Prevalence and Clinical Significance of Respiratory Effort-Related Arousals in the General Population

Role of esophageal manometry in polysomnography of patients with chronic respiratory failure

Esophageal pressure (Pes) monitoring is performed during polysomnography (PSG) with a thin, water-filled catheter connected to a transducer. The resulting quantitative assessment of respiratory effort can aid in the accurate diagnosis of sleep-related breathing disorders.  This was a prospective observational study using Pes in PSG for thirty patients with chronic respiratory failure (CRF) conducted in the Department of Pulmonary, Critical Care and Sleep Medicine at a tertiary care center of North India. Sleep Scoring was done by conventional method and using esophageal manometry and compared- Polysomnography normal without esophageal manometry recording (PSGN) and polysomnography with esophageal manometry scoring (PSGE). AHI index was similar in both groups. However, RERAs were diagnosed easily using Pes resulting in significant increase in RDI and even reclassification in terms of severity of sleep apnea. Besides, Pes was also useful to distinguish obstructive from central hypopnea which cannot be distinguished by routine PSG which can help guide therapy particularly in chronic respiratory failure patients with hypoventilation. Such patients with hypoventilation often require bilevel positive airway pressure as ventilatory support. Central hypopneas and apneas with hypercapnia may require a higher-pressure support, a backup rate or even advanced volume assured modes of ventilation.  Thus, it can be concluded that Pes in PSG remains a safe and generally well-tolerated procedure. Use of Pes aids to detect RERA and thereby respiratory disturbance index (RDI); a better marker of Sleep related breathing disorder rather than AHI. It also helps in differentiate between obstructive and central hypopnea.

Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics

Apnea and other breathing-related disorders have been linked to the development of hypertension or impairments of the cardiovascular, cognitive or metabolic systems. The combined assessment of multiple physiological signals acquired during sleep is of fundamental importance for providing additional insights about breathing disorder events and the associated impairments. In this work, we apply information-theoretic measures to describe the joint dynamics of cardiorespiratory physiological processes in a large group of patients reporting repeated episodes of hypopneas, apneas (central, obstructive, mixed) and respiratory effort related arousals (RERAs). We analyze the heart period as the target process and the airflow amplitude as the driver, computing the predictive information, the information storage, the information transfer, the internal information and the cross information, using a fuzzy kernel entropy estimator. The analyses were performed comparing the information measures among segments during, immediately before and after the respiratory event and with control segments. Results highlight a general tendency to decrease of predictive information and information storage of heart period, as well as of cross information and information transfer from respiration to heart period, during the breathing disordered events. The information-theoretic measures also vary according to the breathing disorder, and significant changes of information transfer can be detected during RERAs, suggesting that the latter could represent a risk factor for developing cardiovascular diseases. These findings reflect the impact of different sleep breathing disorders on respiratory sinus arrhythmia, suggesting overall higher complexity of the cardiac dynamics and weaker cardiorespiratory interactions which may have physiological and clinical relevance.

Rhinologic disease and its impact on sleep: a systematic review

BACKGROUND

Rhinologic disease can be responsible for systemic symptoms affecting mood, cognition, and sleep. It is unclear whether sleep disturbance in specific rhinologic disorders (chronic rhinosinusitis [CRS], rhinitis, and nasal septal deviation [NSD]) is an obstructive phenomenon or due to other mechanisms. In this review we examine the impact of CRS, rhinitis, and NSD on objective and subjective sleep outcome metrics and draw comparisons to normal controls and patients with known obstructive sleep apnea (OSA).

METHODS

A systematic review of 4 databases (PubMed, Scopus, Cochrane Library, and Web of Science) was performed. Studies reporting on objective (apnea-hypopnea index [AHI], respiratory disturbance index [RDI], oxygen nadir) and subjective (Epworth Sleepiness Scale [EpSS], Pittsburgh Sleep Quality Index [PSQI], Fatigue Severity Scale [FSS]) sleep parameters and disease-specific patient-reported outcome measures (PROMs; 22-item Sino-Nasal Outcome Test [SNOT-22], Rhinoconjunctivitis Quality of Life Questionnaire [RQLQ], Nasal Obstruction Symptom Evaluation [NOSE]) were included.

RESULTS

The database search yielded 1414 unique articles, of which 103 were included for analysis. Baseline PROMs were at the high end of normal to abnormal for all 3 conditions: EpSS: CRS (9.8 ± 4.0), rhinitis (9.7 ± 4.3), and NSD (8.9 ± 4.6); and PSQI: CRS (11.0 ± 4.5), rhinitis (6.1 ± 3.7), and NSD (8.6 ± 3.5). Objective measures demonstrated a mild to moderate OSA in the studied diseases: AHI: CRS (10.4 ± 11.5), rhinitis (8.6 ± 8.8), and NSD (13.0 ± 6.9). There were significant differences when compared with reported norms in all measured outcomes (p < 0.001).

CONCLUSION

Sleep quality is impacted by rhinologic (CRS, rhinitis, NSD) disease. There is likely a mild obstructive component contributing to poor sleep, but other contributing factors may be involved.

The Evaluation of Autonomic Arousals in Scoring Sleep Respiratory Disturbances with Polysomnography and Portable Monitor Devices: A Proof of Concept Study

BACKGROUND

Autonomic arousals can be considered as surrogates of electroencephalography (EEG) arousals when calculating respiratory disturbance index (RDI). The main objective of this proof of concept study was to evaluate the use of heart rate acceleration (HRa) arousals associated with sleep respiratory events in a population undergoing full polysomnography (type 1) and in another undergoing portable monitor study (type 3). Our hypothesis is that when compared to other commonly used indexes, RDI based on HRa will capture more events in both types of recording.

MATERIALS AND METHODS

A retrospective analysis was performed in two different populations of patients with suspected OSA: a) 72 patients undergoing one night of type 1 recording and b) 79 patients undergoing one night of type 3 recording. Variables for type 1 were 4% oxygen desaturation index (ODI), apnea/hypopnea index (AHI), RDI based on EEG arousals (RDIe), and RDI based on HRa with threshold of 5bpm (RDIa5). For type 3, variables were 4% ODI, AHI, and RDIa5 (it is not possible to calculate RDIe due to the absence of EEG). Calculated data were 1) Mean values for each sleep disturbance index in type 1 and 3 recordings; 2) Frequency of migration from lower to higher OSA severity categories using RDIa5 in comparison to AHI (thresholds: ≥5/h mild, ≥15/h moderate, ≥30/h severe); and 3) Bland-Altman plots to assess agreement between AHI vs RDIe and RDIa5 in type 1 population, and AHI vs RDIa5 in type 3 populations.

RESULTS

More respiratory disturbance events were captured with RDIa5 index in both type 1 and type 3 recordings when compared to the other indexes. In type 1 recording, when using RDIa5 37% of patients classified as not having OSA with AHI were now identified as having OSA, and a total of 59% migrated to higher severity categories. In type 3 recording, similar results were obtained, as 37% of patients classified as not having OSA with AHI were now identified as having OSA using RDIa5, and a total of 55% patients migrated to higher severity categories. Mean differences for RDIa5 and AHI in type 1 and 3 populations were similar.

CONCLUSION

The use of autonomic arousals such as HRa can help to detect more respiratory disturbance events when compared to other indexes, being a variable that may help to capture borderline mild cases. This becomes especially relevant in type 3 recordings. Future research is needed to determine its validity, optimization, and its clinical significance.

Effect of Three Hypopnea Scoring Criteria on OSA Prevalence and Associated Comorbidities in the General Population

STUDY OBJECTIVES

Apnea-hypopnea index (AHI) is the main polysomnographic measure to diagnose obstructive sleep apnea (OSA). We aimed to evaluate the effect of three standard hypopnea definitions on the prevalence of OSA and its association with cardiometabolic outcomes in the general population.

METHODS

We analyzed data from the HypnoLaus study (Lausanne, Switzerland), in which 2,162 participants (51% women, 57 ± 19 years) underwent in-home full polysomnography. AHI was calculated using three hypopnea definitions: AASM₁₉₉₉ (≥ 50% decrease in airflow or lower airflow reduction associated with oxygen desaturation ≥ 3% or an arousal), AASM₂₀₀₇ (≥ 30% airflow reduction associated with ≥ 4% oxygen desaturation), and AASM_{2012 (≥} 30% airflow reduction associated with ≥ 3% oxygen desaturation or an arousal). Participants underwent clinical assessment for hypertension, diabetes, and metabolic syndrome.

RESULTS

Median AHI of AASM₁₉₉₉, AASM₂₀₀₇ and AASM₂₀₁₂ criteria were 10.9, 4.4, and 10.1 events/h, respectively. OSA prevalence defined as AHI ≥ 5, ≥ 15, and ≥ 30 events/h was 74.5%, 39.3%, and 16.3% using AASM₁₉₉₉; 46.9%, 18.8%, and 6.8% using AASM₂₀₀₇; and 72.2%, 36.6%, and 14.9% using AASM₂₀₁₂. Different AHI thresholds derived from AASM₁₉₉₉, AASM₂₀₀₇, and AASM₂₀₁₂ criteria_, respectively, were associated with hypertension (11.5, 4.8, 10.7 events/h), diabetes (15.7, 7.1, 14.4 events/h), and metabolic syndrome (12.8, 5.5, 11.8 events/h).

CONCLUSIONS

Hypopnea definition has a major effect on AHI and on OSA prevalence in the general population and, hence, important implications for public health policies. There is a twofold difference in the threshold above which an association with diabetes, hypertension, and metabolic syndrome is observed using AASM₂₀₀₇ compared to AASM₁₉₉₉ or AASM₂₀₁₂ criteria.