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A classification model was developed using training and validation patient sets, distinguishing between individuals at high risk of developing complications from those with normal pregnancies, achieving 80% sensitivity, 90% specificity, 89% positive predictive value (PPV), and 82% negative predictive value (NPV). Superparamagnetic nanoflowers that captured target EVs (CD9\n                    <jats:sup>+<\/jats:sup>\n                    \/PLAP\n                    <jats:sup>+<\/jats:sup>\n                    ) were used to construct a 4-flex glass strip nanozymatic readout system. The sensor analyzes plasma for EVs, identifying gestational diabetes mellitus risk with a 95% combined sensitivity, 100% specificity, 100% PPV, and 96% NPV. This nanoplatform identifies individuals at risk of developing pregnancy complications with a\u00a0&gt;90% classification accuracy, exhibiting potential for clinical applications.\n                  <\/jats:p>","DOI":"10.1126\/sciadv.adr4074","type":"journal-article","created":{"date-parts":[[2025,2,26]],"date-time":"2025-02-26T13:58:46Z","timestamp":1740578326000},"update-policy":"https:\/\/doi.org\/10.34133\/aaas_crossmark","source":"Crossref","is-referenced-by-count":13,"title":["Rapid and high-sensitivity screening of pregnancy complications by profiling circulating placental extracellular vesicles"],"prefix":"10.1126","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6182-7501","authenticated-orcid":true,"given":"Carlos","family":"Palma","sequence":"first","affiliation":[{"name":"Translational Extracellular Vesicles in Obstetrics and Gynae-Oncology Group, University of Queensland Centre for Clinical Research, Faculty of Medicine, Royal Brisbane and Women\u2019s 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