In this study, the investigators seek to determine the effect of antibiotic use post-surgery on antimicrobial resistance. The investigators will be studying adults (aged 18 or older) who will undergo eye surgery at University of California, San Francisco (UCSF). We seek to gain a better understanding of how antibiotic use during the perioperative period influences local and systemic antibiotic resistance at the individual level.
Antibiotic use has saved millions of lives globally. However, this comes at the cost of selecting for antibiotic-resistant organisms at the individual and the community level. It is estimated that every year, approximately 700,000 deaths are associated with drug resistance globally. This places a significant burden on the public health system and the judicious use of antibiotics is more important than ever before. The proposed masked, randomized controlled trial evaluates the effects of topical antibiotic use on the selection of antibiotic resistance determinants at the local and systemic levels. The results will provide guidance for antibiotic usage in ophthalmology and may have the potential to inform public health policies.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
TREATMENT
Masking
SINGLE
Enrollment
108
We are using moxifloxacin as indicated and as intended for use as an antibiotic during surgery. Frequency of postoperative antibiotics dependent on group randomization.
University of California, San Francisco
San Francisco, California, United States
Antimicrobial Resistance (AMR) of Conjunctiva at 1 Week
Normalized read counts (reads per million reads or rM) for fluoroquinolone resistance determinants from DNA deep sequencing for the conjunctival swabs at 1 week, which represent the abundance of resistance in the sample.
Time frame: 1 Week
Antimicrobial Resistance (AMR) of Nasopharynx at 1 Week
Normalized read counts (reads per million reads or rM) for fluoroquinolone resistance determinants from DNA deep sequencing for the nasopharyngeal swabs at 1 week, which represent the abundance of resistance in the sample.
Time frame: 1 week
Shannon's Index
Conjunctival samples were evaluated for microbiome heterogeneity at 1 week. Shannon's index (H) represents a measure of bacteria species heterogeneity and is calculated through the following formula, H = -sum(pi\*log(b)\*pi), where pi is the proportional abundance of species and b is the base of the logarithm. Here, we are using the natural logarithm. The Shannon's Index ranges from 0 to ln(S), where S is the number of species in the community. We report the exponentiated Shannon's Index, which is expressed as the "effective number of species", which ranges from 1 to S species. An effective number of species of 1 indicates that 1 species dominates the microbiome. The greater the effective number of species, the greater the heterogeneity of species abundance in the microbiome. Low heterogeneity of bacterial species in the microbiome is a proxy for a less healthy system.
Time frame: 1 week
Simpson's Index
Conjunctival samples were evaluated for microbiome heterogeneity at 1 week. Simpson's index (D) represents a measure of bacteria species heterogeneity and is calculated through the following formula, D = sum(pi\^2), where pi is the proportional abundance of species. The Simpson's Index ranges from 0 to 1, where 0 represents infinite heterogeneity and 1 represents no heterogeneity. We report the inverse of Simpson's Index, which is expressed as the "effective number of species", which ranges from 1 to S species. An effective number of species of 1 indicates that 1 species dominates the microbiome. The greater the effective number of species, the greater the heterogeneity of species abundance in the microbiome. Low heterogeneity of bacterial species in the microbiome is a proxy for a less healthy system.
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Time frame: 1 week
Simpson's Index
Nasopharyngeal samples were evaluated for microbiome heterogeneity at 1 week. Simpson's index (D) represents a measure of bacteria species heterogeneity and is calculated through the following formula, D = sum(pi\^2), where pi is the proportional abundance of species. The Simpson's Index ranges from 0 to 1, where 0 represents infinite heterogeneity and 1 represents no heterogeneity. We report the inverse of Simpson's Index, which is expressed as the "effective number of species", which ranges from 1 to S species. An effective number of species of 1 indicates that 1 species dominates the microbiome. The greater the effective number of species, the greater the heterogeneity of species abundance in the microbiome. Low heterogeneity of bacterial species in the microbiome is a proxy for a less healthy system.
Time frame: 1 week