{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T11:10:18Z","timestamp":1788952218874,"version":"build-2803163510"},"reference-count":35,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"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. Med."],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Hypertriglyceridemia-associated acute pancreatitis (HTG-AP) is a clinically important subtype of acute pancreatitis associated with adverse outcomes. Previous assessments have mainly relied on admission or peak triglyceride (TG) levels, which may not capture early in-hospital TG clearance dynamics or sustained exposure intensity. This study investigated the associations of TG clearance trajectories and time-weighted mean triglyceride exposure (TWM-TG) with severe acute pancreatitis (SAP) and pancreatic necrosis in HTG-AP.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This retrospective cohort study included 526 patients with HTG-AP. Serial TG measurements obtained within 7 days after admission were analyzed. A latent class mixed model (LCMM) was used to identify TG clearance trajectories. The area under the TG exposure curve was calculated using the trapezoidal rule and standardized by the interval between the first and last TG measurements to derive TWM-TG. Missing data were handled using multiple imputation by chained equations. Covariates were selected using the Boruta algorithm, followed by LASSO regression with 10-fold cross-validation and variance inflation factor assessment. Firth logistic regression was performed in five imputed datasets, and estimates were pooled using Rubin's rules.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      Two TG trajectories were identified: a rapid-decline group (\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"IM1\">\n                          <mml:mrow>\n                            <mml:mi mathvariant=\"normal\">n<\/mml:mi>\n                          <\/mml:mrow>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>430<\/mml:mn>\n                          <mml:mo stretchy=\"false\">)<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      and a slow-decline group\n                      <jats:inline-formula>\n                        <mml:math xmlns:mml=\"http:\/\/www.w3.org\/1998\/Math\/MathML\" id=\"IM2\">\n                          <mml:mrow>\n                            <mml:mo stretchy=\"false\">(<\/mml:mo>\n                            <mml:mi mathvariant=\"normal\">n<\/mml:mi>\n                          <\/mml:mrow>\n                          <mml:mo>=<\/mml:mo>\n                          <mml:mn>96<\/mml:mn>\n                          <mml:mo stretchy=\"false\">)<\/mml:mo>\n                        <\/mml:math>\n                      <\/jats:inline-formula>\n                      . The proportion of patients with SAP was higher in the slow-decline group than in the rapid-decline group (46.9% vs 11.9%). After multivariable adjustment, a slow-decline TG trajectory (OR=6.44, 95% CI: 3.55\u201311.69,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&amp;lt;\u20090.001) and TWM-TG (OR=1.66, 95% CI: 1.33\u20132.08,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009&amp;lt;\u20090.001) were associated with higher odds of SAP, whereas maximum TG was not significantly associated with SAP. For pancreatic necrosis, only TWM-TG remained significantly associated (OR=1.27, 95% CI: 1.05\u20131.54,\n                      <jats:italic>P<\/jats:italic>\n                      \u2009=\u20090.016).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>TG clearance trajectories and TWM-TG were associated with disease severity in HTG-AP and may provide supplementary information beyond static TG measurements. TWM-TG was also associated with pancreatic necrosis, suggesting relevance to local pancreatic injury. Further multicenter validation is warranted to confirm the generalizability and clinical relevance of these findings.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fmed.2026.1921788","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T10:16:23Z","timestamp":1788948983000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Early in-hospital triglyceride clearance trajectories and time-weighted mean exposure in hypertriglyceridemia-associated acute pancreatitis: associations with disease severity and pancreatic necrosis"],"prefix":"10.3389","volume":"13","author":[{"given":"Jiali","family":"Cui","sequence":"first","affiliation":[{"name":"Department of Gastroenterology, Zhengzhou Central Hospital Affiliated to Zhengzhou University","place":["Zhengzhou, 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