{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T00:48:25Z","timestamp":1788482905203,"version":"build-2803163510"},"reference-count":52,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T00:00:00Z","timestamp":1778457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Endocrinol."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Missing data is common in observational studies, and even more so in type 2 diabetes mellitus with mild cognitive impairment(T2DM-MCI), which limits the completion of assessments. We evaluated the extent, current reporting, and handling of missing data, as well as the prevailing research trends in observational studies related to T2DM-MCI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>A systematic search of PubMed, Embase, and Cochrane Library was conducted from January 2020 to April 2025 to identify observational studies related to T2DM-MCI. Bibliometrics was performed using VOSviewer and CiteSpace to evaluate publishing trends, authors, journals, and keywords. The reporting and handling of missing data were assessed according to the guidelines recommended by STROBE and Sterne et\u00a0al., with a focus on the recording, causes, mechanisms, processing methods, and sensitivity analysis of missing data. Data analysis was conducted using SPSS 26, and visualization was performed using Origin Pro 2024.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Among the 4,471 screened records, 88 studies (78 in English and 10 in Chinese) were included in this analysis. Among the 78 English articles, the annual publication volume exhibited fluctuations, peaking in 2024. Chinese institutions and authors led in research output.\n                      <jats:italic>Diabetes, Metabolic Syndrome, and Obesity<\/jats:italic>\n                      had the highest publication volume (7, 8.97%). Keyword identified five clusters: 1) resting-state functional magnetic resonance imaging, 2) metabolic disorders, 3) clinical assessment tools, 4) molecular mechanisms, and 5) emerging fields such as the gut microbiome.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Missing data<\/jats:title>\n                    <jats:p>Only 22.7% (n = 20) of the studies quantified the missing data, with an average of 9.1%. Among studies with missing data (n = 23), 52.2% (n = 12) provided reasons for missing data, primarily citing poor quality of data collection (41.7%) and loss to follow-up (41.7%). Complete case analysis was the predominant method for addressing missing data (93.3%). No study articulated the hypothesized mechanisms underlying the missing data, and only 4.4% (n = 1) performed a sensitivity analysis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>In the domain of T2DM-MCI, research outcomes post-COVID-19 pandemic indicate a rebound, with China maintaining a leading position in scientific research output. However, the reporting of missing data remains ambiguous, and the methods employed to handle such data are insufficient, which may potentially introduce bias.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Systematic Review Registration<\/jats:title>\n                    <jats:p>\n                      <jats:ext-link>https:\/\/doi.org\/10.17605\/OSF.IO\/EZDXM<\/jats:ext-link>\n                      .\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fendo.2026.1649881","type":"journal-article","created":{"date-parts":[[2026,5,11]],"date-time":"2026-05-11T04:27:39Z","timestamp":1778473659000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Global research trends, reporting and handling of missing data in observational studies of type 2 diabetes mellitus with mild cognitive impairment from 2020 to 2025: a systematic review"],"prefix":"10.3389","volume":"17","author":[{"given":"Yang","family":"Liu","sequence":"first","affiliation":[{"name":"Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maoyi","family":"Yang","sequence":"additional","affiliation":[{"name":"Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Liao","sequence":"additional","affiliation":[{"name":"Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhipeng","family":"Hu","sequence":"additional","affiliation":[{"name":"Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu University of Traditional Chinese Medicine","place":["Chengdu, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,5,11]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.diabres.2019.107843","article-title":"Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition","volume":"157","author":"Saeedi","year":"2019","journal-title":"Diabetes Res Clin Pract"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1016\/s1474-4422(08)70021-8","article-title":"Cognition and diabetes: a lifespan perspective","volume":"7","author":"Biessels","year":"2008","journal-title":"Lancet Neurol"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1007\/s00125-005-0023-4","article-title":"Cognitive decline and dementia in diabetes\u2013systematic overview of prospective observational studies","volume":"48","author":"Cukierman","year":"2005","journal-title":"Diabetologia"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2020.00856","article-title":"Type 2 diabetes mellitus may exacerbate gray matter atrophy in patients with early-onset mild cognitive impairment","volume":"14","author":"Li","year":"2020","journal-title":"Front Neurosci"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.2174\/1570159x13666141204220539","article-title":"Can tea consumption be a safe and effective therapy against diabetes mellitus-induced neurodegeneration","volume":"12","author":"Nunes","year":"2014","journal-title":"Curr Neuropharmacol"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMcp0910237","article-title":"Clinical practice. 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