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An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

An “All-Data-on-Hand” Deep Learning Model to Predict Hospitalization for Diabetic Ketoacidosis in Youth With Type 1 Diabetes: Development and Validation Study

We constructed a predictive model using a recurrent neural network–based approach suited to processing time series and other sequential data [13]. We specifically developed and evaluated the performance characteristics of a long short-term memory (LSTM) model to predict the 180-day risk of DKA-related hospitalization among youth with T1 D [14]. We developed a model to predict DKA-related hospitalizations within the T1 D population of diabetes centers.

David D Williams, Diana Ferro, Colin Mullaney, Lydia Skrabonja, Mitchell S Barnes, Susana R Patton, Brent Lockee, Erin M Tallon, Craig A Vandervelden, Cintya Schweisberger, Sanjeev Mehta, Ryan McDonough, Marcus Lind, Leonard D'Avolio, Mark A Clements

JMIR Diabetes 2023;8:e47592

Digital Gaming and Exercise Among Youth With Type 1 Diabetes: Cross-Sectional Analysis of Data From the Type 1 Diabetes Exercise Initiative Pediatric Study

Digital Gaming and Exercise Among Youth With Type 1 Diabetes: Cross-Sectional Analysis of Data From the Type 1 Diabetes Exercise Initiative Pediatric Study

Type 1 diabetes (T1 D) is a common chronic medical condition among children [1]. It is characterized by a loss of endogenous insulin production in the pancreas and an inability to self-regulate blood glucose levels. The daily treatment for T1 D includes vigilant glucose monitoring, carbohydrate counting, and intensive insulin delivery, with the goal of trying to achieve near-normal glucose levels [2].

Susana R Patton, Robin L Gal, Simon Bergford, Peter Calhoun, Mark A Clements, Jennifer L Sherr, Michael C Riddell

JMIR Pediatr Parent 2024;7:e57198


Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study

Accuracy of Wrist-Worn Activity Monitors During Common Daily Physical Activities and Types of Structured Exercise: Evaluation Study

Activities included sitting on a chair or lying on a bed, washing of dishes and simulated loading and unloading of a dishwasher, sweeping or vacuuming of a small room, organizing a room or adjusting furniture in the room, scrubbing of walls and carpet/floor, and self-paced ascending and descending of a flight of stairs. These activities were preceded and followed by two 5-min segments of seated rest.

Ravi Kondama G Reddy, Rubin Pooni, Dessi P Zaharieva, Brian Senf, Joseph El Youssef, Eyal Dassau, Francis J Doyle III, Mark A Clements, Michael R Rickels, Susana R Patton, Jessica R Castle, Michael C Riddell, Peter G Jacobs

JMIR Mhealth Uhealth 2018;6(12):e10338

Reducing Emotional Distress for Childhood Hypoglycemia in Parents (REDCHiP): Protocol for a Randomized Clinical Trial to Test a Video-Based Telehealth Intervention

Reducing Emotional Distress for Childhood Hypoglycemia in Parents (REDCHiP): Protocol for a Randomized Clinical Trial to Test a Video-Based Telehealth Intervention

Building on past research, we developed a theoretical model for caregiver fear of hypoglycemia (Figure 1) which identifies child and caregiver variables that may underlie caregiver fear of hypoglycemia. For example, we have data suggesting that a child’s T1 D history, including past experience with hypoglycemia, and a child’s sleeping behavior may relate to caregiver fear of hypoglycemia [15,17,18].

Susana R Patton, Andrew McConville, Arwen M Marker, Alexandra D Monzon, Kimberly A Driscoll, Mark A Clements

JMIR Res Protoc 2020;9(8):e17877