Beginning in 1992, a sustained outbreak of multiresistantAcinetobacter baumannii infections was noted in our 1,000-bed hospital in Barcelona, Spain, resulting in considerable overuse of imipenem, to which the organisms were uniformly susceptible. In January 1997, carbapenem-resistant (CR)A. baumannii strains emerged and rapidly disseminated in the intensive care units (ICUs), prompting us to conduct a prospective investigation. It was an 18-month longitudinal intervention study aimed at the identification of the clinical and microbiological epidemiology of the outbreak and its response to a multicomponent infection control strategy. From January 1997 to June 1998, clinical samples from 153 (8%) of 1,836 consecutive ICU patients were found to contain CR A. baumannii. Isolates were verified to be A. baumannii by restriction analysis of the 16S-23S ribosomal genes and the intergenic spacer region. Molecular typing by repetitive extragenic palindromic sequence-based PCR and pulsed-field gel electrophoresis showed that the emergence of carbapenem resistance was not by the selection of resistant mutants but was by the introduction of two new epidemic clones that were different from those responsible for the endemic. Multivariate regression analysis selected those patients with previous carriage of CR A. baumannii(relative risk [RR], 35.3; 95% confidence interval [CI], 7.2 to 173.1), those patients who had previously received therapy with carbapenems (RR, 4.6; 95% CI, 1.3 to 15.6), or those who were admitted into a ward with a high density of patients infected with CR A. baumannii (RR, 1.7; 95% CI, 1.2 to 2.5) to be at a significantly greater risk for the development of clinical colonization or infection with CR A. baumannii strains. In accordance, a combined infection control strategy was designed and implemented, including the sequential closure of all ICUs for decontamination, strict compliance with cross-transmission prevention protocols, and a program that restricted the use of carbapenem. Subsequently, a sharp reduction in the incidence rates of infection or colonization with A. baumannii, whether resistant or susceptible to carbapenems, was shown, although an alarming dominance of the carbapenem-resistant clones was shown at the end of the study.

An outbreak due to extended-spectrum β-lactamase-producingKlebsiella pneumoniae (ESBL-KP) was detected from May 1993 to June 1995. A total of 145 patients, particularly patients in intensive care units (ICUs) (107 patients [72%]), were colonized or infected. Infection developed in 92 (63%) patients, and primary bacteremia caused by ESBL-KP was the most frequent infection (40 of 92 patients [43%]). A single clone of ESBL-KP was identified by pulsed-field gel electrophoresis analysis throughout the whole period, and no molecular epidemiological relationship could be found between the epidemic strain and non-ESBL-KP isolates. To determine risk factors for ESBL-KP infection weekly rectal swabs were obtained in three serial incidence surveys (470 patients); the probabilities of carriage of ESBL-KP in the digestive tract were 33% (October and November 1993), 40% (May and June 1994), and 0% (October and November 1995) at 10 days of ICU admission. A logistic regression model identified prior carriage of ESBL-KP in the digestive tract (odds ratio, 3.4; 95% confidence interval 1.1 to 10.4) as an independent variable associated with ESBL-KP infection. A statistically significant correlation was observed between the restricted use of oxyimino-β-lactams (189 defined daily doses [DDD]/1,000 patient-days to 24 DDD/1,000 patient-days) and the trends of ESBL-KP infection (r = 0.7; P = 0.03).

Fecal colonization with multiresistant Acinetobacter baumannii was evaluated in 189 consecutive patients in intensive care units (ICUs) during two different 2-month periods (October-November 1993 and May-June 1994). Rectal swabs were obtained weekly from admission to discharge from the ICU. Overall, 77 patients (41%) had multiresistant A. baumannii fecal colonization; colonization was detected in 55 (71%) of the patients within the first week of their ICU stay. Clinical infections due to multiresistant A. baumannii occurred more frequently in patients with fecal colonization than in those without fecal colonization (26% vs. 5%, respectively; P < .001). The reinforcement of isolation measures between study periods reduced both the number of fecal carriers of multiresistant A. baumannii (from 52% to 31%; P < .01) and the number of patients with multiresistant A. baumannii infections (from 17% to 11%; no statistical significance). The digestive tract of ICU patients could be an important epidemiologic reservoir for multiresistant A. baumannii infections in hospital outbreaks. Further prospective studies should be undertaken to define the relative significance of digestive tract colonization compared with other body site colonizations.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...