Suppr超能文献

自动血糖钳夹算法的改进

Improved Algorithm for Automated Glucose Clamps.

机构信息

Profil, Neuss, Germany .

出版信息

Diabetes Technol Ther. 2017 Feb;19(2):124-130. doi: 10.1089/dia.2016.0355. Epub 2016 Dec 22.

Abstract

BACKGROUND

In glucose clamp experiments, blood glucose concentrations (BGs) are kept as close as possible to a predefined target level using variable glucose infusion rates (GIRs). In automated clamps, GIRs are calculated by algorithms implemented in the device (e.g., the Biostator). Low BG- and GIR-variability is needed for high clamp quality. We therefore tried to reduce oscillations in both BG and GIR with an improved algorithm implemented in ClampArt, a modern clamp device.

SUBJECTS AND METHODS

The Biostator algorithm was first improved by numerical simulations of glucose clamps (in silico). With the results of the simulations, we started in vitro experiments using the ClampArt device and a container with water and glucose as "test subject." After a small pilot in vivo study, a larger clinical study was performed to compare the original with the optimized algorithm.

RESULTS

With the improved algorithm, in silico, in vitro, and in vivo experiments showed reduced oscillations in both BG and GIR. In the clinical study, the coefficient of variation (CV) of BG values was lowered from 6.0% (4.6%-7.8%) [median (interquartile range)] to 4.2% (3.6%-5.0%), P < 0.0001 and the CV of GIR from 60.7% (49.6%-82.0%) to 43.5% (32.8%-57.2%), P < 0.0001. Other clamp quality parameters did not change substantially, median deviation from target slightly increased from 0.6% (0.2%-1.0%) to 1.1% (0.7%-1.5%), P = 0.0005, whereas utility did not change [97.0% (93.4%-100.0%) vs. 97.0% (94.0%-98.8%), P = 0.57].

CONCLUSIONS

With the improved algorithm, all experiments confirmed a reduction in BG- and GIR-oscillations without a major impact on other glucose clamp parameters. The optimized algorithm has been implemented in ClampArt for all future glucose clamp studies.

摘要

背景

在葡萄糖钳夹实验中,通过使用可变的葡萄糖输注率(GIR),使血糖浓度(BG)尽可能接近预定的目标水平。在自动钳夹中,GIR 是由设备中实现的算法(例如 Biostator)计算得出的。为了获得高质量的钳夹,需要低的 BG 和 GIR 变异性。因此,我们尝试使用一种新的算法(ClampArt)来减少 BG 和 GIR 的波动。

研究对象和方法

首先,通过葡萄糖钳夹的数值模拟(in silico)来改进 Biostator 算法。根据模拟结果,我们使用 ClampArt 设备和一个装有水和葡萄糖的容器作为“测试对象”开始进行体外实验。在进行了一项小型的体内初步研究之后,我们进行了一项更大的临床研究,以比较原始算法和优化算法。

结果

通过改进算法,in silico、in vitro 和 in vivo 实验都显示出 BG 和 GIR 的波动减少。在临床研究中,BG 值的变异系数(CV)从 6.0%(4.6%-7.8%)[中位数(四分位距)]降低到 4.2%(3.6%-5.0%),P<0.0001,GIR 的 CV 从 60.7%(49.6%-82.0%)降低到 43.5%(32.8%-57.2%),P<0.0001。其他钳夹质量参数没有显著变化,目标偏差的中位数从 0.6%(0.2%-1.0%)略微增加到 1.1%(0.7%-1.5%),P=0.0005,而实用性没有改变[97.0%(93.4%-100.0%)vs. 97.0%(94.0%-98.8%),P=0.57]。

结论

通过改进算法,所有实验都证实了 BG 和 GIR 波动的减少,而对其他葡萄糖钳夹参数没有重大影响。优化后的算法已在 ClampArt 中用于所有未来的葡萄糖钳夹研究。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验