Prediction of Persistent Impaired Glucose Tolerance in Patients with Minor Ischemic Stroke or Transient Ischemic Attack

• Published in: Journal of stroke and cerebrovascular diseases Vol. 29; no. 6; p. 104815
• Main Authors: Osei, Elizabeth, den Hertog, Heleen M., Fonville, Susanne, Brouwers, Paul J.A.M., Mulder, Laus J.M.M., Koudstaal, Peter J., Dippel, Diederik W.J., Zandbergen, Adrienne A.M., Lingsma, Hester F.
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01-06-2020
• Subjects: Glucose; prediabetes; prediction; stroke; TIA; treatment; prediction; treatment; Glucose; stroke; TIA; prediabetes
• ISSN: 1052-3057; 1532-8511
• DOI: 10.1016/j.jstrokecerebrovasdis.2020.104815

Background: Impaired glucose tolerance (IGT) in patients with ischemic stroke can return to normal, reflecting an acute stress response, or persist. Persistent IGT is associated with an increased risk of recurrent stroke, other cardiovascular diseases and unfavorable outcome after stroke. We aim to validate our previously developed model to identify patients at risk of persistent IGT in an independent data set, and, if necessary, update the model. Methods: The validation data set consisted of 239 nondiabetic patients with a minor ischemic stroke or TIA and IGT in the acute phase (2-hour post-load glucose levels between 7.8 and 11.0 mmol/l). The outcome was persistent versus normalized IGT, based on repeated oral glucose tolerance test after a median of 46 days. The discriminative ability of the original model was assessed with the area under the ROC curve (AUC). The updated model was internally validated with bootstrap resampling and cross-validated in the development population of the original model. Results: One-hundred eighteen of 239 (49%) patients had persistent IGT. The original model, with the predictors age, current smoking, statin use, triglyceride, hypertension, history of cardiovascular diseases, body mass index (BMI), fasting plasma glucose performed poorly (AUC .60). The newly developed model included only BMI, hypertension, statin use, atrial fibrillation, 2-hour post-load glucose levels, HbA1c, large artery atherosclerosis, and predicted persistent IGT more accurately (internally validated AUC 0.66, externally validated AUC .71). Conclusions: This prediction model with simple clinical variables can be used to predict persistent IGT in patients with IGT directly after minor stroke or TIA, and may be useful to optimize secondary prevention by early identification of patients with disturbed glucose metabolism.