Background: Serum lipase levels are crucial biomarkers in acute pancreatitis (AP), yet their dynamic patterns and prognostic implications remain incompletely understood. This study aimed to identify distinct lipase trajectory phenotypes and evaluate their association with in-hospital mortality in AP patients. Methods: We conducted a retrospective analysis of 834 AP patients from the MIMIC-IV database using latent class trajectory modeling (LCTM) to identify distinct lipase trajectory phenotypes. Cox regression models, adjusted for demographics, comorbidities, clinical therapies, and critical illness markers, were employed to assess the association between trajectory classes and in-hospital mortality. Results: Three distinct lipase trajectory phenotypes were identified: Class 1 ( n = 543) with consistently low levels, Class 2 ( n = 51) with extremely high and variable levels, and Class 3 ( n = 240) with moderately elevated levels. Class 2 patients were significantly older (66.8 ± 17.6 years) and had higher comorbidity burden (CCI: 5.6 ± 3.0). In-hospital mortality rates were 12.2%, 17.6%, and 19.2% for Classes 1, 2, and 3, respectively. After comprehensive adjustment, both Class 2 (HR: 2.21, 95% CI 1.04–4.71, p = 0.042) and Class 3 (HR: 1.61, 95% CI 1.08–2.40, p = 0.022) showed significantly higher mortality risk compared to Class 1. Conclusions: Dynamic lipase trajectory patterns in AP patients demonstrate distinct phenotypes with significant prognostic value for in-hospital mortality. These findings suggest that monitoring lipase trajectories may enhance risk stratification and guide clinical management in AP patients.

Background: The triglyceride-glucose (TyG) index, a simple and validated surrogate marker of insulin resistance, may be clinically relevant to colorectal polyp development because insulin resistance can promote colorectal neoplasia through hyperinsulinemia, chronic inflammation, oxidative stress, and dysregulated insulin-like growth factor signaling. However, the relationship between TyG index and colorectal polyps remains incompletely understood. This study aimed to investigate the association between TyG index and colorectal polyp risk using both observational and genetic approaches. Methods: We conducted a cross-sectional study of 4,263 patients undergoing colonoscopy. Associations between TyG index and colorectal adenomatous polyps were assessed using multivariable logistic regression. A two-sample Mendelian randomization (MR) analysis evaluated potential causal effects, with inverse-variance weighted (IVW) method as primary analysis and multiple sensitivity analyses. Results: Although the crude distribution of colorectal polyps across TyG quartiles did not show a strictly monotonic pattern, participants in different TyG quartiles differed substantially in age, sex distribution, BMI, lifestyle factors, comorbidities, and metabolic profiles. Therefore, multivariable logistic regression was performed to account for potential confounding. Higher TyG index was significantly associated with increased prevalence of colorectal adenomatous polyps after full adjustment (odds ratio [OR] 1.13, 95% CI: 1.01–1.27; P-trend = 0.032). Restricted cubic spline analysis showed no evidence of a nonlinear association between the TyG index and colorectal adenomatous polyp risk (P for nonlinearity = 0.459), supporting the use of a linear model in this dataset. MR analysis supported a observational and potential causal association between genetically predicted TyG index and colon polyps (inverse-variance weighted OR: 1.20, 95% CI: 1.10–1.31; P < 0.001), with consistent results across sensitivity analyses and no evidence of directional pleiotropy (P = 0.884). However, no significant association was found for rectal polyps. Conclusion: Both observational evidence and genetic evidence support a positive association between the TyG index and colon polyps, whereas the MR analysis did not provide evidence for a causal association with rectal polyps. These findings suggest the potential utility of the TyG index in risk stratification and underscore the role of insulin resistance in the pathogenesis of colorectal neoplasia.

This study aimed to examine the association between the composite dietary antioxidant index (CDAI) and advanced cardiovascular–kidney–metabolic syndrome (CKM) and characterize its dose–response shape. This cross-sectional study included 23,968 National Health and Nutrition Examination Survey participants aged ≥20 years (2001–2018). Advanced CKM was stages 3 and 4 combined, per the 2023 American Heart Association framework. The CDAI was the sum of sex-specific z-scores for 6 dietary antioxidants (vitamins A, C, and E, carotenoids, zinc, and selenium) from a single 24-hour recall, analyzed in quartiles (Q1–Q4). Multivariable logistic regression assessed the association, and restricted cubic splines tested nonlinearity. Multiple imputation, propensity score matching, survey-weighted models, and subgroup analyses evaluated robustness. Crude prevalence of advanced CKM fell from 33.6% (Q1) to 20.8% (Q4). After full adjustment, odds ratios (ORs) vs Q1 were 0.87 (95% confidence interval 0.78–0.97) for Q2, 0.79 (0.70–0.89) for Q3, and 0.83 (0.72–0.95) for Q4 ( P for trend = .002). Splines showed an L-shaped association with a nadir at a CDAI of approximately 0.36; below this threshold each 1-unit increase was associated with marginally lower odds (OR 0.96, 95% confidence interval 0.92–1.00, P = .048), whereas above it the association plateaued. The associations were consistent across age, sex, smoking, alcohol intake, poverty income ratio, and physical activity strata (all P for interaction > .05). After multiple imputation the Q4 OR was 0.77 (0.69–0.85); propensity score–matched and survey-weighted estimates were directionally consistent, with a significant trend in each ( P for trend = .045, .039). A higher food-derived CDAI was independently associated with a lower prevalence of advanced CKM, with the inverse association confined to the low-to-moderate intake range. These findings are consistent with dietary guidance emphasizing whole foods rich in diverse antioxidants, although the cross-sectional design precludes causal inference.

Dietary live microbes have gained attention as potential modulators in chronic disease management, yet their impact on the survival of cancer patients remains underexplored. This study assessed the association between dietary live microbe intake from food and all-cause as well as cause-specific mortality in cancer patients. Data from 3649 adult cancer patients in the 1999 to 2018 National Health and Nutrition Examination Survey were analyzed. Participants were grouped according to their intake of foods with medium-to-high microbial content (MedHi food): G1 (no intake), G2 (below median), and G3 (above median). Kaplan–Meier survival analysis and multivariable Cox regression were used to evaluate mortality outcomes, while restricted cubic spline models assessed dose–response relationships. Over a median follow-up of 7.08 years, 1290 participants died, including 424 cancer-specific deaths. Compared with G1, G3 had 21% lower all-cause mortality and 27% lower noncancer mortality. No significant association was observed with cancer-specific mortality. A nonlinear, inverse relationship was observed for all-cause mortality at intake levels below 489.7 grams, plateauing beyond this threshold. Higher MedHi food intake was associated with lower risks of all-cause and noncancer mortality among adults with self-reported cancer, but not with cancer-specific mortality. Because National Health and Nutrition Examination Survey lacks detailed information on cancer type, stage, treatment, and time since diagnosis, these cancer-specific clinical factors were not adjusted for in the present analyses. These findings should therefore be interpreted as observational and hypothesis-generating, and may inform future prospective studies on dietary live microbes and survival among cancer survivors.