Automated glucose control systems in post-pancreatectomy diabetes: systematic review of clinical efficacy and nursing care implications.

INTRODUCTION

Post-pancreatectomy diabetes (type 3c diabetes) is a frequent consequence of pancreatic cancer surgery and is characterized by extreme glycemic variability, high risk of severe hypoglycemia, and a substantial impact on quality of life and nursing workload. Technological solutions such as continuous glucose monitoring (CGM) and closed-loop insulin delivery may help address these challenges.

EVIDENCE ACQUISITION: We conducted a systematic review according to the Cochrane Handbook 6.5 and PRISMA 2020 guidelines, with prospective registration on PROSPERO (CRD420251117523). PubMed, Embase, CINAHL, Scopus, and the Cochrane Library were searched from 2006 to October 2025 for primary studies evaluating automated or semi-automated glucose control systems in adults with diabetes secondary to pancreatic resection for malignancy. Risk of bias was assessed with RoB 2.0 and ROBINS-I; certainty of evidence was rated using the GRADE approach.

EVIDENCE SYNTHESIS: Four studies (three randomized trials and one prospective time-motion simulation; N.=66) met the inclusion criteria. Fully closed-loop systems increased time in range to 77.7±4.6% versus 41.1±19.5% with standard care and virtually eliminated severe hypoglycemia. A bihormonal artificial pancreas increased euglycemia from 54% to 78% and reduced time below range to 0%. A hybrid closed-loop system maintained improved glycemic control over long-term follow-up, while a simulation study estimated a 67% reduction in nursing workload for major surgery. Overall certainty of evidence ranged from very low for continuous metrics (TIR, TBR) to moderate for prevention of severe hypoglycemia.

CONCLUSIONS

Automated glucose control systems improve peri- and postoperative glycemic stability in post-pancreatectomy diabetes and may substantially reduce nursing workload. Structured training, institutional protocols, and multicenter studies with larger samples and longer follow-up are needed to confirm clinical effectiveness, cost-efficiency, and implementation strategies.