Ying Zhen, Fan Yujuan, Chen Congling, Liu Yuchen, Tang Qi, Chen Zhiwei, Yang Qian, Yan Hongmei, Wu Liming, Lu Jiaping, Liu Zhiwen, Liu Jun, Li Xiaoying, Chen Ying
Ministry of Education Key Laboratory of Metabolism and Molecular Medicine, Department of Endocrinology and Metabolism, Zhongshan Hospital, Fudan University, Shanghai, China.
Department of Endocrinology and Metabolism, Minhang Hospital, Fudan University, Shanghai, China.
JAMA Netw Open. 2025 May 1;8(5):e258910. doi: 10.1001/jamanetworkopen.2025.8910.
Type 2 diabetes (T2D) is one of the most prevalent chronic diseases in the world. Insulin titration for glycemic control in T2D is crucial but limited by the lack of personalized and real-time tools.
To examine whether an artificial intelligence-based insulin clinical decision support system (iNCDSS) for glycemic control in hospitalized patients with T2D is noninferior to standard insulin therapy administered by senior physicians.
DESIGN, SETTING, AND PARTICIPANTS: This multicenter, single-blind, parallel randomized clinical trial (RCT) was conducted between October 1, 2021, and September 8, 2022, in endocrinology wards of 3 medical centers. Eligible participants were adults (aged ≥18 years) with glycated hemoglobin levels between 7.0% and 11.0% who had received antidiabetic treatments in the previous 3 months.
Participants were randomized in a 1:1 ratio to receive insulin dosage titration by iNCDSS or senior endocrinology physicians for 5 consecutive days.
The primary outcome was the proportion of time in the target glucose range (70-180 mg/dL) during the 5-day study period; the noninferiority margin was 6 percentage points. Secondary outcomes included other glycemic control measurements and adverse events.
A total of 149 participants (mean [SD] age, 64.2 [12.0] years; 84 male [56.4%]) were enrolled and randomized to the iNCDSS group (n = 75) or physician group (n = 74). The mean (SD) target glucose range (primary outcome) was 76.4% (16.4%) in the iNCDSS group and 73.6% (16.8%) in the physician group, which achieved the prespecified noninferiority criterion (estimated treatment difference, 2.7%; 95% CI, -2.7% to 8.0%). There were no significant differences in adverse events between the 2 groups. Most physicians were satisfied with the iNCDSS for its clear, time-saving, effective, and safe clinical support.
In this RCT of an iNCDSS, the system demonstrated noninferiority to senior endocrinology physicians in insulin titration in an inpatient setting, indicating its potential as a favorable tool for insulin titration in patients with T2D.
ClinicalTrials.gov Identifier: NCT04642378.
2型糖尿病（T2D）是全球最常见的慢性病之一。T2D患者血糖控制的胰岛素滴定至关重要，但因缺乏个性化和实时工具而受到限制。
检验基于人工智能的胰岛素临床决策支持系统（iNCDSS）用于住院T2D患者血糖控制是否不劣于资深医生给予的标准胰岛素治疗。
设计、地点和参与者：这项多中心、单盲、平行随机临床试验（RCT）于2021年10月1日至2022年9月8日在3个医疗中心的内分泌科病房进行。符合条件的参与者为年龄≥18岁、糖化血红蛋白水平在7.0%至11.0%之间且在过去3个月内接受过抗糖尿病治疗的成年人。
参与者按1:1比例随机分组，连续5天接受iNCDSS或资深内分泌科医生的胰岛素剂量滴定。
主要结局是5天研究期间血糖处于目标范围（70 - 180 mg/dL）的时间比例；非劣效界值为6个百分点。次要结局包括其他血糖控制指标和不良事件。
共纳入149名参与者（平均[标准差]年龄，64.2[12.0]岁；84名男性[56.4%]），随机分为iNCDSS组（n = 75）或医生组（n = 74）。iNCDSS组的平均（标准差）目标血糖范围（主要结局）为76.4%（16.4%），医生组为73.6%（16.8%），达到了预先设定的非劣效标准（估计治疗差异，2.7%；95%置信区间，-2.7%至8.0%）。两组之间不良事件无显著差异。大多数医生对iNCDSS清晰、省时、有效和安全的临床支持感到满意。
在这项iNCDSS的RCT中，该系统在住院环境中胰岛素滴定方面表现出不劣于资深内分泌科医生，表明其有潜力成为T2D患者胰岛素滴定的有利工具。
ClinicalTrials.gov标识符：NCT04642378。
