Zhonghua wei zhong bing ji jiu yi xue · 2025
[Development and validation of a prediction model for bloodstream infection caused by carbapenem-resistant Klebsiella pneumoniae].
Аннотация на английскомСтатьяНазвание и аннотация: Перевод в очереди
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Jin Shanshan, Zhou Fangqing, Wei Dongpo, Zheng Jingjing, Chen Changxing, Wang Ruilan
Аннотация
OBJECTIVE: To develop and validate a predictive model for the risk of bloodstream infection (BSI) caused by carbapenem-resistant Klebsiella pneumoniae (CRKP).
METHODS: A literature search was conducted in PubMed, Cochrane Library, and Embase databases from inception to July 2022 to identify studies reporting statistically significant risk factors for CRKP-BSI. Relative risks (RR) were extracted and pooled. Based on factor weights, a risk-scoring model was established. For external validation, hospitalized CRKP-infected patients from January 2016 to January 2022 at Shanghai First People's Hospital were included. Clinical data were used to calculate individual risk scores. The predictive accuracy was assessed using receiver operator characteristic curve (ROC curve). Patients were stratified into low-to-intermediate-risk and high-risk groups based on the optimal cut-off, and CRKP BSI incidence was compared between groups.
RESULTS: The literatures related to the risk factors of CRKP-BSI published from database inception to July 2022 was retrieved and screened from PubMed, Cochrane Library, and Embase. Fourteen risk factors were included in the scoring model: cardiovascular disease, severe neutropenia or immunosuppression, intensive care unit (ICU) stay history, prior hospitalization, carbapenem exposure, aminoglycoside exposure, antifungal exposure, endotracheal intubation or tracheostomy, mechanical ventilation, hemodialysis, central venous catheter, indwelling urinary catheter, CRKP colonization, and Klebsiella pneumoniae positivity at non infection sites. The total score ranged from 0 to 173.5 points. In the validation cohort of 230 CRKP-infected patients, 41 developed CRKP BSI. The model yielded an area under the curve (AUC) of 0.783 (95%CI was 0.689-0.876). The optimal cut off was 81.25 points, with sensitivity of 75.6% and specificity of 81.0%. Based on this cut off, 163 patients were categorized as low-to-intermediate risk and 67 patients as high risk. The incidence of CRKP BSI in the high-risk group was significantly higher than in the low-to-intermediate-risk group [64.2% (43/67) vs. 4.9% (8/163); RR = 13.175 (95%CI was 5.920-29.319), P < 0.001].
CONCLUSIONS: The model, based on 14 routinely available clinical parameters, demonstrated good performance in predicting CRKP BSI risk and may assist clinicians in early identification of high risk patients.
METHODS: A literature search was conducted in PubMed, Cochrane Library, and Embase databases from inception to July 2022 to identify studies reporting statistically significant risk factors for CRKP-BSI. Relative risks (RR) were extracted and pooled. Based on factor weights, a risk-scoring model was established. For external validation, hospitalized CRKP-infected patients from January 2016 to January 2022 at Shanghai First People's Hospital were included. Clinical data were used to calculate individual risk scores. The predictive accuracy was assessed using receiver operator characteristic curve (ROC curve). Patients were stratified into low-to-intermediate-risk and high-risk groups based on the optimal cut-off, and CRKP BSI incidence was compared between groups.
RESULTS: The literatures related to the risk factors of CRKP-BSI published from database inception to July 2022 was retrieved and screened from PubMed, Cochrane Library, and Embase. Fourteen risk factors were included in the scoring model: cardiovascular disease, severe neutropenia or immunosuppression, intensive care unit (ICU) stay history, prior hospitalization, carbapenem exposure, aminoglycoside exposure, antifungal exposure, endotracheal intubation or tracheostomy, mechanical ventilation, hemodialysis, central venous catheter, indwelling urinary catheter, CRKP colonization, and Klebsiella pneumoniae positivity at non infection sites. The total score ranged from 0 to 173.5 points. In the validation cohort of 230 CRKP-infected patients, 41 developed CRKP BSI. The model yielded an area under the curve (AUC) of 0.783 (95%CI was 0.689-0.876). The optimal cut off was 81.25 points, with sensitivity of 75.6% and specificity of 81.0%. Based on this cut off, 163 patients were categorized as low-to-intermediate risk and 67 patients as high risk. The incidence of CRKP BSI in the high-risk group was significantly higher than in the low-to-intermediate-risk group [64.2% (43/67) vs. 4.9% (8/163); RR = 13.175 (95%CI was 5.920-29.319), P < 0.001].
CONCLUSIONS: The model, based on 14 routinely available clinical parameters, demonstrated good performance in predicting CRKP BSI risk and may assist clinicians in early identification of high risk patients.