Acceptability and implementation considerations of the patient-collected rectal swab for sexually transmitted infections testing among men who have sex with men and transgender women in Kigali, Rwanda
Bibliographic record
Abstract
Background Rectal sexually transmitted infections (STI) are prevalent among men who have sex with men (MSM) and transgender women (TGW). Self-collection of rectal specimens is widely used globally, but limited data exist on its implementation in Africa. We report experiences of MSM/TGW self-collecting rectal STI specimens in Kigali. Methods From March to August 2018, 738 MSM/TGW were recruited in a cross-sectional study using respondent-driven sampling in Kigali. We tested for Neisseria gonorrhea and Chlamydia trachomatis using the Cepheid GeneXpert CT/NG platform on self-collected rectal swabs. Likert scales assessed self-collection difficulty and comfort. Ordered logistic regression analyses were performed to characterize factors associated with self-collection difficulty. Results Overall, 14%(106) identified as TGW. In total, 78%(577) found rectal swab self-collection easy/very easy, while 15%(108) found it difficult/very difficult. Most, 92%(679), were comfortable/very comfortable with the test, and 98%(730) said they would repeat the test in the future. In multivariable RDS-adjusted analyses, discomfort with the swab was positively associated with difficulty in self-collection (adjusted cumulative odds ratios ((aCOR): 7.9(95%CI: 4.9-12.8)) and having a prevalent rectal STI (aCOR: 4.19, 95%CI: 2.02-8.72) was significantly associated with difficulty. Furthermore, 10%(75) of rectal swabs returned indeterminate results (65 invalid results and 10 errors). Conclusion Most MSM/TGW found self-collection of rectal swabs easy, comfortable, and collected valid samples. Self-collection of rectal swabs could be used alongside clinic- and community-based STI testing to improve diagnosis and treatment in Rwanda. However, measures to optimize sample collection and processing are needed to reduce the cost and clinical implications of indeterminate results
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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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".