Research Appraisals
Evidence-based critical appraisals of the latest medical research, systematically evaluated using Oxford CEBM methodology.
Showing 5 appraisals
Current opinion in pediatrics
Artificial intelligence in pediatric endocrinology: clinical applications, governance, and future directions.
PURPOSE OF REVIEW: Artificial intelligence has transitioned from theoretical promise to practical implementation across medicine including pediatric endocrinology. This review examines artificial intelligence applications across diabetes care, obesity management, thyroid disorders, growth and puberty, and bone age assessment followed by discussion of limitations and future directions. RECENT FINDINGS: Artificial intelligence-driven tools ranging from machine learning algorithms to multimodal large language models enable personalized risk prediction, diagnostic support, and treatment optimization. Human-in-the-Loop frameworks enhance safety by integrating computational efficiency with clinician oversight. In diabetes, artificial intelligence supports glycemic forecasting, automated insulin delivery, complication screening, and digital twin modeling for therapeutic discovery. In obesity, thyroid disease, growth disorders, and bone age assessment, artificial intelligence enhances diagnostic accuracy, risk stratification, and clinical workflow efficiency. However, widespread implementation raises concerns regarding algorithmic bias, data privacy, transparency, regulatory oversight, and health equity. Addressing these limitations through explainable artificial intelligence, federated learning, and continuous performance monitoring is essential. SUMMARY: Artificial intelligence should be viewed as an augmentative tool that enhances clinical judgment in pediatric endocrinology. Preparing the next generation of pediatric endocrinologists will require intentional integration of artificial intelligence literacy into training programs, equipping clinicians to critically evaluate algorithms, interpret outputs responsibly, and participate in the ethical development of future artificial intelligence-enabled tools.
2 Aug 2026
Read appraisal →The Journal of clinical endocrinology and metabolism
Diazoxide Choline Extended-release Tablets in Prader-Willi Syndrome: A Randomized, Double-blind, Withdrawal Period Study
CONTEXT: The hallmark condition of Prader-Willi syndrome, a rare, genetic neurobehavioral/metabolic disorder, is life-threatening hyperphagia. OBJECTIVE: We assessed the efficacy and safety of diazoxide choline extended-release (DCCR) tablets for the treatment of hyperphagia in adults and children four years of age and older with Prader-Willi syndrome. METHODS: We conducted a 16-week, randomized withdrawal study in children and adults with Prader-Willi syndrome and hyperphagia. Participants who previously completed randomized (13-week DCCR or placebo) and open-label (2.5-4.5 years DCCR) studies were randomized 1:1 to receive once-daily DCCR or placebo. The primary endpoint was Hyperphagia Questionnaire for Clinical Trials (HQ-CT) total score change from baseline to 16 weeks. Secondary endpoints included Clinical Global Impression of Severity (CGI-S) and Improvement (CGI-I); exploratory endpoints included weight and body mass index (BMI) z-score. RESULTS: Seventy-seven participants were randomized (DCCR:38; placebo:39). Statistically significant increases in HQ-CT from baseline to week 16 were observed with placebo vs DCCR [least square (LS) mean (standard error) change 7.6 (1.09)] with placebo and 2.6 (1.12) with DCCR; P = .0022. CGI scores favored DCCR but were not significantly changed. Consistent with the hyperphagia response, the placebo cohort gained more weight and increased their BMI z-score more than the DCCR cohort [LS mean weight difference (95% confidence interval) -1.6 kg (-3.1, -0.1)]; LS mean z-score difference was -0.09 (-0.17, -0.01). Adverse events were similar with both treatments, with no serious adverse events in the DCCR arm. CONCLUSION: Continued DCCR treatment was superior to placebo for hyperphagia. DCCR appears to offer meaningful therapeutic benefits for people with Prader-Willi syndrome.
19 May 2026
Read appraisal →JMIR research protocols
Evaluating Patient-Entered Electronic Health Data as a Strategy to Improve Quality of Care in a Diabetes Clinic: Protocol for a Randomized Controlled Trial
BACKGROUND: Quality care for pediatric type 1 diabetes (T1D) requires frequent, multidisciplinary visits. Technological and clinical innovation have led to changes in T1D management, resulting in increasing data exchange required during these visits. Capturing comprehensive personal health and diabetes-related information discretely and integrating it into the clinical workflow is critical for optimal T1D care but is time-consuming. Time spent on data transfer often results in less time for holistic care and can lead to unmet needs for patients, families, and health care providers, as well as increased time pressures in clinic. To address this, the Children's Hospital of Eastern Ontario developed a caregiver proxy-reported questionnaire distributed via the MyChart patient portal, allowing families to input care information ahead of visits with the aim of dedicating more clinic time to personalized care. The launch of this tool, which integrates caregiver-entered information into the physician's documentation workflow, brings the opportunity to systematically evaluate its impact on care quality and efficiency, with potential implications for broader adoption. OBJECTIVE: Our objective is to evaluate the impact of a caregiver proxy-reported, electronic health record-integrated preclinic questionnaire (MyChart questionnaire) on the quality of care in a pediatric diabetes clinic, through measurement of its impact on caregiver-perceived quality of care compared to the standard of care using 2 validated measures of care quality. We also aim to explore the impact of the intervention on glycemic control and visit efficiency. METHODS: We conducted a single-center, parallel-group randomized controlled trial designed for 222 children with T1D. Participants were randomly allocated in a 1:1 ratio to either the intervention (MyChart questionnaire) or standard care. Our primary outcome is caregiver-perceived quality of care, as measured by the Patient's Evaluation of the Quality of Diabetes Care at 8 months, administered with caregivers serving as proxy respondents for patients. Secondary outcomes are the Patient's Evaluation of the Quality of Diabetes Care at 4 months and Perceived Quality of Medical Care at 4 and 8 months. Tertiary outcomes include glycemic control and physician-reported visit efficiency at 4 and 8 months. Analysis of covariance models will be used to assess changes between baseline and postintervention outcomes across treatment groups. RESULTS: Recruitment for this study began in April 2023 and was completed in February 2024, with a total of 139 participants enrolled. Data collection has concluded, and the first results are expected in the spring of 2026. CONCLUSIONS: This study is the first randomized trial to assess the impact of a caregiver proxy-reported, electronic health record-integrated, preclinic questionnaire distributed via a patient portal on caregiver-perceived quality of care in a pediatric care setting. The results will guide changes in health service infrastructure and delivery to enhance comprehensive data capture and improve care quality within and beyond pediatric T1D.
13 May 2026
Read appraisal →The Journal of clinical endocrinology and metabolism
Effect of Vosoritide Therapy on IGF-I and Endogenous C-Type Natriuretic Peptide in Hypochondroplasia
CONTEXT: Insulin-like growth factor-1 (IGF-1) and C-type natriuretic peptide (CNP) promote endochondral bone growth. We previously reported that vosoritide, a CNP analogue, increases annualized growth velocity (AGV) and height SD in prepubertal children with hypochondroplasia (HCH). OBJECTIVE: We hypothesized that IGF-1 and CNP will be inversely associated at baseline and will respond differentially during a single-arm, unblinded, standardized 12-month phase 2 clinical trial of vosoritide in prepubertal patients aged 3 to 11 years with HCH and height less than -2.25 SD. Participants were followed for a baseline 6-month observation period and then received a dose of 15 μg/kg/day of vosoritide subcutaneous daily injections for 12 months. Anthropometrics, IGF-1, and NTproCNP were measured every 6 months. Longitudinal changes in IGF-1 and NTproCNP as well as the correlations between these 2 analytes and changes in height SD and AGV were analyzed. RESULTS: Baseline IGF-1 values are reduced in children with HCH and increased throughout the study, but IGF-1 SD did not change significantly. NTproCNP was raised at baseline and declined throughout the study, with NTproCNP SD significantly lower at months 6 and 12 on treatment. Change in height SD or AGV were not correlated to IGF-1 or NTproCNP SD at 12 months. The change in IGF-1 concentrations at 12 months was positively correlated with the change in NTproCNP plasma concentrations (ρ = 0.57; P = .024). CONCLUSION: In children with HCH, IGF-1 levels are reduced and NTproCNP levels are elevated at baseline. A correlation between changes in these levels during treatment suggests a possible interaction between IGF-1 and CNP signaling.
24 Apr 2026
Read appraisal →Journal of medical Internet research
Artificial Intelligence, Connected Care, and Enabling Digital Health Technologies in Rare Diseases With a Focus on Lysosomal Storage Disorders: Scoping Review
BACKGROUND: Rare diseases affect more than 300 million people globally, and only about 5% have approved therapies. Lysosomal storage disorders (LSDs) exemplify the diagnostic and long-term care complexity typical of rare diseases, and digital health technologies (DHTs), especially artificial intelligence (AI) and connected care (CC), are emerging tools to support LSD management. OBJECTIVE: We aimed to map and synthesize peer-reviewed and gray literature from the past decade on DHTs relevant for LSD care, with a primary analytic focus on AI-enabled and CC solutions and a contextual mapping of other enabling DHTs. Evidence distribution was charted by population, care-journey phase, and outcome domains to identify gaps, methodological limitations, and timely priorities relevant for research, clinical practice implementation, and policies. METHODS: We conducted a scoping review guided by a population, concept, context framework and operationalized through a Population, Intervention, Comparison, and Outcome (PICO)-informed data-charting structure to map study characteristics and reported outcomes, without causal or effectiveness assumptions and without risk-of-bias assessment. We searched PubMed, Google Scholar, and ClinicalTrials.gov for studies published between October 2015 and September 2024, complemented by AI-assisted discovery tools for citation extension. Reproducibility logs (search strings, run dates, filters, and stepwise counts) were maintained. Of 1751 records retrieved, 245 were included. Evidence was charted by LSD population, intervention class (AI, CC, and other enabling DHTs), outcome domains (patient, health care, and societal), and phase of the care journey. RESULTS: Among 245 included records, 92.2% (226/245) were peer-reviewed, and 7.8% (19/245) were gray literature; no completed and published randomized controlled trials or LSD-specific systematic reviews were identified, with evidence dominated by small, single-center observational studies. Overall, 40 peer-reviewed records reported AI-driven DHTs, 89 reported CC DHTs, and 144 reported other enabling DHTs (some multilabeled). Evidence was concentrated mostly in Gaucher and Fabry diseases. Nearly half of the mapped literature focused on screening and diagnosis, with fewer records addressing treatment intensification, rehabilitation, and end-of-life care. Outcomes were predominantly health care delivery performance measures, with fewer patient and societal outcomes. AI applications mainly supported diagnostic decision support, phenotyping, monitoring, tracking, and risk stratification; CC commonly involved telemedicine, remote monitoring, and patient-engagement platforms; enabling DHTs included interoperable data systems, registries, and digital infrastructures. CONCLUSIONS: The evidence base is appreciable for a niche field and reflects growing interest in AI and CC for LSD care, but heterogeneity and methodological limitations preclude inferences on effectiveness or routine implementation. This evidence map highlights relatively stronger areas and gaps, providing a structured foundation to inform timely expert consensus-building and research prioritization. Key priorities include interoperable data infrastructures and data availability, prospective multicenter evaluations, transparent reporting of algorithms and workflows, and implementation-relevant outcomes to support safe, equitable, and scalable adoption aligned with evolving European Union and global rare-disease priorities.
4 Apr 2026
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