IMPORTANCEThe effects of chlorhexidine (CHX) mouthwash, selective oropharyngeal decontamination (SOD), and selective digestive tract decontamination (SDD) on patient outcomes in ICUs with moderate to high levels of antibiotic resistance are unknown. OBJECTIVETo determine associations between CHX 2%, SOD, and SDD and the occurrence of ICU-acquired bloodstream infections with multidrug-resistant gram-negative bacteria (MDRGNB) and 28-day mortality in ICUs with moderate to high levels of antibiotic resistance. DESIGN, SETTING, AND PARTICIPANTS Randomized trial conducted from December 1, 2013, to May 31, 2017 European ICUs where at least 5% of bloodstream infections are caused by extendedspectrumβ-lactamase-producingEnterobacteriaceae.Patientswithanticipatedmechanicalventilation of more than 24 hours were eligible. The final date of follow-up was September 20, 2017.INTERVENTIONS Standard care was daily CHX 2% body washings and a hand hygiene improvement program. Following a baseline period from 6 to 14 months, each ICU was assigned in random order to 3 separate 6-month intervention periods with either CHX 2% mouthwash, SOD (mouthpaste with colistin, tobramycin, and nystatin), or SDD (the same mouthpaste and gastrointestinal suspension with the same antibiotics), all applied 4 times daily. MAIN OUTCOMES AND MEASURESThe occurrence of ICU-acquired bloodstream infection with MDRGNB (primary outcome) and 28-day mortality (secondary outcome) during each intervention period compared with the baseline period. RESULTS A total of 8665 patients (median age, 64.1 years; 5561 men [64.2%]) were included in the study (2251, 2108, 2224, and 2082 in the baseline, CHX, SOD, and SDD periods, respectively). ICU-acquired bloodstream infection with MDRGNB occurred among 144 patients (154 episodes) in 2.1%, 1.8%, 1.5%, and 1.2% of included patients during the baseline, CHX, SOD, and SDD periods, respectively. Absolute risk reductions were 0.3% (95% CI, −0.6% to 1.1%), 0.6% (95% CI, −0.2% to 1.4%), and 0.8% (95% CI, 0.1% to 1.6%) for CHX, SOD, and SDD, respectively, compared with baseline. Adjusted hazard ratios were 1.13 (95% CI, 0.68-1.88), 0.89 (95% CI, 0.55-1.45), and 0.70 (95% CI, 0.43-1.14) during the CHX, SOD, and SDD periods, respectively, vs baseline. Crude mortality risks on day 28 were 31.9%, 32.9%, 32.4%, and 34.1% during the baseline, CHX, SOD, and SDD periods, respectively. Adjusted odds ratios for 28-day mortality were 1.07 (95% CI, 0.86-1.32), 1.05 (95% CI, 0.85-1.29), and 1.03 (95% CI, 0.80-1.32) for CHX, SOD, and SDD, respectively, vs baseline. CONCLUSIONS AND RELEVANCE Among patients receiving mechanical ventilation in ICUs with moderate to high antibiotic resistance prevalence, use of CHX mouthwash, SOD, or SDD was not associated with reductions in ICU-acquired bloodstream infections caused by MDRGNB compared with standard care.
BackgroundThe relationship between anti-SARS-CoV-2 humoral immune response, pathogenic inflammation, lymphocytes and fatal COVID-19 is poorly understood.MethodsLongitudinal prospective cohort of hospitalized patients with COVID-19 (N=254) was followed up to 35 d after admission (median, 8 d). We measured early anti-SARS-CoV-2 S1 antibody IgG levels and dynamic (698 samples) of quantitative circulating T, B, NK lymphocyte subsets and serum interleukin-6 response. We used machine learning to identify patterns of the immune response, and related these patterns to the primary outcome of 28-day mortality in analyses adjusted for clinical severity factors.ResultsOverall, 45 (18%) patients died within 28 days after hospitalization. We identified six clusters representing discrete anti-SARS-CoV-2 immunophenotypes. Clusters differed considerably in COVID-19 survival. Two clusters, the anti-S1-IgGlowestTlowestBlowestNKmodIL-6mod, and the anti-S1-IgGhighTlowBmodNKmodIL-6highest had a high risk of fatal COVID-19 (HR, 3.36–21.69; 95% CI, 1.51–163.61 and HR, 8.39–10.79; 95% CI, 1.20–82.67; P≤0.03, respectively). The anti-S1-IgGhighestTlowestBmodNKmodIL-6mod and anti-S1-IgGlowThighestBhighestNKhighestIL-6low cluster were associated with moderate risk of mortality. In contrast, two clusters the anti-S1- anti-S1-IgGhighThighBmodNKmodIL-6low and anti-S1-IgGhighestThighestBhighNKhighIL-6lowest clusters were characterized by a very low risk of mortality.ConclusionsBy employing unsupervised machine learning we identified multiple anti-SARS-CoV-2 immune response clusters and observed major differences in COVID-19 mortality between these clusters. Two discrete immune pathways may lead to fatal COVID-19. One is driven by impaired or delayed antiviral humoral immunity, independently of hyper-inflammation, and the other may arise through excessive IL-6 mediated host inflammation response, independently of the protective humoral response. Those observations could be explored further for application in clinical practice.
Background Repeated rotation of empiric antibiotic treatment strategies is hypothesized to reduce antibiotic resistance. Clinical rotation studies failed to change unit-wide prevalence of antibiotic resistant bacteria (ARB) carriage, including an international cluster-randomized crossover study. Unit-wide effects may differ from individual effects due to “ecological fallacy”. This post-hoc analysis of a cluster-randomized crossover study assesses differences between cycling and mixing rotation strategies in acquisition of carriage with Gram-negative ARB in individual patients. Methods This was a controlled cluster-randomized crossover study in 7 ICUs in 5 European countries. Clinical cultures taken as routine care were used for endpoint assessment. Patients with a first negative culture and at least one culture collected in total were included. Community acquisitions (2 days of admission or less) were excluded. Primary outcome was ICU-acquisition of Enterobacterales species with reduced susceptibility to: third- or fourth generation cephalosporins or piperacillin-tazobactam, and Acinetobacter species and Pseudomonas aeruginosa with reduced susceptibility for piperacillin-tazobactam or carbapenems. Cycling (altering first-line empiric therapy for Gram-negative bacteria, every other 6-weeks), to mixing (changing antibiotic type every empiric antibiotic course). Rotated antibiotics were third- or fourth generation cephalosporins, piperacillin-tazobactam and carbapenems. Results For this analysis 1,613 admissions were eligible (855 and 758 during cycling and mixing, respectively), with 16,437 microbiological cultures obtained. Incidences of acquisition with ARB during ICU-stay were 7.3% (n = 62) and 5.1% (n = 39) during cycling and mixing, respectively (p-value 0.13), after a mean of 17.7 (median 15) and 20.8 (median 13) days. Adjusted odds ratio for acquisition of ARB carriage during mixing was 0.62 (95% CI 0.38 to 1.00). Acquired carriage with ARB were Enterobacterales species (n = 61), Pseudomonas aeruginosa (n = 38) and Acinetobacter species (n = 20), with no statistically significant differences between interventions. Conclusions There was no statistically significant difference in individual patients’ risk of acquiring carriage with Gram-negative ARB during cycling and mixing. These findings substantiate the absence of difference between cycling and mixing on the epidemiology of Gram-negative ARB in ICU. Trial registration This trial is registered with ClinicalTrials.gov, registered 10 January 2011, NCT01293071.
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