ArticleTurkish journal of anaesthesiology and reanimation2026
The Association Between Systemic Inflammatory and Metabolic Indices and Early Adverse Clinical Outcomes in Adult Patients Admitted to the Post-anaesthesia Care Unit: A Retrospective Observational Study.
Article in Turkish journal of anaesthesiology and reanimation, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: This study aimed to investigate the association of systemic inflammatory and metabolic indices with short-term adverse clinical outcomes in adult patients admitted to the post-anaesthesia care unit (PACU). Methods: In this retrospective single-center observational study, adults admitted to the PACU following surgical procedures were analysed. The association between systemic inflammatory and metabolic indices, calculated from routine laboratory data, and short-term clinical outcomes was evaluated. Missing data were handled using multiple imputation. Associated risk factors were examined using multiple statistical analyses, and ridge regression was performed to assess model stability and potential multicollinearity. Receiver operating characteristic (ROC) analysis was performed to assess the discriminative ability of the investigated markers. Results: A total of 860 patients were included in the analysis. In multiple analyses, use of inotropic agents on arrival at the PACU, higher monocyte-to-lymphocyte ratio (MLR), and higher blood urea nitrogen-to-albumin ratio were associated with poor short-term clinical outcomes. ROC analysis demonstrated limited discriminative performance, with area under the curve values of 0.545 for the MLR and 0.582 for the blood urea nitrogen-to-albumin ratio in predicting poor short-term clinical outcomes. Conclusion: Higher monocyte-to-lymphocyte and blood urea nitrogen-to-albumin ratios were associated with poor short-term clinical outcomes in adult patients admitted to the PACU. However, the low discriminative performance observed in ROC analyses suggests that these indices should not be interpreted as strong standalone predictors. Instead, they may provide supporting information within multiparametric clinical risk assessment models.
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