{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T19:07:10Z","timestamp":1782846430612,"version":"3.54.5"},"reference-count":34,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Diabetes"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n \n Glycated hemoglobin (HbA\n 1c<\/jats:sub>\n ) is a convenient tool to evaluate glycemic status but its ability to detect individuals at risk for type 2 diabetes is limited.\n <\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n \n Exploiting the glycemic variability captured in continuous glucose monitoring (CGM), we used a well-characterized Asian cohort study from Singapore to assess whether utilizing CGM features in a machine learning model can improve the detection of prediabetes as compared to using HbA\n 1c<\/jats:sub>\n alone.\n <\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n \n In this study, 406 nondiabetic Asian participants underwent an oral glucose tolerance test and had their fasting and 2-hour plasma glucose concentrations measured, together with HbA\n 1c<\/jats:sub>\n , to classify them as with normoglycemia or prediabetes. They also wore a CGM sensor for 14 days. CGM profile features were extracted and prediction models were constructed with random subsampling validation to evaluate predictive efficacy. The use of CGM and HbA\n 1c<\/jats:sub>\n data alone or in combination was assessed for the ability to correctly distinguish prediabetes from normoglycemia.\n <\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n In this cohort (N=406), 189 (46.6%) individuals had prediabetes. The majority of the cohort were women (n=236, 58.1%) and of Chinese ethnicity (n=267, 65.8%). Those with prediabetes were slightly older, heavier, and had higher glucose levels with more variability than the normoglycemia group. A 2-step approach was used where those with HbA\n 1c<\/jats:sub>\n \u22655.7% were automatically categorized as having prediabetes; the model then focused on the prediction capability of the CGM features among individuals with HbA\n 1c<\/jats:sub>\n <5.7%. The prediction models with CGM outperformed the benchmark for comparison defined by HbA\n 1c<\/jats:sub>\n \u22655.7%, where they yielded an area under the receiver operating characteristic curve of 0.866\u20100.876, with a lower specificity of 78%\u201080% but a vastly improved sensitivity of 76%\u201078%.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n \n Adding CGM to HbA\n 1c<\/jats:sub>\n in a 2-step approach greatly improved the sensitivity of detecting prediabetes in an Asian population. Given the benefits to optimizing lifestyle behaviors and its growing acceptability among the nondiabetic population, CGM is a promising alternative for type 2 diabetes mellitus risk screening.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/81520","type":"journal-article","created":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T18:23:12Z","timestamp":1777314192000},"page":"e81520-e81520","source":"Crossref","is-referenced-by-count":0,"title":["Integration of Continuous Glucose Monitoring With HbA1c to Improve the Detection of Prediabetes in Asian Individuals: Model Development Study"],"prefix":"10.2196","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2703-7308","authenticated-orcid":false,"given":"Michelle H","family":"Lee","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0079-7390","authenticated-orcid":false,"given":"Shihui","family":"Jin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-8912-1702","authenticated-orcid":false,"given":"Eveline","family":"Febriana","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1526-1180","authenticated-orcid":false,"given":"Maybritte","family":"Lim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5195-3512","authenticated-orcid":false,"given":"Sonia","family":"Baig","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0360-3507","authenticated-orcid":false,"given":"Shahmir H","family":"Ali","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1124-3764","authenticated-orcid":false,"given":"Ian Yi Han","family":"Ang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4272-0001","authenticated-orcid":false,"given":"Tze Ping","family":"Loh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4921-1864","authenticated-orcid":false,"given":"Ashna","family":"Nastar","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0629-5570","authenticated-orcid":false,"given":"Kee Seng","family":"Chia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8927-6764","authenticated-orcid":false,"given":"Alice Pik-Shan","family":"Kong","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1312-7364","authenticated-orcid":false,"given":"Faidon","family":"Magkos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6271-5832","authenticated-orcid":false,"given":"Alex R","family":"Cook","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1570-4417","authenticated-orcid":false,"given":"Sue-Anne","family":"Toh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1010","published-online":{"date-parts":[[2026,4,27]]},"reference":[{"issue":"14","key":"R1","doi-asserted-by":"publisher","first-page":"977","DOI":"10.1056\/NEJM199309303291401","article-title":"The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus","volume":"329","author":"Diabetes Control and Complications Trial Research Group","journal-title":"N Engl J Med"},{"issue":"9131","key":"R2","doi-asserted-by":"publisher","first-page":"837","DOI":"10.1016\/S0140-6736(98)07019-6","article-title":"Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). 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