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1.
Ann Am Thorac Soc ; 21(2): 296-307, 2024 Feb.
Article in English | MEDLINE | ID: mdl-37938917

ABSTRACT

Rationale: Randomized trials have shown inconsistent cardiovascular benefits from obstructive sleep apnea (OSA) therapy. Intermittent hypoxemia can increase both sympathetic nerve activity and loop gain ("ventilatory instability"), which may thus herald cardiovascular treatment benefit. Objectives: To test the hypothesis that loop gain predicts changes in 24-hour mean blood pressure (MBP) in response to OSA therapy and compare its predictive value against that of other novel biomarkers. Methods: The HeartBEAT (Heart Biomarker Evaluation in Apnea Treatment) trial assessed the effect of 12 weeks of continuous positive airway pressure (CPAP) versus oxygen versus control on 24-hour MBP. We measured loop gain and hypoxic burden from sleep tests and identified subjects with a sleepy phenotype using cluster analysis. Associations between biomarkers and 24-h MBP were assessed in the CPAP/oxygen arms using linear regression models adjusting for various covariates. Secondary outcomes and predictors were analyzed similarly. Results: We included 93 and 94 participants in the CPAP and oxygen arms, respectively. Overall, changes in 24-hour MBP were small, but interindividual variability was substantial (mean [standard deviation], -2 [8] and 1 [8] mm Hg in the CPAP and oxygen arms, respectively). Higher loop gain was significantly associated with greater reductions in 24-hour MBP independent of covariates in the CPAP arm (-1.5 to -1.9 mm Hg per 1-standard-deviation increase in loop gain; P ⩽ 0.03) but not in the oxygen arm. Other biomarkers were not associated with improved cardiovascular outcomes. Conclusions: To our knowledge, this is the first study suggesting that loop gain predicts blood pressure response to CPAP therapy. Eventually, loop gain estimates may facilitate patient selection for research and clinical practice. Clinical trial registered with www.clinicaltrials.gov (NCT01086800).


Subject(s)
Sleep Apnea, Obstructive , Humans , Blood Pressure , Sleep Apnea, Obstructive/complications , Polysomnography , Continuous Positive Airway Pressure , Hypoxia/complications , Oxygen , Biomarkers
2.
BMC Pulm Med ; 22(1): 158, 2022 Apr 25.
Article in English | MEDLINE | ID: mdl-35468829

ABSTRACT

BACKGROUND: High loop gain (unstable ventilatory control) is an important-but difficult to measure-contributor to obstructive sleep apnea (OSA) pathogenesis, predicting OSA sequelae and/or treatment response. Our objective was to develop and validate a clinical prediction tool of loop gain. METHODS: A retrospective cohort of consecutive adults with OSA (apnea-hypopnea index, AHI > 5/hour) based on in-laboratory polysomnography 01/2017-12/2018 was randomly split into a training and test-set (3:1-ratio). Using a customized algorithm ("reference standard") loop gain was quantified from raw polysomnography signals on a continuous scale and additionally dichotomized (high > 0.7). Candidate predictors included general patient characteristics and routine polysomnography data. The model was developed (training-set) using linear regression with backward selection (tenfold cross-validated mean square errors); the predicted loop gain of the final linear regression model was used to predict loop gain class. More complex, alternative models including lasso regression or random forests were considered but did not meet pre-specified superiority-criteria. Final model performance was validated on the test-set. RESULTS: The total cohort included 1055 patients (33% high loop gain). Based on the final model, higher AHI (beta = 0.0016; P < .001) and lower hypopnea-percentage (beta = -0.0019; P < .001) predicted higher loop gain values. The predicted loop gain showed moderate-to-high correlation with the reference loop gain (r = 0.48; 95% CI 0.38-0.57) and moderate discrimination of patients with high versus low loop gain (area under the curve = 0.73; 95% CI 0.67-0.80). CONCLUSION: To our knowledge this is the first prediction model of loop gain based on readily-available clinical data, which may facilitate retrospective analyses of existing datasets, better patient selection for clinical trials and eventually clinical practice.


Subject(s)
Point-of-Care Systems , Sleep Apnea, Obstructive , Adult , Cohort Studies , Humans , Polysomnography , Retrospective Studies , Sleep Apnea, Obstructive/therapy
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