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Record W2074267839 · doi:10.1002/pd.1736

Flow cytometric assessment of feto‐maternal hemorrhage; a comparison with Betke–Kleihauer

2007· article· en· W2074267839 on OpenAlexafffund
J. Fernandes, Peter von Dadelszen, Inez Fazal, Nikki Bansil, Greg Ryan

Bibliographic record

VenuePrenatal Diagnosis · 2007
Typearticle
Languageen
FieldMedicine
TopicBlood groups and transfusion
Canadian institutionsUniversity of British ColumbiaUniversity of TorontoMount Sinai Hospital
FundersCanadian Institutes of Health ResearchUniversity of TorontoMichael Smith Health Research BCChild and Family Research Institute
KeywordsMedicineFetusObstetricsPregnancyGynecologyAndrologyBiology

Abstract

fetched live from OpenAlex

OBJECTIVES: Assessing the number of fetal cells in the maternal circulation quantifies the volume of feto-maternal hemorrhage, enhancing the ability to provide effective prevention of Rhesus (Rh) allommunization and appropriate fetal surveillance in cases of significant feto-maternal hemorrhage. METHODS: Having developed a standard curve with maternal samples spiked with known volumes of fetal red blood cells, we used a flow cytometric method using fluorescent labeled antihemoglobin F to quantitate fetal cells in the maternal circulatory system in two groups of women undergoing chorionic villus sampling (CVS), by either biopsy forceps or cannula aspiration (n = 170 women). We compared these results with the gold standard, the Betke-Kleihauer test. RESULTS: Our results show good correlation between the flow cytometric method and the traditional Betke-Kleihauer method for fetal red cell quantitation (r(2) = 0.99). Fetal red blood cells were identified in 10 women by the Betke-Kleihauer method, and in 26 women by flow cytometry. CVS was not associated with an increase in feto-maternal hemorrhage. CONCLUSION: Flow cytometry was both more sensitive and more timely for the quantitation of feto-maternal hemorrhage than was Betke-Kleihauer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.593

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.302
Teacher spread0.288 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations27
Published2007
Admission routes2
Has abstractyes

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