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Characterization of pathogens and prognostic factors in cerebral infarction patients complicated by pulmonary infections
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DOI：10.1097/MD.0000000000045309.png)
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Abstract
En 中文
This study aimed to investigate the microbial spectrum and prognostic indicators in patients who developed pulmonary infections secondary to cerebral infarction (CI). A total of 175 retrospective cases with post-CI pneumonia were reviewed. The study was conducted at the First Affiliated Hospital of Anhui University of Science and Technology, a single tertiary care center, between October 2023 and October 2024. Pathogenic organisms were identified, and patients were stratified into favorable (n = 116) and unfavorable (n = 59) outcome groups based on clinical prognosis. Variables with significant differences in univariate analysis were further assessed using multivariate logistic regression. A prognostic nomogram was constructed, and its predictive efficacy was evaluated using the area under the receiver operating characteristic curve (AUC). A total of 169 bacterial strains were isolated, with gram-negative organisms comprising 63.31% (107/169). Twenty-eight cases involved polymicrobial infections. Acinetobacter baumannii demonstrated high antimicrobial resistance, showing 95.5% resistance to carbapenems, 90.9% to cephalosporins, and 86.4% to aminoglycosides. Statistically significant differences between the prognosis groups were observed in ICU admission status, presence of atrial fibrillation, consciousness level, invasive interventions, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein/albumin ratio (CAR), and occurrence of multiple infections (P < .05). Logistic regression confirmed atrial fibrillation, polymicrobial infections, invasive procedures, elevated NLR, and higher CAR as independent predictors of poor clinical outcome (P < .05). The nomogram exhibited strong predictive capability with an AUC of 0.883 (95% CI: 0.828-0.937), sensitivity of 83.1%, and specificity of 86.2%. Internal validation via 1000 bootstrap replicates yielded a comparable AUC of 0.881 (95% CI: 0.830-0.931). Gram-negative bacteria are the predominant pathogens in pulmonary infections following CI, and coinfections are relatively frequent. Several clinical and inflammatory markers (particularly atrial fibrillation, polymicrobial infection, invasive procedures, NLR, and CAR) serve as independent prognostic factors. Early recognition and intervention targeting these parameters may improve clinical outcomes in this high-risk patient population. In clinical practice, serial monitoring of NLR and CAR (e.g., every 48 hours) may help detect early deterioration and guide timely interventions, such as ICU transfer, adjustment of antimicrobial regimens, and intensified supportive care.
Keywords:
cerebral infarction
logistic regression
nomogram
pathogenetic features
prognostic factors
pulmonary infection
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