Clinical Scorecard: Efficacy of Artificial Intelligence in Forecasting the Transition from Gestational Diabetes to Type 2 Diabetes: A Systematic Review and Meta-Analysis
At a Glance
Category
Detail
Condition
Gestational Diabetes Mellitus (GDM)
Key Mechanisms
Increased risk of developing Type 2 Diabetes Mellitus (T2DM) post-partum due to elevated blood glucose levels.
Target Population
Women with a history of gestational diabetes.
Care Setting
Postpartum care and diabetes prevention programs.
Key Highlights
Women with GDM have a tenfold higher risk of developing T2DM compared to those with normoglycemic pregnancies.
30%-50% of women with previous GDM develop T2DM within 5 to 10 years post-partum.
Annual screening for T2DM is recommended for women with a history of GDM.
Guideline-Based Recommendations
Diagnosis
Structured follow-up and annual T2DM screening for women with GDM.
Management
Targeted prevention programs to reduce future risk of T2DM.
Monitoring & Follow-up
Regular monitoring of blood glucose levels post-partum.
Risks
Poor adherence to postpartum screening guidelines, with compliance as low as 16%-19%.
Patient & Prescribing Data
Women diagnosed with gestational diabetes.
AI tools can stratify risk for future progression to T2DM and prediabetes.
Clinical Best Practices
Utilize AI methods for predictive population risk stratification.
Implement comprehensive patient data analysis for improved prognosis accuracy.
by Alaa Abd-alrazaq, Shahira Padinharepattel Mohamed, Mohannad Alajlani, Aliya Tabassum, José Manuel Ordóñez-Mena, Shehel Yoosuf, Mais Alkhateeb, Arfan Ahmed, Mohammed Bashir, Junaid Qadir, Ali AlSanousi, Javaid Sheikh
