Prospects and development of intelligent monitoring technology in blood glucose management of acute pancreatitis
智能监测技术在急性胰腺炎血糖管理中的前景与发展

摘要

目的 探究智能动态血糖监测技术在急性胰腺炎（AP）患者血糖管理中的应用效果。方法 选取2023年3月至2025年3月收治的32例AP患者，按随机数字表法分为对照组与实验组各16例。对照组采用传统指尖血糖监测（POCT）联合常规护理，实验组采用硅基智能动态血糖监测系统（CGMS）联合精细化护理，对比两组血糖控制指标、临床康复指标及并发症发生率。结果 实验组平均血糖（MBG）、血糖变异系数（CV）显著低于对照组，血糖达标时间（TIR）占比显著高于对照组（P＜0.05）；实验组住院时间、肠功能恢复时间短于对照组，感染发生率低于对照组，差异均有统计学意义（P＜0.05）。结论 智能监测技术可提升AP患者血糖管控精准度，加速临床康复，降低并发症风险，具备良好临床应用前景，为AP血糖管理智能化、个体化发展提供支撑。

Abstract

Objective To investigate the application effect of intelligent dynamic blood glucose monitoring technology in blood glucose management of patients with acute pancreatitis(AP).
Methods A total of 32 AP patients admitted from March 2023 to March 2025 were selected and randomly divided into a control group and an experimental group (16 cases each) using a random number table. The control group received traditional point-of-care blood glucose monitoring (POCT) combined with routine nursing, while the experimental group was treated with a silicon-based intelligent dynamic blood glucose monitoring system (CGMS) combined with refined nursing. The blood glucose control indicators, clinical recovery indicators, and complication incidence rates were compared between the two groups.
Results The mean blood glucose (MBG) and blood glucose coefficient of variation (CV) in the experimental group were significantly lower than those in the control group, and the proportion of time to achieve glycemic targets (TIR) was significantly higher (P<0.05). The experimental group also exhibited shorter hospitalization duration, faster recovery of intestinal function, and lower infection incidence compared to the control group, with all differences being statistically significant (P<0.05).
Conclusion   Intelligent monitoring technology can improve the precision of blood glucose management in AP patients, accelerate clinical recovery, reduce the risk of complications, and has promising clinical application prospects. It provides support for the intelligent and individualized development of blood glucose management in AP.