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Record W2803726083 · doi:10.1093/ndt/gfy104.fp385

FP385INTER-LABORATORY VARIABILITY IN PTH MEASUREMENT AND ATTAINMENT OF ANALTIC PERFORMANCE GOALS

2018· article· en· W2803726083 on OpenAlexaffabout
Sam Sarabia, Christine Collier, Rachel M. Holden, Mandy E. Turner, Christine A. White

Bibliographic record

VenueNephrology Dialysis Transplantation · 2018
Typearticle
Languageen
FieldEngineering
TopicFault Detection and Control Systems
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicineInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION AND AIMS: Hyperparathyroidism is a common complication of chronic kidney disease (CKD). PTH is measured routinely in CKD and prescriptions of phosphate binders, vitamin D analogues and calcimimetics are adjusted to meet target values. A number of different PTH assays and manufacturers exist. At present there are no higher order reference methods for PTH although the use of reference material PTH IS 95/646 is advocated by the IFCC. Performance goals for PTH assays have been proposed based on biologic variation. The goals of this study are to assess the extent of inter-laboratory PTH variability and the attainment of analytic error goals. METHODS: Data were collected from Ontario Canada’s Institute for Quality Management in Healthcare’s (IQMH) Proficiency Testing Program reports. Between 2015 and 2016, IQMH provided 24 challenge vials for PTH measurement to 115-133 laboratories in Canada and Australia. While individual laboratory data is not publicly available, data is compiled for all methods together and by manufacturer. Bias, precision (CVa) and total error (TE) were assessed for each challenge vial for all methods together and by manufacturer. The percentage of challenge vials that met bias, precision and total error goals proposed by Westgard for PTH were determined. RESULTS: Figure 1 shows the mean, SD, max and min values for each challenge vial. Comparing all manufacturers combined against the all methods mean produced an overall weighted mean percent bias of -1.69 ± 6.18% while the mean CVa was 30.2% and mean total error was 51.6 ± 11.6%. Manufacturer specific mean percent biases ranged between -15.9% to 38.3%, mean precisions between 7.6% to 15% and mean total error between 30% to 62%. The percent of challenge vials meeting bias and total error goals shows substantial differences between manufacturers (Table 1). CONCLUSIONS: Significant inter-laboratory variability in PTH exists even within individual manufacturers. Bias and total error goals are inconsistently reached with some manufacturers performing better than others. Further improvements are needed to optimize PTH assay performance and ensure it is fit for purpose.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.027
metaresearch head score (Gemma)0.051
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.048
Threshold uncertainty score0.144

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.051
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.008
GPT teacher head0.208
Teacher spread0.200 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2018
Admission routes2
Has abstractyes

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