The Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) Trial: A Randomized Controlled Trial of Early Intervention With an Electronic Specialist-Led Model of Diabetes Care

Category Primary study
JournalDiabetes Care
Year 2024
OBJECTIVE To investigate the effect of early intervention with an electronic specialist-led “proactive” model of care on glycemic and clinical outcomes. RESEARCH DESIGN AND METHODS The Specialist Treatment of Inpatients: Caring for Diabetes in Surgery (STOIC-D Surgery) randomized controlled trial was performed at the Royal Melbourne Hospital. Eligible participants were adults admitted to a surgical ward during the study with either known diabetes or newly detected hyperglycemia (at least one random blood glucose result $11.1 mmol/L). Participants were randomized 1:1 to standard diabetes care or the inter- vention consisting of an early consult by a specialist inpatient diabetes team using elec- tronic tools for patient identification, communication of recommendations, and therapy intensification. The primary outcome was median patient-day mean glucose (PDMG). The key secondary outcome was incidence of health care-associated infection (HAI). RESULTS Between 12 February 2021 and 17 December 2021, 1,371 admissions met inclusion cri- teria, with 680 assigned to early intervention and 691 to standard diabetes care. Base- line characteristics were similar between groups. The early intervention group achieved a lower median PDMG of 8.2 mmol/L (interquartile range [IQR] 6.9-10.0 mmol/L) com- pared with 8.6 mmol/L (IQR 7.2-10.3 mmol/L) in the control group for an estimated dif- ference of 20.3 mmol/L (95% CI 20.4 to 20.2 mmol/L, P < 0.0001). The incidence of HAI was lower in the intervention group (77 [11%] vs. 110 [16%]), for an absolute risk difference of 24.6% (95% CI 28.2 to 21.0, P = 0.016). CONCLUSIONS In surgical inpatients, early diabetes management intervention with an electronic specialist-led diabetes model of care reduces glucose and HAI.
Epistemonikos ID: daebd2df50d65956921a7e13f0780c2fc537a742
First added on: Jan 19, 2024