Use of Quinolones for Treatment of Sexually Transmitted Diseases
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Bacterial sexually transmitted diseases (STDs) are a global public health problem. The annual incidence of bacterial STDs exceeds 100,000,000. Unrecognized, asymptomatic, or latent infections may make this number closer to 200,000,000. A table depicts the bacterial STDs that are discussed in this chapter and identifies acute presentations and sequelae. Bacterial STDs, specifically those caused by Chlamydia trachomatis and Neisseria gonorrhoeae, are responsible for serious morbidity in women including pelvic inflammatory disease, ectopic pregnancy, tubal infertility, chronic pelvic pain, neonatal infection, and increased risks of acquiring or transmitting human immunodeficiency virus (HIV). Heterotypic resistance was found in up to 69% of isolates each year, and patients with this pattern of resistance were more likely to fail therapy. Heterotypic resistance to the quinolones was recently reported in three patients whose isolates were resistant to doxycycline, azithromycin, and ofloxacin at concentrations > 4.0 mg/liter. Ofloxacin is now an alternate regimen for treatment of chlamydial infection in both the Canadian and U.S. treatment guidelines. The quinolones were found to be excellent drugs for the treatment of gonococcal infection. The fluoroquinolones, especially ciprofloxacin, were effective single-dose therapeutic agents for N. gonorrhoeae. Granuloma inguinale is a cause of genital ulceration in some parts of the world, including Southeast Asia, India, Australia, and South Africa. Ofloxacin, levofloxacin, and perhaps sparfloxacin provide equivalence to doxycycline for the treatment of C. trachomatis infections.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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