{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"volume":["9"],"submitter":["Xu F"],"pubmed_abstract":["<h4>Background</h4>Sepsis is a serious disease with high clinical morbidity and mortality. Despite the tremendous advances in medicine and nursing, treatment of sepsis remains a huge challenge. Our purpose was to explore the effects of shock index (SI) trajectory changes on the prognosis of patients within 24 h after the diagnosis of sepsis.<h4>Methods</h4>This study was based on Medical Information Mart for Intensive Care IV (MIMIC- IV). The effects of SI on the prognosis of patients with sepsis were investigated using C-index and restricted cubic spline (RCS). The trajectory of SI in 24 h after sepsis diagnosis was classified by latent growth mixture modeling (LGMM). Cox proportional hazard model, double robust analysis, and subgroup analysis were conducted to investigate the influence o"],"journal":["Frontiers in medicine"],"pagination":["898424"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC9441919"],"repository":["biostudies-literature"],"pubmed_title":["Effects of growth trajectory of shock index within 24 h on the prognosis of patients with sepsis."],"pmcid":["PMC9441919"],"pubmed_authors":["Yin H","Huang T","Lyu J","Zheng S","Xu F","Yang R","Zhang L","Huang L","Han D","Feng A"],"additional_accession":[]},"is_claimable":false,"name":"Effects of growth trajectory of shock index within 24 h on the prognosis of patients with sepsis.","description":"<h4>Background</h4>Sepsis is a serious disease with high clinical morbidity and mortality. Despite the tremendous advances in medicine and nursing, treatment of sepsis remains a huge challenge. Our purpose was to explore the effects of shock index (SI) trajectory changes on the prognosis of patients within 24 h after the diagnosis of sepsis.<h4>Methods</h4>This study was based on Medical Information Mart for Intensive Care IV (MIMIC- IV). The effects of SI on the prognosis of patients with sepsis were investigated using C-index and restricted cubic spline (RCS). The trajectory of SI in 24 h after sepsis diagnosis was classified by latent growth mixture modeling (LGMM). Cox proportional hazard model, double robust analysis, and subgroup analysis were conducted to investigate the influence o","dates":{"release":"2022-01-01T00:00:00Z","publication":"2022","modification":"2025-04-22T10:56:29.433Z","creation":"2024-11-20T07:54:43.759Z"},"accession":"S-EPMC9441919","cross_references":{"pubmed":["36072946"],"doi":["10.3389/fmed.2022.898424"]}}