Bedside Risk Scoring for Carbapenem-Resistant Gram-Negative Bacterial Infections in Patients with Hematological Malignancies.

Abstract

Background/objectives: This study aimed to create a 'carbapenem resistance score' with the risk factors of carbapenem-resistant Gram-negative bacterial infections (GNBIs) in patients with hematological malignancies.

Methods: Patients with carbapenem-resistant and susceptible GNBIs were included in this study and compared in terms of risk factors. Three models of "carbapenem resistance risk scores" were created with statistically significant variables.

Results: The study included 154 patients with hospital-acquired GNBIs, of whom 64 had carbapenem-resistant GNBIs and 90 had carbapenem-susceptible GNBIs. Univariate and multivariate analyses identified several statistically significant risk factors for carbapenem resistance, including transfer from another hospital or clinic (p = 0.038), prior use of antibiotics like fluoroquinolones (p = 0.009) and carbapenems (p = 0.001), a history of carbapenem-resistant infection in the last six months (p < 0.001), rectal Klebsiella pneumoniae colonization (p < 0.001), hospitalization for ≥30 days (p = 0.001), and the presence of a urinary catheter (p = 0.002). Notably, the 14-day mortality rate was significantly higher in the carbapenem-resistant group (p < 0.001). Based on these findings, three risk-scoring models were developed. Common factors in all three models were fluoroquinolone use in the last six months, rectal K. pneumoniae colonization, and the presence of a urinary catheter. The fourth variable was transfer from another hospital (Model 1), a history of carbapenem-resistant infection (Model 2), or hospitalization for ≥30 days (Model 3). All models demonstrated strong discriminative power (AUC for Model 1: 0.830, Model 2: 0.826, Model 3: 0.831). For all three models, a cutoff value of >2.5 was adopted as the threshold to identify patients at high risk for carbapenem resistance, a value which yielded high positive and negative predictive values.

Conclusions: This study successfully developed three practical risk-scoring models to predict carbapenem resistance in patients with hematological malignancies using common clinical risk factors. A cutoff score of >2.5 proved to be a reliable threshold for identifying high-risk patients across all models, providing clinicians with a valuable tool to guide appropriate empirical antibiotic therapy.