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Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

Machine Learning Models for Prediction of Maternal Hemorrhage and Transfusion: Model Development Study

A modified F2 score was chosen to minimize false negatives and thus maximize the identification of patients at high risk for bleeding and transfusion. Existing LR models and risk classification schemes perform poorly, and the majority of patients with hemorrhage or transfusion are misclassified as low risk. Misclassification of a “high risk” patient as “low risk” may have important clinical implications.

Homa Khorrami Ahmadzia, Alexa C Dzienny, Mike Bopf, Jaclyn M Phillips, Jerome Jeffrey Federspiel, Richard Amdur, Madeline Murguia Rice, Laritza Rodriguez

JMIR Bioinform Biotech 2024;5:e52059

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Treatments for Trauma-Induced Coagulopathy: Protocol for a Systematic Review and Meta-Analysis

Treatments for Trauma-Induced Coagulopathy: Protocol for a Systematic Review and Meta-Analysis

Death during the early phase of trauma is primarily attributable to uncontrolled bleeding, which is exacerbated by trauma-induced coagulopathy (TIC) [2-4]. Pathophysiology and clinical aspects of TIC comprise blood loss, consumption of coagulation factors, dilution, and fibrinolytic activation [2-5]. TIC correlates with an increased demand for massive transfusion as well as higher mortality. Thus, effective treatment of TIC is crucial for decreasing deaths following trauma [3-5].

Yuki Itagaki, Mineji Hayakawa, Yuki Takahashi, Yuichiro Sakamoto, Shigeki Kushimoto, Yutaka Eguchi, Yoshinobu Seki, Kohji Okamoto

JMIR Res Protoc 2023;12:e49582

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Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study

Relation Classification for Bleeding Events From Electronic Health Records Using Deep Learning Systems: An Empirical Study

Bleeding refers to the escape of blood from the circulatory system either internally or externally. Bleeding events are common and frequently have a major impact on patient quality of life and survival. Bleeding events are common adverse drug events, particularly among patients with cardiovascular conditions who are prescribed anticoagulant medications [1].

Avijit Mitra, Bhanu Pratap Singh Rawat, David D McManus, Hong Yu

JMIR Med Inform 2021;9(7):e27527

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Effectiveness of the Alfalfa App in Warfarin Therapy Management for Patients Undergoing Venous Thrombosis Prevention and Treatment: Cohort Study

Effectiveness of the Alfalfa App in Warfarin Therapy Management for Patients Undergoing Venous Thrombosis Prevention and Treatment: Cohort Study

Secondary outcomes included minor bleeding events, major bleeding events, thrombotic events, warfarin-related emergency department visits, warfarin-related hospital admissions, and high INR values. Major bleeding events included any bleeding requiring hospitalization or transfusion, as defined in the International Society on Thrombosis and Haemostasis classification [12].

Hua Cao, Shaojun Jiang, Meina Lv, Tingting Wu, Wenjun Chen, Jinhua Zhang

JMIR Mhealth Uhealth 2021;9(3):e23332

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Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Detection of Bleeding Events in Electronic Health Record Notes Using Convolutional Neural Network Models Enhanced With Recurrent Neural Network Autoencoders: Deep Learning Approach

Bleeding is defined as the escape of blood from the circulatory system (arteries and veins) due to trauma, anatomic malformation, bleeding disorder, medications, and aging. Bleeding events include symptoms like reddening or darkening of urine or stools, bleeding of gums, blood blisters, bruises, and vomiting of blood.

Rumeng Li, Baotian Hu, Feifan Liu, Weisong Liu, Francesca Cunningham, David D McManus, Hong Yu

JMIR Med Inform 2019;7(1):e10788

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The Use of Aspirin to Reduce the Risk of Thrombotic Events in Patients With End-Stage Renal Disease: Protocol for a Randomized Controlled Trial

The Use of Aspirin to Reduce the Risk of Thrombotic Events in Patients With End-Stage Renal Disease: Protocol for a Randomized Controlled Trial

Concerning the risk of aspirin-related bleeding, there is some discrepancy between the results of observational and interventional studies, as an increased risk of bleeding has been reported in some observational studies [13,14]. However, interventional studies of patients with ESRD have found that low doses of aspirin are not associated with an increased risk of major bleeding in dialysis patients, despite an apparent increased risk of minor bleeding (eg, gastrointestinal bleeding) [10,15].

Tiago Monique Lemos Cerqueira, Armando Fartolino Guerrero, Clara Krystal Pérez Fermin, Ricardo Wang, Evelin Elfriede Balbino, Janis L Breeze, Paola Gonzalez Mego, Daniele Argentina Silva, Walid Ezzeldin Omer, Nathalie Monique Vandevelde

JMIR Res Protoc 2018;7(8):e10516

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