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Record W4205510064 · doi:10.5858/arpa.2020-0643-le

In Reply

2021· letter· en· W4205510064 on OpenAlexaboutno aff
Lauren A. Beste, Michael Icardi, Christine M. Hunt, Ina Gylys-Colwell, Elliott Lowy, Leslie Taylor, Timothy R. Morgan, Michael F. Chang, Marissa Maier, Ramsey Cheung

Bibliographic record

VenueArchives of Pathology & Laboratory Medicine · 2021
Typeletter
Languageen
FieldMedicine
TopicClinical Laboratory Practices and Quality Control
Canadian institutionsnot available
FundersRoy J. and Lucille A. Carver College of Medicine, University of IowaUniversity of California, IrvineUniversity of WashingtonHealth Services Research and Development
KeywordsContext (archaeology)HarmonizationAlanine aminotransferaseMedicineMedical physicsCertificationInternal medicine

Abstract

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In Reply.—Current US guidelines that endorse universal alanine aminotransferase (ALT) thresholds to define “normal” values1 are problematic and could result in unnecessary clinical interventions. In our 5-year national Veterans Health Administration analysis, we reported clinically significant differences in ALT measurements in analyzers by 5 manufacturers. We analyzed more than 22 000 samples using external ALT proficiency testing with standardized College of American Pathologists samples which, as we point out in our manuscript,2 are not commutable with human samples.3 Our findings closely align with a Canadian national study (performed with pooled human blood samples) and an Indiana statewide study demonstrating that ALT measurements vary significantly across North American analyzers.4,5 Taken in the context of this prior work, our observed lack of harmonization in ALT assays affirms that universal ALT thresholds should be avoided as a trigger for clinical action until analyzers and ALT proficiency testing materials are standardized.Proficiency testing material allows comparisons of analytical performance across systems and is used in the daily calibration and equipment maintenance procedures to enable measurement of patient samples to guide treatment decisions. We note that if proficiency testing material were entirely noncommutable, this would not be possible. Nevertheless, our aim was not to quantify the absolute differences between manufacturer systems, which would require the use of split samples and parallel testing. Rather, our goal was to illustrate the problems inherent in uncritically applying universal ALT thresholds given the lack of a sufficiently commutable “standardized” testing material.While a European certified reference material for ALT is commercially available, the use of a single “international reference” material is impractical from an operational viewpoint. As occurred with the World Health Organization thromboplastin for the international normalized ratio, the standard may eventually be depleted. Reliance on a global certified reference standard produced by a single source is inadvisable.The test platforms for the 5 analyzers we studied have differing reference ranges within the same patient population. This key finding affirms the need to examine the reference range when interpreting ALT data for each analyzer, as they are not standardized. We fully endorse the authors' concluding statement, “By appropriately establishing reference ranges, medical decisions will not be hindered by misinterpretations…”.

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)0.001
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.088
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.362
Teacher spread0.317 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations1
Published2021
Admission routes1
Has abstractyes

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