Performance of Indirect Immunoglobulin M (IgM) Serology Tests and IgM Capture Assays for Laboratory Diagnosis of Measles
Bibliographic record
Abstract
As progress is made toward elimination of measles, the laboratory confirmation of measles becomes increasingly important. However, both false-positive and false-negative results can occur with the routinely used indirect measles immunoglobulin M (IgM) serology tests. The measles IgM capture assay is considered to be more specific, and therefore, its use is indicated for confirmatory testing, but its relative performance has not been fully assessed. Four commercial indirect measles IgM serology test kits (the Behring, Clark, Gull, and PanBio assays) and a commercial IgM capture assay (the Light Diagnostics assay) were evaluated for their abilities to detect measles virus-specific IgM antibody with a total of 308 serum samples from patients involved in a measles outbreak and with confirmed cases of measles and 454 samples from subjects without measles. The Centers for Disease Control and Prevention (CDC) IgM capture assay was also used in a part of the evaluation. Among the indirect assays, the overall sensitivities ranged from 82.8% (Clark assay) to 88.6% (Behring assay) and specificity ranged from 86.6% (PanBio assay) to 99.6% (Gull assay). These rates were 92.2 and 86. 6%, respectively, for the Light Diagnostics capture assay and 87.0 and 94.8%, respectively, for the CDC capture assay. While the Light Diagnostics capture assay had the best detection rate (80%) with the acute-phase samples compared with those for the rest of the tests (CDC capture assay, 77%; Behring assay, 70%; Gull assay, 69%; PanBio assay, 58%; and Clark assay, 57%), all tests showed a significantly improved sensitivity in the range of 92% (Clark and PanBio assays) to 97% (Light Diagnostics and CDC capture assays) with the convalescent-phase samples, as expected. The best seropositivity rates (in the range of 92 to 100%) were observed with samples collected 6 to 14 days after the onset of symptoms. The Gull assay showed the highest positive predictive value (99.6%), followed by the Behring assay (97.8%) and the CDC capture assay (96.1%). Overall, the Gull and Behring assays were found to be as good as or better than the capture assays. In conclusion, laboratory diagnosis of measles based on IgM serology varies depending on the timing of specimen collection and the test used, and the case for the use of the IgM capture assay as the confirmatory test appears to be uncertain.
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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 | 0.012 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".