Performance of the Alethia CMV Assay for Detection of Cytomegalovirus by Use of Neonatal Saliva Swabs
Bibliographic record
Abstract
Congenital cytomegalovirus (cCMV) infection is a major cause of childhood hearing loss and neurodevelopmental delay. Identification of newborns with cCMV infection allows provision of beneficial interventions. However, most infants with cCMV infection have subclinical infection and go undiagnosed. Thus, expanded neonatal CMV testing is increasingly recommended. Saliva is an attractive sample type for CMV testing of newborns, because it is easier to collect than urine and more sensitive for CMV detection than dried blood spots. We evaluated the Alethia CMV assay, a rapid, easy-to-use loop-mediated isothermal amplification method for qualitative detection of CMV DNA in neonatal saliva samples. Saliva swabs were collected prospectively from newborns <21 days old and tested by the Alethia assay according to the manufacturer's instructions. Archived saliva swabs from newborns with cCMV infection were also tested retrospectively. A composite reference method (CRM; two validated PCR assays followed by bidirectional sequencing of amplicons) was performed on all samples as the reference standard comparator. Of 1,480 prospectively collected saliva swabs, 1,472 (99.5%) were negative by both the Alethia assay and CRM, 5 (0.34%) were positive by both the Alethia assay and CRM, and 3 (0.20%) were positive only by the Alethia assay. All 34 (100%) archived swabs from newborns with cCMV infection were positive by both the CRM and the Alethia assay. Overall, the Alethia assay showed 100% and 99.8% positive and negative agreement with the CRM, respectively. The Alethia CMV assay is an accurate method for identifying neonates with cCMV infection and, given its simplicity, appears suitable for CMV testing using neonatal saliva outside a reference laboratory, including remote and resource-limited settings.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".