{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,23]],"date-time":"2026-10-23T19:49:21Z","timestamp":1792784961264,"version":"4.5.0"},"reference-count":59,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J Med Internet Res"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec sec-type=\"background\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Gestational diabetes mellitus (GDM) has a rising global prevalence and brings short-term and long-term adverse risks for mothers and fetuses. Conventional in-person GDM care is limited by time and geographic barriers, often resulting in suboptimal compliance and delayed individualized interventions. Telemedicine is increasingly applied in GDM management; however, randomized controlled trial (RCT) evidence remains inconsistent.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"objective\">\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The study aims to pool data from RCTs to quantify the effects of telemedicine on glycemic control and pregnancy-related outcomes in women with GDM and to inform optimized clinical management.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"methods\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We searched PubMed, Embase, Cochrane Library, Web of Science, and Scopus up to August 16, 2026. Two reviewers independently performed study screening and data extraction. Risk of bias was assessed using RoB\u202f2. Meta-analyses were conducted in Stata 18.0. For heterogeneous outcomes, 95% prediction intervals (PIs) were calculated to estimate effect ranges for future studies. Heterogeneity was explored via leave-one-out sensitivity, meta-regression, and subgroup analyses. The GRADE (Grading of Recommendations Assessment, Development, and Evaluation) framework rated evidence certainty. Publication bias was evaluated for outcomes reported in \u226510 studies.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"results\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Twenty-three RCTs (3055 women with GDM) were included. Pooled estimates suggested that telemedicine may reduce fasting glucose (mean difference [MD] \u22120.26, 95% CI \u22120.42 to \u22120.09, 95% PI \u22120.93 to 0.42;\n                      <jats:italic>P<\/jats:italic>\n                      =.002), 2-hour postprandial glucose (MD \u22120.50, 95% CI \u22120.87 to \u22120.14, 95% PI \u22121.84 to 0.84;\n                      <jats:italic>P<\/jats:italic>\n                      =.007), and gestational weight gain (MD \u22120.78, 95% CI \u22121.40 to \u22120.17, 95% PI \u22122.83 to 1.26;\n                      <jats:italic>P<\/jats:italic>\n                      =.01). Telemedicine was also associated with lower risks of cesarean section, emergency cesarean section, macrosomia, neonatal hypoglycemia, and neonatal respiratory distress. No significant differences were found for\n                      <jats:sub\/>\n                      hemoglobin A\n                      <jats:sub>1c<\/jats:sub>\n                      , preterm birth, or neonatal intensive care unit admission. Notably, fasting glucose, 2-hour postprandial glucose, and gestational weight gain exhibited very high unexplained heterogeneity (\n                      <jats:italic>I<\/jats:italic>\n                      \u00b2&gt;90%), with their 95% PIs crossing the null value despite statistically significant pooled effects. The GRADE certainty of evidence was very low to low across all assessed outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec sec-type=\"conclusions\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Telemedicine may improve selected glycemic and perinatal outcomes for women with GDM and may serve as a promising supplementary option for prenatal care, particularly in resource-limited settings where routine in-person follow-up is difficult to implement. Nevertheless, the apparent benefits for glycemic control and gestational weight gain remain tentative due to extreme, unexplained between-study heterogeneity and 95% PIs crossing the null. Based on current evidence, telemedicine should not completely replace standard antenatal care. Future well-designed, large-sample RCTs are warranted; such trials should adopt standardized definitions for telemedicine interventions, fully report intervention components, and conduct long-term follow-up to verify sustained maternal and neonatal clinical benefits.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/103569","type":"journal-article","created":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T17:10:05Z","timestamp":1790183405000},"page":"e103569-e103569","source":"Crossref","is-referenced-by-count":0,"title":["The Impact of Telemedicine Interventions on Maternal and Fetal Outcomes in Women With Gestational Diabetes: Systematic Review and Meta-Analysis of Randomized Controlled 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