Background: Malnutrition is common in patients with acute myocardial infarction (AMI) and is associated with a poor prognosis. The prognostic value of the prognostic nutritional index (PNI) in patients with AMI remains controversial. We aimed to explore the relationship between PNI and all-cause mortality in critically ill patients with AMI and evaluate the incremental prognostic value of PNI to commonly used prognostic assessment tools. Methods: The Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was used to conduct a retrospective cohort analysis on 1180 critically ill patients with AMI. The primary endpoints were defined as 6-month and 1-year all-cause mortality. Cox regression analysis was used to investigate the relationship between admission PNI and all-cause mortality. The effect of adding PNI to sequential organ failure assessment (SOFA) score, or charlson comorbidity index (CCI) on its discriminative ability was assessed using C-statistic, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Results: Multivariate cox regression analysis demonstrated that the low PNI was regarded as an independent predictor of 1-year all-cause mortality in AMI patients admitted to ICU (adjusted Hazard Ratio: 95% CI = 1.75 (1.22–2.49)). The ROC test showed that admission PNI had a moderate predictive ability to predict all-cause mortality of critically ill patients with AMI. Furthermore, the net reclassification and integrated discrimination of the CCI alone model improved significantly with PNI. [C-statistic increased from 0.669 to 0.752, p < 0.001; NRI = 0.698, p < 0.001; IDI = 0.073, p < 0.001]. When PNI was added to the SOFA score, the C-statistic significantly improved from 0.770 to 0.805 (p < 0.001), and the NRI and IDI were estimated at 0.573 (p < 0.001) and 0.041 (p < 0.001), respectively. Conclusion: PNI could be a novel predictor for identifying patients at high risk of 1-year all-cause mortality in critically ill patients with AMI. The addition of PNI to the SOFA score or CCI may be useful for very early risk stratification.

A bidirectional 2-sample Mendelian randomization (MR) analysis was used to investigate the causal relationship between hypothyroidism and multiple types of cardiovascular diseases (CVDs). Single nucleotide polymorphisms strongly associated with hypothyroidism and 4 CVDs (myocardial infarction, coronary artery disease, heart failure [HF], hypertension) were extracted from genome-wide association study summary data as instrumental variables, excluding linkage disequilibrium. First, a forward MR analysis assessed causal effects of hypothyroidism on cardiovascular outcomes using inverse-variance weighted, weighted median, MR-Egger regression, simple mode, and weighted mode methods. Heterogeneity was evaluated via inverse-variance weighted and MR-Egger Q -tests, pleiotropy via Egger intercept test, and sensitivity via leave-one-out analysis. Reverse MR tested causality from CVDs to hypothyroidism. A bidirectional MR framework ensured robustness, with comprehensive statistical validations (heterogeneity, pleiotropy, sensitivity) to minimize confounding bias and confirm reliability of causal inferences. Genetically predicted hypothyroidism causally increased risks of myocardial infarction (odds ratio [OR] = 3.003, P = .002), coronary heart disease (OR = 2.780, P = .001), HF (OR = 1.892, P = .009), and hypertension (OR = 1.102, P = .024). Reverse MR revealed HF reciprocally elevated hypothyroidism risk (OR = 1.006, P = .040). Analyses confirmed absence of pleiotropy (all P > .05) and robustness through leave-one-out sensitivity analysis. Causal relationships remained consistent across sensitivity methods, supporting thyroid dysfunction as cardiovascular risk modifier in bidirectional pathways. This study affirms that hypothyroidism heightens the susceptibility to multiple types of CVDs, and establishes a causal link between HF and hypothyroidism.

Chemotherapy-induced side effects restrain anti-tumor efficiency, with hyperlipidemia being the most common accompanying disease to cause treatment failure. In this work, a chimeric peptide-engineered nanomedicine (designated as PRS) was fabricated for the synergistic suppression of tumor growth and therapy-induced hyperlipidemia. Within this nanomedicine, the tumor matrix-targeting peptide palmitic-K(palmitic)CREKA can self-assemble into a nano-micelle to encapsulate Rapamycin (mTOR inhibitor) and SBC-115076 (PCSK9 inhibitor). This PRS nanomedicine exhibits a uniform nano-distribution with good stability which enhances intracellular drug delivery and tumor-targeting delivery. Also, PRS was found to synergistically inhibit tumor cell proliferation by interrupting the mTOR pathway and reducing Rapamycin-induced hyperlipidemia by increasing the production of LDLR. In vitro and in vivo results demonstrate the superiority of PRS for systematic suppression of tumor growth and the reduction of hyperlipidemia without initiating any other toxic side effects. This work proposes a sophisticated strategy to inhibit tumor growth and also provides new insights for cooperative management of chemotherapy-induced side effects.