Lyme disease: clinical diagnosis and treatment
Bibliographic record
Abstract
BACKGROUND: the bacterium that causes Lyme disease. OBJECTIVE: To review the clinical diagnosis and treatment of Lyme disease for front-line clinicians. METHODS: A literature search using PubMed and restricted to articles published in English between 1977 and 2014. RESULTS: Individuals in Lyme-endemic areas are at greatest risk, but not all tick bites transmit Lyme disease. The diagnosis is predominantly clinical. Patients with Lyme disease may present with early disease that is characterized by a "bull's eye rash", fever and myalgias or with early disseminated disease that can manifest with arthralgias, cardiac conduction abnormalities or neurologic symptoms. Late Lyme disease in North America typically manifests with oligoarticular arthritis but can present with a subacute encephalopathy. Antibiotic treatment is effective against Lyme disease and works best when given early in the infection. Prophylaxis with doxycyline may be indicated in certain circumstances. While a minority of patients may have persistent symptoms, evidence does not demonstrate that prolonged courses of antibiotics improve outcome. CONCLUSION: infection is endemic in North America is important for recognizing patients at risk and informing the need for treatment.
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 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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".