Daniel DeSalvo, MD

Dr. Daniel DeSalvo is a Pediatric Endocrinologist and Clinical Researcher specializing in type 1 diabetes, diabetes technology and strategies to improve outcomes for children and adolescents living with diabetes. His clinical and research work focuses on advancing the use of automated insulin delivery systems, continuous glucose monitoring and disease-modifying therapies to reduce the burden of diabetes management for patients and families. Dr. DeSalvo leads and collaborates on clinical trials and quality improvement initiatives aimed at accelerating the translation of innovative diabetes therapies into routine clinical practice.

In addition to his clinical responsibilities, Dr. DeSalvo is actively involved in clinical research, program development and the training and mentorship of students, trainees and healthcare professionals. He regularly presents at regional and national meetings and works closely with academic, industry and community partners to advance the care of children and adolescents with diabetes.

Personal Statement

I believe that caring for children and adolescents with diabetes is about much more than managing blood glucose levels. My goal is to partner with children and families to develop practical, personalized treatment plans that fit their lives, reduce the burden of diabetes management and help every child thrive. I strive to create an environment where families feel heard, supported and empowered to make informed decisions about their care. I am passionate about helping patients benefit from advances in diabetes technology and emerging therapies that have the potential to improve both health outcomes and quality of life. I believe that excellent diabetes care combines evidence-based medicine, innovation, education and strong relationships built on trust and communication.

As a physician-scientist, I am committed to advancing pediatric diabetes care through clinical research and quality improvement initiatives that bring new discoveries from the research setting into everyday clinical practice. I consider it a remarkable privilege to care for children living with diabetes, and I am committed to supporting them throughout every stage of their journey.

Clinical Interests

Pediatric Diabetes

Education

Organizations

* Texas Children’s Hospital physicians’ licenses and credentials are reviewed prior to practicing at any of our facilities. Sections titled From the Doctor, Professional Organizations and Publications were provided by the physician’s office and were not verified by Texas Children’s Hospital.

Research interests

Diabetes technology, automated insulin delivery systems, disease-modifying therapies for type 1 diabetes, and clinical strategies that improve outcomes and reduce the burden of care for children and adolescents living with diabetes

DeSalvo DJ, Bode B, Forlenza GP, Laffel LM, Buckingham BA, Criego A, Schoelwer M, MacLeish SA, Sherr JL, Hansen D, Ly TT. Glycemic Outcomes Persist for up to 2 Years in Very Young Children with the Omnipod 5 Automated Insulin Delivery System. Diabetes Technology & Therapeutics. 2024 Feb. PMID: 38277156

Crain ER, Ramphul R, Butler AM, Huang X, Minard CG, Redondo MJ, DeSalvo DJ. Social determinants of health impact on diabetes device use and clinical outcomes in youth with type 1 diabetes. Pediatric Diabetes. 2023 Oct

DeSalvo DJ, Noor N, Xie C, Corathers S, Majidi S, McDonough RJ, Polsky S, Izquierdo R, Rioles N, Weinstock R, Obrynba K, Roberts A, Vendrame F, Sanchez F, Ebekozien O. Patient demographics and clinical outcomes among type 1 diabetes patients using continuous glucose monitors: Data from T1D Exchange real-world observational study. Journal of Diabetes Science and Technology. 2023 Mar; 17(2):322-328. PMID: 34632823

DeSalvo DJ, Lanzinger S, Noor N, Steigleder-Schweiger C, Ebekozien O, von Sengbusch K, Jones NHY, Laubner K, Maahs DM, Holl R. Transatlantic Comparison of Pediatric Continuous Glucose Monitoring use in the DPV Initiative and T1D Exchange Quality Improvement Collaborative. Diabetes Technology & Therapeutics. 2022 Dec; 24(12):920-924. PMID: 35947079

Dave D, DeSalvo DJ, Haridas B, McKay S, Shenoy A, Koh CJ, Lawley M, Erraguntla M. Feature-based machine learning model for real-time hypoglycemia prediction. Journal of Diabetes Science and Technology. 2021 Jul; 15(4):842-855. PMID: 32476492

Laffel LM, Kanapka LG, Beck RW, Bergamo K, Clements MA, Criego A, DeSalvo DJ, Goland RS, Hood K, Liljenquist D, Messer LH, Monzavi R, Mouse TJ, Prahalad P, Sherr J, Simmons JH, Wadwa RP, Weinstock RS, Willi SM, Miller KM. Effect of continuous glucose monitoring on glycemic control in adolescents and young adults with type 1 diabetes. JAMA. 2020 Jun 16;323(23):2388-2396. PMID: 32543683

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