Clinical Trial Details
— Status: Recruiting
Administrative data
NCT number |
NCT05275335 |
Other study ID # |
21-0012 |
Secondary ID |
|
Status |
Recruiting |
Phase |
|
First received |
|
Last updated |
|
Start date |
November 1, 2022 |
Est. completion date |
June 30, 2026 |
Study information
Verified date |
October 2023 |
Source |
The University of Texas Medical Branch, Galveston |
Contact |
Steven E Wolf, MD |
Phone |
12107870507 |
Email |
swolf[@]utmb.edu |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational [Patient Registry]
|
Clinical Trial Summary
The purpose of this investigation is to better understand the wound microbiome in burn wounds
and the role it plays in outcomes and complications related to treatment.
Description:
1. - INTRODUCTION: The human microbiome consists of microorganisms including bacteria,
fungi, archaea and viruses that live in association with the body. In the average
person, bacteria alone outnumber host cells ten-fold and contain a thousand more genes
than the human genome. Therefore, despite consisting of <3% of the body's biomass, the
human microbiome plays a crucial role in establishing and maintaining the complex
biomechanics of our health and development. In the last two decades, the NIH Human
Microbiome Project has spotlighted a number of newly discovered influences the
microbiome has on human physiology (Turnbaugh et al., 2007). Despite the remarkable
progress achieved in the last two decades, the diverse ecosystem of microbiota present
in cutaneous wounds and their influence on host regeneration, immune response and wound
healing have only recently begun to be deciphered. To date we have only a superficial
understanding of the burn wound microbiome and its impact on infection, systemic
inflammation, wound healing and ultimately patient prognosis.
2. - BACKGROUND: Severe burns are a major global source of morbidity and mortality.
According to the National Center for Injury Prevention and Control and the American Burn
Association, 450,000 patients suffer thermal burns each year in the United States alone;
of those admitted for treatment, 3% will not survive mostly due to infection and sepsis.
After severe burn, the pattern of microbial colonization in burn wounds follows a
relatively predictable sequence of supplementation beginning with gram-positive bacteria
followed by gram-negative bacteria and subsequently more virulent pathogens. Several
studies showed length of hospitalisation is associated with the microbial species
isolated from burn wounds. Numerous studies explored the microbiome of chronic cutaneous
wounds with findings suggesting healing is influenced by both pathologic and beneficial
microbial populations. Traditional microbiology culture analysis is a surrogate for the
actual wound microbiome but fails to identify the full breath of the microbial ecosystem
present in burn wounds, as many species are difficult to cultivate under standard
conditions and the culture environment itself differs substantially from the wound
environment. Furthermore, the wound microbiome is dynamic and changing influenced by
environmental factors, wound care agents, the host immune response, and medications. In
addition, traditional wound cultures take several days to finalise and over the course
of such time may no longer reflect the current microbial residents of the wound itself.
Lastly, a great deal of attention is focussed on known pathogenic species and multi-drug
resistant strains (Pseudomonas aeruginosa, Haemophilus influenzae, carbapenem-resistant
Enterobacteriaceae to name a few), but the presence and influence of beneficial species
is often overlooked.
Culture-independent methods using Next Generation Sequencing (NGS) technology, such as
the 16S and 18S amplicon sequencing and metagenome shotgun sequencing, have proven to be
faster and more sensitive than traditional microbiology cultures. 16S NGS technology
utilises 16S rDNA to encode for ribosomal rRNA sequences of prokaryotes. Nine variable
regions are present within the 16S rDNA sequence, which target genetic differences
between bacterial species. In a similar manner 18S NGS technology encodes for ribosomal
rRNA sequences of eukaryotes and the variable regions are used to classify species
differences among eukaryotic micro-organisms in a sample.
3. - STUDY PROCEDURES Specimen and Data Collection: The Burn Wound Data/Bio-Repository will
collect biospecimens from excised burn wound tissues to be discarded by the surgical
team. No more than two progenitor specimens will be collected from any individual
operative case. Each specimen will be divided at the time of collection into two
sub-specimens that each weigh approximately 0.5-2 grams. Each specimen must be from only
one specific body region classified as upper extremities (either arm or hand), lower
extremities (either leg or foot), anterior thorax, posterior thorax or head/neck. In
addition, no specimens will be collected from the genitalia or perineum due to the high
risk of specimen contamination.
The sub-specimens will be transported immediately on ice and temporarily stored in a -20ºC
freezer, then a portion of the tissue (less than 0.5 cm) will be placed in RNAlater(R) RNA
Stabilization Solution (RNAlater(R)) in order for nucleotide preservation/stabilization.
Tissue placed in RNAlater(R) will be refrigerated at 4ºC overnight to allow sufficient tissue
penetration. Afterwards preserved specimens will be stored at -20ºC to -80ºC. This process
will be performed within 1 hour of collection. Each sub-specimen will generate two additional
specimens to be placed in RNAlater(R). After the initial period of refrigeration, RNAlater(R)
specimens will be stored in the Second Bio-Repository in a -80ºC freezer. Un-used tissue will
be labeled with the same de-identified sequence and barcode and stored in a -80ºC freezer for
a period of no more than 12 months and no less than 6 months (First Bio-Repository).
To address the other labeled sub-specimen, it will be transported to the Clinical
Microbiology Laboratory (CML) in a 15mL specimen collection vial to undergo microbiology
culture analysis. After completion of the microbiology culture analysis, specific bacterial
colonies from the culture plates at the CML will be isolated and processed in a nucleotide
preserving solution (RNAlater(R)). Similar to their counterparts from the Second
Bio-Repository, the specimens will be batched for NGS analysis. When sufficiently batched,
specimens from the Third Bio-Repository will undergo nucleotide extraction by the NGS
Facility staff prior to NGS analysis using Shotgun Whole Genome Sequencing analysis.
Patients/LARs will be approached for informed consent after introduction to the study by the
clinical staff and confirmed that more information regarding informed consent is acceptable.
Once signed informed consent is obtained, clinically pertinent wound-specific data will be
collected for the First Database under the same de-identified label. If informed consent is
not obtained, the specimens will be discarded and not considered further. All collected
information will be linked to the de-identified unique identifiers, which will be specific to
each progenitor specimen. All collected data will be independent of the clinical record and
stored securely.
The following patient-specific data will be collected:
- Age of patient in years at time of burn injury (input is numerical in years)
- Gender of patient at time of burn injury (categories are Male, Female, Other)
- Ethnicity of the patient (categories are White, Black, Hispanic, Asian, Native American,
Pacific Islander, and other)
- Weight and BMI of the patient at the time of surgery (input is numerical)
- Pregnancy status (categories are positive, negative or unknown)
- COVID-19 status (categories are positive, negative or unknown)
- Oral or IV antibiotics received within 24 hours of surgery (categories are vancomycin,
meropenem, daptomycin, Zosyn, doxycycline, Ancef, Bactrim, Augmentin, any anti-fungal or
any anti-viral)
- Medication Class - home and inpatient (categories are diabetic therapy, steroids,
immunotherapy, or chemotherapy)
- Any previous de-identified sequence associated with the subject from the current
admission
- TBSA burned (input is numerical: % total body surface area)
The following wound-specific data will be collected:
- Days since admission and hospital days on the day of collection (input is numerical)
- Days since burn injury (input is numerical)
- Number of operative interventions during the current admission including the surgery at
time of specimen collection (input is numerical)
- Number of total operative interventions associated with index burn injury including
operations performed at other facilities, operations performed on previous admissions to
UTMB and the surgery at time of specimen collection (input is numerical)
- Body location from which the specimen is collected (categories are upper extremity
either arm or hand, lower extremity either leg or foot, anterior thorax, posterior
thorax or head/neck). Tissues from the genitalia and groin will not be collected.
- Total body surface area burned (TBSA) percentage as determined on admission (input is
numerical)
- Concern for full thickness or 3rd degree burn injury depth from the site where specimen
is being collected (categories are yes or no)
- Presumed type of tissue from the site where specimen is being collected (categories are
cutaneous, subcutaneous or myofascial)
- Etiology of burn injury (categories are flame, scald, contact, chemical, electrical or
other)
- Antimicrobial wound care immediately prior to surgery on the wound from with tissue is
being collected (categories include antibiotic ointment, Dakins' solution irrigation,
silver nitrate irrigation, mafenide acetate irrigation, amphotericin soaks, silver
sulfadiazine cream, silver-based synthetic dressing, non-silver-based synthetic
dressing).
BIOSTATISTICS
We are proposing to gather at least 300 progenitor samples to include in the Bio-Repository
to analyze data to answer (at least) the following questions:
- What is the correlation between the NGS burn wound microbiome and traditional culture
techniques?
- What is the relative distribution of microbe species in the burn wound?
- What is the relative distribution of microbe number and concentration in burn wounds
compared to traditional techniques?
All of these questions can be answered solely with de-identified discarded samples. For
additional questions, those samples with associated clinical and wound-specific data can be
used to answer the following:
- Does age in years of the patient engender different burn wound microbiome? Is this
reflected with classical culture techniques?
- Does gender have any effect on burn wound microbiome? Is this reflected with classic
culture techniques?
- Does ethnicity affect the burn wound microbiome? Weight and BMI? Pregnancy? COVID-19?
Burn size?
- Does topical and/or systemic antibiotic use affect the burn wound microbiome?
- Does age of the burn wound affect the burn wound microbiome? Does number of previous or
subsequent operative interventions have any effect?
- Does the body region injured have any effect on the burn wound microbiome?
STATISTICAL ANALYSIS:
Descriptive statistics for continuous variables will be presented as mean ± SD, and for
categorical variables as frequencies and proportions. Bivariate analysis will include
correlation testing with Pearson correlation coefficient where the normality assumption is
not violated, and Spearman's rho when normality is not assumed. Using multiple linear
regression models, we will assess the relationship between NGS burn wound microbiome and
traditional culture techniques as well as determine the predictors of burn wound microbiome
in collected biospecimens from adult burn patients. Diagnostic testing will be performed on
the full multiple regression models. Two-sided statistical significance will be considered
for alpha at the 0.01 level.
Power analysis: Power analysis for our prediction model was based on an effect size f2 of
0.136 calculated from anticipated r2 of 0.12 with 20 predictors at alpha=0.01 and for a power
of the f test to reject the null hypothesis at 90%. The sample size needed for such a model
with 20 predictors to explain at least 12% of the variation on the dependent variable (burn
wound microbiome) at 90% power and at alpha=0.01 is 271 progenitor samples. We aim to collect
300 progenitor samples to account for 10% analytical failure. We used G*power (version
3.1.9.7) under the f test family to estimate this sample size suggested.