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Record W3153671878 · doi:10.1111/trf.16375

Implementation of measures to reduce vasovagal reactions: Donor participation and results

2021· article· en· W3153671878 on OpenAlexaffabout
Mindy Goldman, Samra Uzicanin, Lynne Marquis‐Boyle, Sheila F. O’Brien

Bibliographic record

VenueTransfusion · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBlood donation and transfusion practices
Canadian institutionsCanadian Blood ServicesUniversity of Ottawa
Fundersnot available
KeywordsDonationBlood donorMedicineOrgan donationBlood donationsSurgeryTransplantationPolitical science

Abstract

fetched live from OpenAlex

BACKGROUND: There are several strategies to reduce donor reactions. We report donor participation and reaction rates before and after implementing multiple measures at Canadian Blood Services. STUDY DESIGN AND METHODS: We introduced a structured program of 500 mL of water and a salty snack pre-donation and applied muscle tension (AMT) during donation. Donors were not deferred for out of range blood pressure (BP); however, BP was measured in first time donors. Time on the donation chair post-donation was decreased from 5 to 2 min for repeat donors. We assessed participation rates using our quarterly survey of 10,000 recent donors. We extracted vasovagal reactions with loss of consciousness (LOC) from our operational database and compared pre-implementation (Oct 12,018-March 31,2019) and post-implementation (Oct 12,019-March 31,2020) periods. RESULTS: Survey response rates varied from 11% to 16%. The percentage of donors who drank the water and ate the salty snack increased from 58% to 82% and 44% to 70% over 4 quarters; those performing AMT increased from 24% to 41%. Reactions decreased from 19.07 per 10,000 (744 reactions in 390,123 donations) to 14.04 per 10,000 (537 in 382,382 donations) (p < .0001). No first-time donors with high BP (n = 684) but 5 with low BP (n = 718) had reactions, CI were very large. CONCLUSIONS: Achieving optimal participation was challenging. After implementation of a donor wellness initiative based on best practice, rates of vasovagal reactions with LOC decreased by 25%. A larger dataset is necessary to assess the safety contribution of BP deferrals when other mitigation measures are in place.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.400

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 communication0.0000.001
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 head0.044
GPT teacher head0.319
Teacher spread0.275 · 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 designBench or experimental
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

Citations16
Published2021
Admission routes2
Has abstractyes

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