The Epidemiology of Chlamydia trachomatis Organism Load During Genital Infection: A Systematic Review
Bibliographic record
Abstract
BACKGROUND: The role of organism load in Chlamydia trachomatis infection is not well understood. We conducted a systematic review to investigate the epidemiology of C. trachomatis organism load in human genital chlamydia infection. METHODS: Embase, PubMed, and Medline databases were searched for literature published through August 2014. English-language publications that quantified load in humans were eligible. Participant characteristics and laboratory data were extracted. RESULTS: A total of 737 records were identified, and 29 publications involving 40 883 participants were included. In women, load was highest for cervical swabs and lowest for urine specimens. In men, load was highest for rectal swabs and similar for urethral swabs and urine specimens. Evidence of any association between load and age, serovar, risk of transmission, hormone levels, and concurrent sexually transmitted infections was inconsistent. Eight of 9 culture-based studies found an association between load and signs and symptoms, in contrast with only 3 of 8 nucleic acid amplification test (NAAT)-based studies (P = .03). CONCLUSION: Chlamydia organism load varies by specimen type and site of sampling, and viable chlamydia organism load may be a more important indicator of severity of infection than total load measured by NAAT.
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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 | 0.006 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.014 | 0.018 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".