ArticleBMC infectious diseases2025
Clinical characteristics and prognostic factors analysis in patients with post-neurosurgical intracranial infection caused by Acinetobacter baumannii.
Article in BMC infectious diseases, 2025. 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
backgroundAcinetobacter baumannii intracranial infection is a significant problem affecting the prognosis of neurosurgical patients. This study aimed to analyze the clinical characteristics and identify prognostic factors for in-hospital mortality in patients with post-neurosurgical A. baumannii intracranial infections.
methodsWe retrospectively analyzed clinical data from 109 patients diagnosed with A. baumannii intracranial infection following neurosurgery between January 2015 and December 2022. A nomogram predicting in-hospital mortality was developed using logistic regression and validated through receiver operating characteristic(ROC) analysis.
resultsA total of 109 patients were included in this study, with an in-hospital mortality rate of 58.7%. Among the A. baumannii strains isolated from cerebrospinal fluid(CSF) cultures, 95.4% exhibited carbapenem resistance. Multivariate analysis identified CSF protein level (OR = 1.132, 95% CI = 1.039–1.233), A. baumannii bloodstream infection (OR = 8.9, 95% CI = 1.536–51.559), length of stay(OR = 0.946, 95% CI = 0.919–0.974), sex(male)(OR = 0.263, 95% CI = 0.077–0.894), platelet count (OR = 0.996, 95% CI = 0.992–0.999), and albumin level (OR = 0.896, 95% CI = 0.818–0.982) as independent factors associated with in-hospital mortality. A nomogram incorporating these factors achieved an area under the curve(AUC) of 0.879 (95% CI = 0.806–0.952).
conclusionPost-neurosurgical intracranial infection with A. baumannii is associated with a high in-hospital mortality rate. Our study identified several independent prognostic factors, including CSF protein level, A. baumannii bloodstream infection, length of stay, sex(male), platelet count, and albumin level. These findings highlight the need for early identification and targeted interventions to improve patient outcomes.
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