Humoral Response Following 3 Doses of mRNA COVID-19 Vaccines in Patients With Non-Dialysis-Dependent CKD: An Observational Study
Bibliographic record
Abstract
Background:Chronic kidney disease (CKD) is associated with a lower serologic response to vaccination compared to the general population. There is limited information regarding the serologic response to coronavirus disease 2019 (COVID-19) vaccination in the non-dialysis-dependent CKD (NDD-CKD) population, particularly after the third dose and whether this response varies by estimated glomerular filtration rate (eGFR).Methods:The NDD-CKD (G1-G5) patients who received 3 doses of mRNA COVID-19 vaccines were recruited from renal clinics within British Columbia and Ontario, Canada. Between August 27, 2021, and November 30, 2022, blood samples were collected serially for serological testing every 3 months within a 9-month follow-up period. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) anti-spike, anti-receptor binding domain (RBD), and anti-nucleocapsid protein (NP) levels were determined by enzyme-linked immunosorbent assay (ELISA).Results:Among 285 NDD-CKD patients, the median age was 67 (interquartile range [IQR], 52-77) years, 58% were men, 48% received BNT162b2 as their third dose, 22% were on immunosuppressive treatment, and COVID-19 infection by anti-NP seropositivity was observed in 37 of 285 (13%) patients. Following the third dose, anti-spike and anti-RBD levels peaked at 2 months, with geometric mean levels at 1131 and 1672 binding antibody units per milliliter (BAU/mL), respectively, and seropositivity rates above 93% and 85%, respectively, over the 9-month follow-up period. There was no association between eGFR or urine albumin-creatinine ratio (ACR) with mounting a robust antibody response or in antibody levels over time. The NDD-CKD patients on immunosuppressive treatment were less likely to mount a robust anti-spike response in univariable (odds ratio [OR] 0.43, 95% confidence interval [CI]: 0.20, 0.93) and multivariable (OR 0.52, 95% CI: 0.25, 1.10) analyses. An interaction between age, immunoglobulin G (IgG) antibody levels, and time was observed in both unadjusted (anti-spike: <i>P</i> = .005; anti-RBD: <i>P</i> = .03) and adjusted (anti-spike: <i>P</i> = .004; anti-RBD: <i>P</i> = .03) models, with older individuals having a more pronounced decline in antibody levels over time.Conclusion:Most NDD-CKD patients were seropositive for anti-spike and anti-RBD after 3 doses of mRNA COVID-19 vaccines and we did not observe any differences in the antibody response by eGFR.
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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 | 0.007 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".