Prediction of ventilator weaning failure in postoperative cardiac surgery patients using vasoactive-ventilation-renal score and nomogram analysis.

Objective: This study evaluated the predictive value of the vasoactive-ventilation-renal (VVR) score in identifying the risk of weaning failure after cardiac surgery and developing a nomogram model to help physicians improve the success rate of weaning from mechanical ventilation in adult patients undergoing postoperative cardiac surgery. Methods: Clinical data were retrospectively collected from adult patients who underwent extracorporeal circulation cardiac surgery at the First Affiliated Hospital of Nanjing Medical University between August 2022 and April 2023 and who were subsequently transferred to the Intensive Care Unit (ICU) and treated with vasoactive drugs. Patients were divided into successful and unsuccessful weaning groups based on first-attempt weaning success. Variable selection was regularized using univariate logistic regression and Least absolute shrinkage and selection operator (LASSO) regularization. Multivariate logistic regression was performed to identify predictors and a nomogram was created to predict the risk of weaning failure. Results: A total of 519 patients were included in the study. After selecting multiple stepwise variables, the VVR score before weaning, the modified Sequential Organ Failure Assessment (mSOFA) score on weaning day, and mechanical ventilation duration before weaning were determined as predictive indicators of weaning failure in adult patients after cardiac surgery. The optimal cut-off values for these indicators were 18.46 points, 4.33 points, and 20.50 h, respectively. The predictive model constructed using these three factors demonstrated good predictive performance. Conclusions: The VVR score before weaning accurately predicts the probability of weaning failure in adult patients after cardiac surgery. The weaning risk-predictive nomogram model, established based on the VVR score, mSOFA score, and mechanical ventilation duration before weaning, demonstrated robust predictive ability.

Investigating the impact of human blood metabolites on the Sepsis development and progression: a study utilizing two-sample Mendelian randomization.

Background: Existing data suggests a potential link between human blood metabolites and sepsis, yet the precise cause-and-effect relationship remains elusive. By using a two-sample Mendelian randomization (MR) analysis, this study aims to establish a causal link between human blood metabolites and sepsis. Methods: A two-sample MR analysis was employed to investigate the relationship between blood metabolites and sepsis. To assess the causal connection between sepsis and human blood metabolites, five different MR methods were employed, A variety of sensitivity analyses were conducted, including Cochrane's Q test, MR-Egger intercept test, MR-PRESSO and leave-one-out (LOO) analysis. In order to ensure the robustness of the causal association between exposure and outcome, the Bonferroni adjustment was employed. Additionally, we conducted analyses of the metabolic pathways of the identified metabolites using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and the Small Molecule Pathway Database (SMPDB) database. Results: The MR analysis revealed a total of 27 metabolites (16 known and 11 unknown) causally linked to the development and progression of sepsis. After applying the Bonferroni correction, 3-carboxy-4-methyl-5-propyl-2-furanpropanoate (CMPF) remained significant in relation to 28-day all-cause mortality in sepsis. By pathway enrichment analysis, we identified four significant metabolic pathways. Notably, the Alpha Linolenic Acid and Linoleic Acid metabolism pathway emerged as a pivotal contributor to the occurrence and progression of sepsis. Conclusion: This study provides preliminary evidence of causal associations between human blood metabolites and sepsis, as ascertained by MR analysis. The findings offer valuable insights into the pathogenesis of sepsis and may provide insight into preventive and therapeutic approaches.

Intestinal fibrosis in aganglionic segment of Hirschsprung's disease revealed by single-cell RNA sequencing.

BACKGROUND: Hirschsprung's disease (HSCR) is a relatively common congenital disability. Accumulating extracellular matrix (ECM) prompts intestinal fibrosis remodelling in the aganglionic segments of HSCR. The contributions of various cellular subsets in the fibrogenesis of HSCR segments are poorly understood. METHODS: Single-cell transcriptomics from 8 aganglionic segments and 5 normal segments of 7 HSCR subjects and 26 healthy segments of seven healthy donors were analysed. Fibrotic phenotype and alterations were explored using differential expression analysis and single-cell trajectory analysis. Fibrosis-related transcription factors were inferred through single-cell regulatory network inference. Bulk transcriptomic data, proteomic data, immunohistochemistry (IHC) and real-time polymerase chain reaction were used to validate the alterations in the HSCR intestine. RESULTS: Various collagen, fibronectin and laminin protein-coding genes expression were up-regulated in the stromal and glial cells of the HSCR intestine. The number of fibroblasts and myofibroblasts in the aganglionic segments increased, and more myofibroblasts were activated at an earlier stage in HSCR segments, which infers that there is an intestinal fibrosis phenotype in HSCR segments. The fibrotic regulators POSTN, ANXA1 and HSP70 were highly expressed in the ECM-related cellular subsets in the transitional segments and aganglionic segments. The transcription factor regulatory network revealed that fibrosis-related and megacolon-related NR2F1 in the fibroblasts and glial subsets was up-regulated in the aganglionic segment. CONCLUSIONS: This work identifies intestinal fibrosis and related regulators in aganglionic segments of HSCR; hence, anti-fibrotic therapy may be considered to prevent HSCR-associated enterocolitis (HAEC), relieve intestinal stricture and improve cell therapy.