Polyvalent Human Immune Globulin: A Prospective, Open-Label Study Assessing Anti-Hepatitis A Virus (HAV) Antibody Levels, Pharmacokinetics, and Safety in HAV-Seronegative Healthy Subjects
Bibliographic record
Abstract
Analytical data suggesting that immunoglobulin given intramuscularly (IGIM) may have reduced protection against hepatitis A virus (HAV) infection led to an update in the recommended IGIM dose (0.2 ml/kg). This prospective, open-label, single-arm clinical study evaluated whether a single 0.2 ml/kg dose of IGIM provided protective levels of anti-HAV antibodies (≥ 10 mIU/ml for up to 60 days) in HAV-seronegative healthy adults. Of the 28 subjects enrolled and dosed, 26 (93%) completed the study. Mean uncorrected anti-HAV antibody titers peaked at 109 mIU/ml on day 5 and stayed above 10 mIU/ml through day 60 ( N = 26). The mean uncorrected anti-HAV antibody titers had a median T max of 95.33 h, a mean C max of 118 mIU/ml, and a mean observed T half of 63.3 days; baseline-corrected titers had a median T max of 95.33 h, a mean C max of 114 mIU/ml, and a mean observed T half of 47.1 days ( N = 27). All subjects (28/28) experienced at least 1 treatment-emergent adverse event (TEAE), with a total of 83 TEAEs reported; none was serious, and 96% (80/83) resolved without sequelae. Most (63%) events judged definitely and possibly related to study treatment involved localized pain due to intramuscular injections. There were no serious adverse events and no deaths or discontinuations due to TEAEs. A single 0.2 ml/kg dose of IGIM provided protective anti-HAV levels for at least 60 days, with acceptable safety and tolerability profiles in healthy subjects. Uncorrected and baseline-corrected pharmacokinetic findings were similar and consistent with the corresponding sampling points in previous research. ClinicalTrials.gov Identifier, NCT03351933.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".