Variability in Response to Hepatitis B Vaccine in Hemodialysis Patients
Bibliographic record
Abstract
BACKGROUND: Hemodialysis patients are exposed to blood and blood products more than the general population and are also at higher risk for hepatitis B (HB) contamination. For these reasons, it is highly recommended that this patient population gets the HB vaccine. The efficacy of the vaccine is measured by measuring titers of antibody in the serum of the patient. A minimum titer of 10 mIU/mL is considered to be a response. The conversion rate in hemodialysis patients ranges from 50% to 80%, as compared to the general population where the conversion rate is over 95%. As opposed to the general population, end-stage renal patients on hemodialysis do not always respond to the vaccine. The main objective in this study was to try to identify factors that may hinder the response. Correction of these factors in the future may help non-responders. METHODS: This was a retrospective chart review at a single hemodialysis center to compare the laboratory and clinical differences between responders and non-responders. Inclusion criteria are hemodialysis patients who received the HB vaccine and patients with concomitant hepatitis C. Exclusion criteria are patients who refused the vaccine and patients who did not complete the vaccine course. RESULTS: There are a total of 108 subjects included in the study, out of which 44 (42.3%) are responders to the HB vaccine. A multivariate logistic regression was performed using the statistically significant risk factors as identified by the univariate logistic regression, including age range, albumin, hemodialysis vintage, vascular access and diabetes status. The results from the multivariate logistic regression show that advanced age (P = 0.005) and diabetes status (P = 0.003) are found to be strong independent risk factors of responder status. The type of vascular access (AVF or other types) is also marginally statistically significant (P = 0.05). CONCLUSIONS: In this retrospective chart review comparing HB vaccine in responders versus non-responders, we found that advanced age and a history of diabetes are independent risk factors in predicting responder status.
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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 | 0.001 | 0.005 |
| 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 | 0.000 |
| 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".