MP720COMPARISON OF HEPATITIS B SEROCONVERSION RATES WITH ENGERIX-B AND RECOMBIVAX-HB IN PATIENTS ON HEMODIALYSIS
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Engerix-B® (GlaxoSmithKline, Atlanta, GA, USA) and Recombivax-HB® (Merck, Whitehouse Station, NJ, USA) are the two hepatitis B vaccinations approved by the FDA and currently used in end-stage renal disease patients in the United States. Previous studies indicated that seroconversion rates are significantly higher in people vaccinated with Engerix-B (ENG) versus Recombivax-HB (REC). The same has been reported in small studies in patients undergoing chronic hemodialysis [1-3]. The aim of this study was to further validate the potential different efficacy of the two vaccines in a large nationally representative population of hemodialysis patients from the U.S.. METHODS: All patients treated in Fresenius Kidney Care (FKC) clinics from January 2010 to December 2015 were included if they were negative for both hepatitis B virus surface antigen (HBsAg) and anti- HBsAg antibodies. After a complete vaccination course (4 doses of 40 μg for ENG or 3 doses of 40 μg for REC), seroconversion was assessed using the first anti-HBsAg titer between 23 and 365 days after the last vaccine dose. For primary non-responders, seroconversion was assessed in the same way after a second complete vaccination series. Population characteristics were compared between ENG and REC patients using Student’s t test or chi squared test as appropriate. Seroconversion rates were compared between the two vaccines using chi squared test. RESULTS: ENG patients (N = 24,677) were older (63. 9 vs. 63.1 years), had a higher eKt/V (1.6 vs. 1.5), a higher proportion of diabetics (61.5% vs. 54.9%), fewer patients with congestion heart failure (12.3% vs. 16.1%), lower dialysis vintage (0.8 vs. 1.1 years) and lower hemoglobin (11.2 vs. 11.5 g/dL) compared to REC patients (N = 1,320) (Table 1). Seroconversion rates were significantly higher with ENG compared to REC (1st series: 73.7% vs. 64.3%, Δ=9.4% 95% CI: 6.7 % to 12.1%); 1st and 2nd series combined: 78.5% vs. 64.6%, Δ=13.9%, 95% CI: 11.2% to 16.5%) (Figure 1). CONCLUSIONS: When administering full vaccination courses as outlined above, Engerix-B yields substantially higher primary seroconversion rates than Recombivax-HB. The same is true when looking at cumulative response rates for the 1st and 2nd series combined. These results hold true even after adjusting for differences in population characteristics. MP720 Figure
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".