Background

Acanthamoeba keratitis is challenging to treat and thought to result in poor outcomes, but very few comparative studies exist to assess whether ulcers caused by Acanthamoeba are worse than those caused by bacteria or fungus.

Methods

In a retrospective cohort study, all cases of smear- or culture-proven Acanthamoeba keratitis diagnosed from January 2006 to June 2011 at an eye hospital in South India were identified from the microbiology database. Random samples of the same number of cases of bacterial and fungal keratitis, matched by year, were identified from the same database in order to compare outcomes between the three types of organism. The main outcomes were the time until the following events: re-epithelialization, discontinuation of antimicrobials, perforation/keratoplasty, elevated intraocular pressure, and new cataract.

Results

The median time until re-epithelialization was 113 days for Acanthamoeba keratitis, 30 days for fungal keratitis, and 25 days for bacterial keratitis, and the median time until discontinuation of antimicrobial therapy was 100 days for Acanthamoeba keratitis, 49 days for fungal keratitis, and 40 days for bacterial keratitis. Compared to the other two organisms, Acanthamoeba ulcers took significantly longer to re-epithelialize (adjusted HR 0.4, 95% CI 0.3 to 0.6 relative to bacterial ulcers and HR 0.3, 95% CI 0.2 to 0.5 relative to fungal ulcers; overall p<0.001) and had significantly longer courses of antimicrobials (adjusted HR 0.3, 95% CI 0.2 to 0.6 relative to bacterial ulcers and HR 0.5, 95%CI 0.3 to 0.8 relative to fungal ulcers; overall p<0.001). No statistically significant difference was observed between the three organisms for the other time-to-event outcomes.

Conclusions

Acanthamoeba keratitis was more difficult to treat and had worse clinical outcomes than bacterial or fungal ulcers, highlighting the lack of adequate treatment regimens for this infection.

This study quantifies the performance of an international cohort of cornea specialists in image-based differentiation of bacterial and fungal keratitis, identifying significant regional variation and establishing a reference standard for comparison against machine learning models.