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Clinical Trial Summary

This study will create a new model to predict hypoglycemic events in diabetic inpatients on anti-hyperglycemic therapy using retrospective data with the goal of developing a model that will accurately predict hypoglycemic episodes in the patient population - piloting the risk score that was developed in the context of EndoTool being rolled out at the institution, to determine the feasibility and acceptability of viewing the risk score in the Electronic Health Record


Clinical Trial Description

Design a model to predict hypoglycemic episodes in real time, rather than retrospectively identifying high risk patients who experienced a hypoglycemic event at some point during their hospitalization, as has been done prior. Potential predictors of hypoglycemia identified in prior work and additional predictors identified by the clinical team to develop a discrete-time multinomial logistic regression model to predict hypoglycemic events in real time. The risk score then will be piloted in the context of our institution's EndoTool Subcutaneous implementation determine the feasibility and acceptability of viewing the risk score in the Electronic Health Record ;


Study Design


NCT number NCT05989256
Study type Interventional
Source Wake Forest University Health Sciences
Contact Sarah Stern
Phone 407.913.7232
Email srstern@wakehealth.edu
Status Not yet recruiting
Phase N/A
Start date October 2024
Completion date January 2025