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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

Accuracy of Smartphone-Mediated Snore Detection in a Simulated Real-World Setting: Algorithm Development and Validation

Accuracy of Smartphone-Mediated Snore Detection in a Simulated Real-World Setting: Algorithm Development and Validation

Analytical validation reference table showing the schematic and equationsa,b,c,d,e used to report snore detection performance of the Sleep Watch app in this study. a Accuracy = (true positive + true negative)/(true positive + true negative + false positive + false negative). b Sensitivity = true positive/(true positive + false negative). c Specificity = true negative/(false positive + true negative). d Positive predictive value = true positive/(true positive + false positive). e Negative predictive value = true negative

Jeffrey Brown, Zachary Mitchell, Yu Albert Jiang, Ryan Archdeacon

JMIR Form Res 2025;9:e67861

Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Acceptability of a Web-Based Health App (PortfolioDiet.app) to Translate a Nutrition Therapy for Cardiovascular Disease in High-Risk Adults: Mixed Methods Randomized Ancillary Pilot Study

Several recent Canadian population-based studies have shown that many patients at high CVD risk continue to have low-density lipoprotein cholesterol (LDL-C) levels well above the guideline targets [2,3]. LDL-C has been extensively studied and described as a causal factor for CVD [4]. LDL-C levels above the target can result from multiple factors such as insufficient LDL-C lowering with statins, statin-related side effects, suboptimal medication adherence, and treatment inertia [5].

Meaghan E Kavanagh, Laura Chiavaroli, Selina M Quibrantar, Gabrielle Viscardi, Kimberly Ramboanga, Natalie Amlin, Melanie Paquette, Sandhya Sahye-Pudaruth, Darshna Patel, Shannan M Grant, Andrea J Glenn, Sabrina Ayoub-Charette, Andreea Zurbau, Robert G Josse, Vasanti S Malik, Cyril W C Kendall, David J A Jenkins, John L Sievenpiper

JMIR Cardio 2025;9:e58124