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Standard analyses treat insulin as a confounder rather than a mediator, obscuring these distinct causal channels and patient-level heterogeneity in carbohydrate response. Using meal-centered continuous glucose monitoring windows from twelve adults in the OhioT1DM cohorts, we apply causal mediation analysis to decompose the total effect of carbohydrate intake on glucose change into average direct (ADE), insulin-mediated (ACME), and total effects, by meal type and across outcome quantiles. To adjust for pre-meal confounding, we introduce a Causally-constrained Linear Autoencoder that learns low-dimensional representations improving adjustment for measured pre-meal state. Across cohorts, carbohydrate intake raises postprandial glucose chiefly through a large direct effect that insulin only partially offsets. The prespecified primary endpoint, the pooled ADE of a +30 g contrast at two hours, is large and highly significant, robust to multiple-testing correction, and replicates in the independent DiaTrend cohort (54 adults); the insulin-mediated effect is comparatively small. Meal- and quantile-specific signals, including greater dinner-time excursions, do not survive false-discovery-rate correction and are reported as hypothesis-generating. These results localize where postprandial insulin dosing may be refined.<\/jats:p>","DOI":"10.64898\/2026.03.16.26348520","type":"posted-content","created":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T00:10:31Z","timestamp":1773792631000},"source":"Crossref","is-referenced-by-count":0,"title":["Causal Mediation Pathways in Continuous Postprandial Glucose Monitoring for Type 1 Diabetes Patients"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7053-359X","authenticated-orcid":false,"given":"Spencer","family":"Hilligoss","sequence":"first","affiliation":[{"name":"Department of Statistics, University of California, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Annie","family":"Qu","sequence":"additional","affiliation":[{"name":"Department of Statistics and Applied Probability, University of California, Santa Barbara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026072714005841000_2026.03.16.26348520v2.1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(13)60591-7"},{"key":"2026072714005841000_2026.03.16.26348520v2.2","doi-asserted-by":"publisher","DOI":"10.2337\/dci19-0028"},{"key":"2026072714005841000_2026.03.16.26348520v2.3","doi-asserted-by":"publisher","DOI":"10.2337\/dc20-0882"},{"key":"2026072714005841000_2026.03.16.26348520v2.4","doi-asserted-by":"publisher","DOI":"10.2337\/db08-1084"},{"key":"2026072714005841000_2026.03.16.26348520v2.5","doi-asserted-by":"publisher","DOI":"10.2337\/diacare.26.6.1902"},{"key":"2026072714005841000_2026.03.16.26348520v2.6","first-page":"57","article-title":"Uncovering undetected hypoglycemic events","volume":"5","year":"2012","journal-title":"Diabetes Metab. 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