Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressure

Oppersma, Eline; Ganglberger, Wolfgang; Sun, Haoqi; Thomas, Robert J.; Westover, M. Brandon

doi:10.1093/sleep/zsaa215

Cited by 17 publications

(4 citation statements)

References 26 publications

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“…More importantly, one may argue that there is no real “gold standard” to measure loop gain, but the primary purpose of loop gain estimation is typically to match OSA patients with personalized treatments. As such, the ideal benchmark to assess the (criterion) validity for any loop gain model is the prediction of clinically important outcomes (e.g., response to surgeries or drug therapies), which is increasingly well documented for the reference standard that we used [ 6 , 7 , 9 , 11 , 14 , 34 ] Interestingly, a “self-similarity” metric has been recently shown to predict residual central events (a clinical consequence of high loop gain), but this technique requires advanced signal analyses, and has not yet been externally validated or shown to predict other loop gain related outcomes [ 35 ].…”

Section: Discussionmentioning

confidence: 99%

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

et al. 2022

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“…The Phenotyping Using Polysomnography (PUP) method is a promising, potentially scalable method, of estimating endotypes from existing polysomnograms by using changes in estimated minute ventilation to determine metrics of respiratory drive (Finnson et al, 2021). Objective measurement of respiratory self-similarity (respiratory events with clone-like timing and morphology) also aids in risk-prediction (Oppersma et al, 2021). Residual events after several months of CPAP use also is a useful marker of a person who may need therapy targeting high loop gain, though mechanical effects of an oronasal mask (Genta et al, 2020), high leak or sleep fragmentation may all contribute .…”

Section: Patient Selectionmentioning

confidence: 99%

Enhanced expiratory rebreathing space for high loop gain sleep apnea treatment

Quinn,

Thomas,

Heckman

2023

Front. Sleep

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The pathophysiology of sleep apnea goes beyond anatomic predisposition to airway collapse and includes additional factors such as arousal threshold and loop gain. High loop gain is a prominent feature in central and complex sleep apnea (with a mixture of obstructive and central features) where relative hypocapnia can lead to respiratory instability and periodic breathing. Existing therapies, including continuous positive airway pressure (CPAP) and adaptive servo-ventilators, often inadequately treat sleep apnea with high loop gain features. Enhanced expiratory rebreathing space (EERS) targets prevention of the hypocapnia that triggers central events in sleep by increasing dead space in amounts less than typical tidal volumes. This is accomplished by covering traditional exhalation ports on positive airway pressure masks and adding small additional tubing with distal exhalation and safety valves. This technique reduces carbon dioxide (CO2) blow-off during arousals and the associated large recovery breaths, typically producing a maximal increase in resting CO2 by 1–2 mmHg, thus increasing the CO2 reserve and making it less likely to encounter the hypocapnic apneic threshold. Typically, the amount of EERS is titrated in response to central events and periodic breathing rather than aiming for a goal CO2 level. Ideally CO2 monitoring is used during titration of EERS and the technique is avoided in the setting of baseline hypercapnia. This method has been used in clinical practice at our sleep center for over 15 years, and retrospective data suggests an excellent safety profile and high rates of successful therapy including in patients who have previously failed CPAP therapy. Limitations include decreased effectiveness in the setting of leak and decreased tolerance of the bulkier circuit. EERS represents a simple, affordable modification of existing positive airway pressure modalities for treatment of central and complex sleep apnea. Areas of future study include randomized controlled trials of the technique and study of use of EERS in combination with adaptive ventilation, and pharmacologic adjuncts targeting high loop gain physiology.

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“…Since there is no fixed criterion for determining temporal and spatial regions, the tracks can be divided into different particle sizes in time and space, and other particle sizes can be assigned to different weights. The larger the particle size, the more accessible the spatio-temporal range and, therefore, the lower the mass; the smaller the particle size, the tighter the time interval, and the higher the group (Oppersma, 2021). The technique for measuring spatial pyramid ballistic similarity should have the following characteristics:…”

Section: Algorithm Characterization and Modelingmentioning

confidence: 99%

Similarity-Based Algorithm for Urban Street Refinement Design Model Extraction Research

Song

2023

EAI Endorsed Trans Energy Web

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INTRODUCTION: The function of many public street spaces in Chinese cities is declining, but urban street space is essential in cities. How to enhance the street's fireworks and reshape the street's rich living atmosphere is worthy of further research and discussion. OBJECTIVES: Based on the similarity algorithm urban street enhancement-related theories, paper summarizes the current problems of urban street space in China, researches the corresponding enhancement strategies according to the issues, and makes a strategic research and summary on the relationship between the interfaces of the scope of the visual field and the human behavior, as well as the relationship between the pedestrian and the vehicular traffic. METHODS: An in-depth study after defining the concept, summarizing the idea and extracting the urban street refinement design model using the similarity algorithm. RESULTS: The new urban street refinement design model can improve the psychological satisfaction of people walking in the application; the street space design model of the walking experience will also use the algorithm to simulate the joy; lastly, a recommended optimization technique is presented for the construction of a humanized street scale and other related factors. CONCLUSION: The study of urban street space is a refined design strategy for the improvement of the urban landscape; the growth of the happiness index of urban residents is of great significance and, at the same time, for the enhancement of China's modernization level, improve the human habitat environment are of great importance, and should pay attention to the urban street refinement design.

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Algorithm for automatic detection of self-similarity and prediction of residual central respiratory events during continuous positive airway pressure

Cited by 17 publications

References 26 publications

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

Point-of-care prediction model of loop gain in patients with obstructive sleep apnea: development and validation

Enhanced expiratory rebreathing space for high loop gain sleep apnea treatment

Similarity-Based Algorithm for Urban Street Refinement Design Model Extraction Research

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