Leprosy chemoprophylaxis of household contacts: A survey of Canadian infectious disease and tropical medicine specialists
Bibliographic record
Abstract
BACKGROUND: Leprosy is uncommon in Canada. However, immigration from leprosy-endemic areas has introduced the infection to a Canadian context, in which most doctors have little knowledge of the disease. Although post-exposure chemoprophylaxis (PEP) is reported to decrease leprosy transmission, no Canadian guidelines advise clinical decision making about leprosy PEP. Here, we characterize the practice patterns of Canadian infectious disease specialists with respect to leprosy PEP and screening of household contacts by yearly physical examinations. METHODS: Canadian infectious disease specialists with known experience treating leprosy were identified using university faculty lists. An online anonymous survey was distributed. Certain questions allowed more than one response. RESULTS: The survey response rate was 46.5% (20/43). Thirty-five percent responded that PEP is needed for household contacts, 40.0% responded that PEP is not needed for household contacts, and 25.0% did not know whether PEP is needed (multinomial test p = 0.79). Twenty-five percent responded that PEP should be given to all household contacts, 62.5% responded that PEP should be given to contacts of multibacillary cases, and 25.0% responded that PEP should be given to contacts who are genetically related to the index case. For specialists who prescribe PEP, 57.1% use rifampicin, ofloxacin (levofloxacin), and minocycline; 14.3% prescribe single-dose rifampicin; and 28.6% prescribe multiple doses of rifampicin (multinomial test p = 0.11). In addition, 68.4% recommend yearly screening of household contacts, whereas 31.6% do not (multinomial test p = 0.17). CONCLUSION: Consensus among Canadian infectious diseases specialists is lacking regarding leprosy PEP and screening of household contacts.
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 | 0.001 | 0.009 |
| 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 | 0.000 |
| 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".