Chrome Extension
WeChat Mini Program
Use on ChatGLM

Quality gaps in screening and monitoring for postoperative hyperglycemia in a Canadian hospital: a retrospective cohort study

BMJ open diabetes research & care(2021)

Cited 2|Views1
No score
Abstract
Introduction Evidence-based preoperative, intraoperative and postoperative glycemic management may reduce poor surgical outcomes. Previous studies suggest that quality gaps in perioperative glycemic management may be common. Research design and methods This retrospective cohort study used administrative health and laboratory data from a single center to estimate quality gaps in perioperative glycemic management in patients with and without diabetes between April 2019 and March 2020. We examined the proportion of patients with preoperative hemoglobin A1c (HbA1c) measurement, postoperative point-of-care testing (POCT) for glucose, hyperglycemia, and basal bolus insulin regimens. We compared the median length of stay (LOS) in patients with and without postoperative hyperglycemia, adjusted for age and sex. Results There were 6576 patients in our cohort; 1165 (17.8%) had diabetes. Most patients with diabetes had an HbA1c measured prior to surgery (n=697, 59.8%). Postoperatively, 16.9% of patients with diabetes had no POCT monitoring (n=197) and 65.7% had hyperglycemia (n=636). Only 35.9% of patients who received insulin had a basal bolus insulin regimen (n=229). Patients with diabetes who had postoperative hyperglycemia had a longer median LOS compared with those who did not have postoperative hyperglycemia (8.4 days (95% CI 7.5 to 9.4) and 6.7 days (95% CI 6.3 to 7.1), respectively). In patients without diabetes, median LOS was 7.4 days (95% CI 4.4 to 10.4) for those with hyperglycemia and 5.2 days (95% CI 5.1 to 5.4) for those with in-target glucose. Conclusions Quality gaps in perioperative glycemic management include measurement of blood glucose after surgery and treatment of postoperative hyperglycemia. These gaps may contribute to longer LOS.
More
Translated text
Key words
quality improvement,general surgery,hospitalization
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined