A trend of dropping anti‐SARS‐CoV‐2 plaque reduction neutralization test titers over time in Canadian convalescent plasma donors
Bibliographic record
Abstract
Abstract Background Convalescent plasma products are a potential passive immunotherapy for Coronavirus disease 2019 (COVID‐19) disease. Various approaches have been utilized to determine the concentration of Severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2)‐neutralizing antibodies in plasma products. The Canadian Blood Services used Plaque Reduction Neutralization Test 50 (PRNT50)‐generated values to qualify convalescent plasma donations supporting clinical trials in Canada. This manuscript describes changes in PRNT50 titers of repeat male plasma donations collected approximately 1–4 months after onset of COVID‐19 signs and symptoms in donors. Study Design and Methods Men were eligible to donate if they: met standard criteria, were < 67 years of age, reported a previous SARS‐CoV‐2‐positive nucleic acid test, and recovered and were symptom free for at least 28 days prior to donation. Repeat donation analysis required at least one original and one repeat donation where a PRNT50 was performed. Results From April 29, 2020 to July 25, 2020, 156 donors donated once, with 78 (50%) of the donated plasma having PRNT50 titers of ≥1:160. Thirty‐seven (23.7%) of the donated plasma had a titer of 1:40 or 1:80 (individuals donating this plasma were asked to donate a second time only). A total of 30 donors (19.2%) had repeat donations. Of the repeat donors, 15 (50%) had at least an eightfold change from peak to trough PRNT50 titers within greater than 90 days after onset of COVID‐19 symptoms. Conclusions Blood operators cannot infer that SARS‐CoV‐2 PRNT50 will remain high in repeat plasma donors 3–4 months after onset of COVID‐19 symptoms.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".