Laboratory Diagnosis of Amoebic Keratitis: Comparison of Four Diagnostic Methods for Different Types of Clinical Specimens
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Bibliographic record
Abstract
Amoebic keratitis causes significant ocular morbidity in contact lens wearers. Current diagnostic methods for amoebic keratitis are insensitive and labor-intensive and have poor turnaround time. We evaluated four laboratory methods for detection of acanthamoebae in clinical specimens. Deidentified, delinked consecutive specimens from patients with suspected amoebic keratitis were assayed for acanthamoebae by direct smear analysis, culture, and PCR using two different primer sets specific for Acanthamoeba ribosomal DNA. The consensus reference standard was considered fulfilled when the results for any two of the four tests were positive, and the outcome measures were sensitivity and specificity. Of 107 specimens assayed over an 18-month period, 20 were positive for acanthamoebae. The sensitivity and specificity of each assay were as follows, respectively: for smear analysis, 55% (95% confidence interval [CI], 33.2 to 76.8%) and 100%; for culture, 73.7% (95% CI, 54.4 to 93.0%) and 100%; for PCR using Nelson primers, 90% (95% CI, 76.9 to 100%) and 90.8% (95% CI, 84.7 to 96.9%); and for PCR using JDP primers, 65% (95% CI, 44.1 to 85.9%) and 100%. Nelson primer PCR demonstrated a single-organism level of analytic sensitivity. The performance characteristics of the assays varied by specimen type, with contact lenses and casings showing the highest rates of detectable acanthamoebae and the highest diagnostic sensitivities for direct smear analysis, culture, and JDP primer PCR, though these results are based on small numbers and should be interpreted cautiously. These findings have important implications for clinicians collecting diagnostic specimens and for diagnostic laboratories, especially in outbreak situations.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it