Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease.

BACKGROUND: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). METHODS: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. RESULTS: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with ≈20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. CONCLUSIONS: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.Analyses supported by the UK Medical Research Council (MR/M012190/1), Cancer Research UK (C8221/A19170 and 570/A16491), and the Wellcome Trust (Our Planet Our Health, Livestock Environment and People 205212/Z/16/Z). EPIC-CVD has been supported by the European Union Framework 7 (HEALTH-F2-2012-279233), the European Research Council (268834), the UK Medical Research Council (G0800270 and MR/L003120/1), the British Heart Foundation (SP/09/002 and RG/08/014 and RG13/13/30194), and the UK National Institute of Health Research. The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Générale de l’Education Nationale, Institut National de la Santé et de la Recherche Médicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); the Hellenic Health Foundation (Greece); Italian Association for Research on Cancer (AIRC), National Research Council (Italy) and MIUR "Dipartimenti di Eccellenza"(Project D15D18000410001) to the Department of Medical Sciences (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andalucía, Asturias, Basque Country, Murcia (no. 6236) and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skåne and Västerbotten (Sweden); Cancer Research UK (14136 to EPICNorfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), UK Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford, MC_UU_12015/1 (CL, NJW), and MC_UU_12015/5 (NF), and NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme (IS-BRC-1215-20014) to the MRC Epidemiology Unit Cambridge. Kathryn Bradbury holds the Girdlers’ New Zealand Health Research Council Fellowship. Marinka Steur received Core MRC Unit support through the Nutritional Epidemiology Programme (MC_UU_12015/5) whilst at the MRC Epidemiology Unit, and received funding from the Alpro Foundation whilst at the Cardiovascular Epidemiology Unit. JD holds a BHF Professorship, NIHR Senior Investigator Award, and ERC Senior Investigator Award. The funders play no role in the design of the study; the collection, analysis, and interpretation of the data; or the decision to approve publication of the finished manuscript. The authors assume full responsibility for analyses and interpretation of these data

Daily Chlorhexidine Bathing in General Hospital Units – Results of the ABATE Infection Trial (Active BAThing to Eliminate Infection)

Abstract Background: Universal decolonization with daily chlorhexidine (CHG) bathing with and without nasal decolonization has significantly reduced positive MRSA clinical cultures and bloodstream infections in adult ICUs in several clinical trials. We evaluated whether decolonization was similarly effective in a lower risk hospitalized population. Methods: We conducted a 2 arm cluster-randomized trial involving a 1-year baseline period (April 2013–March 2014) and a 21-month intervention period (June 2014–February 2016). All noncritical care units in a hospital were assigned to the same strategy. These were (1) Routine Care: routine bathing product and frequency and (2) Decolonization: CHG for routine daily bathing (2% leave-on CHG) or showering (4% rinse-off CHG) for all patients plus mupirocin for 5 days for known MRSA. Universal ICU decolonization was in place in both arms by September 2013. Differences between the arms in the outcome rates between the baseline and intervention periods were assessed with proportional hazards models, using shared frailties to account for clustering by hospital. The primary analysis was as-randomized and unadjusted. Primary outcome was any MRSA or VRE clinical isolate attributable to the unit. Secondary outcome was all-cause bloodstream infections. Additional analyses adjusted for age, gender, race, Medicaid insurer, surgery, and comorbidities. Results: We randomized 53 hospitals in 15 states. There were 194 adult units with 189,616 admissions in the baseline period and 340,350 in the intervention period. Common unit types included mixed medical surgical (30%), cardiac (20%), step-down (11%), medical (10%), surgical (10%), and oncology (4%). There were no significant differences between arms in the relative hazards for intervention vs. baseline for either outcome (Table and Figure). Adjusted analyses yielded similar results. Conclusion: Universal daily CHG bathing or showering plus targeted mupirocin for MRSA+ patients in non-critical care units did not reduce the combination of positive MRSA and VRE clinical cultures or bloodstream infections due to all pathogens. Further analyses to assess for any differential effects in high-risk subpopulations will be important. Disclosures S. S. Huang, Sage Products: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Xttrium Laboratories: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Clorox: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; 3M: Receipt of contributed product, Conducting studies in which participating healthcare facilities are receiving contributed product (no contribution in submitted abstract), Participating healthcare facilities in my studies received contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; E. Septimus, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; K. Kleinman, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Moody, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Hickok, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. Heim, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; A. Gombosev, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; 3M: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Avery, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design K. Haffenreffer, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; L. Shimelman, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; M. K. Hayden, OpGen, Inc.: Receipt of donated laboratory services for project, Research support; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. A. Weinstein, Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; OpGen Inc.: Receipt of donated laboratory services for project, Research support; C. Spencer-Smith, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. E. Kaganov, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. V. Murphy, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; T. Forehand, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Lankiewicz, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; M. H. Coady, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; received research funds from Clorox, but Clorox has no role in the design.; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; L. M. Portillo, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Patel Sarup, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; J. Perlin, Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Clorox: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; R. Platt, Clorox: Receipt of contributed product, Conducting clinical studies in which participating healthcare facilities are receiving contributed product; receive research funds from Clorox, but Clorox has no role in the design; Molnlycke: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Sage Products: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed product; Xttrium: Receipt of contributed product, Conducting studies in healthcare facilities that are receiving contributed produc

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world\u27s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Global maps of soil temperature.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km2 resolution for 0-5 and 5-15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1-km2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Revisiting cytomegalovirus serology in allogeneic hematopoietic cell transplant recipients

Background: Allogeneic hematopoietic cell transplant recipients (allo-HCTR) with positive CMV serology may have false positive results due to blood product transfusions associated passive immunity. Methods: This is a single-center cohort study including consecutive adult allo-HCTR (01.01.2018-31.12.2022) with negative baseline (at hematologic malignancy diagnosis) and indeterminate or low-positive (CMV-IgG-titer: ≥ 0.6-&lt;50 U/mL) pretransplant CMV-serology with negative pretransplant plasma CMV DNAemia. The CMV serology status of those patients was reclassified from R + to R- (CMVR- reclassification group). We compared those patients to allo-HCTR with negative (CMV-IgG-titer &lt; 0.6 U/mL) pretransplant CMV IgG serology (CMVR- group). We describe the number and type of patients, whose pretransplant CMV serology status was reclassified from indeterminate/positive to negative. Moreover, we reviewed all plasma CMV DNAemia tests performed during the first 6 months posttransplant in both groups, to assess the safety of this approach. Results: Amongst 246 (84.5%) of 291 transplanted patients identified as CMVR + pretransplant, 60/246 (24.4%) were reclassified from CMV serology indeterminate (N:10) or low-positive (N:50) to R-. Only 1/60 (1.67%) patient in the CMVR- reclassification group vs 3/44(6.8%; p = 0.30) in the CMVR- group developed CMV-DNAemia during the 6-month posttransplant follow-up period. There were no significant differences in the number of CMV-DNAemia tests performed, CMV-DNAemia range and time posttransplant between the two groups. Conclusion: One out of four allo-HCT CMVR + may be falsely flagged as R+, with significant impact on donor selection and prophylaxis administration. A 2-step approach including CMV-serology testing at hematologic malignancy diagnosis in allo-HCTR candidates and careful review of pretransplant CMV IgG-titers may help correctly classify CMV-serology status.</p

Consumption of Meat, Fish, Dairy Products, and Eggs and Risk of Ischemic Heart Disease A Prospective Study of 7198 Incident Cases Among 409 885 Participants in the Pan-European EPIC Cohort

Background: There is uncertainty about the relevance of animal foods to the pathogenesis of ischemic heart disease (IHD). We examined meat, fish, dairy products, and eggs and risk for IHD in the pan-European EPIC cohort (European Prospective Investigation Into Cancer and Nutrition). Methods: In this prospective study of 409 885 men and women in 9 European countries, diet was assessed with validated questionnaires and calibrated with 24-hour recalls. Lipids and blood pressure were measured in a subsample. During a mean of 12.6 years of follow-up, 7198 participants had a myocardial infarction or died of IHD. The relationships of animal foods with risk were examined with Cox regression with adjustment for other animal foods and relevant covariates. Results: The hazard ratio (HR) for IHD was 1.19 (95% CI, 1.06-1.33) for a 100-g/d increment in intake of red and processed meat, and this remained significant after exclusion of the first 4 years of follow-up (HR, 1.25 [95% CI, 1.09-1.42]). Risk was inversely associated with intakes of yogurt (HR, 0.93 [95% CI, 0.89-0.98] per 100-g/d increment), cheese (HR, 0.92 [95% CI, 0.86-0.98] per 30-g/d increment), and eggs (HR, 0.93 [95% CI, 0.88-0.99] per 20-g/d increment); the associations with yogurt and eggs were attenuated and nonsignificant after exclusion of the first 4 years of follow-up. Risk was not significantly associated with intakes of poultry, fish, or milk. In analyses modeling dietary substitutions, replacement of 100 kcal/d from red and processed meat with 100 kcal/d from fatty fish, yogurt, cheese, or eggs was associated with approximate to 20% lower risk of IHD. Consumption of red and processed meat was positively associated with serum non-high-density lipoprotein cholesterol concentration and systolic blood pressure, and consumption of cheese was inversely associated with serum non-high-density lipoprotein cholesterol. Conclusions: Risk for IHD was positively associated with consumption of red and processed meat and inversely associated with consumption of yogurt, cheese, and eggs, although the associations with yogurt and eggs may be influenced by reverse causation bias. It is not clear whether the associations with red and processed meat and cheese reflect causality, but they were consistent with the associations of these foods with plasma non-high-density lipoprotein cholesterol and for red and processed meat with systolic blood pressure, which could mediate such effects.Peer reviewe

Chlorhexidine versus routine bathing to prevent multidrug-resistant organisms and all-cause bloodstream infections in general medical and surgical units (ABATE Infection trial): a cluster-randomised trial.

BackgroundUniversal skin and nasal decolonisation reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonisation on pathogens and infections in non-critical-care units is unknown. The aim of the ABATE Infection trial was to evaluate the use of chlorhexidine bathing in non-critical-care units, with an intervention similar to one that was found to reduce multidrug-resistant organisms and bacteraemia in intensive care units.MethodsThe ABATE Infection (active bathing to eliminate infection) trial was a cluster-randomised trial of 53 hospitals comparing routine bathing to decolonisation with universal chlorhexidine and targeted nasal mupirocin in non-critical-care units. The trial was done in hospitals affiliated with HCA Healthcare and consisted of a 12-month baseline period from March 1, 2013, to Feb 28, 2014, a 2-month phase-in period from April 1, 2014, to May 31, 2014, and a 21-month intervention period from June 1, 2014, to Feb 29, 2016. Hospitals were randomised and their participating non-critical-care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The primary outcome was MRSA or vancomycin-resistant enterococcus clinical cultures attributed to participating units, measured in the unadjusted, intention-to-treat population as the HR for the intervention period versus the baseline period in the decolonisation group versus the HR in the routine care group. Proportional hazards models assessed differences in outcome reductions across groups, accounting for clustering within hospitals. This trial is registered with ClinicalTrials.gov, number NCT02063867.FindingsThere were 189 081 patients in the baseline period and 339 902 patients (156 889 patients in the routine care group and 183 013 patients in the decolonisation group) in the intervention period across 194 non-critical-care units in 53 hospitals. For the primary outcome of unit-attributable MRSA-positive or VRE-positive clinical cultures (figure 2), the HR for the intervention period versus the baseline period was 0·79 (0·73-0·87) in the decolonisation group versus 0·87 (95% CI 0·79-0·95) in the routine care group. No difference was seen in the relative HRs (p=0·17). There were 25 (&lt;1%) adverse events, all involving chlorhexidine, among 183 013 patients in units assigned to chlorhexidine, and none were reported for mupirocin.InterpretationDecolonisation with universal chlorhexidine bathing and targeted mupirocin for MRSA carriers did not significantly reduce multidrug-resistant organisms in non-critical-care patients.FundingNational Institutes of Health

Chlorhexidine versus routine bathing to prevent multidrug-resistant organisms and all-cause bloodstream infections in general medical and surgical units (ABATE Infection trial): a cluster-randomised trial.

BACKGROUND:Universal skin and nasal decolonisation reduces multidrug-resistant pathogens and bloodstream infections in intensive care units. The effect of universal decolonisation on pathogens and infections in non-critical-care units is unknown. The aim of the ABATE Infection trial was to evaluate the use of chlorhexidine bathing in non-critical-care units, with an intervention similar to one that was found to reduce multidrug-resistant organisms and bacteraemia in intensive care units. METHODS:The ABATE Infection (active bathing to eliminate infection) trial was a cluster-randomised trial of 53 hospitals comparing routine bathing to decolonisation with universal chlorhexidine and targeted nasal mupirocin in non-critical-care units. The trial was done in hospitals affiliated with HCA Healthcare and consisted of a 12-month baseline period from March 1, 2013, to Feb 28, 2014, a 2-month phase-in period from April 1, 2014, to May 31, 2014, and a 21-month intervention period from June 1, 2014, to Feb 29, 2016. Hospitals were randomised and their participating non-critical-care units assigned to either routine care or daily chlorhexidine bathing for all patients plus mupirocin for known methicillin-resistant Staphylococcus aureus (MRSA) carriers. The primary outcome was MRSA or vancomycin-resistant enterococcus clinical cultures attributed to participating units, measured in the unadjusted, intention-to-treat population as the HR for the intervention period versus the baseline period in the decolonisation group versus the HR in the routine care group. Proportional hazards models assessed differences in outcome reductions across groups, accounting for clustering within hospitals. This trial is registered with ClinicalTrials.gov, number NCT02063867. FINDINGS:There were 189 081 patients in the baseline period and 339 902 patients (156 889 patients in the routine care group and 183 013 patients in the decolonisation group) in the intervention period across 194 non-critical-care units in 53 hospitals. For the primary outcome of unit-attributable MRSA-positive or VRE-positive clinical cultures (figure 2), the HR for the intervention period versus the baseline period was 0·79 (0·73-0·87) in the decolonisation group versus 0·87 (95% CI 0·79-0·95) in the routine care group. No difference was seen in the relative HRs (p=0·17). There were 25 (&lt;1%) adverse events, all involving chlorhexidine, among 183 013 patients in units assigned to chlorhexidine, and none were reported for mupirocin. INTERPRETATION:Decolonisation with universal chlorhexidine bathing and targeted mupirocin for MRSA carriers did not significantly reduce multidrug-resistant organisms in non-critical-care patients. FUNDING:National Institutes of Health