Integrated pulmonary index during procedural sedation and analgesia: A cluster-randomized trial.

AIM: To evaluate the effectiveness of utilizing the integrated pulmonary index for capnography implementation during sedation administered by nurses. DESIGN: Cluster-randomized trial. METHODS: Participants were enrolled from the interventional radiology department at an academic hospital in Canada. Nurses were randomized to either enable or disable the Integrated Pulmonary Index feature of the capnography monitor. Procedures were observed by a research assistant to collect information about alarm performance characteristics. The primary outcome was the number of seconds in an alert condition state without an intervention being applied. RESULTS: The number of seconds in an alarm state without intervention was higher in the group that enabled the integrated pulmonary index compared to the group that disabled this feature, but this difference did not reach statistical significance. Likewise, the difference between groups for the total alarm duration, total number of alarms and the total number of appropriate alarms was not statistically significant. The number of inappropriate alarms was higher in the group that enabled the Integrated Pulmonary Index, but this estimate was highly imprecise. There was no difference in the odds of an adverse event (measured by the Tracking and Reporting Outcomes of Procedural Sedation tool) occurring between groups. Desaturation events were uncommon and brief in both groups but the area under the SpO2 90% desaturation curve scores were lower for the group that enabled the integrated pulmonary index. CONCLUSION: Enabling the integrated pulmonary index during nurse-administered procedural sedation did not reduce nurses' response times to alarms. Therefore, integrating multiple physiological parameters related to respiratory assessment into a single index did not lower the threshold for intervention by nurses. IMPLICATIONS FOR THE PROFESSION AND/OR PATIENT CARE: The time it takes to respond to capnography monitor alarms will not be reduced if the integrated pulmonary Iindex feature of capnography monitors is enabled during nurse-administered procedural sedation. IMPACT: Results do not support the routine enabling of the integrated pulmonary index when nurses use capnography to monitor patients during procedural sedation as a strategy to reduce the time it takes to initiate responses to alarms. REPORTING METHOD: CONSORT. PATIENT OR PUBLIC CONTRIBUTION: There was no patient or public contribution. TRIAL REGISTRATION: This study was prospectively registered at ClinicalTrials.gov (ID: NCT05068700).

Deep learning classification of capnography waveforms: secondary analysis of the PRODIGY study.

Capnography monitors trigger high priority 'no breath' alarms when CO2 measurements do not exceed a given threshold over a specified time-period. False alarms occur when the underlying breathing pattern is stable, but the alarm is triggered when the CO2 value reduces even slightly below the threshold. True 'no breath' events can be falsely classified as breathing if waveform artifact causes an aberrant spike in CO2 values above the threshold. The aim of this study was to determine the accuracy of a deep learning approach to classifying segments of capnography waveforms as either 'breath' or 'no breath'. A post hoc secondary analysis of data from 9 North American sites included in the PRediction of Opioid-induced Respiratory Depression In Patients Monitored by capnoGraphY (PRODIGY) study was conducted. We used a convolutional neural network to classify 15 s capnography waveform segments drawn from a random sample of 400 participants. Loss was calculated over batches of 32 using the binary cross-entropy loss function with weights updated using the Adam optimizer. Internal-external validation was performed by iteratively fitting the model using data from all but one hospital and then assessing its performance in the remaining hospital. The labelled dataset consisted of 10,391 capnography waveform segments. The neural network's accuracy was 0.97, precision was 0.97 and recall was 0.96. Performance was consistent across hospitals in internal-external validation. The neural network could reduce false capnography alarms. Further research is needed to compare the frequency of alarms derived from the neural network with the standard approach.

Integrated Pulmonary Index during nurse-administered procedural sedation: Study protocol for a cluster-randomized trial.

AIM: To determine if smart alarm-guided treatment of respiratory depression using the Integrated Pulmonary Index is an effective way to implement capnography during nurse-administered sedation. DESIGN: Parallel cluster-randomized trial. METHODS: Nurses will be randomized to use capnography with or without the Integrated Pulmonary Index enabled. Capnography alarm performance will be compared between nurses using capnography alone or with the Integrated Pulmonary Index enabled. The target sample size is 400 adult patients scheduled for elective procedures with nurse-administered sedation. The primary outcome is the number of seconds in an alert condition state without an intervention being applied. Secondary outcomes are alarm burden, number of appropriate alarms, number of inappropriate alarms, total duration of alert conditions, choice of alarm settings and adverse sedation events. This study has been funded since April 2021. DISCUSSION: Implementing capnography into practice for respiratory monitoring during nurse-administered sedation is considered a high priority. The Integrated Pulmonary Index shows promise as a strategy to optimize the implementation of capnography for respiratory monitoring during nurse-administered sedation. If it is found in this study that using the Integrated Pulmonary Index improves the nursing management of physiologically abnormal states during nurse-administered sedation, it would provide the high-level evidence needed to support broader use of this 'smart alarm' strategy for respiratory monitoring in practice. IMPACT: With advances in medical technology continuing to expand the indications for minimally invasive surgical techniques, the use of nurse-administered sedation during medical procedures is likely to expand in the future. The findings may be applied to other populations receiving nurse-administered sedation during medical procedures. Results from this study will help translate the usage of smart alarm-guided treatment of respiratory depression during procedural sedation. TRIAL REGISTRATION: NCT05068700.

Effect of prone position on respiratory parameters, intubation and death rate in COVID-19 patients: systematic review and meta-analysis.

Prone position (PP) is known to improve oxygenation and reduce mortality in COVID-19 patients. This systematic review and meta-analysis aimed to determine the effects of PP on respiratory parameters and outcomes. PubMed, EMBASE, ProQuest, SCOPUS, Web of Sciences, Cochrane library, and Google Scholar were searched up to 1st January 2021. Twenty-eight studies were included. The Cochran's Q-test and I2 statistic were assessed heterogeneity, the random-effects model was estimated the pooled mean difference (PMD), and a meta-regression method has utilized the factors affecting heterogeneity between studies. PMD with 95% confidence interval (CI) of PaO2/FIO2 Ratio in before-after design, quasi-experimental design and in overall was 55.74, 56.38, and 56.20 mmHg. These values for Spo2 (Sao2) were 3.38, 17.03, and 7.58. PP in COVID-19 patients lead to significantly decrease of the Paco2 (PMD: - 8.69; 95% CI - 14.69 to - 2.69 mmHg) but significantly increase the PaO2 (PMD: 37.74; 95% CI 7.16-68.33 mmHg). PP has no significant effect on the respiratory rate. Based on meta-regression, the study design has a significant effect on the heterogeneity of Spo2 (Sao2) (Coefficient: 12.80; p < 0.001). No significant associations were observed for other respiratory parameters with sample size and study design. The pooled estimate for death rate and intubation rates were 19.03 (8.19-32.61) and 30.68 (21.39-40.75). The prone positioning was associated with improved oxygenation parameters and reduced mortality and intubation rate in COVID-19 related respiratory failure.