Surgical endoscopy · 2025
Automated tagging of intraoperative physiologic events: understanding the clinical consequences.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
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Ошибки и ограничения
История · было → стало
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Bain Andrew P, Succar Bahaa, Odeh Jaffer, Al Abbas Amr, Bishop Samantha, Reed Mary Grace, Wan Bingchun, Zeh Herbert J, Mansour John C, Bartolome Sonja
Аннотация
INTRODUCTION: Hypotension, hypoxia, and hypothermia tissue have unclear effects on postoperative outcomes. The Operating Room Black Box™ (ORBB) is a novel monitoring platform that automates "tagging" of intraoperative hypotension, hypoxia, and hypothermia. We hypothesized that intraoperative physiologic event tags would serve as predictive variables of adverse postoperative outcomes.
METHODS: Using the ORBB, tags were prospectively applied for moderate and severe episodes of hypotension, hypothermia, and hypoxia. Regression modeling was performed to examine the association between intraoperative tags and adverse outcomes of surgical site infection, patient safety indicator (PSI) events, length of stay, readmission, return to OR, and mortality.
RESULTS: 2875 cases were performed and monitored with the ORBB tag system between August 17, 2020 and September 3, 2022. 567 cases (19%) were tagged. Regression models had improved performance after adding in intraoperative physiologic data. Hypothermia and hypoxia were independent predictors of increased return to the operating room (p < 0.02, p < 0.01, respectively). Hypotension was an independent predictor of length of stay (p < 0.03) and patient safety indicator events (p = 0.03). Comorbidities, length of case, BMI, age, and ASA status played significant roles in the predictive models.
CONCLUSION: Intraoperative physiologic events are important variables to consider regarding postoperative complications and should be incorporated into quality and safety analysis. As real-time OR data monitoring becomes a reality, work must be done to identify the intraoperative events and patient factors that most affect outcomes. This retrospective modeling serves as the first step toward intraoperative predictive analytics that can provide decision support for postoperative care.
METHODS: Using the ORBB, tags were prospectively applied for moderate and severe episodes of hypotension, hypothermia, and hypoxia. Regression modeling was performed to examine the association between intraoperative tags and adverse outcomes of surgical site infection, patient safety indicator (PSI) events, length of stay, readmission, return to OR, and mortality.
RESULTS: 2875 cases were performed and monitored with the ORBB tag system between August 17, 2020 and September 3, 2022. 567 cases (19%) were tagged. Regression models had improved performance after adding in intraoperative physiologic data. Hypothermia and hypoxia were independent predictors of increased return to the operating room (p < 0.02, p < 0.01, respectively). Hypotension was an independent predictor of length of stay (p < 0.03) and patient safety indicator events (p = 0.03). Comorbidities, length of case, BMI, age, and ASA status played significant roles in the predictive models.
CONCLUSION: Intraoperative physiologic events are important variables to consider regarding postoperative complications and should be incorporated into quality and safety analysis. As real-time OR data monitoring becomes a reality, work must be done to identify the intraoperative events and patient factors that most affect outcomes. This retrospective modeling serves as the first step toward intraoperative predictive analytics that can provide decision support for postoperative care.