Critical care explorations · 2025
Physiological Signal Entropy in Pediatric Traumatic Brain Injury: Looking Beyond the Obvious: A STARSHIP Study.
СтатьяМногоцентровое исследованиеНаблюдательное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Bögli Stefan Yu, Smith Claudia Ann, Hutchinson Peter, Agrawal Shruti, Smielewski Peter, Studying Trends of Autoregulation in Severe Head Injury in Paediatrics (STARSHIP) study team
Аннотация
OBJECTIVES: Multimodality monitoring based prognostication in pediatric traumatic brain injury (TBI) relies heavily on the evaluation of instantaneous and easily interpretable monitoring values. Entropy quantifies the level of disorder within a system reflecting overall activity of sensitive closed-loop feedback homeostatic mechanisms. Multiscale entropy (MSE) assesses entropy across different time scales to examine various physiologic systems and processes that operate across different time scales. The current understanding of MSE suggests that low entropy reflects increased rigidity of the various homeostatic control systems, reflecting underperformance of mechanisms such as cerebral autoregulation. This hypothesis-generating retrospective study explores the value of MSE for prognostication after pediatric TBI.
DESIGN: Retrospective analysis of data from an observational multicenter database.
SETTING: Ten PICUs across the United Kingdom.
PATIENTS: One hundred thirty-five children with severe pediatric TBI receiving invasive neuromonitoring between 2018 and 2022.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: MSE was calculated based on 10-second time trends of different biosignals (incl. blood pressure, heart rate, intracranial pressure [ICP]). MSE metrics were assessed using univariable and multivariable (logistic regression with backward stepwise elimination and sliding dichotomy) methods. Last, correlation coefficients between MSE and clinical or monitoring metrics were assessed. Decreased MSE of physiologic biosignals were associated with worse outcomes and remained associated with outcomes when added to multivariable analyses. Within multivariable logistic regression analyses (covariates: Injury Severity Score [ISS], Rotterdam score, ICP, pressure reactivity index [PRx]), the resulting odds ratios (ORs) were: MSE arterial blood pressure (abp: OR, 0.83; p = 0.014), MSE cerebral perfusion pressure (cpp: OR, 0.86; p = 0.024), and MSE icp (OR, 0.87; p = 0.029). MSE displayed weak associations with clinical parameters reflecting higher TBI severity (i.e., ISS, Abbreviated Injury Scale, Glasgow Coma Scale, etc.) but moderate correlations with PRx (correlation coefficients: MSE abp, -0.47; MSE cpp, -0.55) and ICP (MSE abp, -0.3).
CONCLUSIONS: Biosignal complexity is a promising tool for improving individualized prognostication after pediatric TBI. Our results further underpin the association between MSE and the function of physiologic autoregulatory mechanisms.
DESIGN: Retrospective analysis of data from an observational multicenter database.
SETTING: Ten PICUs across the United Kingdom.
PATIENTS: One hundred thirty-five children with severe pediatric TBI receiving invasive neuromonitoring between 2018 and 2022.
INTERVENTIONS: None.
MEASUREMENTS AND MAIN RESULTS: MSE was calculated based on 10-second time trends of different biosignals (incl. blood pressure, heart rate, intracranial pressure [ICP]). MSE metrics were assessed using univariable and multivariable (logistic regression with backward stepwise elimination and sliding dichotomy) methods. Last, correlation coefficients between MSE and clinical or monitoring metrics were assessed. Decreased MSE of physiologic biosignals were associated with worse outcomes and remained associated with outcomes when added to multivariable analyses. Within multivariable logistic regression analyses (covariates: Injury Severity Score [ISS], Rotterdam score, ICP, pressure reactivity index [PRx]), the resulting odds ratios (ORs) were: MSE arterial blood pressure (abp: OR, 0.83; p = 0.014), MSE cerebral perfusion pressure (cpp: OR, 0.86; p = 0.024), and MSE icp (OR, 0.87; p = 0.029). MSE displayed weak associations with clinical parameters reflecting higher TBI severity (i.e., ISS, Abbreviated Injury Scale, Glasgow Coma Scale, etc.) but moderate correlations with PRx (correlation coefficients: MSE abp, -0.47; MSE cpp, -0.55) and ICP (MSE abp, -0.3).
CONCLUSIONS: Biosignal complexity is a promising tool for improving individualized prognostication after pediatric TBI. Our results further underpin the association between MSE and the function of physiologic autoregulatory mechanisms.