Automated Self-Adjusting Subcutaneous Insulin Algorithm for Patients NPO or on TPN or Enteral Feedings.

BACKGROUND: Perioperative diabetes patients are often treated with sliding-scale insulin, despite a lack of evidence to support therapeutic effectiveness. We introduced an automated subcutaneous insulin algorithm (SQIA) to improve glycemic control in these patients while maintaining the simplicity of a q4 hour adjustable sliding-scale insulin order set. METHODS: In this pilot study, we implemented a fully programmed, self-adjusting SQIA as part of a structured order set in the electronic medical record for adult patients who are nil per os, or on continuous enteral tube feedings or total parenteral nutrition. The nurse only enters the current glucose in the Medication Administration Record, and then the calculated dose is shown. The new dose is based on previous dose, and current and previous glucoses. The SQIA titrates the glucose to 120-180 mg/dL. For this pilot, this order set was utilized for complex perioperative oncologic patients. RESULTS: The median duration on the SQIA was 58 hours. Glucoses at titration initiation were highest at 206 ± 63 mg/dL, and came down to 156 ± 29 mg/dL by 72 hours. The majority of measured glucoses (66.8%, n = 647) were maintained between 80 and 180 mg/dL. There were no glucoses lower than 60 mg/dL, and only 0.3% (n = 3) were below 70 mg/dL. There was a low rate of errors (1%). CONCLUSIONS: A simple automated SQIA can be used to titrate insulin to meet the changing metabolic requirements of individuals perioperatively and maintain glucose within the target range for these hospitalized patients.

Facile synthesis of tin oxide nanoparticles stabilized by dendritic polymers.

Tin(IV) oxide nanoparticles were synthesized via the reaction of carbon dioxide with stannate ions immobilized by dendritic polymers. For PAMAM and PPI dendrimer hosts, resultant nanoparticle diameters were 2.5-3 nm; 3-3.5 nm nanoparticles resulted from use of a poly(ethyleneimine) hyperbranched polymer. Our conditions represent the only precedent for SnO2 nanoparticulate growth using dendritic architectures, as well as a novel application for CO2 as a reactive gas for the controlled growth of metal oxide nanoparticles.