Endocrine disorders in obstructive sleep apnoea syndrome: A bidirectional relationship.

Obstructive sleep apnoea (OSA) is a common disorder characterized by recurrent episodes of apnoea or hypopnea due to total or partial pharyngeal collapse and temporary upper airway obstruction during sleep. The prevalence of OSA is increasing and currently affects about 30% of men and 13% of women in Europe. Intermittent hypoxia, oxidative stress, systemic inflammation, and sleep fragmentation resulting from OSA can provoke subsequent cardiometabolic disorders. The relationships between endocrine disorders and OSA are complex and bidirectional. Indeed, several endocrine disorders are risk factors for OSA. Compared with the general population, the prevalence of OSA is increased in patients with obesity, hypothyroidism, acromegaly, Cushing syndrome, and type 1 and 2 diabetes. In some cases, treatment of the underlying endocrine disorder can improve, and occasionally cure, OSA. On the other hand, OSA can also induce endocrine disorders, particularly glucose metabolism abnormalities. Whether continuous positive airway pressure (CPAP) treatment for OSA can improve these endocrine disturbances remains unclear due to the presence of several confounding factors. In this review, we discuss the current state-of-the-art based on the review of the current medical literature for key articles focusing on the bidirectional relationship between endocrine disorders and OSA and the effects of treatment. Screening of OSA in endocrine patients is also discussed, as it remains a subject of debate.

Cardiometabolic comorbidities in obstructive sleep apnea patients are related to disease severity, nocturnal hypoxemia, and decreased sleep quality.

BACKGROUND: Obstructive sleep apnea syndrome (OSA) is currently recognized as an independent risk factor for hypertension, arrhythmia, coronary heart disease, stroke, and metabolic disorders (e.g. diabetes, dyslipidemia). In clinical practice, apnea-hypopnea index (AHI) is the marker used to classify disease severity and guide treatment. However, AHI alone does not sufficiently identify OSA patients at risk for cardiometabolic comorbidities. With this in mind, the aim of this retrospective study was to determine whether some polysomnographic parameters (e.g. apnea-hypopnea duration, sleep structure, nocturnal hypoxemia) are specifically associated with cardiometabolic comorbidities in OSA. METHODS: In this retrospective study, 1717 patients suffering from moderate/severe OSA were included between 2013 and 2017. Data on demographics, comorbidities, and polysomnographic characteristics were collected and analyzed to identify factors associated with cardiometabolic complications. RESULTS: The medical files of 1717 patients (68% male) were reviewed. The mean AHI was 43.1 +/- 27.7 with 57.3% of patients suffering from severe OSA, and 52% from at least one cardiovascular comorbidity (CVCo). Diabetes affected 22% of the patients and 27% exhibited dyslipidemia. Patients affected by CVCos were older, and more often women and non-smokers. These patients also had worse sleep quality, and a more marked intermittent/global nocturnal hypoxemia. With regard to diabetes, diabetics were older, more often non-smoker, non-drinker women, and were more obese. These patients also exhibited more severe OSA, especially in non-REM (NREM) sleep, worse sleep quality, and a more marked intermittent/global nocturnal hypoxemia. Dyslipidemia was more frequent in the absence of alcohol consumption, and was associated with OSA severity, decreased sleep quality, and longer AH in REM sleep. CONCLUSIONS: This study identifies demographic and polysomnographic factors associated with cardiometabolic comorbidities. Patients (especially women) suffering from more severe OSA, longer sleep apneas and hypopneas, worse sleep quality, and marked intermittent/global nocturnal hypoxemia are more likely to develop cardiometabolic comorbidities. This should stimulate clinicians to obtain adequate treatment in this population.

African ethnicity is associated with a higher prevalence of diabetes in obstructive sleep apnea patients: results of a retrospective analysis.

PURPOSE: Obstructive sleep apnea (OSA) syndrome is a well-recognized independent risk factor for cardiovascular disease and its prevalence is increasing. OSA symptomology, polysomnographic features, and comorbidities are heterogeneous among patients. Ethnicity is thought to influence OSA phenotypes, but extensive knowledge of OSA ethnic patterns is lacking. The primary aim of the present study was to compare comorbidities in Caucasian and African OSA. Secondary aims were to observe OSA symptomatology, polysomnographic characteristics, and CPAP adherence in these two ethnic groups. METHODS: In this retrospective study, 1717 patients suffering from moderate/severe OSA were included between 2013 and 2017. Data on demographics, symptomatology, comorbidities, polysomnographic characteristics, and CPAP adherence were collected. Data were analyzed to identify potential differences between Caucasians and Africans. RESULTS: Despite healthier lifestyles and lower BMI, a higher prevalence of diabetes but less cardiac comorbidities and dyslipidemia was observed in the African population. Younger African patients (< 56 years) suffered more from cognitive impairment than Caucasians and both younger and older Africans complained more of nighttime choking than Caucasians. In analysis of polysomnographic data, Africans had higher apnea-hypopnea index (AHI) in REM sleep, lower supine AHI, lower desaturation time, and lower periodic leg movements index. CONCLUSIONS: Compared with Caucasians, African OSA showed a particular comorbidity profile. There are younger patients who exhibit more diabetes but less cardiac comorbidities than the Caucasians. African diabetics should be more promptly referred for OSA testing. Moreover, as they suffer more often from choking and cognitive impairment, OSA treatment could positively impact their quality of life.

Impact of Desaturation Patterns versus Apnea-Hypopnea Index in the Development of Cardiovascular Comorbidities in Obstructive Sleep Apnea Patients.

Various phenotypes of obstructive sleep apnea (OSA) have been recently described and are poorly assessed by the commonly used polysomnographic indices, such as the apnea-hypopnea index and oxygen desaturation index. Nocturnal hypoxemia is the hallmark of OSA and new quantitative markers, as hypoxic burden or desaturation severity, have been shown to be associated with cardiovascular (CV) mortality. The purpose of this overview is to review the endophenotypical and clinical characteristics of OSA, the current metrics, and to analyze different measurements of hypoxemia in OSA to predict the cardiovascular impact (eg hypoxic burden). Potential interest of multidimensional models to classify OSA, such as BAVENO classification, is also discussed, with the goal of focusing on specific endophenotypes that are likely to develop CV comorbidities, in order to guide clinicians to more aggressive management of OSA in these individuals.

Obstructive Sleep Apnea Syndrome Phenotyping by Cluster Analysis: Typical Sleepy, Obese Middle-aged Men with Desaturating Events are A Minority of Patients in A Multi-ethnic Cohort of 33% Women.

OBJECTIVE: Several clinical obstructive sleep apnea syndrome (OSAS) phenotypes associated with heterogeneous cardiovascular risk profiles have been recently identified. The purpose of this study was to identify clusters amongst these profiles that allow for the differentiation of patients. METHODS: This retrospective study included all moderate-to-severe OSAS patients referred to the sleep unit over a 5-year period. Demographic, symptom, comorbidity, polysomnographic, and continuous positive airway pressure (CPAP) adherence data were collected. Statistical analyses were performed to identify clusters of patients. RESULTS: A total of 567 patients were included (67% men, 54±13 years, body mass index: 32±7 kg/m2, 65% Caucasian, 32% European African). Five clusters were identified: less severe OSAS (n=172); healthier severe OSAS (n=160); poorly sleeping OSAS patients with cardiometabolic comorbidities (n=87); younger obese men with sleepiness at the wheel (n=94); sleepy obese men with very severe desaturating OSAS and cardiometabolic comorbidities (n=54). Patients in clusters 3 and 5 were older than those in clusters 2 and 4 (P=0.034). Patients in clusters 4 and 5 were significantly more obese than those in the other clusters (P=0.04). No significant differences were detected in terms of symptoms and comorbidities. Polysomnographic profiles were very discriminating between clusters. CPAP adherence was similar in all clusters but, among adherent patients, daily usage was more important in cluster 1 (less severe patients) than in cluster 5. CONCLUSION: This study highlights that the typical sleepy obese middle-aged men with desaturating events represent only a minority of patients in our multi-ethnic moderate-to-severe OSAS cohort of 33% females.

Critically ill cancer patient's resuscitation: a Belgian/French societies' consensus conference.

To respond to the legitimate questions raised by the application of invasive methods of monitoring and life-support techniques in cancer patients admitted in the ICU, the European Lung Cancer Working Party and the Groupe de Recherche Respiratoire en Réanimation Onco-Hématologique, set up a consensus conference. The methodology involved a systematic literature review, experts' opinion and a final consensus conference about nine predefined questions1. Which triage criteria, in terms of complications and considering the underlying neoplastic disease and possible therapeutic limitations, should be used to guide admission of cancer patient to intensive care units?2. Which ventilatory support [High Flow Oxygenation, Non-invasive Ventilation (NIV), Invasive Mechanical Ventilation (IMV), Extra-Corporeal Membrane Oxygenation (ECMO)] should be used, for which complications and in which environment?3. Which support should be used for extra-renal purification, in which conditions and environment?4. Which haemodynamic support should be used, for which complications, and in which environment?5. Which benefit of cardiopulmonary resuscitation in cancer patients and for which complications?6. Which intensive monitoring in the context of oncologic treatment (surgery, anti-cancer treatment …)?7. What specific considerations should be taken into account in the intensive care unit?8. Based on which criteria, in terms of benefit and complications and taking into account the neoplastic disease, patients hospitalized in an intensive care unit (or equivalent) should receive cellular elements derived from the blood (red blood cells, white blood cells and platelets)?9. Which training is required for critical care doctors in charge of cancer patients?