Repeat infection with <i>Neisseria gonorrhoeae</i> among active duty U.S. Army personnel: a population-based case-series study
Bibliographic record
Abstract
Little information is known on the rate of repeat gonorrhea infection among U.S. military personnel. We analyzed all gonorrhea cases reported to the Defense Medical Surveillance System during 2006-2012 to determine the rate of repeat infection. During the seven-year study period, 17,602 active duty U.S. Army personnel with a first incident gonorrhea infection were reported. Among the 4987 women with a first gonorrhea infection, 14.4% had at least one repeat infection. Among the 12,615 men with a first gonorrhea infection, 13.7% had at least one repeat infection. Overall, the rate of repeat gonorrhea infection was 44.5 and 48.9 per 1000 person-years for women and men, respectively. Service members aged 17-19 years (hazard ratio [HR] for women = 1.51; HR for men = 1.71), African-American personnel (HR for women = 1.26; HR for men = 2.17), junior enlisted personnel (HR for women = 2.64; HR for men = 1.37), and those with one year or less of service (HR for women = 1.23; HR for men = 1.37) were at higher risk of repeat infection. The findings from this study highlight the need to develop targeted prevention initiatives including education, counseling, and retesting to prevent gonorrhea reinfections among U.S. Army personnel.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| 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 | 0.000 |
| Research integrity | 0.001 | 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".