Purpose In the critically ill, hospital-acquired bloodstream infections (HA-BSI) are associated with significant mortality. Granular data are required for optimizing management, and developing guidelines and clinical trials. Methods We carried out a prospective international cohort study of adult patients (≥ 18 years of age) with HA-BSI treated in intensive care units (ICUs) between June 2019 and February 2021. Results 2600 patients from 333 ICUs in 52 countries were included. 78% HA-BSI were ICU-acquired. Median Sequential Organ Failure Assessment (SOFA) score was 8 [IQR 5; 11] at HA-BSI diagnosis. Most frequent sources of infection included pneumonia (26.7%) and intravascular catheters (26.4%). Most frequent pathogens were Gram-negative bacteria (59.0%), predominantly Klebsiella spp. (27.9%), Acinetobacter spp . (20.3%), Escherichia coli (15.8%), and Pseudomonas spp . (14.3%). Carbapenem resistance was present in 37.8%, 84.6%, 7.4%, and 33.2%, respectively. Difficult-to-treat resistance (DTR) was present in 23.5% and pan-drug resistance in 1.5%. Antimicrobial therapy was deemed adequate within 24 h for 51.5%. Antimicrobial resistance was associated with longer delays to adequate antimicrobial therapy. Source control was needed in 52.5% but not achieved in 18.2%. Mortality was 37.1%, and only 16.1% had been discharged alive from hospital by day-28. Conclusions HA-BSI was frequently caused by Gram-negative, carbapenem-resistant and DTR pathogens. Antimicrobial resistance led to delays in adequate antimicrobial therapy. Mortality was high, and at day-28 only a minority of the patients were discharged alive from the hospital. Prevention of antimicrobial resistance and focusing on adequate antimicrobial therapy and source control are important to optimize patient management and outcomes. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-022-06944-2.

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Background and Aims Acute kidney injury (AKI) is one of the most common and severe complications in intensive care units’ (ICU) patients. It is associated with worst outcomes, such as longer hospital stays and higher mortality. In the past years three consensus have been developed to provide uniform identification of AKI in clinical practice. An ideal classification should be sensitive but also correlate with the outcomes. RIFLE and AKIN have been exhaustively studied in critical patients. In the studies made until date, KDIGO classifications seems to be as sensitive as the other two. With this study the authors intend to compare the three systems of AKI classification in an ICU population. Method Retrospective observational study with descriptive and bivariate analysis using SPSS Statistics. Demographic and laboratory studies were collected from the patient’s charts. The authors included patients who were admitted to a polyvalent ICU in the first six months of 2019. The exclusion criteria were patients under 18 years old, pregnant women, stage 5 chronic kidney disease and less than 24 hours ICU stays. Only the serum creatinine, and not urine output, was used as criteria to the three classifications. Results A total of 130 patients were studied. The mean age was 62.20±15.78 years (min 19; max 87) and 54.6% (n=71) were male. Medical causes were the most frequent type of admission (n=82; 63.1%). The median length of ICU and hospital stays were 6.50±9.19 days (min 2; max 48) and 23.00±25.68 days (min 2; max 126) respectively. The mortality rate in ICU and hospital were, respectively, 9.2% (n=12) and 20% (n=26). Eight patients (6.2%) needed renal replacement therapy. KDIGO classification identified more patients with AKI than RIFLE (p<0.001) and AKIN (p<0.001). There were no statistically differences between the median length of ICU (p=0.191 for KDIGO, p=0.257 for AKIN and p=0.223 for RIFLE) or hospital (p=0.762 for KDIGO, p=0.096 for AKIN and p=0.105 for RIFLE) stays between the patients with and without AKI by the 3 classifications. There was a significant statistically association between mortality in the ICU and AKI for KDIGO (p=0.008) and AKIN (p=0.004) classifications, but not for RIFLE (p=0.167). Likewise, there was also an association between mortality in the hospital and AKI patients identified by KDIGO (p<0.0001) and AKIN (p=0.001) classifications, but not with RIFLE (p=0.054). The AKI patients that were identified by KDIGO criteria but not by AKIN did not have and association with ICU mortality (p=0.28) but did have a statically significant association with hospital death (p=0.026) with an odds ratio of 4 (CI 95% [1.229-13.018]). Conclusion The authors concluded that KDIGO classification is the most sensitive of the three for AKI in critical patients. There were no differences in the length of ICU or hospital stays between the 3 classifications cases identified. On the other hand, there was a statistically association between KDIGO and AKIN cases with ICU and hospital mortality, but not with RIFLE. Still, patients who are identified by KDIGO but not by AKIN criteria have an odd 4 times higher to die in the hospital. This means that KDIGO classification is the most sensitive and correlates better with outcomes in critical patients with AKI than the other two.