کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
2797750 | 1155664 | 2010 | 6 صفحه PDF | دانلود رایگان |
AimsTo develop a prediction algorithm to rule out diabetic ketoacidosis (DKA) and non-ketotic hyperosmolar syndrome (NKHS) based on vital signs for early triage of patients with diabetes.MethodsThe subjects were consecutive adult diabetic patients with hyperglycemia (blood glucose ≥250 mg/dl) who presented at an emergency department. Based on a derivation sample (n = 392, 70% of 544 patients at a hospital in Okinawa), recursive partitioning analysis was used to develop a tree-based algorithm. Validation was conducted using the other 30% of the patients in Okinawa (n = 152, internal validation) and patients at a hospital in Tokyo (n = 95, external validation).ResultsThree risk groups for DKA/NKHS were identified: a high-risk group of patients with glucose >400 mg/dl or systolic blood pressure <100 mmHg; a low risk group of patients with glucose ≤400 mg/dl and normal vital signs (systolic blood pressure ≥100 mmHg, pulse ≤90/min, and respiratory rate ≤20/min); and an intermediate risk group. The prevalences of DKA/NKHS were 2% (derivation set), 0% (internal validation set), and 0% (external validation set) in the low risk group, respectively.ConclusionsOur algorithm may help DKA/NKHS triage and patients with normal vital signs can be initially triaged as low risk for DKA/NKHS.
Journal: Diabetes Research and Clinical Practice - Volume 87, Issue 3, March 2010, Pages 366–371