PP121 How To Involve Patients In Decisions About Antibiotic Prophylaxis After Tick Bite
Bibliographic record
Abstract
Introduction Antibiotic prophylaxis with a single dose of doxycycline after a tick bite is one of the tools for preventing Lyme disease, which is becoming increasingly prevalent in Quebec. The aim of this work was to revisit this practice in adults and children younger than 8 years of age. Methods To assess the safety and absolute risk reduction (ARR) of doxycycline for preventing Lyme disease in contraindicated populations, two systematic reviews were conducted with a re-analysis of the original efficacy data. A knowledge mobilization framework was used to consider the scientific, contextual, and experiential evidence, taking into account information on patients’ and clinicians’ experiences. Results A single dose of doxycycline prescribed within 72 hours of being bitten by a tick (Ixodes scapularis) could prevent cutaneous manifestation of Lyme disease (ARR -2.8%, 95% confidence interval: -11.7–6.1; p = 0.06), without serious side effects, provided that the bite occurred in a geographical region where at least 25 percent of nymph and 50 percent of adult ticks are infected with the disease. However, the level of evidence was low and its generalizability to other contexts was doubtful. The decision to prescribe antibiotic prophylaxis may be based more on the fear of Lyme disease, rather than on effectiveness data and the real risk of contracting Lyme disease. Conclusions It may be challenging for clinicians to discuss Lyme disease prophylaxis with patients and their families in contexts where people are fearful of the disease, and the risk of contracting it from a tick bite is uncertain. Decision aids that provide scientific evidence on the real risk of developing Lyme disease after a tick bite, particularly in Quebec, can promote informed decisions based on patient preferences and values by supporting discussion between clinicians and patients.
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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 | 0.023 | 0.124 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.029 | 0.005 |
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".