneficial effect of corticosteroids in preventing mortality in patients receiving tocilizumab to treat severe COVID-19 illness.

OBJECTIVES: To assess the characteristics and risk factors for mortality in patients with severe coronavirus disease-2019 (COVID-19) treated with tocilizumab (TCZ), alone or in combination with corticosteroids (CS). METHODS: From March 17 to April 7, 2020, a real-world observational retrospective analysis of consecutive hospitalized adult patients receiving TCZ to treat severe COVID-19 was conducted at our 750-bed university hospital. The main outcome was all-cause in-hospital mortality. RESULTS: A total of 1,092 patients with COVID-19 were admitted during the study period. Of them, 186 (17%) were treated with TCZ, of which 129 (87.8%) in combination with CS. Of the total 186 patients, 155 (83.3 %) patients were receiving noninvasive ventilation when TCZ was initiated. Mean time from symptoms onset and hospital admission to TCZ use was 12 (±4.3) and 4.3 days (±3.4), respectively. Overall, 147 (79%) survived and 39 (21%) died. By multivariate analysis, mortality was associated with older age (HR = 1.09, p < 0.001), chronic heart failure (HR = 4.4, p = 0.003), and chronic liver disease (HR = 4.69, p = 0.004). The use of CS, in combination with TCZ, was identified as a protective factor against mortality (HR = 0.26, p < 0.001) in such severe COVID-19 patients receiving TCZ. No serious superinfections were observed after a 30-day follow-up. CONCLUSIONS: In patients with severe COVID-19 receiving TCZ due to systemic host-immune inflammatory response syndrome, the use of CS in addition to TCZ therapy, showed a beneficial effect in preventing in-hospital mortality.

Effectiveness of an intensive weight-loss program for severe OSA in patients undergoing CPAP treatment: a randomized controlled trial.

STUDY OBJECTIVES: To determine whether an intensive weight-loss program (IWLP) is effective for reducing weight, the severity of obstructive sleep apnea (OSA), and metabolic variables in patients with obesity and severe OSA undergoing continuous positive airway pressure treatment. METHODS: Forty-two patients were randomized to the control (CG, n = 20) or the intervention group (IG, n = 22), who followed a 12-month IWLP. The primary outcome was a reduction in the apnea-hypopnea index (AHI) as measured at 3 and 12 months by full polysomnography. Metabolic variables, blood pressure, body fat composition by bioimpedance, carotid intima media thickness, and visceral fat by computed tomography were also assessed. RESULTS: Mean age was 49 (6.7) years, body mass index 35 (2.7) kg/m², and AHI 69 (20) events/h. Weight reduction was higher for the IG than the CG at 3 and 12 months, -10.5 versus -2.3 kg (P < .001), and -8.2 versus -0.1 kg (P < .001), respectively, as was loss of visceral fat at 12 months. AHI decreased more in the IG at 3 months (-23.72 versus -9 events/h) but the difference was not significant at 12 months, though 28% of patients from the IG had an AHI < 30 events/h compared to none in the CG (P = .046). At 12 months, the IG showed a reduction in C-reactive protein (P = .013), glycated hemoglobin (P = .031) and an increase in high density lipoprotein cholesterol (P = .027). CONCLUSIONS: An IWLP in patients with obesity and severe OSA is effective for reducing weight and OSA severity. It also results in an improvement in lipid profiles, glycemic control, and inflammatory markers. CLINICAL TRIAL REGISTRATION: Registry: ClinicalTrials.gov; Title: Effectiveness of an Intensive Weight Loss Program for Obstructive Sleep Apnea Syndrome (OSAS) Treatment; Identifier: NCT02832414; URL: https://clinicaltrials.gov/ct2/show/record/NCT02832414.

Anthropometrical phenotypes are important when explaining obstructive sleep apnea in female bariatric cohorts.

Central obesity is the main risk factor for obstructive sleep apnea (OSA). Whether there exists a central-obesity anthropometric that better explains apnea-hypopnea index (AHI) variability in the general population and in sleep cohorts is unknown, and this is even less explored among increasing grades of obesity. The objective of the study is to investigate whether there is an anthropometric that better explains AHI variability in a sample of morbidly obese women awaiting bariatric surgery (BS). A prospective multicentre cross-sectional study was conducted in consecutive women before BS. Demographic and anthropometric characteristics included age, body mass index (BMI), neck circumference (NC), waist circumference (WC), hip circumference (HC) and waist-to-hip ratio (WHR). OSA was diagnosed by polysomnography. The capacity of anthropometrics to explain AHI variance was investigated using regression linear models. A total of 115 women were evaluated: age, 44 ± 10 years; BMI, 46 ± 5 kg/m2 ; AHI, 35 ± 26 events/hr. AHI was associated with all anthropometrics except weight, height and HC. The best univariate predictor was WHR, which accounted for 15% of AHI variance. The simplest model (age + BMI) accounted for 9%, which increased to 20% when applying more complex measurements (age + BMI + NC + WC + HC). The explanatory capacity did not change significantly when applying a simpler model (age + WHR + NC, 19%). In this female morbidly obese cohort, anthropometrics explained one-fifth of AHI variability. WHR is the best univariate parameter and models including waist and neck data provide more information than BMI when explaining AHI variability. Thus, even in young women with extreme obesity, OSA seems to be linked to a specific central-obesity phenotype rather than to a whole-obesity pattern.

A randomized controlled trial: branched-chain amino acid levels and glucose metabolism in patients with obesity and sleep apnea.

There is evidence that changes in branched-chain amino acid (BCAA) levels may correlate with the efficacy of therapeutic interventions for affecting improvement in metabolic control. The objective of this study was to evaluate whether serum concentrations of BCAAs (leucine, isoleucine, valine) could mediate in insulin sensitivity and glucose tolerance after continuous positive airway pressure (CPAP) treatment in patients with obstructive sleep apnea (OSA). A prospective randomized controlled trial of OSA patients with morbid obesity was conducted. Eighty patients were randomized into two groups: 38 received conservative treatment and 42 received CPAP treatment for 12 weeks. Plasma levels of BCAA, glucose tolerance and insulin resistance were evaluated at baseline and after treatment. After treatment, significant decreases of leucine levels were observed in both groups when compared with baseline levels (P < 0.005). With respect to patients with normal glucose tolerance (NGT), patients with impaired glucose tolerance (IGT) had higher baseline levels of isoleucine (78 ± 16 versus 70 ± 13 µmol L-1 , P = 0.014) and valine (286 ± 36 versus 268 ± 41 µmol L-1 , P = 0.049), respectively. Changes in levels of leucine and isoleucine after treatment were related negatively to changes in fasting plasma glucose and glycosylated haemoglobin values only in the conservative group (P < 0.05). In summary, we found that the treatment with CPAP for 12 weeks caused similar changes in circulating BCAAs concentrations to conservative treatment and a differential metabolic response of CPAP and conservative treatment was observed between the relationship of BCAAs and glucose homeostasis. Additional studies are needed to determine the interplay between branched-chain amino acids and glucose metabolism in patients with sleep apnea.

A Randomized Controlled Trial of Continuous Positive Airway Pressure on Glucose Tolerance in Obese Patients with Obstructive Sleep Apnea.

STUDY OBJECTIVES: Obstructive sleep apnea (OSA) is associated with an increased prevalence of metabolic syndrome (MetS), even in patients with morbid obesity. Our goal was to address whether continuous positive airway pressure (CPAP) treatment improved glucose metabolism in this population. METHODS: A prospective randomized controlled trial was performed in severe OSA patients with morbid obesity without diabetes in two university referral hospitals. Patients received conservative (CT) versus CPAP treatment for 12 weeks. MetS components, homeostasis model assessment of insulin resistance (HOMA-IR) and oral glucose tolerance were assessed at baseline and after treatment. RESULTS: A total of 80 patients completed the study (42 CPAP and 38 CT patients). After 12 w of CPAP treatment, weight loss was similar in both groups and physical activity, prevalence of MetS, and HOMA-IR did not change in either group. In the CPAP group impaired glucose tolerance (IGT) reversed in nine patients and IGT developed in none, whereas IGT reversed in five patients and IGT developed in five patients in the CT group (P = 0.039 in the Fisher test). Changes in 2-h plasma glucose after glucose load were greater in the CPAP group than in the CT group (CPAP: -0.5 ± 1.5 versus CT: 0.33 ± 1.9, P = 0.007). CONCLUSIONS: The improvement of glucose tolerance in morbidly obese patients with severe obstructive sleep apnea, without changes in homeostasis model assessment of insulin resistance, supports an improvement in peripheral insulin resistance after continuous positive airway pressure treatment. CLINICAL TRIALS REGISTRATION: NCT 01029561.

Impact of OSA on biological markers in morbid obesity and metabolic syndrome.

BACKGROUND AND OBJECTIVE: There is compelling evidence that obstructive sleep apnoea (OSA) can affect metabolic syndrome (MetS) and cardiovascular risk, but the intermediate mechanisms through which it occurs have not been well defined. We explored the impact of OSA in morbidly obese patients with MetS on adipokines, pro-inflammatory markers, endothelial dysfunction, and atherosclerosis markers. METHODS: We included 52 morbidly obese patients in an observational study matched for age, gender and central obesity in 3 groups (OSA-MetS, Non-OSA-MetS, and Non OSA-non-MetS). Anthropometrical, blood pressure, and fasting blood measurements were obtained the morning after an overnight polysomnography. VEGF, soluble CD40 ligand (sCD40L), TNF-α, IL-6, leptin, adiponectin, and chemerin were determined in serum by ELISA. OSA was defined as apnea/ hypopnea index ≥ 15 and MetS by NCEP-ATP III. RESULTS: Cases and control subjects did not differ in age, BMI, waist circumference, and gender (43 ± 10 years, 46 ± 5 kg/m(2), 128 ± 10 cm, 71% females). The cases had severe OSA with 47 (32-66) events/h, time spent < 90% SpO2 7% (5%-31%). All groups presented similar serum cytokines, adipokines, VEGF, and sCD40L levels. CONCLUSIONS: In a morbidly obese population with established MetS, the presence of OSA did not determine any differences in the studied mediators when matched by central obesity. Morbidly obese NonOSA-NonMetS had a similar inflammatory, adipokine VEGF, and sCD40L profile as those with established MetS, with or without OSA. Obesity itself could overwhelm the effect of sleep apnea and MetS in the studied biomarkers. CITATION: Salord N; Gasa M; Mayos M; Fortuna-Gutierrez AM; Montserrat JM; Sánchez-de-la-Torre M; Barceló A; Barbé F; Vilarrasa N; Monasterio C. Impact of OSA on biological markers in morbid obesity and metabolic syndrome.

Residual sleepiness in sleep apnea patients treated by continuous positive airway pressure.

Hypoxic brain damage might explain persistent sleepiness in some continuous positive airway pressure-compliant obstructive sleep apnea called residual excessive sleepiness. Although continuous positive airway pressure may not be fully efficient in treating this symptom, wake-promoting drug prescription in residual excessive sleepiness is no longer allowed by the European Medicines Agency. The aim of this study is to describe residual excessive sleepiness phenotypes in a large prospective sample of patients with obstructive sleep apnea. Residual excessive sleepiness was defined by an Epworth Sleepiness Scale score ≥ 11. Eligible patients from the French National Sleep Registry attending follow-up continuous positive airway pressure visits numbered 1047. Patients using continuous positive airway pressure < 3 h (n = 275), with residual apnea-hypopnea index > 15 h⁻¹ (n = 31) or with major depression were excluded (n = 150). Residual excessive sleepiness prevalence in continuous positive airway pressure-treated obstructive sleep apnea was 13% (18% for those with an initial Epworth Sleepiness Scale score > 11), and significantly decreased with continuous positive airway pressure use (9% in ≥ 6 h night⁻¹ continuous positive airway pressure users, P < 0.005). At the time of diagnosis, patients with residual excessive sleepiness had worse subjective appreciation of their disease (general health scale, Epworth Sleepiness Scale and fatigue score), and complained more frequently of continuous positive airway pressure side-effects. Residual excessive sleepiness prevalence was lower in severe obstructive sleep apnea than in moderate obstructive sleep apnea (11% when AHI > 30 h⁻¹ versus 18% when AHI 15-30, P < 0.005). There was no relationship between residual excessive sleepiness and body mass index, cardiovascular co-morbidities or diabetes. Continuous positive airway pressure improved symptoms in the whole population, but to a lower extent in patients with residual excessive sleepiness (fatigue scale: -5.2 versus -2.7 in residual excessive sleepiness- and residual excessive sleepiness+ patients, respectively, P < 0.001). Residual excessive sleepiness prevalence decreased with continuous positive airway pressure compliance. Hypoxic insult is unlikely to explain residual excessive sleepiness as obstructive sleep apnea severity does not seem to be critical. Residual symptoms are not limited to sleepiness, suggesting a true 'continuous positive airway pressure-resistant syndrome', which may justify treatment by wake-promoting drugs.

Optimizing screening of severe obstructive sleep apnea in patients undergoing bariatric surgery.

BACKGROUND: Obstructive sleep apnea is common in patients waiting for bariatric surgery (BS). International consensuses have recommended assessment of obstructive sleep apnea in the preoperative evaluation to avoid perioperative complications. Polysomnography is the standard diagnostic method but is expensive and time-consuming. The aim of our study was to detect those patients who merit treatment before BS using a simple predictor model. The study was conducted at 3 university hospitals (Hospital de Bellvitge, Hospital de la Santa Creu i Sant Pau, Hospital Clinic de Barcelona). METHODS: A prospective cross-sectional study was conducted of 136 consecutive bariatric subjects. The outcome variable was severe obstructive sleep apnea, defined as an apnea-hypoapnea index of ≥30 events/hr by polysomnography. The predictors evaluated were anthropometric and clinical in the first model, with an oxygen desaturation index of ≥3% added to the second model. Predictive models were constructed using multivariate logistic regression analysis. The best model was selected according to the area under the receiver operating characteristic curve. RESULTS: The first model identified 4 independent factors: age, waist circumference, systolic blood pressure, and witnessed apnea episodes, with a sensitivity of 78%, specificity of 68%, and area under the receiver operating characteristic curve of .83 (95% confidence interval .76-.90, P < .001). The second model identified 2 independent factors (witness apnea episodes, oxygen desaturation index of ≥3%), with a sensitivity of 91%, specificity of 85%, and area under the receiver operating characteristic curve of .94 (95% confidence interval .89-.98, P < .001). The 2-step model predictive values were sensitivity of 90%, specificity of 91%, and accuracy of 90% (95% confidence interval 84-94%). After applying the first model and then the second, 45% of subjects would have been ruled out (15% and 30%, respectively) and 55% would require additional sleep management before BS. CONCLUSION: The proposed model could be useful for improving the management of complex patients before BS and optimizing limited polysomnography resources.