{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,10]],"date-time":"2026-10-10T22:03:52Z","timestamp":1791669832650,"version":"4.3.4"},"reference-count":64,"publisher":"SAGE Publications","license":[{"start":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T00:00:00Z","timestamp":1779408000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"National Innovation and Research Office of Hungary","award":["TKP2021-NKTA-36"],"award-info":[{"award-number":["TKP2021-NKTA-36"]}]}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["J Diabetes Sci Technol"],"abstract":"<jats:sec>\n                    <jats:title>Background:<\/jats:title>\n                    <jats:p>Continuous glucose monitoring (CGM) is a wearable medical device that continuously tracks blood glucose levels through a small sensor implanted typically on the abdomen, arm, or buttocks of the patient with diabetes to ensure real-time tracking of blood glucose. Many systematic literature reviews (SLRs) explored the efficacy of CGM versus self-monitoring of blood glucose (SMBG) in different patient populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective:<\/jats:title>\n                    <jats:p>To conduct an umbrella review of existing SLRs and perform a meta-analysis of their underlying primary studies to compare CGM versus SMBG in terms of glycated hemoglobin (Hb1Ac).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods:<\/jats:title>\n                    <jats:p>This is an umbrella review (overview of reviews) of studies assessing CGM efficacy compared with SMBG. PubMed, EMBASE, and Web of Science databases were searched systematically between January 2000 and February 2024. To avoid double counting of overlapping data across reviews, quantitative synthesis was conducted at the level of the primary studies identified within the SLRs. Data extracted included HbA1c measurements, population characteristics (diabetes type\/age category\/Insulin regimen), study characteristics (study design\/follow-up duration), and device type were collected. AMSTAR-2 (A MeaSurement Tool to Assess systematic Reviews) checklist and Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool were used to appraise the quality of the included SLRs. Effect sizes with corresponding 95% confidence intervals (CIs) of the individual included studies of HbA1c were synthesized using the DerSimonian-Laird method with random effects model. Meta-regression was performed to explore the impact of different variables on the treatment effect.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results:<\/jats:title>\n                    <jats:p>\n                      Forty SLRs were included in the review with a total of 78\u2009261 patients. Continuous glucose monitoring achieved greater reduction in HbA1c than in the control group (absolute mean difference: 0.31% (95% CI 0.26%-0.36%). While the direction of effect favored CGM across subgroups, high unexplained heterogeneity was observed (\n                      <jats:italic toggle=\"yes\">I<\/jats:italic>\n                      <jats:sup>2<\/jats:sup>\n                      = 89.7%).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion:<\/jats:title>\n                    <jats:p>This is the first overview of SLRs involving quantitative primary-level meta-analysis of studies of patients with diabetes of all ages and all CGM devices. While CGM devices show a significant overall benefit in reducing HbA1c, the high unexplained heterogeneity suggests that results should be generalized with caution, as the degree of benefit may vary across different clinical settings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/19322968261445111","type":"journal-article","created":{"date-parts":[[2026,5,23]],"date-time":"2026-05-23T05:13:04Z","timestamp":1779513184000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":1,"title":["Optimizing Glycemic Control Using Continuous Glucose Monitoring: An Umbrella Review of Systematic Reviews and Meta-Analysis"],"prefix":"10.1177","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5502-8743","authenticated-orcid":false,"given":"Hana A.","family":"Al-Abdulkarim","sequence":"first","affiliation":[{"name":"Doctoral School of Applied Informatics and Applied Mathematics, \u00d3buda University, Budapest, Hungary"},{"name":"King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0804-4659","authenticated-orcid":false,"given":"Mohammad","family":"Al-Shraim","sequence":"additional","affiliation":[{"name":"King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, King Saud bin Abdulaziz University for Health Sciences (KSAU-HS), Riyadh, Kingdom of Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hossein","family":"Motahari-Nezhad","sequence":"additional","affiliation":[{"name":"Doctoral School of Business and Management, Corvinus University, Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Meriem","family":"Fgaier","sequence":"additional","affiliation":[{"name":"Doctoral School of Applied Informatics and Applied Mathematics, \u00d3buda University, Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"M\u00e1rta","family":"P\u00e9ntek","sequence":"additional","affiliation":[{"name":"Health Economics Research Center, University Research and Innovation Center, \u00d3buda University, Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L\u00e1szl\u00f3","family":"Gul\u00e1csi","sequence":"additional","affiliation":[{"name":"Health Economics Research Center, University Research and Innovation Center, \u00d3buda University, Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raed","family":"Aldahash","sequence":"additional","affiliation":[{"name":"Department of Medicine, Ministry of National Guard Health Affairs, King Abdullah International Medical Research Center, King Saud bin Abdulaziz for Health Science, Riyadh, Saudi Arabia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1992-6087","authenticated-orcid":false,"given":"Zsombor","family":"Zrubka","sequence":"additional","affiliation":[{"name":"Health Economics Research Center, University Research and Innovation Center, \u00d3buda University, Budapest, Hungary"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,5,22]]},"reference":[{"key":"e_1_3_2_2_2","doi-asserted-by":"publisher","DOI":"10.2337\/dci19-0062"},{"key":"e_1_3_2_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-019-4864-7"},{"key":"e_1_3_2_4_2","doi-asserted-by":"publisher","DOI":"10.2337\/dc17-1600"},{"issue":"9","key":"e_1_3_2_5_2","first-page":"550","article-title":"Continuous glucose monitoring: a review of available systems","volume":"44","author":"Funtanilla VD","year":"2019","unstructured":"Funtanilla VD, Candidate P, Caliendo T, Hilas O. 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