持续葡萄糖监测中数据丢失对临床决策的影响：回顾性队列研究

Consequences of Data Loss on Clinical Decision-Making in Continuous Glucose Monitoring: Retrospective Cohort Study.

作者信息

den Braber Niala, Braem Carlijn I R, Vollenbroek-Hutten Miriam M R, Hermens Hermie J, Urgert Thomas, Yavuz Utku S, Veltink Peter H, Laverman Gozewijn D

机构信息

Biomedical Signal and Systems, Faculty of Electrical Engineering, Mathematics And Computer Science, University of Twente, Enschede, Netherlands.

Internal Medicine, Ziekenhuisgroep Twente, Almelo, Netherlands.

出版信息

Interact J Med Res. 2024 Jul 31;13:e50849. doi: 10.2196/50849.

DOI:10.2196/50849

PMID:39083801

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11325125/

Abstract

BACKGROUND

The impact of missing data on individual continuous glucose monitoring (CGM) data is unknown but can influence clinical decision-making for patients.

OBJECTIVE

We aimed to investigate the consequences of data loss on glucose metrics in individual patient recordings from continuous glucose monitors and assess its implications on clinical decision-making.

METHODS

The CGM data were collected from patients with type 1 and 2 diabetes using the FreeStyle Libre sensor (Abbott Diabetes Care). We selected 7-28 days of 24 hours of continuous data without any missing values from each individual patient. To mimic real-world data loss, missing data ranging from 5% to 50% were introduced into the data set. From this modified data set, clinical metrics including time below range (TBR), TBR level 2 (TBR2), and other common glucose metrics were calculated in the data sets with and that without data loss. Recordings in which glucose metrics deviated relevantly due to data loss, as determined by clinical experts, were defined as expert panel boundary error (ε). These errors were expressed as a percentage of the total number of recordings. The errors for the recordings with glucose management indicator <53 mmol/mol were investigated.

RESULTS

A total of 84 patients contributed to 798 recordings over 28 days. With 5%-50% data loss for 7-28 days recordings, the ε varied from 0 out of 798 (0.0%) to 147 out of 736 (20.0%) for TBR and 0 out of 612 (0.0%) to 22 out of 408 (5.4%) recordings for TBR2. In the case of 14-day recordings, TBR and TBR2 episodes completely disappeared due to 30% data loss in 2 out of 786 (0.3%) and 32 out of 522 (6.1%) of the cases, respectively. However, the initial values of the disappeared TBR and TBR2 were relatively small (<0.1%). In the recordings with glucose management indicator <53 mmol/mol the ε was 9.6% for 14 days with 30% data loss.

CONCLUSIONS

With a maximum of 30% data loss in 14-day CGM recordings, there is minimal impact of missing data on the clinical interpretation of various glucose metrics.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05584293; https://clinicaltrials.gov/study/NCT05584293.

摘要

背景

缺失数据对个体连续血糖监测（CGM）数据的影响尚不清楚，但可能会影响患者的临床决策。

目的

我们旨在研究连续血糖监测仪记录的个体患者数据中数据丢失对血糖指标的影响，并评估其对临床决策的影响。

方法

使用FreeStyle Libre传感器（雅培糖尿病护理公司）收集1型和2型糖尿病患者的CGM数据。我们从每个个体患者中选择7至28天的24小时连续数据，且无任何缺失值。为模拟实际数据丢失情况，将5%至50%的缺失数据引入数据集中。从这个修改后的数据集中，计算有数据丢失和无数据丢失的数据集中的临床指标，包括低于范围时间（TBR）、二级低于范围时间（TBR2）以及其他常见血糖指标。临床专家确定因数据丢失导致血糖指标有显著偏差的记录被定义为专家小组边界误差（ε）。这些误差以记录总数的百分比表示。对血糖管理指标<53 mmol/mol的记录中的误差进行了研究。

结果

共有84名患者在28天内贡献了798条记录。对于7至28天的记录，数据丢失5%至50%时，TBR的ε从798条记录中的0条（0.0%）到736条记录中的147条（20.0%）不等，TBR2的ε从612条记录中的0条（0.0%）到408条记录中的22条（5.4%）不等。在14天记录的情况下，由于786例中有2例（0.3%）和522例中有32例（6.1%）分别出现30%的数据丢失，TBR和TBR2事件完全消失。然而，消失的TBR和TBR2的初始值相对较小（<0.1%）。在血糖管理指标<53 mmol/mol的记录中，14天内数据丢失30%时的ε为9.6%。