Immune Response and Prognosis of Chronic Kidney Disease Patients Undergoing Hemodialysis Against COVID-19: A Systematic Review
Bibliographic record
Abstract
Background: Chronic kidney disease (CKD) patients are characterized by immune response dysfunction which increased susceptibility to infections. CKD is one of the Coronavirus disease-2019 (COVID-19) comorbidity that generally has a poor clinical outcome and patients undergoing hemodialysis had a 50% hospitalization rate and 20%-30% mortality rate. Seroconversion after confirmation of COVID-19 infection is close to 100% in the dialysis population, but the durability of the immune response and the extent as a protection against infection remains unclear. This study aimed to determine the immune response and prognosis of CKD patients undergoing hemodialysis against COVID-19.Objective: To determine immune response and prognosis of CKD patients undergoing hemodialysis against COVID-19.Methods: This is a systematic review study that used literature sourced from online journal databases on Google Scholar, PubMed, Cochrane, and Clinical Key sites. Literature that has passed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) staging and the journal quality review based on the Newcastle-Ottawa Scale (NOS) assessment is then synthesized qualitatively and presented systematically.Results: Based on the data analysis, there were positive immune responses in 460 of 735 (62.6%) CKD patients undergoing hemodialysis against COVID-19 and a higher mortality rate (10.5%) than the control group (6.9%).Conclusion: The immune response and prognosis of CKD patients undergoing hemodialysis against COVID-19 were worse than the control group. Therefore, COVID-19 vaccination should be prioritized in CKD patients undergoing hemodialysis.
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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 | 0.004 | 0.025 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".