Pediatric pulse oximetry-based OSA screening at different thresholds of the apnea-hypopnea index with an expression of uncertainty for inconclusive classifications.

BACKGROUND: Assessments of pediatric obstructive sleep apnea (OSA) are underutilized across Canada due to a lack of resources. Polysomnography (PSG) measures OSA severity through the average number of apnea/hypopnea events per hour (AHI), but is resource intensive and requires a specialized sleep laboratory, which results in long waitlists and delays in OSA detection. Prompt diagnosis and treatment of OSA are crucial for children, as untreated OSA is linked to behavioral deficits, growth failure, and negative cardiovascular consequences. We aim to assess the performance of a portable pediatric OSA screening tool at different AHI cut-offs using overnight smartphone-based pulse oximetry. MATERIAL AND METHODS: Following ethics approval and informed consent, children referred to British Columbia Children's Hospital for overnight PSG were recruited for two studies including 160 and 75 children, respectively. An additional smartphone-based pulse oximeter sensor was used in both studies to record overnight pulse oximetry [SpO2 and photoplethysmogram (PPG)] alongside the PSG. Features characterizing SpO2 dynamics and heart rate variability from pulse peak intervals of the PPG signal were derived from pulse oximetry recordings. Three multivariate logistic regression screening models, targeted at three different levels of OSA severity (AHI ≥ 1, 5, and 10), were developed using stepwise-selection of features using the Bayesian information criterion (BIC). The "Gray Zone" approach was also implemented for different tolerance values to allow for more precise detection of children with inconclusive classification results. RESULTS: The optimal diagnostic tolerance values defining the "Gray Zone" borders (15, 10, and 5, respectively) were selected to develop the final models to screen for children at AHI cut-offs of 1, 5, and 10. The final models evaluated through cross-validation showed good accuracy (75%, 82% and 89%), sensitivity (80%, 85% and 82%) and specificity (65%, 79% and 91%) values for detecting children with AHI ≥ 1, AHI ≥ 5 and AHI ≥ 10. The percentage of children classified as inconclusive was 28%, 38% and 16% for models detecting AHI ≥ 1, AHI ≥ 5, and AHI ≥ 10, respectively. CONCLUSIONS: The proposed pulse oximetry-based OSA screening tool at different AHI cut-offs may assist clinicians in identifying children at different OSA severity levels. Using this tool at home prior to PSG can help with optimizing the limited resources for PSG screening. Further validation with larger and more heterogeneous datasets is required before introducing in clinical practice.

Oxygen therapy for acutely ill medical patients: a clinical practice guideline

What is the best way to use oxygen therapy for patients with an acute medical illness? A systematic review published in the Lancet in April 2018 found that supplemental oxygen in inpatients with normal oxygen saturation increases mortality.1 Its authors concluded that oxygen should be administered conservatively, but they did not make specific recommendations on how to do it. An international expert panel used that review to inform this guideline. It aims to promptly and transparently translate potentially practice-changing evidence to usable recommendations for clinicians and patients.2 The panel used the GRADE framework and following standards for trustworthy guidelines.3

Research: Comparison of the Accuracy of a Pocket versus Standard Pulse Oximeter.

BACKGROUND: Pulse oximetry has become an essential tool in clinical practice. With patient self-management becoming more prevalent, pulse oximetry self-monitoring has the potential to become common practice in the near future. This study sought to compare the accuracy of two pulse oximeters, a high-quality standard pulse oximeter and an inexpensive pocket pulse oximeter, and to compare both devices with arterial blood co-oximetry oxygen saturation. METHODS: A total of 95 patients (35.8% women; mean [±SD] age 63.1 ± 13.9 years; mean arterial pressure was 92 ± 12.0 mmHg; mean axillar temperature 36.3 ± 0.4°C) presenting to our hospital for blood gas analysis was evaluated. The Bland-Altman technique was performed to calculate bias and precision, as well as agreement limits. Student's t test was performed. RESULTS: Standard oximeter presented 1.84% bias and a precision error of 1.80%. Pocket oximeter presented a bias of 1.85% and a precision error of 2.21%. Agreement limits were -1.69% to 5.37% (standard oximeter) and -2.48% to 6.18% (pocket oximeter). CONCLUSION: Both oximeters presented bias, which was expected given previous research. The pocket oximeter was less precise but had agreement limits that were comparable with current evidence. Pocket oximeters can be powerful allies in clinical monitoring of patients based on a self-monitoring/efficacy strategy.

Oximetry: state-of-the-art.

Measuring arterial hemoglobin saturation via traditional arterial blood gas testing or co-oximetry complements the fundamental physical examination process. Within the last two decades, advancements in diagnostic technologies made possible the dynamic, noninvasive assessment of hemoglobin saturation through pulse oximetry. Technology assessment teams must determine the relative cost-effectiveness of these techniques and their effect on patient outcome.