Nasal Iodophor Antiseptic vs Nasal Mupirocin Antibiotic in the Setting of Chlorhexidine Bathing to Prevent Infections in Adult ICUs: A Randomized Clinical Trial.

Importance: Universal nasal mupirocin plus chlorhexidine gluconate (CHG) bathing in intensive care units (ICUs) prevents methicillin-resistant Staphylococcus aureus (MRSA) infections and all-cause bloodstream infections. Antibiotic resistance to mupirocin has raised questions about whether an antiseptic could be advantageous for ICU decolonization. Objective: To compare the effectiveness of iodophor vs mupirocin for universal ICU nasal decolonization in combination with CHG bathing. Design, Setting, and Participants: Two-group noninferiority, pragmatic, cluster-randomized trial conducted in US community hospitals, all of which used mupirocin-CHG for universal decolonization in ICUs at baseline. Adult ICU patients in 137 randomized hospitals during baseline (May 1, 2015-April 30, 2017) and intervention (November 1, 2017-April 30, 2019) were included. Intervention: Universal decolonization involving switching to iodophor-CHG (intervention) or continuing mupirocin-CHG (baseline). Main Outcomes and Measures: ICU-attributable S aureus clinical cultures (primary outcome), MRSA clinical cultures, and all-cause bloodstream infections were evaluated using proportional hazard models to assess differences from baseline to intervention periods between the strategies. Results were also compared with a 2009-2011 trial of mupirocin-CHG vs no decolonization in the same hospital network. The prespecified noninferiority margin for the primary outcome was 10%. Results: Among the 801 668 admissions in 233 ICUs, the participants' mean (SD) age was 63.4 (17.2) years, 46.3% were female, and the mean (SD) ICU length of stay was 4.8 (4.7) days. Hazard ratios (HRs) for S aureus clinical isolates in the intervention vs baseline periods were 1.17 for iodophor-CHG (raw rate: 5.0 vs 4.3/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 4.1 vs 4.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 18.4% [95% CI, 10.7%-26.6%] for mupirocin-CHG, P < .001). For MRSA clinical cultures, HRs were 1.13 for iodophor-CHG (raw rate: 2.3 vs 2.1/1000 ICU-attributable days) and 0.99 for mupirocin-CHG (raw rate: 2.0 vs 2.0/1000 ICU-attributable days) (HR difference in differences significantly lower by 14.1% [95% CI, 3.7%-25.5%] for mupirocin-CHG, P = .007). For all-pathogen bloodstream infections, HRs were 1.00 (2.7 vs 2.7/1000) for iodophor-CHG and 1.01 (2.6 vs 2.6/1000) for mupirocin-CHG (nonsignificant HR difference in differences, -0.9% [95% CI, -9.0% to 8.0%]; P = .84). Compared with the 2009-2011 trial, the 30-day relative reduction in hazards in the mupirocin-CHG group relative to no decolonization (2009-2011 trial) were as follows: S aureus clinical cultures (current trial: 48.1% [95% CI, 35.6%-60.1%]; 2009-2011 trial: 58.8% [95% CI, 47.5%-70.7%]) and bloodstream infection rates (current trial: 70.4% [95% CI, 62.9%-77.8%]; 2009-2011 trial: 60.1% [95% CI, 49.1%-70.7%]). Conclusions and Relevance: Nasal iodophor antiseptic did not meet criteria to be considered noninferior to nasal mupirocin antibiotic for the outcome of S aureus clinical cultures in adult ICU patients in the context of daily CHG bathing. In addition, the results were consistent with nasal iodophor being inferior to nasal mupirocin. Trial Registration: ClinicalTrials.gov Identifier: NCT03140423.

Decolonization in Nursing Homes to Prevent Infection and Hospitalization.

BACKGROUND: Nursing home residents are at high risk for infection, hospitalization, and colonization with multidrug-resistant organisms. METHODS: We performed a cluster-randomized trial of universal decolonization as compared with routine-care bathing in nursing homes. The trial included an 18-month baseline period and an 18-month intervention period. Decolonization entailed the use of chlorhexidine for all routine bathing and showering and administration of nasal povidone-iodine twice daily for the first 5 days after admission and then twice daily for 5 days every other week. The primary outcome was transfer to a hospital due to infection. The secondary outcome was transfer to a hospital for any reason. An intention-to-treat (as-assigned) difference-in-differences analysis was performed for each outcome with the use of generalized linear mixed models to compare the intervention period with the baseline period across trial groups. RESULTS: Data were obtained from 28 nursing homes with a total of 28,956 residents. Among the transfers to a hospital in the routine-care group, 62.2% (the mean across facilities) were due to infection during the baseline period and 62.6% were due to infection during the intervention period (risk ratio, 1.00; 95% confidence interval [CI], 0.96 to 1.04). The corresponding values in the decolonization group were 62.9% and 52.2% (risk ratio, 0.83; 95% CI, 0.79 to 0.88), for a difference in risk ratio, as compared with routine care, of 16.6% (95% CI, 11.0 to 21.8; P<0.001). Among the discharges from the nursing home in the routine-care group, transfer to a hospital for any reason accounted for 36.6% during the baseline period and for 39.2% during the intervention period (risk ratio, 1.08; 95% CI, 1.04 to 1.12). The corresponding values in the decolonization group were 35.5% and 32.4% (risk ratio, 0.92; 95% CI, 0.88 to 0.96), for a difference in risk ratio, as compared with routine care, of 14.6% (95% CI, 9.7 to 19.2). The number needed to treat was 9.7 to prevent one infection-related hospitalization and 8.9 to prevent one hospitalization for any reason. CONCLUSIONS: In nursing homes, universal decolonization with chlorhexidine and nasal iodophor led to a significantly lower risk of transfer to a hospital due to infection than routine care. (Funded by the Agency for Healthcare Research and Quality; Protect ClinicalTrials.gov number, NCT03118232.).

Matching in cluster randomized trials using the Goldilocks Approach.

In group or cluster-randomized trials (GRTs), matching is a technique that can be used to improve covariate balance. When baseline data are available, we suggest a strategy that can be used to achieve the desired balance between treatment and control groups across numerous potential confounding variables. This strategy minimizes the overall within-pair Mahalanobis distance; and involves iteratively: 1) making pairs that minimize the distance between pairs of clusters with respect to potentially confounding variables; 2) visually assessing the potential effects of these pairs and resulting possible randomizations; and 3) reweighting variables of selecting weights to make pairs of clusters. In step 2, we plot the between-arm differences with a parallel-coordinates plot. Investigators can compare plots of different weighting schemes to determine the one that best suits their needs prior to the actual, final, randomization. We demonstrate application of the approach with the Mupirocin-Iodophor Swap Out trial. A webapp is provided.

Statistical methods for testing carryover effects: A mixed effects model approach.

Carryover, or the effects of treatment after it ceases, has been largely ignored in statistical literature except as a nuisance parameter. When testing for carryover, comparing cumulative incidence rates is biased when diagnosis is based on a noisy measurement crossing a threshold (such as in blood pressure) then followed by open-label treatment. This issue was raised in the context of preventing hypertension by the TROPHY trial. We show that modelling the noisy measurement itself using linear mixed effect models, then computing the expected proportion over the threshold, gives valid tests and consistent estimates. The key insight is that the data made unavailable by open-label treatment after diagnosis are missing at random. We demonstrate the analysis in simulations based on a large set of blood pressure measurements from a New Zealand healthcare organisation and show that properly specified random effects models accurately estimate carryover effects even in the presence of data censored at diagnosis.

Testing for carryover effects after cessation of treatments: a design approach.

BACKGROUND: Recently, trials addressing noisy measurements with diagnosis occurring by exceeding thresholds (such as diabetes and hypertension) have been published which attempt to measure carryover - the impact that treatment has on an outcome after cessation. The design of these trials has been criticised and simulations have been conducted which suggest that the parallel-designs used are not adequate to test this hypothesis; two solutions are that either a differing parallel-design or a cross-over design could allow for diagnosis of carryover. METHODS: We undertook a systematic simulation study to determine the ability of a cross-over or a parallel-group trial design to detect carryover effects on incident hypertension in a population with prehypertension. We simulated blood pressure and focused on varying criteria to diagnose systolic hypertension. RESULTS: Using the difference in cumulative incidence hypertension to analyse parallel-group or cross-over trials resulted in none of the designs having acceptable Type I error rate. Under the null hypothesis of no carryover the difference is well above the nominal 5 % error rate. CONCLUSIONS: When a treatment is effective during the intervention period, reliable testing for a carryover effect is difficult. Neither parallel-group nor cross-over designs using the difference in cumulative incidence appear to be a feasible approach. Future trials should ensure their design and analysis is validated by simulation.