Obesity Hypoventilation Syndrome: Early Detection of Nocturnal-Only Hypercapnia in an Obese Population

Hypoxic burden and sleep hypoventilation in obese patients

INTRODUCTION

Novel biomarkers of hypoxic load have emerged, as sleep apnea-specific hypoxic burden which provides more precise assessment of intermittent hypoxemia severity. Our main objective was to assess the potential benefit of hypoxic burden to identify obesity-related sleep hypoventilation. We hypothesized that hypoxic burden may help diagnose obesity-related sleep hypoventilation better than usual sleep respiratory measures (i.e., apnea-hypopnea index (AHI), mean SpO2, time with SpO2 < 90 %).

METHODS

This retrospective study was conducted from June 2022 to October 2023 at the University Hospital of Rouen, France. All consecutive obese patients (BMI ≥30 kg/m2), adults, with no other respiratory or neurological diseases who underwent a polysomnography or polygraphy with concomitant capnography were included. Sleep hypoventilation was defined according to American Academy of Sleep Medicine criteria based on transcutaneous CO2 monitoring (PtcCO2). Diagnostic performance of sleep-related respiratory measures i.e., sleep apnea-specific hypoxic burden, apnea-hypopnea index (AHI), mean SpO2, time with SpO2 < 90 % was evaluated using Receiver Operating Characteristic (ROC) curves. Correlations between sleep-related respiratory measures were assessed by a Spearman correlation matrix.

RESULTS

Among 107 obese patients with analyzed capnography, 37 (35 %) had sleep hypoventilation. Patients were 53 ± 14 years old, mean BMI = 38 ± 6 kg/m2, mean AHI = 26.5 ± 25/h, mean hypoxic burden = 67 ± 109 %min/h, mean SpO2 = 91.5 ± 3 %, mean time with SpO2<90 % = 19.4 ± 28 %, mean PtcCO2 = 6.2 ± 0.7 kPa. A low positive correlation was found between hypoxic burden and mean PtcCO2 (r = 0.4, p < 0.001). Multivariate logistic regression model explaining sleep hypoventilation was insufficient with area under ROC curve of hypoxic burden estimated at 0.74 (95 % CI 0.65 to 0.84).

CONCLUSION

Hypoxic burden has low correlation with transcutaneous CO2 pressure and a low ability to diagnose obesity-related sleep hypoventilation.

Nocturnal Hypoventilation in the Patients Submitted to Thoracic Surgery

Introduction

Nocturnal hypoventilation may occur due to obesity, concomitant chronic obstructive pulmonary disease (COPD), obstructive sleep apnea, and/or the use of narcotic analgesics. The aim of the study was to evaluate the risk and severity of nocturnal hypoventilation as assessed by transcutaneous continuous capnography in the patients submitted to thoracic surgery.

Materials and Methods

The material of the study consisted of 45 obese (BMI 34.8 ± 3.7 kg/m2) and 23 nonobese (25.5 ± 3.6 kg/m2) patients, who underwent thoracic surgery because of malignant (57 patients) and nonmalignant tumors. All the patients received routine analgesic treatment after surgery including intravenous morphine sulfate. Overnight transcutaneous measurements of CO2 partial pressure (tcpCO2) were performed before and after surgery in search of nocturnal hypoventilation, i.e., the periods lasting at least 10 minutes with tcpCO2 above 55 mmHg.

Results

Nocturnal hypoventilation during the first night after thoracic surgery was detected in 10 patients (15%), all obese, three of them with COPD, four with high suspicion of moderate-to-severe OSA syndrome, and one with chronic daytime hypercapnia. In the patients with nocturnal hypoventilation, the mean tcpCO2 was 53.4 ± 6.1 mmHg, maximal tcpCO2 was 59.9 ± 8.4 mmHg, and minimal tcpCO2 was 46.4 ± 6.7 mmHg during the first night after surgery. In these patients, there were higher values of minimal, mean, and maximal tcpCO2 in the preoperative period. Nocturnal hypoventilation in the postoperative period did not influence the duration of hospitalization. Among 12 patients with primary lung cancer who died during the first two years of observation, there were 11 patients without nocturnal hypoventilation in the early postoperative period.

Conclusion

Nocturnal hypoventilation may occur in the patients after thoracic surgery, especially in obese patients with bronchial obstruction, obstructive sleep apnea, or chronic daytime hypercapnia, and does not influence the duration of hospitalization.

Hypoxia modeling techniques: A review

Hypoxia is the main cause and effect of a large number of diseases, including the most recent one facing the world, the coronavirus disease (COVID-19). Hypoxia is divided into short-term, long-term, and periodic, it can be the result of diseases, climate change, or living and traveling in the high mountain regions of the world. Since each type of hypoxia can be a cause and a consequence of various physiological changes, the methods for modeling these hypoxias are also different. There are many techniques for modeling hypoxia under experimental conditions. The most common animal for modeling hypoxia is a rat. Hypoxia models (hypoxia simulations) in rats are a tool to study the effect of various conditions on the oxygen supply of the body. These models can provide a necessary information to understand hypoxia and also provide effective treatment, highlighting the importance of various reactions of the body to hypoxia. The main parameters when choosing a model should be reproducibility and the goal that the scientist wants to achieve. Hypoxia in rats can be reproduced both ways exogenously and endogenously. The reason for writing this review was the aim to systematize the models of rats available in the literature in order to facilitate their selection by scientists. The relative strengths and limitations of each model need to be identified and understood in order to evaluate the information obtained from these models and extrapolate these results to humans to develop the necessary generalizations. Despite these problems, animal models have been and remain vital to understanding the mechanisms involved in the development and progression of hypoxia. The eligibility criteria for the selected studies was a comprehensive review of the methods and results obtained from the studies. This made it possible to make generalizations and give recommendations on the application of these methods. The review will assist scientists in choosing an appropriate hypoxia simulation method, as well as assist in interpreting the results obtained with these methods.

Obesity-associated sleep hypoventilation and increased adverse postoperative bariatric surgery outcomes in a large clinical retrospective cohort

STUDY OBJECTIVES

Although obesity hypoventilation syndrome (OHS) is associated with increased morbidity and mortality, post-bariatric surgery OHS risk remains unclear due to often nonsystematic OHS assessments.

METHODS

We leverage a clinical cohort with nocturnal CO2 monitoring during polysomnography to address the hypothesis that patients with obesity-associated sleep hypoventilation (OaSH; ie, stage II OHS) have increased adverse postoperative bariatric surgery outcomes. We retrospectively analyzed data from patients undergoing pre-bariatric surgery polysomnography at the Cleveland Clinic from 2011-2018. OaSH was defined by body mass index ≥ 30 kg/m2 and either polysomnography-based end-tidal CO2 ≥ 45 mmHg or serum bicarbonate ≥ 27 mEq/L. Outcomes considered were as follows: intensive care unit stay, intubation, tracheostomy, discharge disposition other than home or 30-day readmission individually and as a composite, and all-cause mortality. Two-sample t test or Wilcoxon rank-sum test for continuous variables and chi-square or Fisher's exact test for categorical variables were used for OaSH vs non-OaSH comparisons. All-cause mortality was compared using Kaplan-Meier estimation and Cox proportional hazards models.

RESULTS

The analytic sample (n = 1,665) was aged 45.2 ± 12 years, 20.4% were male, had a body mass index of 48.7 ± 9 kg/m2, and 63.6% were White. OaSH prevalence was 68.5%. OaSH patients were older and more likely to be male with a higher BMI, apnea-hypopnea index, and glycated hemoglobin. The composite outcome was higher in OaSH vs non-OaSH patients (18.9% vs 14.3%, P = .021). Although some individual outcomes were respectively higher in OaSH vs non-OaSH patients, differences were not statistically significant: intubation (1.5% vs 1.3%, P = .81) and 30-day readmission (13.8% vs 11.3%, P = .16). Long-term mortality (median follow-up: 22.9 months) was not significantly different between groups, likely due to overall low event rate (hazard ratio = 1.39, 95% confidence interval: 0.56, 3.42).

CONCLUSIONS

In this largest sample to date of systematically phenotyped OaSH in a bariatric surgery cohort, we identify increased postoperative morbidity in those with sleep-related hypoventilation in stage II OHS when a composite outcome was considered, but individual contributors of intubation, intensive care unit admission, and hospital length of stay were not increased. Further study is needed to identify whether perioperative treatment of OaSH improves post-bariatric surgery outcomes.

CITATION

Chindamporn P, Wang L, Bena J, et al. Obesity-associated sleep hypoventilation and increased adverse postoperative bariatric surgery outcomes in a large clinical retrospective cohort. J Clin Sleep Med. 2022;18(12):2793-2801.

Defining obesity hypoventilation syndrome

With increasing prevalence of obesity, the substantial contribution of obesity hypoventilation syndrome (OHS) to morbidity and mortality is likely to increase. It is therefore crucial that the condition has a clear definition to allow timely identification of patients. OHS was first described as “Pickwickian syndrome” in the 1950s; in subsequent decades, case reports did not clearly delineate between patients suffering from OHS and those suffering from obstructive sleep apnoea. In 1999, the American Academy of Sleep Medicine published a guideline that delineated the cause of daytime hypercapnia as either predominantly upper airway or predominantly hypoventilation. This was the first formal definition of OHS as the presence of daytime alveolar hypoventilation (arterial carbon dioxide tension >45 mmHg) in patients with body mass index >30 kg·m⁻² in the absence of other causes of hypoventilation. This definition is reflected in the most recent guidelines published on OHS. Recent developments in defining OHS include proposed classification systems of severity and demonstrating the value of using serum bicarbonate to exclude OHS in patients with a low index of suspicion.

Obesity hypoventilation syndrome is defined as daytime alveolar hypoventilation in obese patients in the absence of other causes of hypoventilation. Classifications of severity are now needed to target treatment at the most appropriate individuals.https://bit.ly/3yLuiL9

Severity stages of obesity-related breathing disorders - a cross-sectional cohort study

INTRODUCTION

There is a general underappreciation of the spectrum of obesity-related breathing disorders and their consequences. We therefore compared characteristics of obese patients with eucapnic obstructive sleep apnea (OSA), OSA with obesity-related sleep hypoventilation (ORSH) or obesity hypoventilation syndrome (OHS) to identify the major determinants of hypoventilation.

PATIENTS AND METHODS

In this prospective, diagnostic study (NCT04570540), obese patients with OSA, ORSH or OHS were characterized applying polysomnography with transcutaneous capnometry, blood gas analyses, bodyplethysmography and measurement of hypercapnic ventilatory response (HCVR). Pathophysiological variables known to contribute to hypoventilation and differing significantly between the groups were specified as potential independent variables in a multivariable logistic regression to identify major determinants of hypoventilation.

RESULTS

Twenty, 43 and 19 patients were in the OSA, ORSH and OHS group, respectively. BMI was significantly lower in OSA as compared to OHS. The extent of SRBD was significantly higher in OHS as compared to OSA or ORSH. Patients with ORSH or OHS showed a significantly decreased forced expiratory volume in 1 s and forced vital capacity compared to OSA. HCVR was significantly lower in OHS and identified as the major determinant of hypoventilation in a multivariable logistic regression (Nagelkerke R² = 0.346, p = 0.050, odds ratio (95%-confidence interval) 0.129 (0.017-1.004)).

CONCLUSION

Although there were differences in BMI, respiratory mechanics and severity of upper airway obstruction between groups, our data support HCVR as the major determinant of obesity-associated hypoventilation.

Fusion of Whole Night Features and Desaturation Segments Combined with Feature Extraction for Event-Level Screening of Sleep-Disordered Breathing

PURPOSE

Misdiagnosis and missed diagnosis of sleep-disordered breathing (SDB) is common because polysomnography (PSG) is time-consuming, expensive, and uncomfortable. The use of recording methods based on the oxygen saturation (SpO2) signals detected by wearable devices is impractical and inaccurate for extracting signal features and detecting apnoeic events. We propose a method to automatically detect the apnoea-based SpO₂ signal segments and compute the apnoea-hypopnea index (AHI) for SDB screening and grading.

PATIENTS AND METHODS

First, apnoea-related desaturation segments in raw SpO₂ signals were detected; global features were extracted from whole night signals. Then, the SpO₂ signal segments and global features were fed into a bi-directional long short-term memory convolutional neural network model to identify apnoea-related and non-apnoea-related events. The apnoea-related segments were used to assess the AHI.

RESULTS

The model was trained on 500 individuals and tested on 8131 individuals from two public hospitals and one private centre. In the testing data, the classification accuracy for apnoea-related segments was 84.3%. Individuals with SDB (AHI 15) were identified with a mean accuracy of 88.95%.

CONCLUSION

Using automatic SDB detection based on SpO₂ signals can accurately screen for SDB.

Diagnostic approach to sleep disordered-breathing among patients with grade III obesity

Sleep apnea test (SAT) is a cost-effective approach to evaluate subjects without associated comorbidities suspected for obstructive sleep apnea (OSA), a disorder particularly common in obese subjects. The association of obesity with awake hypercapnia (carbon dioxide arterial pressure, PaCO₂ ≥45 mmHg) defines the obesity-hypoventilation syndrome (OHS), which in turn results in increased morbidity and mortality compared to simple OSA. Isolated hypoventilation during sleep in obese patients (obesity-related sleep hypoventilation, ORSH) is now considered as an early stage of OHS. The aim of this study was to assess the performance of SAT in diagnosing OSA and predicting the presence of ORHS among patients with grade III obesity without awake hypercapnia.

METHODS

Over a 14-months period, patients with grade III obesity (body mass index≥40 kg/m²) presenting moderate-to-severe OSA (apnea-hypopnea index [AHI]≥15) upon SAT and normal awake PaCO₂ at arterial blood gas analysis, systematically underwent in-lab nocturnal polysomnography combined with transcutaneous carbon dioxide pressure (PtcCO₂) monitoring.

RESULTS

Among 48 patients included in the study, 16 (33%) presented an AHI<15 upon polysomnography and 14 (29%) had ORSH. The test revealed no difference in ORSH prevalence between patients with AHI <15 or ≥15 (31% vs. 25%). No SAT variables were independently associated with increased PtCO₂.

CONCLUSIONS

This study shows that SAT overestimates OSA severity and ORSH affects one third of patients with grade III obesity without awake hypercapnia and with moderate-to-severe OSA at SAT, suggesting how polysomnography combined with PtCO₂ monitoring is the most appropriate diagnostic approach for OSA and ORSH in this population.

Severe paediatric obesity and sleep: A mutual interactive relationship!

Childhood severe obesity is a serious, urgent and complex global health problem with long-term co-morbidities. Obstructive sleep-disordered breathing is more common in obese children and adolescents. Increased body mass index is associated with an increase in apnea-hypopnea index. Obstructive sleep apnea leads to a decrease in rapid eye movement sleep, and obese children have been noted to have a decrease in rapid eye movement sleep, leading to weight gain. Short sleep duration and poor sleep quality are associated with childhood obesity and cardiometabolic risks. Public health strategies for obesity prevention should focus more on sleep. Targeting childhood obesity is important in the prevention and management of obstructive sleep-disordered breathing.

Predicting CPAP failure in patients with suspected sleep hypoventilation identified on ambulatory testing

STUDY OBJECTIVES

Home sleep apnea testing (HSAT) is commonly used to diagnose obstructive sleep apnea, but its role in identifying patients with suspected hypoventilation or predicting their response to continuous positive airway pressure (CPAP) therapy has not been assessed. The primary objective was to determine if HSAT, combined with clinical variables, could predict the failure of CPAP to correct nocturnal hypoxemia during polysomnography in a population with suspected hypoventilation. Secondary objectives were to determine if HSAT and clinical parameters could predict awake or sleep hypoventilation.

METHODS

A retrospective review was performed of 142 consecutive patients who underwent split-night polysomnography for suspected hypoventilation after clinical assessment by a sleep physician and review of HSAT. We collected quantitative indices of nocturnal hypoxemia, patient demographics, medications, pulmonary function tests, as well as arterial blood gas data from the night of the polysomnography . CPAP failure was defined as persistent obstructive sleep apnea, hypoxemia (oxygen saturation measured by pulse oximetry < 85%), or hypercapnia despite maximal CPAP.

RESULTS

Failure of CPAP was predicted by awake oxygen saturation and arterial blood gas results but not by HSAT indices of nocturnal hypoxemia. Awake oxygen saturation ≥ 94% ruled out CPAP failure, and partial pressure of oxygen measured by arterial blood gas ≥ 68 mmHg decreased the likelihood of CPAP failure significantly.

CONCLUSIONS

In patients with suspected hypoventilation based on clinical review and HSAT interpretation by a sleep physician, awake oxygen saturation measured by pulse oximetry and partial pressure of oxygen measured by arterial blood gas can reliably identify patients in whom CPAP is likely to fail. Additional research is required to determine the role of HSAT in the identification and treatment of patients with hypoventilation.

Predictors of obesity hypoventilation syndrome among patients with sleep-disordered breathing in India

Introduction

No study has been done in India to evaluate obesity hypoventilation syndrome (OHS) among patients with sleep-disordered breathing (SDB). The known predictors of OHS, i.e., body mass index (BMI) >35 kg/m² and forced vital capacity (FVC) <3.5 L for men and <2.3 L for women from western countries, cannot be applied to Indian patients.

Objectives

To find out the prevalence of OHS and to determine the predictors of OHS among Indian SDB patients.

Materials and Methods

It was a retrospective observational study conducted in a tertiary care institute from September 1, 2017, to August 31, 2018. All the patients who underwent polysomnography were analyzed for the presence of OHS. Of 85 patients referred for polysomnography, 76 had SDB. Thirteen patients were excluded because of hypoventilation due to other known causes or could not perform spirometry.

Results

The prevalence of OHS among SDB after excluding the other causes of hypoventilation was 15.87% (10/63). The predictors were determined using univariate analysis between daytime partial pressure of carbon dioxide (PaCO₂) and other predictors. PaCO₂ significantly correlated with minimum nocturnal oxygen saturation by pulse oximetry (SpO₂), FVC %predicted, BMI, daytime SpO₂, forced expiratory volume %predicted, and partial pressure of oxygen (PaO₂). Following a stepwise multiple regression, minimum nocturnal SpO₂, FVC %predicted, and BMI were found to be independent predictors of OHS. A minimum nocturnal SpO₂ threshold of 60%, FVC %predicted <74.5%, BMI >30.95 kg/m², and absolute FVC <2.33 L for men and <1.68 L for women were found to be predictors of OHS.

Conclusion

The prevalence of OHS in Indian patients is similar to Caucasians. OHS is seen in Indian patients even at a lower BMI and lower spirometric parameters.

Diagnosing obstructive sleep apnea patients with isolated nocturnal hypoventilation and defining obesity hypoventilation syndrome using new European Respiratory Society classification criteria: an Indian perspective

BACKGROUND

Recently, new classification criteria for obesity hypoventilation syndrome (OHS) have been described. OHS prevalence according to new criteria has not been reported in obstructive sleep apnea (OSA). Prevalence of OHS has not been previously reported from India.

METHODS

Retrospective study was carried out in OSA patients for whom both arterial blood gases (ABG) and end-tidal CO₂ (etCO₂) records were available. OHS was defined according to old and new criteria. Analysis was carried out among various groups: patients without OHS (Group A), patients with sleep hypoventilation but without daytime hypercapnia (Group B) and patients with daytime hypercapnia (Group C).

RESULTS

Out of 367 patients with OSA (body mass index, BMI) 31.9 ± 12.27 kg/m²), finally 128 obese OSA patients were included for analysis. Of those, 15 (5.9%, 95% confidence interval (CI) 3.5-9.4) and 45 patients (17.8%, 95% CI 13.4-22.9) fulfilled prevalence of OHS according to old and new criteria, respectively. Continuous positive airway pressure (CPAP) titration failed in 9.6%, 53.3% and 66.7% in Groups A, B, and C, respectively. For all parameters of OSA severity (apnea-hypopnea index (AHI), Nadir O₂, T90) and positive airway pressure (PAP) requirements, patients in Group B were in between those in Groups A and C. Statistically significant difference was seen between Group A and Group B, and between Groups A and C, but not between Groups B and C.

CONCLUSION

One in six OSA patients and one in three obese OSA patients (BMI >30 kg/m²) have OHS according to new criteria. Since patients with isolated nocturnal hypoventilation were as sick as patients with daytime hypercapnia, screening for sleep hypoventilation should be carried out in all obese OSA patients.

Effects of Intermittent Hypoxia on Pulmonary Vascular and Systemic Diseases

Obstructive sleep apnea (OSA) causes many systemic disorders via mechanisms related to sympathetic nerve activation, systemic inflammation, and oxidative stress. OSA typically shows repeated sleep apnea followed by hyperventilation, which results in intermittent hypoxia (IH). IH is associated with an increase in sympathetic activity, which is a well-known pathophysiological mechanism in hypertension and insulin resistance. In this review, we show the basic and clinical significance of IH from the viewpoint of not only systemic regulatory mechanisms focusing on pulmonary circulation, but also cellular mechanisms causing lifestyle-related diseases. First, we demonstrate how IH influences pulmonary circulation to cause pulmonary hypertension during sleep in association with sleep state-specific change in OSA. We also clarify how nocturnal IH activates circulating monocytes to accelerate the infiltration ability to vascular wall in OSA. Finally, the effects of IH on insulin secretion and insulin resistance are elucidated by using an in vitro chamber system that can mimic and manipulate IH. The obtained data implies that glucose-induced insulin secretion (GIS) in pancreatic β cells is significantly attenuated by IH, and that IH increases selenoprotein P, which is one of the hepatokines, as well as TNF-α, CCL-2, and resistin, members of adipokines, to induce insulin resistance via direct cellular mechanisms. Clinical and experimental findings concerning IH give us productive new knowledge of how lifestyle-related diseases and pulmonary hypertension develop during sleep.