How do general practitioners test and treat gonococcal infections in the Australian Capital Territory? Implications for disease surveillance and control
Bibliographic record
Abstract
Abstract: The incidence of Neisseria gonorrhoeae (gonorrhoea) and Treponema pallidum (syphilis) infections in the Australian Capital Territory (ACT) has increased since 2014 in people reporting heterosexual exposure. This population is more likely to present to general practice rather than to specialised sexual health clinics, with potential implications for disease surveillance and control. This study aimed to explore: conformity of self-reported clinical practice with sexually transmitted infection guidelines in general practice; gaps in sexual health knowledge and skills; and areas for improved support from ACT Health Communicable Disease Control. A cross-sectional survey of general practitioners (GPs) and nurse practitioners (NPs) practicing in the ACT was conducted in December 2020, using a 17-item questionnaire and semi-structured interviews. Twenty-three GPs and one NP returned completed surveys (response rate 5.3%); four GPs and one NP participated in interviews. In its complex setting of competing demands, GP practice may not always meet national guidelines. In response to clinical vignettes, although all GPs ordered investigations for gonorrhoea, only 25% of these met the gold-standard by including endocervical or vaginal swabs. With respect to assessing antimicrobial sensitivities to guide treatment, only 58% correctly reported following up a positive gonococcal polymerase chain reaction test with a culture. Around two-thirds of respondents (62.5%) identified the appropriate antibiotic therapy and 75% correctly identified the responsibility of the diagnosing clinician to discuss contact tracing with the patient. Suggestions for increased support focussed on education, communication efficiency, and providing a 'safety net' for follow up.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".