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Record W4410586154 · doi:10.1016/j.ajoint.2025.100134

The effectiveness of antibiotic additives in irrigation fluid used during cataract surgery: A systematic review

2025· review· en· W4410586154 on OpenAlex
Brian Yu, William J Herspiegel, Jeffrey Thevaranjan, Andre Jun Xian Lai, Amit Garg, Cindy Hutnik, Monali S. Malvankar‐Mehta

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueAJO International · 2025
Typereview
Languageen
FieldMedicine
TopicOcular Infections and Treatments
Canadian institutionsMcMaster UniversityWestern University
FundersWestern University
KeywordsCataract surgeryAntibioticsMedicineIntensive care medicineSurgeryMicrobiologyBiology

Abstract

fetched live from OpenAlex

Purpose To conduct a systematic review investigating the efficacy of antibiotics used in irrigation fluid during cataract surgery on the incidence of post-operative endophthalmitis. Design Systematic review of literature. Methods Literature was searched through MEDLINE, EMBASE, CINAHL, Clinical Trials.gov, and ProQuest Dissertations and Theses until February 17, 2024. Conferences held through Association for Research in Vision and Ophthalmology and American Academy of Ophthalmology were searched until March 22, 2024. A total of 5341 records were screened leaving 13. One author independently reviewed them for quality and extracted data. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting guidelines were followed. Data on the types of antibiotics used, as well as the incidence of post-operative endophthalmitis and complications, were extracted. Results A total of 608,064 eyes and 566,760 patients were included in the current study. Surgical procedures included phacoemulsification, manual small-incision, and extracapsular extraction. Results showed antibiotic additives reduced postoperative endophthalmitis and bacterial contamination. Vancomycin showed the lowest infection rates, with one study reporting 0 infections out of 220 patients using a concentration of 20 mg/L. Similarly, gentamicin, tobramycin, and cefuroxime also demonstrated reduced infection rates, with gentamicin achieving rates as low as 0.008% at higher concentrations. Combination therapy with vancomycin and gentamicin further reduced bacterial contamination, with culture positivity rates as low as 2.73%. In comparator groups without antibiotics, infection rates were significantly higher, ranging from 0.04% to 0.07%. No adverse events or complications were reported in those who received antibiotics in their irrigation fluid. Conclusions Antibiotic additives in irrigation fluid reduce postoperative endophthalmitis and bacterial contamination in cataract surgery. These findings support their inclusion in surgical practice to improve patient outcomes. Based on the current systematic review, the overall quality of evidence is moderate, as findings are supported by a mix of randomized controlled trials and observational studies with some heterogeneity. Further high-quality RCTs are needed to determine optimal antibiotic concentrations and establish standardized guidelines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.516

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.020
GPT teacher head0.342
Teacher spread0.323 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it