Humoral Response to the BNT162b2 Vaccine in Hemodialysis Patients
Bibliographic record
Abstract
Background: Hemodialysis (HD) patients have high mortality from COVID-19 and immunity following vaccination remains uncertain. This study evaluated SARS-CoV-2 antibody response in HD patients following BNT162b2 COVID-19 vaccination compared to health care workers (HCW) and convalescent serum. Methods: This single centre observational cohort study enrolled 142 HD patients and 35 HCW receiving the BNT162b2 vaccine. SARS-CoV-2 IgG antibodies to the spike protein (anti-spike), receptor binding domain (anti-RBD), and nucleocapsid protein (anti-NP) were measured in 66 HD patients receiving one vaccine dose, 76 HD patients receiving two vaccine doses, and 35 HCW receiving two vaccine doses. Results: In HD patients receiving a single BNT162b2 dose, seroconversion occurred in 53/66 (80%) for anti-spike and 35/66 (55%) for anti-RBD by 28 days post dose, but only 15/66 (23%) and 4/66 (6%), respectively attained a robust response defined as reaching the median level of anti-spike and anti-RBD in convalescent serum. In patients receiving two doses of BNT162b2 vaccine, seroconversion occurred in 69/72 (96%) for anti-spike and 63/72 (88%) for anti-RBD by 2 weeks following the second dose while 52/72 (72%) and 43/72 (60%) reached median convalescent serum levels of anti-spike and anti-RBD. In HCW, 35/35 (100%) exceeded median levels of anti-spike and anti-RBD in convalescent serum 2-4 weeks post second dose. Conclusions: This study found poor immunogenicity 28 days following a single dose of BNT162b2 vaccine in HD patients, supporting adherence to recommended vaccination schedules, and avoiding delay of the second dose in this population. Funding: Government Support - Non-U.S.Figure 1:: SARS-CoV-2 IgG Spike, RBD, and NP Antibody Response Following One Versus Two Dose BNT162b2 Vaccine in Hemodialysis Patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".