CAZ-AVI appears to be a promising drug for treatment of severe KPC-Kp infections, especially those involving bacteremia.

Our analysis indicates that mixed subpopulations of ceftazidime/avibactam-resistant KPC-Kp emerge after ceftazidime/avibactam treatment. The evolution of different subpopulations that are highly resistant to ceftazidime/avibactam likely contributes to treatment failure, thereby highlighting the need for combination treatment strategies to limit selection of ceftazidime/avibactam-resistant KPC-Kp subpopulations.

Improved understanding of risk factors associated with carbapenem-resistant-Klebsiella pneumoniae (CR-KP) infection after liver transplantation (LT) can aid development of effective preventive strategies. We performed a prospective cohort study of all adult patients undergoing LT at our hospital during 30-month period to define risk factors associated with CR-KP infection. All patients were screened for CR-KP carriage by rectal swabs before and after LT. No therapy was administered to decolonize or treat asymptomatic CR-KP carriers. All patients were monitored up to 180 days after LT. Of 237 transplant patients screened, 41 were identified as CR-KP carriers (11 at LT, 30 after LT), and 20 developed CR-KP infection (18 bloodstream-infection, 2 pneumonia) a median of 41.5 days after LT. CR-KP infection rates among patients non-colonized, colonized at LT, and colonized after LT were 2%, 18.2% and 46.7% (p < 0.001). Independent risk factors for CR-KP infection identified by multivariate analysis, included: renal-replacement-therapy; mechanical ventilation > 48 h; HCV recurrence, and colonization at any time with CR-KP. Based on these four variables, we developed a risk score that effectively discriminated patients at low versus higher risk for CR-KP infection (AUC 0.93, 95% CI 0.86-1.00, p < 0.001). Our results may help to design preventive strategies for LT recipients in CR-KP endemic areas.

Objectives We aimed to develop and validate a risk score to predict severe respiratory failure (SRF) among patients hospitalized with coronavirus disease-2019 (COVID-19). Methods We performed a multicentre cohort study among hospitalized (>24 hours) patients diagnosed with COVID-19 from 22 February to 3 April 2020, at 11 Italian hospitals. Patients were divided into derivation and validation cohorts according to random sorting of hospitals. SRF was assessed from admission to hospital discharge and was defined as: Sp o 2 <93% with 100% Fi o 2 , respiratory rate >30 breaths/min or respiratory distress. Multivariable logistic regression models were built to identify predictors of SRF, β-coefficients were used to develop a risk score. Trial Registration NCT04316949 . Results We analysed 1113 patients (644 derivation, 469 validation cohort). Mean (±SD) age was 65.7 (±15) years, 704 (63.3%) were male. SRF occurred in 189/644 (29%) and 187/469 (40%) patients in the derivation and validation cohorts, respectively. At multivariate analysis, risk factors for SRF in the derivation cohort assessed at hospitalization were age ≥70 years (OR 2.74; 95% CI 1.66–4.50), obesity (OR 4.62; 95% CI 2.78–7.70), body temperature ≥38°C (OR 1.73; 95% CI 1.30–2.29), respiratory rate ≥22 breaths/min (OR 3.75; 95% CI 2.01–7.01), lymphocytes ≤900 cells/mm 3 (OR 2.69; 95% CI 1.60–4.51), creatinine ≥1 mg/dL (OR 2.38; 95% CI 1.59–3.56), C-reactive protein ≥10 mg/dL (OR 5.91; 95% CI 4.88–7.17) and lactate dehydrogenase ≥350 IU/L (OR 2.39; 95% CI 1.11–5.11). Assigning points to each variable, an individual risk score (PREDI-CO score) was obtained. Area under the receiver-operator curve was 0.89 (0.86–0.92). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 71.6% (65%–79%), 89.1% (86%–92%), 74% (67%–80%) and 89% (85%–91%), respectively. PREDI-CO score showed similar prognostic ability in the validation cohort: area under the receiver-operator curve 0.85 (0.81–0.88). At a score of >3, sensitivity, specificity, and positive and negative predictive values were 80% (73%–85%), 76% (70%–81%), 69% (60%–74%) and 85% (80%–89%), respectively. Conclusion PREDI-CO score can be useful to allocate resources and prioritize treatments during the COVID-19 pandemic.

MDRO account for nearly one-third of BSI in cirrhotic patients, often resulting in delayed or inadequate empirical antimicrobial therapy and increased mortality rates. Our data suggest that improved prevention and treatment strategies for MDRO are urgently needed in the liver cirrhosis patients.