{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,30]],"date-time":"2026-08-30T02:06:52Z","timestamp":1788055612169,"version":"build-2784847793"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"8","license":[{"start":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T00:00:00Z","timestamp":1716768000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T00:00:00Z","timestamp":1716768000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100005788","name":"Medical University of Vienna","doi-asserted-by":"crossref","id":[{"id":"10.13039\/501100005788","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Diabetologia"],"published-print":{"date-parts":[[2024,8]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims\/hypothesis<\/jats:title>\n                    <jats:p>Gestational diabetes mellitus (GDM) is a heterogeneous condition. Given such variability among patients, the ability to recognise distinct GDM subgroups using routine clinical variables may guide more personalised treatments. Our main aim was to identify distinct GDM subtypes through cluster analysis using routine clinical variables, and analyse treatment needs and pregnancy outcomes across these subgroups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>\n                      In this cohort study, we analysed datasets from a total of 2682 women with GDM treated at two central European hospitals (1865 participants from Charit\u00e9 University Hospital in Berlin and 817 participants from the Medical University of Vienna), collected between 2015 and 2022. We evaluated various clustering models, including\n                      <jats:italic>k<\/jats:italic>\n                      -means,\n                      <jats:italic>k<\/jats:italic>\n                      -medoids and agglomerative hierarchical clustering. Internal validation techniques were used to guide best model selection, while external validation on independent test sets was used to assess model generalisability. Clinical outcomes such as specific treatment needs and maternal and fetal complications were analysed across the identified clusters.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Our optimal model identified three clusters from routinely available variables, i.e. maternal age, pre-pregnancy BMI (BMIPG) and glucose levels at fasting and 60 and 120 min after the diagnostic OGTT (OGTT0, OGTT60 and OGTT120, respectively). Cluster 1 was characterised by the highest OGTT values and obesity prevalence. Cluster 2 displayed intermediate BMIPG and elevated OGTT0, while cluster 3 consisted mainly of participants with normal BMIPG and high values for OGTT60 and OGTT120. Treatment modalities and clinical outcomes varied among clusters. In particular, cluster 1 participants showed a much higher need for glucose-lowering medications (39.6% of participants, compared with 12.9% and 10.0% in clusters 2 and 3, respectively,\n                      <jats:italic>p<\/jats:italic>\n                      &lt;0.0001). Cluster 1 participants were also at higher risk of delivering large-for-gestational-age infants. Differences in the type of insulin-based treatment between cluster 2 and cluster 3 were observed in the external validation cohort.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions\/interpretation<\/jats:title>\n                    <jats:p>Our findings confirm the heterogeneity of GDM. The identification of subgroups (clusters) has the potential to help clinicians define more tailored treatment approaches for improved maternal and neonatal outcomes.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Graphical Abstract<\/jats:title>\n                  <\/jats:sec>","DOI":"10.1007\/s00125-024-06184-7","type":"journal-article","created":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T02:01:47Z","timestamp":1716775307000},"page":"1552-1566","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Identification and validation of gestational diabetes subgroups by data-driven cluster analysis"],"prefix":"10.1007","volume":"67","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4878-8699","authenticated-orcid":false,"given":"Benedetta","family":"Salvatori","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Silke","family":"Wegener","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Grammata","family":"Kotzaeridi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annika","family":"Herding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Eppel","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9448-475X","authenticated-orcid":false,"given":"Iris","family":"Dressler-Steinbach","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0759-832X","authenticated-orcid":false,"given":"Wolfgang","family":"Henrich","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1921-838X","authenticated-orcid":false,"given":"Agnese","family":"Piersanti","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8327-8379","authenticated-orcid":false,"given":"Micaela","family":"Morettini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3466-5900","authenticated-orcid":false,"given":"Andrea","family":"Tura","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3922-7443","authenticated-orcid":false,"given":"Christian S.","family":"G\u00f6bl","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2024,5,27]]},"reference":[{"key":"6184_CR1","doi-asserted-by":"publisher","first-page":"109067","DOI":"10.1016\/j.diabres.2021.109067","volume":"180","author":"H Tanabe","year":"2021","unstructured":"Tanabe H, Masuzaki H, Shimabukuro M (2021) Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: a perspective. 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BS is currently supported by an Orio Carlini Scholarship (Call 2022) from Consortium GARR, Rome, Italy.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Acknowledgements"}},{"value":"The datasets analysed in the current study are available from the corresponding author upon reasonable request. The request must include an appropriate protocol and analysis plan, and institutional approvals must be in place before transfer of any information.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data availability"}},{"value":"Open access funding provided by Medical University of Vienna. This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Funding"}},{"value":"The authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Authors\u2019 relationships and activities"}},{"value":"CSG conceptualised the study. BS, AP, MM, AT and CSG developed the methodology. CSG, SW, GK, AH, FE, ID-S and WH curated the data. BS, SW, CSG and AT prepared the original draft. GK, AH, FE, ID-S, WH, AP and MM reviewed and edited the manuscript. All authors were involved in data interpretation and critically revising the report, and reviewed and approved the report for submission. BS, SW, CSG and AT had full access to all the data in the study, take responsibility for the integrity of the data and the accuracy of the data analysis, and are the guarantors of the study.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Contribution statement"}}]}}