RESUMEN
Carbapenem-resistant Klebsiella pneumoniae (CRKP) infection has become a significant threat to global health. The application of chemical disinfectants is an effective infection control strategy to prevent the spread of CRKP in hospital environments. However, bacteria have shown reduced sensitivity to clinical disinfectants in recent years. Furthermore, bacteria can acquire antibiotic resistance due to the induction of disinfectants, posing a considerable challenge to hospital infection prevention and control. This study collected 68 CRKP strains from the Fifth Affiliated Hospital of Xinjiang Medical University in China from 2023 to 2024. These strains were isolated from the sputum, urine, and whole blood samples of patients diagnosed with CRKP infection. Antibiotic susceptibility tests were performed on CRKP strains. Concurrently, the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of disinfectants (benzalkonium bromide, 1% iodophor disinfectant, alcohol, and chlorine-containing disinfectant) against the test isolates were determined by the broth microdilution method. The efflux pump genes (cepA, qacE, qacEΔ1, qacEΔ1-SUL1, oqxA, and oqxB) were detected using polymerase chain reaction. The results showed that 21 out of the 68 CRKP strains exhibited extensive drug resistance, whereas 47 were nonextensively drug-resistant. The MIC value for benzalkonium bromide disinfectants displayed statistically significant differences (p < 0.05) between extensively drug-resistant (XDR) and non-XDR strains. Additionally, the MBC values for benzalkonium bromide disinfectants and 1% iodophor disinfectants displayed statistically significant differences (p < 0.05) between XDR and non-XDR strains. The detection rates for the efflux pump genes were as follows: cepA 52.9%, qacE 39.7%, qacEΔ1 35.2%, qacEΔ1-SUL1 52.9%, oqxA 30.8%, and oqxB 32.3%. The detection rate of the qacEΔ1-SUL1 gene in XDR CRKP strains was significantly higher than in non-XDR CRKP strains (p < 0.05). This indicates a potential link between CRKP bacterial disinfectant efflux pump genes and CRKP bacterial resistance patterns. Ongoing monitoring of the declining sensitivity of XDR strains against disinfectants is essential for the effective control and prevention of superbug.
RESUMEN
This study evaluates whether random forest (RF) models are as effective as traditional Logistic Regression (LR) models in predicting multidrug-resistant Gram-negative bacterial nosocomial infections. Data were collected from 541 patients with hospital-acquired Gram-negative bacterial infections at two tertiary-level hospitals in Urumqi, Xinjiang, China, from August 2022 to November 2023. Relevant literature informed the selection of significant predictors based on patients' pre-infection clinical information and medication history. The data were split into a training set of 379 cases and a validation set of 162 cases, adhering to a 7:3 ratio. Both RF and LR models were developed using the training set and subsequently evaluated on the validation set. The LR model achieved an accuracy of 84.57%, sensitivity of 82.89%, specificity of 80.10%, positive predictive value of 84%, negative predictive value of 85.06%, and a Yoden index of 0.69. In contrast, the RF model demonstrated superior performance with an accuracy of 89.51%, sensitivity of 90.79%, specificity of 88.37%, positive predictive value of 87.34%, negative predictive value of 91.57%, and a Yoden index of 0.79. Receiver operating characteristic curve analysis revealed an area under the curve of 0.91 for the LR model and 0.94 for the RF model. These findings indicate that the RF model surpasses the LR model in specificity, sensitivity, and accuracy in predicting hospital-acquired multidrug-resistant Gram-negative infections, showcasing its greater potential for clinical application.