Humoral Responses in the Omicron Era Following 3-Dose SARS-CoV-2 Vaccine Series in Kidney Transplant Recipients
Bibliographic record
Abstract
Kidney transplant recipients (KTRs) have a diminished response to SARS-CoV-2 vaccination compared with immunocompetent individuals. Deeper understanding of antibody responses in KTRs following third-dose vaccination would enable identification of those who remain unprotected against Omicron. Methods: We profiled antibody responses in KTRs pre- and at 1 and 3 mo post-third-dose SARS-CoV-2 mRNA-based vaccine. Binding antibody levels were determined by ELISA. Neutralization against wild type, Beta, Delta, and Omicron (BA.1) variants was determined using a SARS-CoV-2 spike-pseudotyped lentivirus assay. Results: Forty-four KTRs were analyzed at 1 and 3 mo (n = 26) post-third dose. At 1 mo, the proportion of participants with a robust antibody response had increased significantly from baseline, but Omicron-specific neutralizing antibodies were detected in just 45% of KTRs. Median binding antibody levels declined at 3 mo, but the proportion of KTRs with a robust antibody response was unchanged; 38.5% KTRs maintained Omicron-specific neutralization at 3 mo. No clinical variables were significantly associated with Omicron-neutralizing antibodies, but antireceptor binding domain titers appeared to identify those with Omicron-specific neutralizing capacity. Conclusions: Over 50% of KTRs lack Omicron-specific neutralization capacity 1 mo post-third mRNA-vaccine dose. Antibody levels of responders were well preserved at 3 mo. Anti receptor binding domain antibody titers may identify patients with a detectable Omicron-neutralizing antibody response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".