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A gel technology system to determine postpartum RhIG dosage

2000· article· en· W2409911000 on OpenAlexaff
Jorge Fernandes, Raymond J. Chan, Ahmed S. Coovadia, Marciano D. Reis, P. H. P Inkerton

Bibliographic record

VenueImmunohematology · 2000
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineCord bloodObstetricsInternal medicine

Abstract

fetched live from OpenAlex

Failures of Rh immune globulin (RhIG) prophylaxis occur when the dose is too small. We report a test using a gel technology (GT) method to replace the Kleihauer-Betke (K-B) test to assess fetomaternal hemorrhage (FMH) and assist in determining the minimum necessary dose of RhIG. Cord blood (O, D+) was mixed with adult blood (O D-) to mimic an FMH of 10 mL, 20 mL, 28 mL, and 40 mL. Test samples were incubated with anti-D at known concentrations and centrifuged. The supernatant was titrated against D+ and D- red cells using GT and an interpretation of the required RhIG dose was made. Results were compared with the K-B test. Results were easily discernible and interpretations leading to determination of recommended RhIG dosage were reproducible. Correlation to standard K-B testing was confirmed. Elapsed time for result availability by GT testing was 60 minutes, with a direct technical time requirement of 30 minutes. The GT system is easier, objective, and quantitative, and compares well to the standard K-B test. A single procedure will allow assessment of the extent of FMH in the great majority of cases. This technique works well in determining the appropriate dose of anti-D required to treat D- patients with D+ newborns. There are potential cost savings in decreased use of RhIG, less direct technical time required, and more rapid availability of results.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.369
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.002

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.

Opus teacher head0.007
GPT teacher head0.240
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2000
Admission routes1
Has abstractyes

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