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Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

Maternal Metabolic Health and Mother and Baby Health Outcomes (MAMBO): Protocol of a Prospective Observational Study

Summary of study activities. a Hb A1c: hemoglobin A1c. b CRP: C-reactive protein. c OGTT: oral glucose tolerance test. At the first visit, a full medical history will be taken by a trained clinician including past medical history and surgical history. Outcomes of previous pregnancies will be recorded including outcome of the pregnancy, gestation, pregnancy complications, and (if relevant) birthweight and neonatal complications. Current medications including dose, and dosing schedule will be recorded.

Sarah A L Price, Digsu N Koye, Alice Lewin, Alison Nankervis, Stefan C Kane

JMIR Res Protoc 2025;14:e72542

Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study

Decentralized Biobanking Apps for Patient Tracking of Biospecimen Research: Real-World Usability and Feasibility Study

We examined all contexts along the data pipeline, from population-level breast cancer screening to diagnostic biopsies and surgical treatments, clinical pathology, and specimen accessioning through the biobanking platform, where it may be stored for future use in –80 °C freezers or distributed fresh for next-generation biobanking applications such as patient-derived organoids, multi-omics, and high-throughput testing.

William Sanchez, Ananya Dewan, Eve Budd, M Eifler, Robert C Miller, Jeffery Kahn, Mario Macis, Marielle Gross

JMIR Bioinform Biotech 2025;6:e70463

Development of a Mobile Intervention for Procrastination Augmented With a Semigenerative Chatbot for University Students: Pilot Randomized Controlled Trial

Development of a Mobile Intervention for Procrastination Augmented With a Semigenerative Chatbot for University Students: Pilot Randomized Controlled Trial

Screenshots of the time management app we used for the treatment group: (A) main screen with to-do list; (B) calendar screen visualizing success rate; (C) chatting room screen for conversation with the chatbot Moa. The content that was originally in Korean has been translated into English. Moa is a semigenerative chatbot interlocked with the to-do app to facilitate conversations tailored according to the users’ delaying behavior.

Seonmi Lee, Jaehyun Jeong, Myungsung Kim, Sangil Lee, Sung-Phil Kim, Dooyoung Jung

JMIR Mhealth Uhealth 2025;13:e53133

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study

Developing a Machine Learning Model for Predicting 30-Day Major Adverse Cardiac and Cerebrovascular Events in Patients Undergoing Noncardiac Surgery: Retrospective Study

We developed a prediction model by integrating data from preoperative laboratory measurements 16 routinely measured basic parameters: white blood cell, hemoglobin, platelet count, aspartate aminotransferase, alanine aminotransferase, blood urea nitrogen, creatinine, albumin, calcium, sodium, phosphate, total bilirubin, c-reactive protein, cholesterol, hemoglobin A1c, and prothrombin time), previous diagnosis, medication records, and surgical type from the SNUBH CDM development dataset.

Ju-Seung Kwun, Houng-Beom Ahn, Si-Hyuck Kang, Sooyoung Yoo, Seok Kim, Wongeun Song, Junho Hyun, Ji Seon Oh, Gakyoung Baek, Jung-Won Suh

J Med Internet Res 2025;27:e66366

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

Development and Validation of a Machine Learning Model for Early Prediction of Delirium in Intensive Care Units Using Continuous Physiological Data: Retrospective Study

(C) The AUROC and (D) AUPRC of the model in the temporal validation cohort. (E) The AUROC and (F) AUPRC of the model in the external validation cohort. In addition, the correlation coefficient between each variable and the outcome did not have a high correlation coefficient overall but had the highest values for age, PPG-derived variables, and Sp O2-derived variables (Multimedia Appendix 6).

Chanmin Park, Changho Han, Su Kyeong Jang, Hyungjun Kim, Sora Kim, Byung Hee Kang, Kyoungwon Jung, Dukyong Yoon

J Med Internet Res 2025;27:e59520