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SP 9.07 Novel Blood-Based Biomarkers of Frailty and Outcomes Following Emergency Laparotomy

Aug 2026 · British Journal of Surgery · 0 citations

Abstract

Frailty is a well-established predictor of adverse post-operative outcomes in emergency laparotomy (EmLap) patients. However, frailty assessment in time-pressured emergency settings remains challenging. Blood-based frailty metabolites have been investigated as biomarkers in community-dwelling ageing populations but not in EmLap patients. This study aimed to explore novel blood-based metabolites associated with frailty and post-operative outcomes in EmLap patients using metabolomic profiling. Prospective data were collected from EmLap patients aged ≥40 years between May 2022 and July 2023, with 3-month follow-up. Frailty was assessed using Clinical Frailty Scale (score >4 as frail). Serial blood samples were collected at 5 peri-operative timepoints and analysed using liquid chromatography-mass spectrometry (LCMS)-based metabolomics. Univariate and multivariate regression chemometric analyses were performed, with statistical significance defined as p<0.05. 150 patients were recruited (55% female; median age 69 years). 10% were frail pre-EmLap, with an additional 11% became frail post-EmLap. 90-day mortality was 13%. A panel of metabolites was significantly associated with frailty (p<0.05), with distinct metabolic profiles observed between frail and non-frail groups across peri-operative timepoints. LASSO-regression of pre-EmLap samples identified 26 metabolites, spanning 4 biochemical classes, that predicted post-EmLap mortality (p<0.05). EmLap can induce or exacerbate frailty. This study is among the first to characterise blood-based frailty metabolites in EmLap patients using LCMS-based metabolomics. These frailty biomarkers offer a novel, objective approach for frailty assessment and peri-operative risk stratification, with potential implications for targeted optimisation and future therapeutic development. Larger studies are required to validate these findings and determine clinical applicability.

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