Establishing the safety of selective digestive decontamination within the ICU population: a bridge too far?

Abstract

Background: Infection prevention interventions within the intensive care unit (ICU) setting, whether studied within quality improvement projects or cluster randomized trials (CRT), are seen as low risk and grounded in an ethical imperative. Selective digestive decontamination (SDD) appears highly effective at preventing ICU infections within randomized concurrent control trials (RCCTs) prompting mega-CRTs with mortality as the primary endpoint.

Findings: Surprisingly, the summary results of RCCTs versus CRTs differ strikingly, being respectively, a 15-percentage-point versus a zero-percentage-point ICU mortality difference between control versus SDD intervention groups. Multiple other discrepancies are equally puzzling and contrary to both prior expectations and the experience within population-based studies of infection prevention interventions using vaccines. Could spillover effects from SDD conflate the RCCT control group event rate differences and represent population harm? Evidence that SDD is fundamentally safe to concurrent non-recipients in ICU populations is absent. A postulated CRT to realize this, the SDD Herd Effects Estimation Trial (SHEET), would require > 100 ICUs to achieve sufficient statistical power to find a two-percentage-point mortality spillover effect. Moreover, as a potentially harmful population-based intervention, SHEET would pose novel and insurmountable ethical issues including who is the research subject; whether informed consent is required and from whom; whether there is equipoise; the benefit versus the risk; considerations of vulnerable groups; and who should be the gatekeeper?

Conclusion: The basis for the mortality difference between control and intervention groups of SDD studies remains unclear. Several paradoxical results are consistent with a spillover effect that would conflate the inference of benefit originating from RCCTs. Moreover, this spillover effect would constitute to herd peril.

Keywords: Antibiotic prophylaxis; Bacteremia; Herd peril; Intensive care; Mechanical ventilation; Selective digestive decontamination; Study design.

Fig. 1

The ICU mortality incidence for the component (C = control ○; I = intervention Δ) groups (graded by group size) of individual studies of infection prevention interventions among patients receiving MV. Groups originating from RCCTs of interventions studied included non-antimicrobial-based methods (n = 81), topical anti-septic-based methods (n = 22) or topical antibiotic-based methods (n = 64). The overall benchmark being the summary mean (central vertical line) derived from the observational studies (Ob = observational; n = 43) is displayed together with the 95% confidence limits (CIs, horizontal error bars) associated with the summary incidence for each category. These 95% CIs were calculated using random effect methods as described in [52]. One control and one intervention group from each of five mega-CRTs (more than 10 ICUs) (c = CHORAL [69]; d = de Smet [44]; o = Oosterdijk [45]; s = SuDDICU [47]; w = Wittekamp [46]) and median control and intervention group mortality for five large Systematic reviews (more than 4 studies) (|= Bo [15]; ↓ = Gillies [12]; |= Zhao (Toothbrushing ± antispetic) [17]; ↓ = Hua (Topical Chlorhexidine) [16]; ↓ = Minozzi (TAP + PPAP) [7]; |= Minozzi (TAP alone)) [7] are indicated. Note the x-axis is a logit scale. The figure is adapted from reference [52]. and used here under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)

Fig. 2

SHEET trial design. ICUs (n = 52) are cluster randomized to be either a TAP (half red ICUs) or a non-decontamination (i.e. non-antimicrobial) intervention (half blue ICUs) ICU in period 1 and to then cross over after a washout period. Within each ICU, all eligible MV patients are individually randomized to receive either the investigation agent (closed symbol ●) assigned to that ICU or not (open symbol ○). The SHEET trial is designed to enable the estimation of the indirect (population level) effect of TAP on mortality (spillover effect of the red colour onto the yellow) within ICUs. The washout period is necessary to enable any patients that have received the agent to be discharged from the ICU and any contextual effects associated with each investigational agent to dissipate. In previous CRTs, this period has been 3 months. Period 1 and period 2 are anticipated to be 12 months each. SHEET trial analysis. The RCCT component estimates the direct effect of each intervention at the level of individual patients by comparing the mortality among the patients randomly assigned to receive it or not within each ICU. The CRT component estimates the indirect effect of TAP at the population level by comparing the mortality among the patients randomly assigned to not receive the investigation agent (yellow half) within each ICU. The analysis presumes that the non-decontamination intervention will have no effect (direct or indirect) on mortality, as generally observed previously. The expected effects of TAP on mortality would be a lower mortality in those patient populations receiving TAP as the investigational agent versus those populations receiving the non-decontamination intervention. There is no capacity within the SHEET trial to estimate the possibility of any reverse spillover effect, that is the indirect effect from patients not receiving TAP on mortality (spillover effect of the yellow colour onto the red) within ICUs. This would require benchmarking the mortality among patients receiving TAP within the SHEET trial against the mortality among the four TAP CRTs in the literature

Fig. 3

A benchmark ICU mortality of 23% as derived previously is used to represent the background mortality rate without intervention [52]. The intra-cluster coefficient (ICC) used in power calculations in previous mega-CRTs ranged between 0.001 and 0.01 (Table 2). Using these estimates, a study with 104 clusters (ICUs) each with 150 patients (75 directly and 75 indirectly exposed), (or 52 ICUs with a two-period crossover design), and an ICC of 0.001 (left panel), would have an 80% power to detect a 2% absolute increase (or decrease) in mortality at a 0.05 level of significance (using Stata command ‘power twoproportions .23 .25, m1(75) m2(75) rho(0.001)’). A two-period study with crossover would require 52 ICUs for the same power. With an ICC of 0.01 (right panel), the number of ICUs required increases to 168 (‘power twoproportions .23 .25, m1(75) m2(75) rho(0.01)’) (or 84 ICUs for a two-period crossover)