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Validation and Comparison of Pediatric Appendicitis Scores and Management Strategies (Project SPASMS): Protocol for a Prospective Multicenter Observational Study

Validation and Comparison of Pediatric Appendicitis Scores and Management Strategies (Project SPASMS): Protocol for a Prospective Multicenter Observational Study

To describe the epidemiology and management of pediatric appendicitis, illustrating: (A) The burden of disease in patients presenting with acute abdominal pain with the suspicion of appendicitis; (B) The incidence and type of surgical procedures undertaken in the management of appendicitis in ANZ (laparoscopic appendectomy, open appendectomy, nonsurgical management with intravenous antibiotics, and delayed appendectomy); (C) The imaging procedures undertaken in patients assessed for possible appendicitis, and

Wei Hao Lee, Sharon O'Brien, Elizabeth J Mckinnon, Simon Craig, Stuart Dalziel, Michael Collin, Natalie Phillips, Franz E Babl, Sarah Julia Davidson, Shane George, Shefali Jani, Doris Tham, Viet Tran, Meredith L Borland

JMIR Res Protoc 2025;14:e67941

Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

Research Dissemination Strategies in Pediatric Emergency Care Using a Professional Twitter (X) Account: A Mixed Methods Developmental Study of a Logic Model Framework

development (R) Acquisition of external graphics designer (G) Selection of software and metrics (J) Learning to work with existing technologies for scheduling and publishing (AF) Sudden unexpected team member change (U) Outputs Extracting key teaching points from top PECARN articles into tweet (X) Tweet frequency established at the same time each week (3 times per week) (AH) Tweet visual structure: Intentional or strategic polls, emojis, bullet points, and multimedia such as images and videos (AA, AB, AC, C,

Gwendolyn C Hooley, Julia N Magana, Jason M Woods, Shyam Sivasankar, Lauren VonHoltz, Anita R Schmidt, Todd P Chang, Michelle Lin

JMIR Form Res 2025;9:e59481

Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis

Causal AI Recommendation System for Digital Mental Health: Bayesian Decision-Theoretic Analysis

For example, consider a set of variables {A,B,C,D} that have the dependency relations described by the DAG A←B→C→D, then this DAG would be consistent with the partition {{B},{A,C},{D}}. The sampling procedure was run across 8 chains and checked for convergence and resolution (Note S2 in Multimedia Appendix 1). We used the Bayesian Gaussian equivalent score to retain the ordinal information of the random variables. Simulating outcomes given a DAG is performed by constructing a Bayesian network (BN).

Mathew Varidel, Victor An, Ian B Hickie, Sally Cripps, Roman Marchant, Jan Scott, Jacob J Crouse, Adam Poulsen, Bridianne O'Dea, Sarah McKenna, Frank Iorfino

J Med Internet Res 2025;27:e71305