Reducing hyperglycaemia post-kidney and liver transplant: a quality improvement initiative

Background: In-hospital glycaemic management can reduce post-transplant morbidity, but is not always part of transplant care.

Objective: We aimed to reduce the mean number of postoperative days in hyperglycaemia (≥2 blood glucose >12 mmol/L in 24 hours) in kidney and liver transplant recipients by 30%. We also aimed to reduce the mean number of days between transplant admission to endocrine consult by 2.0 days.

Design, setting, participants: We conducted a quality improvement project in liver and kidney transplant recipients admitted to an academic transplant unit in Canada between 1 March 2019 and 1 May 2021.

Intervention: We developed a bedside algorithm to monitor post-transplant capillary blood glucose; the algorithm also included thresholds for nursing-initiated inpatient endocrinology consultation.

Main outcome and measures: We examined outcome (postoperative days in hyperglycaemia, days to inpatient endocrine consultation), process (nursing documentation of postoperative blood sugars) and balancing measures (nursing workload, postoperative days in hypoglycaemia) following implementation of our algorithm. We used Plan-Do-See-Act cycles to study three iterations of our algorithm, and used box plots to present outcomes before and after algorithm implementation.

Results: In the pre-intervention period, 21 transplant recipients spent a mean of 4.1 (SD 2.4) postoperative days in hyperglycaemia before endocrine consultation. The mean number of days between hospital admission to endocrine consult was 10.7 (SD 13.0) days.In the post-intervention period, we observed a 62% reduction in postoperative days in hyperglycaemia. The mean number of days between admission and endocrine consult was reduced by 6.3 days (59% reduction).

Conclusions: Implementation of a simple, bedside algorithm for postoperative glucose monitoring and detection of hyperglycaemia in transplant patients, reduced the mean number of postoperative days in hyperglycaemia and time to inpatient endocrine consultation. Our algorithm continues to be used in our academic transplant unit.