Department of Internal Medicine, Section on Endocrinology, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Department of Endocrinology & Diabetes, Boulder Medical Center, Boulder, CO, USA.
J Diabetes Sci Technol. 2023 Mar;17(2):329-335. doi: 10.1177/19322968211062168. Epub 2021 Dec 15.
Optimal inpatient glycemic management targets a blood glucose (BG) of 140-180 mg/dL and is an important safety measure for hospitalized patients with hyperglycemia. Traditional barriers to appropriate insulin administration include incorrect timing of prandial insulin administration, failure to administer basal insulin to persons with insulin deficiency/type 1 diabetes mellitus (DM), and inaccurate insulin dosing or timing resulting in hypoglycemia. Given the ongoing rapid assimilation of technology to manage our patients with DM, we investigated the use of continuous glucose monitoring (CGM) in the inpatient setting as a potential solution to traditional barriers to optimal hyperglycemia management for inpatient care. In this study, we evaluated the efficacy of use of inpatient CGM for insulin dosing in comparison with current standard of care and whether CGM could aid in minimizing hypoglycemic events.
This study evaluated the use of Abbott professional (blinded) Freestyle Libre CGMs in participants treated with basal bolus insulin administered with subcutaneous insulin (basal bolus therapy [BBT]: n = 20) or on intravenous insulin (IVI) infusions (n =16) compared with standard point of care (POC) BG measurements. All participants on IVI were admitted with a diagnosis of diabetic ketoacidosis (DKA). The CGM data was not available in real time. Sensors were removed at the time of discharge and data uploaded to Libre View. Continuous BG data were aggregated for each subject and matched to POC BG or lab chemistry values within five minutes. The POC BG results were assessed for comparability (CGM vs standard BG testing). Data were further analyzed for clinical decision-making for correction insulin.
The overall mean absolute relative difference including both IVI and BBT groups was 22.3% (SD, 9.0), with a median of 20.0%. By group, the IVI arm mean was 19.6% (SD, 9.4), with a median of 16.0%; for BBT, the arm mean was 24.6% (SD, 8.1), with a median 23.4%. Using the Wilcoxon two-sample test, the means were not different ( = .10), whereas the medians were ( = .015). The CGM consistently reported lower glucose values than POC BG in the majority of paired values (BBT arm mean difference = 44.8 mg/dL, IVI mean difference = 19.7 mg/dL). Glucose results were in agreement for the group 83% of the time with Bland-Altman Plot of Difference versus the mean of all glucometric data. Analysis of correction dose insulin using either CGM or POC BG values resulted in a negligible difference in calculated insulin dose recommended in those receiving subcutaneous insulin. Corrective doses were based on weight and insulin sensitivity (type 1 vs type 2 DM). Participants initially on IVI were included in a data set of BBT once IVI therapy ceased and basal bolus insulin regimen was started. The data of all basal bolus therapy participants with 1142 paired values of CGM versus POC glucose were used. The dosing difference was less for CGM than POC BG in the majority of paired values, and there was an absolute difference in dose of insulin of only 1.34 units. In the IVI group with 300 paired values of CGM versus POC glucose, there was an absolute difference in dose of insulin of only 0.74 units. About a third of the patients studied in the BBT arm experienced a hypoglycemic event with POC BG <70 mg/dL. If used in real time, CGM would have identified a hypoglycemic event for our patients on average 3 hours and 34 minutes before it was detected by standard POC BG. Two participants incurred severe nocturnal hypoglycemia during the study with POC BG <54 mg/dL with hypoglycemia detected on CGM up to 3 hours and 42 minutes before POC testing.
These results suggest that the use of inpatient CGM arrives at similar correction insulin dosing. The routine use of CGM for inpatients would consistently underestimate the BG compared with POC BG and could aid in minimizing and predicting hypoglycemia in the hospital setting. Our data support that the model of adoption of real-time inpatient CGM technology is anticipated to have significant impact in the clinical setting in efforts to maintain adequate glycemic control targeting BG 140-180 mg/dL while minimizing the frequency of hypoglycemic events.
最佳住院患者血糖管理目标为 140-180mg/dL,这是高血糖住院患者的重要安全措施。传统的胰岛素给药不正确时机包括,对于需要胰岛素治疗的患者,未能给予基础胰岛素;对于胰岛素缺乏/1 型糖尿病(DM)患者,胰岛素剂量不准确或时间不准确,导致低血糖。鉴于目前正在迅速采用技术来管理我们的 DM 患者,我们研究了在住院环境中使用连续血糖监测(CGM)作为解决住院患者高血糖管理的传统障碍的潜在方法。在这项研究中,我们评估了在胰岛素剂量方面使用住院 CGM 的效果,与当前的标准护理进行比较,并评估 CGM 是否有助于最大限度地减少低血糖事件。
这项研究评估了 Abbott 专业(盲法)Freestyle Libre CGM 在接受基础-餐时胰岛素皮下注射(基础-餐时疗法[BBT]:n=20)或静脉胰岛素(IVI)输注(n=16)的参与者中的使用情况,与标准即时血糖(POC)测量进行比较。所有接受 IVI 的参与者均被诊断为糖尿病酮症酸中毒(DKA)。CGM 数据无法实时获得。传感器在出院时移除,并将数据上传至 LibreView。将每个受试者的连续 BG 数据汇总,并与 POC BG 或实验室化学值匹配,时间不超过 5 分钟。评估 POC BG 结果的可比性(CGM 与标准 BG 测试)。进一步分析了临床决策以纠正胰岛素。
包括 IVI 和 BBT 两组的总体平均绝对相对差异为 22.3%(标准差,9.0),中位数为 20.0%。按组分析,IVI 组的平均值为 19.6%(标准差,9.4),中位数为 16.0%;对于 BBT,手臂平均值为 24.6%(标准差,8.1),中位数为 23.4%。使用 Wilcoxon 两样本检验,平均值没有差异( =.10),而中位数有差异( =.015)。CGM 报告的血糖值在大多数配对值中均低于 POC BG(BBT 手臂平均值差异=44.8mg/dL,IVI 平均值差异=19.7mg/dL)。Bland-Altman 差异与所有血糖数据的平均值的差异图显示,83%的时间血糖结果是一致的。使用 CGM 或 POC BG 值分析校正胰岛素剂量,接受皮下胰岛素治疗的患者的胰岛素推荐剂量几乎没有差异。校正剂量基于体重和胰岛素敏感性(1 型与 2 型 DM)。一旦 IVI 治疗停止并开始基础-餐时胰岛素治疗方案,最初接受 IVI 的参与者将被纳入 BBT 数据集。CGM 与 POC 血糖的 1142 对配对值的所有基础-餐时治疗参与者的数据用于分析。在大多数配对值中,CGM 的剂量差异小于 POC BG,胰岛素剂量的绝对差异仅为 1.34 单位。在 CGM 与 POC 血糖的 300 对配对值的 IVI 组中,胰岛素剂量的绝对差异仅为 0.74 单位。研究中的 BBT 组大约三分之一的患者出现 POC BG <70mg/dL 的低血糖事件。如果实时使用,CGM 将在标准 POC BG 检测到低血糖事件之前平均提前 3 小时 34 分钟识别出低血糖事件。两名参与者在研究期间发生夜间严重低血糖,POC BG <54mg/dL,CGM 检测到低血糖的时间比 POC 检测提前 3 小时 42 分钟。
这些结果表明,住院患者使用 CGM 可以达到相似的校正胰岛素剂量。常规使用 CGM 可以更准确地测量血糖,这可能有助于在医院环境中最小化和预测低血糖事件。我们的数据支持这样的观点,即实时采用住院 CGM 技术的模式有望在临床实践中产生重大影响,努力在 140-180mg/dL 的目标范围内维持足够的血糖控制,同时最大限度地减少低血糖事件的发生。