Teleassistance for Patients With Type 1 Diabetes During the COVID-19 Pandemic: Results of a Pilot Study.
Teleassistance for Patients With Type 1 Diabetes During the COVID-19 Pandemic: Results of a Pilot Study.
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DOI：
10.2196/24552
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发表时间：
2021-04-06
影响因子：
7.4
通讯作者：
Irace C
中科院分区：
文献类型：
--
作者：
Parise M;Tartaglione L;Cutruzzolà A;Maiorino MI;Esposito K;Pitocco D;Gnasso A;Irace C
在2019冠状病毒病导致的突发卫生事件期间，远程医疗在慢性病管理中的应用显著增加。糖尿病和支持糖尿病护理的技术，包括血糖监测设备、分析血糖数据的软件和胰岛素输送系统，将促进远程和结构化的疾病管理。事实上，目前大多数用于存储和传输基于网络的数据的技术都是与医疗保健提供者共享的。在COVID-19疫情期间，我们通过实施技术为患者提供了远程管理糖尿病的机会。因此，本研究旨在评价2次虚拟访视对1型糖尿病（T1D）患者在锁定期间血糖控制参数的有效性。这项前瞻性观察性研究纳入了在锁定期内完成2次虚拟访视的T1D患者。反映虚拟会诊益处的血糖结局为范围内时间（TIR）、范围以上时间、范围以下时间、平均每日血糖、血糖管理指标（GMI）和血糖变异性。该指标是使用特定的计算机程序生成的，该程序自动上传来自用于监测血液或间质葡萄糖水平的设备的数据。如果需要，我们在第一次虚拟访视时改变正在进行的治疗。在209例合格的T1D患者中，166例完成了2次虚拟访视，35例未能下载血糖数据，8例拒绝访视。在未纳入研究的患者中，我们观察到与完成研究的患者相比，动态血糖监测（CGM）和连续皮下胰岛素输注（CSII）使用者的比例显著较低（分别为n = 7/43，16% vs n = 155/166，93.4%和n = 9/43，21% vs n = 128/166，77.1%; P <.001）。TIR从第一次开始显著增加（62%，SD 18%）至第二位（65%，SD 16%）虚拟访视（P =.02）;使用传统血糖仪的患者中，这种增加更为明显（n = 11;基线TIR = 55%，SD 17%，随访TIR = 66%，SD 13%; P = 0.01）（n = 46;基线TIR = 45%，SD 15%和随访TIR = 53%，SD 18%; P <.001）比GMI <7.5%的患者（n = 120;基线TIR = 68%，SD 15%和随访TIR = 69%，SD 15%; P =.98）。与TIR独立相关的唯一变量是正在进行的治疗的变化。非标准化β系数（B）和95% CI为5（95% CI 0.7 - 8.0）（P = 0.02）。血糖监测设备和胰岛素输送系统的类型不影响血糖参数。这些发现表明，结构化虚拟访视有助于维持和改善血糖控制的情况下，在人的访问是不可行的。
Telemedicine use in chronic disease management has markedly increased during health emergencies due to COVID-19. Diabetes and technologies supporting diabetes care, including glucose monitoring devices, software analyzing glucose data, and insulin delivering systems, would facilitate remote and structured disease management. Indeed, most of the currently available technologies to store and transfer web-based data to be shared with health care providers. During the COVID-19 pandemic, we provided our patients the opportunity to manage their diabetes remotely by implementing technology. Therefore, this study aimed to evaluate the effectiveness of 2 virtual visits on glycemic control parameters among patients with type 1 diabetes (T1D) during the lockdown period. This prospective observational study included T1D patients who completed 2 virtual visits during the lockdown period. The glucose outcomes that reflected the benefits of the virtual consultation were time in range (TIR), time above range, time below range, mean daily glucose, glucose management indicator (GMI), and glycemic variability. This metric was generated using specific computer programs that automatically upload data from the devices used to monitor blood or interstitial glucose levels. If needed, we changed the ongoing treatment at the first virtual visit. Among 209 eligible patients with T1D, 166 completed 2 virtual visits, 35 failed to download glucose data, and 8 declined the visit. Among the patients not included in the study, we observed a significantly lower proportion of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) users (n=7/43, 16% vs n=155/166, 93.4% and n=9/43, 21% vs n=128/166, 77.1%, respectively; P<.001) compared to patients who completed the study. TIR significantly increased from the first (62%, SD 18%) to the second (65%, SD 16%) virtual visit (P=.02); this increase was more marked among patients using the traditional meter (n=11; baseline TIR=55%, SD 17% and follow-up TIR=66%, SD 13%; P=.01) than among those using CGM, and in those with a baseline GMI of ≥7.5% (n=46; baseline TIR=45%, SD 15% and follow-up TIR=53%, SD 18%; P<.001) than in those with a GMI of <7.5% (n=120; baseline TIR=68%, SD 15% and follow-up TIR=69%, SD 15%; P=.98). The only variable independently associated with TIR was the change of ongoing therapy. The unstandardized beta coefficient (B) and 95% CI were 5 (95% CI 0.7-8.0) (P=.02). The type of glucose monitoring device and insulin delivery systems did not influence glucometric parameters. These findings indicate that the structured virtual visits help maintain and improve glycemic control in situations where in-person visits are not feasible.
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