Predictors of Metformin Failure: Repurposing Electronic Health Record Data to Identify High-Risk Patients.

Suzette J Bielinski Licy L Yanes Cardozo Paul Y Takahashi Nicholas B LarsonAlexandra CastilloAlana PodwikaEleanna De FilippisValentina HernandezGouri J MahajanCrystal Gonzaleznull ShubhangiPaul A Decker Jill M Killian Janet E Olson Jennifer L St SauverPankaj ShahAdrian Vella Euijung Ryu Hongfang LiuGailen D MarshallJames R CerhanDavinder SinghRichard L Summers

Published in: The Journal of clinical endocrinology and metabolism (2023)

Baseline hemoglobin A1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.

Keyphrases

electronic health record
clinical decision support
end stage renal disease
newly diagnosed
ejection fraction
chronic kidney disease
adverse drug
big data
prognostic factors
patient reported outcomes
artificial intelligence
patient reported