Clinical Outcomes and Prognostic Factors Associated With Acanthamoeba Keratitis
Bibliographic record
Abstract
PURPOSE: To describe the clinical characteristics, time of presentation, risk factors, treatment, outcomes, and prognostic factors on a recent series of Acanthamoeba keratitis (AK) treated at our institution. METHODS: Retrospective case series of 59 patients diagnosed with AK from January 1, 2004 to December 31, 2008. Of these 59 patients, 51 had complete follow-up data and were analyzed using univariate and multivariate logistic regression analyses performed with "failure" defined as requiring a penetrating keratoplasty (PKP) and/or having (1) best-corrected visual acuity (BCVA) < 20/100 or (2) BCVA < 20/25 at the last follow-up. A single multivariate model incorporating age, sex, steroid use before diagnosis, time to diagnosis, initial visual acuity (VA), stromal involvement, and diagnostic method was performed. RESULTS: Symptom onset was greatest in the summer and lowest in the winter. With failure defined as requiring PKP and/or final BCVA < 20/100, univariate analysis suggests that age > 50 years, female sex, initial VA < 20/50, stromal involvement, and patients with a confirmed tissue diagnosis had a significant risk for failure; however, none of these variables were significant using multivariate analysis. Univariate analysis, with failure defined as requiring PKP and/or final BCVA < 20/25, showed stromal involvement and initial VA < 20/50 were significant for failure-only initial VA < 20/50 was significant using multivariate analysis. CONCLUSIONS: Symptom onset for AK is greatest in the summer. Patients with confirmed tissue diagnosis and female patients may have a higher risk for failure, but a larger prospective population-based study is required to confirm this. Failure is likely associated with patients who present with stromal involvement and patients presenting with an initial BCVA worse than 20/50.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".