The Epidemiology of Herpes Simplex Virus Eye Disease in Northern California
Bibliographic record
Abstract
PURPOSE: To calculate the incidence and prevalence of herpes simplex virus (HSV) eye disease in a large, well-defined population in Northern California, USA, and to determine the recurrence rate following an initial episode of disease in this cohort. METHODS: A retrospective, observational, cohort study using population-based data and medical record review. The patient database of a large, regional health maintenance organization (Northern California Kaiser Permanente) was searched, and the study population consisted of 1,042,351 people over a 1-year study period from 1 July 1998 through 30 June 1999. Only ocular HSV cases with definitive clinical or laboratory confirmed diagnoses were included. Active and inactive cases were included, however only active cases were used in incidence and prevalence calculations. Bilateral disease was counted as one case. Newly diagnosed cases were followed for recurrence from initial presentation through 31 December 2002. RESULTS: After chart review of 322 possible cases, 71 new cases and 59 previously diagnosed active cases of ocular HSV were confirmed. This resulted in an incidence rate of 6.8 new cases/100,000 person-years (95% confidence interval, CI, 5.3-8.6). Incidence increased with age, and rates were highest in people over 75 years of age (p < 0.001). The recurrence rate in new cases was 18% for the 3-year follow-up time, and was equal to 5% per year (95% CI 3-9%). CONCLUSION: The incidence and prevalence of ocular herpes simplex in this study was lower than previously reported. Incidence increased with age, and there were significantly higher rates in the older population.
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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 | 0.001 | 0.002 |
| 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 | 0.000 |
| 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".