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Record W2897320222 · doi:10.1111/trf.14948

International validation of harmonized definitions for complications of blood donations

2018· article· en· W2897320222 on OpenAlexaff
Kevin J. Land, Mary Townsend, Mindy Goldman, Barbee Whitaker, Gabriela Perez, Johanna C. Wiersum‐Osselton

Bibliographic record

VenueTransfusion · 2018
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsCanadian Blood Services
Fundersnot available
KeywordsBlood donationsMedicineIntensive care medicineBlood transfusionInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: In December 2014, a multinational collaboration of hemovigilance experts from the International Society of Blood Transfusion (ISBT), the International Hemovigilance Network, and AABB published harmonized definitions of complications related to blood donation titled "Standard for Surveillance of Complications Related to Blood Donation." Both mandatory and optional terms were included. The definitions are endorsed by the Alliance of Blood Operators and the European Blood Alliance. STUDY DESIGN AND METHODS: The objective of this study was to validate harmonized donor hemovigilance definitions with potential users. In June 2016, 30 real-world cases were sent to potential users around the world along with the definitions, an answer sheet, and instructions on how to complete the validation exercise. RESULTS: Overall, 54 responses from 25 countries were received, including over 400 comments. The results were presented for feedback at both ISBT and AABB meetings. Case diagnoses were consistent across most responders. Exceptions were rare adverse events, nonstandard presentations, or incomplete information. In general, the application of optional definitions, including severity grading and imputability, had the most variability. CONCLUSION: The use of standardized terms in the donor setting serves to increase focus on donor safety, facilitate conversation, foster exchange of information, and frame questions for future research. Overall, the definitions provide adequate coverage of donor reactions; however, some terms require clarification. Severity grading and imputability and other optional terms need clear and objective definitions and instructions on when and how to use them. Additional feedback and final recommendations are summarized in this report.

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.618
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.066
GPT teacher head0.286
Teacher spread0.220 · 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 designTheoretical or conceptual
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

Citations31
Published2018
Admission routes1
Has abstractyes

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