The Accuracy of Diagnostic Tests for Lyme Disease in Humans, A Systematic Review and Meta-Analysis of North American Research
Bibliographic record
Abstract
There has been an increasing incidence of Lyme disease (LD) in Canada and the United States corresponding to the expanding range of the Ixodes tick vector and Lyme disease agent (Borrelia burgdorferi sensu stricto). There are many diagnostic tests for LD available in North America, all of which have some performance issues, and physicians are concerned about the appropriate use and interpretation of these tests. The objective of this systematic review is to summarize the North American evidence on the accuracy of diagnostic tests and test regimes at various stages of LD. Included in the review are 48 studies on diagnostic tests used in North America published since 1995. Thirteen studies examined a two-tier serological test protocol vs. clinical diagnosis, 24 studies examined single assays vs. clinical diagnosis, 9 studies examined single immunoblot vs. clinical diagnosis, 7 studies compared culture or PCR direct detection methods vs. clinical diagnosis, 22 studies compared two or more tests with each other and 8 studies compared a two-tiered serological test protocol to another test. Recent studies examining the sensitivity and specificity of various test protocols noted that the Immunetics® C6 B. burgdorferi ELISA™ and the two tier approach have superior specificity compared to proposed replacements, and the CDC recommended western blot algorithm has equivalent or superior specificity over other proposed test algorithms. There is a dramatic increase in test sensitivity with progression of B. burgdorferi infection from early to late LD. Direct detection methods, culture and PCR of tissue or blood samples were not as sensitive or timely compared to serological testing. It was also noted that there are a large number of both commercial (n = 42) and in-house developed tests used by private laboratories which have not been evaluated in the primary literature.
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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 | 0.020 | 0.065 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".