Journal of clinical monitoring and computing
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J Clin Monit Comput · Apr 2024
Early prediction of mortality at sepsis diagnosis time in critically ill patients by using interpretable machine learning.
This study applied machine learning for the early prediction of 30-day mortality at sepsis diagnosis time in critically ill patients. Retrospective study using data collected from the Medical Information Mart for Intensive Care IV database. The data of the patient cohort was divided on the basis of the year of hospitalization, into training (2008-2013), validation (2014-2016), and testing (2017-2019) datasets. 24,377 patients with the sepsis diagnosis time < 24 h after intensive care unit (ICU) admission were included. ⋯ The calibration plot for the model revealed a slope of 1.03 (95% CI 0.94-1.12) and intercept of 0.14 (95% CI 0.04-0.25). The SHAP revealed the top three most significant features, namely age, increased red blood cell distribution width, and respiratory rate. Our study demonstrated the feasibility of using the interpretable machine learning model to predict mortality at sepsis diagnosis time.
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J Clin Monit Comput · Apr 2024
Accuracy and clinical utility of heart rate variability derived from a wearable heart rate monitor in patients undergoing major abdominal surgery.
Low heart rate variability (HRV) can potentially identify patients at risk of intraoperative hypotension. However, it is unclear whether cheaper, readily accessible consumer heart rate (HR) monitors can provide similar utility to clinical Holter electrocardiograph (ECG) monitors. The objectives of this study were (1) to assess the validity of using the Polar H10 HR monitor as an alternative to a clinical Holter ECG and (2) to test total power (TP) as a predictor of intraoperative hypotension. ⋯ Patients with reduced TP were significantly more likely to require vasoactive drugs to maintain blood pressure. The substantial agreement between Polar H10 and Holter ECG may justify its use clinically. The use of preoperative recordings of HRV has the potential to become part of routine preoperative assessment as a useful screening tool to predict hemodynamic instability in patients undergoing general anesthesia.
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J Clin Monit Comput · Apr 2024
FiO2 prediction formula during low flow oxygen therapy in an adult model: a bench study.
During low-flow oxygen therapy, the true value of inspired oxygen fraction (FiO2) is generally unknown. Knowledge of delivered FiO2 values may be useful as well as to adjust oxygen therapy, as well as to predict patient deterioration. This study proposes a New FiO2 Prediction Formula (NFiO2) for low-flow oxygenation and compares its predictive value to precedent formulas. ⋯ Bias and limits of agreement between predicted FiO2 and benchtop FiO2 highlighted consistent differences between different FiO2 prediction formulas. The NFiO2 and the Duprez Formula 2018 seemed to be the most accurate formulas, followed by the Vincent Formula, and lastly the Shapiro Formula. A New FiO2 Prediction Formula was developed using clinical readily available variables (RR and O2 Flow rate) which showed good accuracy in predicting FiO2 during oxygenation at low flow.
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We review the study by Xu et al. (J Clin Monit Comput 37(4):985-992, 2023. https://doi.org/10.1007/s10877-022-00968-1 ) on ultrasound-guided regional blocks in clavicle surgery, assessing the effects on anaesthesia and postoperative outcomes. However, there are concerns. The defined population of the study differs from the registered title (Xu et al. ⋯ In addition, the method of measuring the diaphragm is not clear (Xu et al. J Clin Monit Comput 37(4):985-992, 2023. https://doi.org/10.1007/s10877-022-00968-1 ). This affects the accurate interpretation of their results.
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J Clin Monit Comput · Apr 2024
ReviewTen good reasons to consider gastrointestinal function after acute brain injury.
The brain-gut axis represents a bidirectional communication linking brain function with the gastrointestinal (GI) system. This interaction comprises a top-down communication from the brain to the gut, and a bottom-up communication from the gut to the brain, including neural, endocrine, immune, and humoral signaling. Acute brain injury (ABI) can lead to systemic complications including GI dysfunction. ⋯ Despite novel biomarkers represent a limitation in clinical practice, intra-abdominal pressure (IAP) is easy-to-use and measurable at bedside. Increased IAP can be both cause and consequence of GI dysfunction, and it can influence cerebral perfusion pressure and intracranial pressure via physiological mechanisms. Here, we address ten good reasons to consider GI function in patients with ABI, highlighting the importance of its assessment in neurocritical care.