Measuring the microbiome of chronic wounds with use of a topical antimicrobial dressing – A feasibility study

Background Polymicrobial communities colonize all wounds, and biofilms are hypothesized to be a key link to the chronic state and stalled healing. Molecular methods offer greater insight when studying microbial ecology in chronic wounds, as only a small fraction of wound bacteria are cultured by currently available methods and studies have shown little agreement between culture and molecular based approaches. Some interventions, like dressings with oxidized silver, are reported to help the stalled wounds move to a normal healing trajectory but the underlying mechanisms are difficult to measure. One hypothesis is that the use of topical antimicrobial dressings targets the wound microbiome and reduces bioburden. Objectives Our objective was to determine if culture-independent molecular methods could be used to identify the microbial composition in chronic wounds, and measure the microbiome over time when a topical antimicrobial dressing is used to reduce bioburden. Methods Patients with chronic wounds defined as >6 weeks in duration and not taking systemic antibiotics were recruited to participate. A wound contact layer containing silver oxynitrate was applied immediately after routine sharp debridement material was collected and swabs of the wound bed taken. Next-generation sequencing of the bacterial 16S rRNA gene in each specimen was used to measure the microbiome. Results Distinct bacterial communities were observed between swab and debridement samples, highlighting spatial differences and the importance of sampling consistency. The microbial communities appeared to be similar between different diabetes statuses, but different among the three wound categories included. Conclusions Culture-independent methods can be applied to measure the microbiome of chronic wounds even when a topical antimicrobial dressing is applied to the wound.


Introduction
Background 2 Scientific background and explanation of rationale Theories used in designing behavioral interventions

Methods
Participants 3 Eligibility criteria for participants, including criteria at different levels in recruitment/sampling plan (e.g., cities, clinics, subjects) Method of recruitment (e.g., referral, self-selection), including the sampling method if a systematic sampling plan was implemented Recruitment setting Settings and locations where the data were collected Interventions 4 Details of the interventions intended for each study condition and how and when they were actually administered, specifically including: Unit of assignment (the unit being assigned to study condition, e.g., individual, group, community) Method used to assign units to study conditions, including details of any restriction (e.g., blocking, stratification, minimization) Inclusion of aspects employed to help minimize potential bias induced due to non-randomization (e.g., matching) Whether or not participants, those administering the interventions, and those assessing the outcomes were blinded to study condition assignment; if so, statement regarding how the blinding was accomplished and how it was assessed.
Unit of Analysis 10 Description of the smallest unit that is being analyzed to assess intervention effects (e.g., individual, group, or community) If the unit of analysis differs from the unit of assignment, the analytical method used to account for this (e.g., adjusting the standard error estimates by the design effect or using multilevel analysis) Statistical Methods

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Statistical methods used to compare study groups for primary methods outcome(s), including complex methods of correlated data Statistical methods used for additional analyses, such as a subgroup analyses and adjusted analysis Methods for imputing missing data, if used Statistical software or programs used 9

Results
Participant flow 12 Flow of participants through each stage of the study: enrollment, assignment, allocation, and intervention exposure, follow-up, analysis (a diagram is strongly recommended) o Enrollment: the numbers of participants screened for eligibility, found to be eligible or not eligible, declined to be enrolled, and enrolled in the study o Assignment: the numbers of participants assigned to a study condition o Allocation and intervention exposure: the number of participants assigned to each study condition and the number of participants who received each intervention o Follow-up: the number of participants who completed the followup or did not complete the follow-up (i.e., lost to follow-up), by study condition o Analysis: the number of participants included in or excluded from the main analysis, by study condition Description of protocol deviations from study as planned, along with reasons Recruitment 13 Dates defining the periods of recruitment and follow-up Baseline Data 14 Baseline demographic and clinical characteristics of participants in each study condition Baseline characteristics for each study condition relevant to specific disease prevention research Baseline comparisons of those lost to follow-up and those retained, overall and by study condition Comparison between study population at baseline and target population of interest Baseline equivalence 15 Data on study group equivalence at baseline and statistical methods used to control for baseline differences Number of participants (denominator) included in each analysis for each study condition, particularly when the denominators change for different outcomes; statement of the results in absolute numbers when feasible Indication of whether the analysis strategy was "intention to treat" or, if not, description of how non-compliers were treated in the analyses Outcomes and estimation 17 For each primary and secondary outcome, a summary of results for each estimation study condition, and the estimated effect size and a confidence interval to indicate the precision Inclusion of null and negative findings Inclusion of results from testing pre-specified causal pathways through which the intervention was intended to operate, if any Ancillary analyses 18 Summary of other analyses performed, including subgroup or restricted analyses, indicating which are pre-specified or exploratory Adverse events 19 Summary of all important adverse events or unintended effects in each study condition (including summary measures, effect size estimates, and confidence intervals)

Interpretation 20
Interpretation of the results, taking into account study hypotheses, sources of potential bias, imprecision of measures, multiplicative analyses, and other limitations or weaknesses of the study Discussion of results taking into account the mechanism by which the intervention was intended to work (causal pathways) or alternative mechanisms or explanations Discussion of the success of and barriers to implementing the intervention, fidelity of implementation Discussion of research, programmatic, or policy implications Generalizability 21 Generalizability (external validity) of the trial findings, taking into account the study population, the characteristics of the intervention, length of follow-up, incentives, compliance rates, specific sites/settings involved in the study, and other contextual issues Overall Evidence

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General interpretation of the results in the context of current evidence and current theory