AGGREGATIBACTER APHROPHILUS AS A RARE CAUSE OF ENDOGENOUS ENDOPHTHALMITIS
Bibliographic record
Abstract
Purpose: To describe a rare case of endogenous endophthalmitis caused by Aggregatibacter aphrophilus (A. aphrophilus) in the context of all previously reported cases of endophthalmitis caused by this organism. Methods: A 59-year-old man with no history of ocular trauma or surgery presented with a red, painful right eye with light perception vision. Examination showed a hypopyon, dense fibrin reaction, and cells in the anterior chamber. B-scan ultrasound showed evidence of vitritis. Broad investigations were initiated for both inflammatory and infectious etiologies. Results: The patient was diagnosed with presumed endogenous bacterial endophthalmitis as the blood cultures were positive for A. aphrophilus and vitreous cultures were negative for growth. The patient was promptly treated with intravitreal and systemic antibiotics and later underwent pars plana vitrectomy. The final visual acuity was 20/50. The patient had a prosthetic aortic valve and careful investigations had ruled out endocarditis. Conclusion: This case emphasizes the importance of early recognition, investigation, and intervention for A. aphrophilus endophthalmitis including the role of therapeutic vitrectomy. While early presentation can mimic ocular inflammatory diseases, infection from underrecognized causative organisms like A. aphrophilus should be ruled out. Systemic and intraocular antibiotics should be started promptly to provide the best visual prognosis.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".