Editorials: Point and Counterpoint

COUNTERPOINT: Is the Apnea-Hypopnea Index the Best Way to Quantify the Severity of Sleep-Disordered Breathing? No

To evaluate the association between cardiovascular morbidity and obstructive sleep apnea (OSA) severity quantified using the sleep breathing impairment index (SBII), a novel measure that captures both respiratory events and event-associated hypoxia.

This retrospective follow-up study included 737 participants with OSA who were diagnosed based on an apnea–hypopnea index of >5/h in polysomnography from January 1, 2012 to December 31, 2015. Data on baseline clinical characteristics and polysomnography parameters were collected. SBII was determined as the sum of products of respiratory events and event-related desaturation areas, and was categorized based on its quintiles. The outcomes were any hospital admission for cardiovascular diseases, including coronary heart disease, stroke, peripheral vascular disease, or heart failure after the diagnosis of OSA. Logistic regression models were constructed to estimate the potential association between SBII and cardiovascular morbidity after adjusting for confounders.

A total of 60 cardiovascular events were recorded. Compared with the first quintile of SBII, the odds ratio (95% confidence interval [CI]) of cardiovascular morbidity for the second, third, and fourth quintiles were 4.01 (95% CI, 1.22–13.24), 3.91 (95% CI, 1.05–14.53), and 7.57 (95% CI, 1.70–33.68) after adjusting for covariables, including anthropometric variables, medical conditions, and sleep parameters.

In patients with OSA, higher SBII was associated with an increased cardiovascular risk. These findings suggest that a more comprehensive measure, such as SBII incorporating the respiratory event and related hypoxia during sleep, may better capture the disease burden and reflect the OSA-associated adverse outcomes.

Conventional measures of obstructive sleep apnea (OSA) severity, such as the apnea-hypopnea index (AHI) and oxygen desaturation index (ODI) are commonly used to quantify OSA severity and guide therapeutical decision-making processes. However, it is widely recognized that both AHI and ODI have important limitations and novel physiologically-informed metrics are needed to better capture the severity of OSA and characterize its physiological consequences, particularly the severity of recurrent nocturnal hypoxemia, ensuing the respiratory events. According to recent studies, the sleep apnea-specific “hypoxic burden (HB)”, defined as the sum of individual areas under the oxygen desaturation curve, has shown some promise in identifying high risk individuals with OSA. In addition to the frequency of respiratory events, HB capture the depth and duration of OSA-related hypoxemia that may prove to be important disease characterizing features, not captured by the conventional “frequency-based” metrics, such as AHI and ODI. In this “perspective” paper the methods to quantify the HB, its characteristics, associations with health outcomes, and its limitations will be discussed.

To examine the relationship between polysomnography-classified obstructive sleep apnea (OSA) severity and cognitive performance in acute moderate-to-severe traumatic brain injury (TBI).

This was a cross-sectional, secondary analysis leveraging data from a clinical trial (NCT03033901) and TBI Model Systems. Sixty participants (mean age = 50 ± 18y, 72% male, 67% white) with moderate-to-severe TBI from five civilian rehabilitation hospitals were assessed at one-month post-injury. Participants underwent Level 1 polysomnography. OSA severity was classified as mild, moderate, and severe using the Apnea-Hypopnea Index (AHI). Associations between OSA metrics of hypoxemia (nadir and total time spent below 90%) and AHI with cognition were examined. Cognition was assessed with the Brief Test of Adult Cognition by Telephone (BTACT), which is comprised of six subtests assessing verbal memory, attention/working memory, processing speed, language, and executive function.

Over three-quarters of this acute TBI sample (76.7%) were diagnosed with OSA (no OSA n = 14; mild OSA n = 19; moderate/severe OSA n = 27). After adjustment for age, gender, and education, those with OSA had worse processing speed, working memory, and executive functioning compared to those without OSA. Compared to those with moderate/severe OSA, those with mild OSA had worse working memory and executive function.

OSA is highly prevalent during acute stages of TBI recovery, and even in mild cases is related to poorer cognitive performance, particularly in the domains of attention/working memory and executive functioning. Our results support the incorporation of OSA diagnostic tools and interventions into routine clinical care in rehabilitation settings.

This study aimed to identify the effectiveness of respiratory mechanic instability (RMI) in the diagnosis of pediatric obstructive sleep apnea syndrome (OSAS). We sought to evaluate the correlations of RMI with sleep-related parameters and determine the effectiveness of using RMI for diagnosing OSAS in children.

Children who underwent polysomnography (PSG) for various reasons were enrolled in this study. Patients' clinical and PSG data at two university hospitals were reviewed retrospectively. During PSG, RMI parameters were automatically calculated according to the phase relationship between thoracic and abdominal movement signals.

Among 263 children who underwent PSG, 183 (70.4%) were diagnosed with OSAS (apnea-hypopnea index [AHI] ≥ 1). RMI parameters were higher in the OSAS group than in the control group. They also tended to increase with disease severity. RMI scores were well correlated with respiratory parameters, showing a stronger correlation in those with moderate or severe OSAS without central apnea. Areas under the receiver operating characteristics curves (AUROCs) of RMI indicators were over 0.65. The percentage of RMI in stage duration showed the highest value of the AUROCs.

Paradoxical thoraco-abdominal movement assessed by RMI provides additional information. It may be useful in diagnosing OSAS in children.

Obstructive Sleep Apnea (OSA) has been recognized as a major health concern worldwide, given its increasing prevalence, difficulties in diagnosis and treatment, and impact on health, economy, and society. Clinical guidelines highlight the need of biomarkers to guide OSA clinical decision-making, but so far, without success. In this systematic review and meta-analysis, registered on the International Prospective Register of Systematic Reviews database (ID CRD42020132556), we proposed to gather and further explore candidates identified in the literature as potential OSA biomarkers.

Search strategies for eight different databases (PubMed/Medline, Cochrane Library, Biblioteca Virtual da Saúde, Web of Science, EMBASE, World Intellectual Property Organization database, and bioRxiV and medRxiV Preprint Servers) were developed. We identified studies exploring potential biomarkers of OSA, in peripheral samples of adults, with and without OSA, with no comorbidities defined in study inclusion criteria, published after the last systematic review and meta-analysis conducted on OSA biomarkers, until May 31st, 2020. Risk of bias was assessed through the 14-item Quality Assessment Tool for Diagnostic Accuracy Studies. Demographic, clinical, and candidate biomarkers’ data were collected and analyzed via random effects meta-analyses.

Among the 1512 unique studies screened, 120 met the inclusion criteria and 16 studies with low risk of bias were selected for meta-analyses. The selected 16 studies enrolled a total of 2156 participants, from which 1369 were diagnosed with OSA and 787 were disease-free controls. The assessed variables showed high heterogeneity. From the 38 biomarker candidates evaluated, only two were evaluated in more than one study. Most studies pinpointed candidates with more potential for OSA prognosis. ADAM29, FLRT2 and SLC18A3 mRNA levels in PBMCs, Endocan and YKL-40 levels in serum, and IL-6 and Vimentin levels in plasma revealed the most promising candidates for OSA diagnosis.

Although the current systematic review and meta-analysis allowed us to identify candidates to further explore as potential biomarkers in future studies, it is evident that OSA biomarkers research is still at an early stage. Most findings derive from small-size single-center study cohorts and single-candidate studies. We point several gaps in current OSA biomarker research that may guide into new directions and approaches towards the identification of OSA biomarkers.