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Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection.
BMC Med Inform Decis Mak
December 2024
Digital Medicine, University Hospital of Augsburg, Augsburg, Germany.
Background: Blood transfusion (BT) is a critical aspect of medical care for surgical patients in the Intensive Care Unit (ICU). Timely and accurate identification of BT needs can enhance patient outcomes and healthcare resource management.
Methods: This study aims to determine whether a machine learning (ML) model can be trained to predict the need for blood transfusion (BT) in patients on the ICU after a wide range of surgeries, utilizing only data from the ICU.
Development, External Validation, and Biomolecular Corroboration of Interoperable Models for Identifying Critically Ill Children at Risk of Neurologic Morbidity.
medRxiv
September 2024
Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA.
Importance: Declining mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients' neurodevelopmental potential as a main objective. Earlier identification of critically ill children at risk for incurring neurologic morbidity would facilitate heightened surveillance that could lead to timelier clinical detection, earlier interventions, and preserved neurodevelopmental trajectory.
Objective: Develop machine-learning models for identifying acquired neurologic morbidity while hospitalized with critical illness and assess correlation with contemporary serum-based, brain injury-derived biomarkers.
Early Prediction of Cardiac Arrest in the Intensive Care Unit Using Explainable Machine Learning: Retrospective Study.
J Med Internet Res
September 2024
Department of Biomedical Software Engineering, The Catholic University of Korea, Bucheon-si, Gyeonggi-do, Republic of Korea.
Background: Cardiac arrest (CA) is one of the leading causes of death among patients in the intensive care unit (ICU). Although many CA prediction models with high sensitivity have been developed to anticipate CA, their practical application has been challenging due to a lack of generalization and validation. Additionally, the heterogeneity among patients in different ICU subtypes has not been adequately addressed.
View Article and Find Full Text PDFComparative effects of time-restricted feeding versus normal diet on physical performance and body composition in healthy adults with regular exercise habits: a systematic review and meta-analysis.
BMJ Open Sport Exerc Med
August 2024
Department of Sports Science and Physical Education, The Chinese University of Hong Kong, Hong Kong, People's Republic of China.
Article Synopsis
- Time-restricted feeding (TRF) is a diet where you eat your meals in a short time frame, which can help with weight loss and better health.
- The study looked at different research papers and found that TRF can help people lose weight and fat without changing their exercise performance.
- The researchers found that although TRF improved body composition, there were mixed results on the quality of the studies reviewed, with most having some concerns.
Chronobioethics: Symphony of biological clocks observed by 7-day/24-hour ambulatory blood pressure monitoring and cardiovascular health.
Biomed J
June 2024
Halberg Chronobiology Center, University of Minnesota, Minneapolis, MN, USA.
Background: The high prevalence of desynchronized biological rhythms is becoming a primary public health concern. We assess complex and diverse inter-modulations among multi-frequency rhythms present in blood pressure (BP) and heart rate (HR).
Subjects: and Methods: We performed 7-day/24-hour Ambulatory BP Monitoring in 220 (133 women) residents (23 to 74 years) of a rural Japanese town in Kochi Prefecture under everyday life conditions.
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