Humoral and cellular immune response to severe acute respiratory syndrome coronavirus‐2 vaccination in haemodialysis and kidney transplant patients
Bibliographic record
Abstract
End-stage renal disease (ESRD) patients are amongst the vulnerable groups and thus prioritized in the Coronavirus disease-2019 vaccination programmes. However, this cohort was excluded from vaccine-trials and yet shares the same vaccination scheme with the general population. Here, we explore trends of immune response-proportions amongst ESRD patients on renal replacement therapy for up to 4 weeks post-vaccination completion with Pfizer/Moderna vaccines. From inception to 10 July 2021, we searched six online-databases for articles reporting humoral and cellular immune response proportions for up to 4 weeks post booster-vaccination. We pooled the responders' proportions by meta-analysis and conducted a meta-regression stratifying outcomes by significant confounders. Twenty-seven eligible studies reported 2789 ESRD patients. 1337, 1452 and 477 were on haemodialysis, received kidney transplantation, and healthy controls, respectively. Haemodialysis patients' proportions of humoral and cellular immune responses varied from 87.29% (80.77-93.81)-88.78% (86.76-90.80) and 62.86% (56.56, 69.17)-85.78% (78.99, 92.57), respectively, between first- and fourth-weeks. Kidney transplant patients' proportions of humoral and cellular immune responses ranged from 2.6% (0.06-13.48)-29.87% (27.68, 32.07) and 5.13% (0.63-17.3)-59.84% (54.57-65.10), respectively, between first- and fourth-weeks. All healthy controls maintained ≥93% proportions of both responses throughout the follow-up. Study design and country of study influenced the pooled response proportions. Conclusively, haemodialysis and kidney transplant patients have lower proportions of humoral and cellular immune responses than healthy controls. However, haemodialysis patients' response proportions improve, reaching near healthy-control levels by the fourth week. Kidney transplant patients' lower responses' proportions also improve but remain significantly lower than healthy controls throughout four-weeks. The "one-size-fits-all" vaccination scheme might be inadequate for kidney transplant patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".