A Novel Risk Predictive Scoring Model for Predicting Subsequent Infection After Carbapenem-Resistant Gram-Negative Bacteria Colonization in Hematological Malignancy Patients

Abstract

BackgroundThis study investigated the high-risk factors associated with the increased vulnerability for subsequent clinical CR-GNB infection in carbapenem-resistant Gram-negative bacteria (CR-GNB)-colonized hematological malignancy (HM) patients and built a statistical model to predict subsequent infection.MethodAll adult HM patients with positive rectoanal swabs culture for CR-GNB between January 2018 and June 2020 were prospectively followed to assess for any subsequent CR-GNB infections and to investigate the risk factors and clinical features of subsequent infection.ResultsA total of 392 HM patients were enrolled. Of them, 46.7% developed a subsequent clinical CR-GNB infection, with 42 (10.7%) cases of confirmed infection and 141 (36%) cases of clinically diagnosed infection. Klebsiella pneumoniae was the dominant species. The overall mortality rate of patients colonized and infected with CR-GNB was 8.6% and 43.7%. A multivariate analysis showed that remission induction chemotherapy and the duration of agranulocytosis, mucositis, and hypoalbuminemia were significant predictors of subsequent infection after CR-GNB colonization. According to our novel risk-predictive scoring model, the high-risk group were >3 times more likely to develop a subsequent infection in comparison with the low-risk group.ConclusionOur risk-predictive scoring model can early and accurately predict a subsequent CR-GNB infection in HM patients with CR-GNB colonization. The early administration of CR-GNB-targeted empirical therapy in the high-risk group is strongly recommended to decrease their mortality.

Carbapenem-resistant gram-negative bacterial infection in intensive care unit patients: Antibiotic resistance analysis and predictive model development

“…Recently, several predictive models have been proposed for subsequent infections after CR-GNB colonization in different types of diseases. In the study of Wu et al (Wu et al, 2022), after reviewing the data of patients with hematological malignancy (n = 437), they constructed a scoring model based on mucositis, duration of agranulocytosis, hypoalbuminemia and remission induction chemotherapy, which could stratify high-risk from low-risk patients with an OR (95%CI) of 3.347 (2.218-5.094) and AUC of 0.708. However, they did not investigate the different strains of CR-GNB nor validate their findings.…”

A Visualized Mortality Prediction Score Model in Hematological Malignancies Patients with Carbapenem-Resistant Organisms Bloodstream Infection

“…Vitek ® 2 automated system (France Biomerieux) and matrix-assisted laser-desorption ionization time-of-flight mass spectrometry (Bruker Daltonics Inc., Billerica, Massachusetts) were used to bacterial identification and drug sensitivity tests. 15 The identification of drug resistance both by disk diffusion method (K-B method) and broth microdilution (BMD), BMD was used to determine MICs. For tigecycline and colistin, the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoint was used, the rest of antibiotics were interpreted according to the standard of the CLSI document.…”