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Record W1983375346 · doi:10.4021/jocmr476w

A Comparison Between the StaRRsed Auto-Compact Erythrocyte Sedimentation Rate Instrument and the Westergren Method

2010· article· en· W1983375346 on OpenAlexvenueno aff
Juha Horsti

Bibliographic record

VenueJournal of Clinical Medicine Research · 2010
Typearticle
Languageen
FieldMedicine
TopicBlood properties and coagulation
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineErythrocyte sedimentation rateSignificant differenceNuclear medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: The Westergren method is the golden standard for measuring erythrocyte sedimentation rate (ESR). All ESR methods should agree with the standardized method of the International Council for Standardization in Hematology (ICSH). Citrate samples are commonly used for ESR. This extra sample adds costs and can be inconvenient for the patient. Therefore, some new automated ESR analyzers use EDTA samples, which are available for other hematology measurements. METHODS: We compared ESR measurements with StaRRsed Auto-Compact instrument to the ICSH standardized Westergren method in 200 patient samples. RESULTS: The correlation between methods was fairly good (R(2) = 0.72, y = 1.066x 0.24). However, with ESR results over 11 mm/h there were 55 subjects with a difference of over 30% between methods. CONCLUSIONS: This may have led to different treatment suggestions in 25 cases according to age- and gender-dependent normal values. The difference may be caused by two different anticoagulants used, different measuring times and the correlation equation used. The StaRRsed ESR method should be in better agreement with the Westergren method, which is the golden standard. ESR results have notable impact on patient diagnosis and follow-up. KEYWORDS: ESR; Erythrocyte sedimentation rate; StaRRsed; Westergren method.

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)0.033
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.523
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0330.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
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 head0.317
GPT teacher head0.575
Teacher spread0.258 · 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 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

Citations20
Published2010
Admission routes1
Has abstractyes

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