Tight glycemic control (TGC) has shown benefits in ICU patients, but been difficult to achieve consistently due to inter- and intra- patient variability that requires more adaptive, patient-specific solutions. STAR (Stochastic TARgeted) is a flexible model-based TGC framework accounting for patient variability with a stochastically derived maximum 5% risk of blood glucose (BG) below 72mg/dL. This research describes the first clinical pilot trial of the STAR approach and the post-trial analysis of the models and methods that underpin the protocol.

The STAR framework works with clinically specified targets and intervention guidelines. The clinically specified glycemic target was 125mg/dL. Each trial was 24h with BG measured 1–2hourly. Two-hourly measurement was used when BG was between 110–135mg/dL for 3h. In the STAR approach, each intervention leads to a predicted BG level and outcome range (5–95th percentile) based on a stochastic model of metabolic patient variability. Carbohydrate intake (all sources) was monitored, but not changed from clinical settings except to prevent BG<100mg/dL when no insulin was given. Insulin infusion rates were limited (6U/h maximum), with limited increases based on current infusion rate (0.5–2.0U/h), making this use of the STAR framework an insulin-only TGC approach. Approval was granted by the Ethics Committee of the Medical Faculty of the University of Liege (Liege, Belgium).

Nine patient trials were undertaken after obtaining informed consent. There were 205 measurements over all 9 trials. Median [IQR] per-patient results were: BG: 138.5 [130.6–146.0]mg/dL; carbohydrate administered: 2–11g/h; median insulin:1.3 [0.9–2.4]U/h with a maximum of 6.0 [4.7–6.0]U/h. Median [IQR] time in the desired 110–140mg/dL band was: 50.0 [31.2–54.2]%. Median model prediction errors ranged: 10–18%, with larger errors due to small meals and other clinical events. The minimum BG was 63mg/dL and no other measurement was below 72mg/dL, so only 1 measurement (0.5%) was below the 5% guaranteed minimum risk level.

Post-trial analysis showed that patients were more variable than predicted by the stochastic model used for control, resulting in some of the prediction errors seen. Analysis and (validated) virtual trial re-simulating the clinical trial using stochastic models relevant to the patient's particular day of ICU stay were seen to be more accurate in capturing the observed variability. This analysis indicated that equivalent control and safety could be obtained with similar or lower glycemic variability in control using more specific stochastic models.

STAR effectively controlled all patients to target. Observed patient variability in response to insulin and thus prediction errors were higher than expected, likely due to the recent insult of cardiac surgery or a major cardiac event, and their immediate recovery. STAR effectively managed this variability with no hypoglycemia. Improved stochastic models will be used to prospectively test these outcomes in further ongoing clinical pilot trials in this and other units.