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Record W2912222068 · doi:10.1161/str.50.suppl_1.tp394

Abstract TP394: Senior Clinical Project Leader

2019· article· en· W2912222068 on OpenAlexaff
Davis Chau, D. Melissa Garman, Corey Adams, Yichaun Zhang, Araslan Rizwan, Karla J. Ryckborst, Mayank Goyal, Michael D. Hill, Jim Christenson, Michael Tymianski

Bibliographic record

VenueStroke · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsUniversity of British ColumbiaUniversity of CalgaryNoNO (Canada)
Fundersnot available
KeywordsMedicineBody weightAmbulatoryStroke (engine)Clinical trialAcute strokeEmergency medicinePlaceboSurgeryNursingInternal medicineEmergency departmentAlternative medicine

Abstract

fetched live from OpenAlex

Introduction: FRONTIER (NCT02315443) and ESCAPE-NA1 (NCT02930018) are two pivotal trials investigating the safety and efficacy of the neuroprotectant NA-1 in acute ischemic stroke (AIS). NA-1 administration is weight-based (2.6mg/Kg), requiring the rapid estimation of body weight by paramedics in the field (FRONTIER) and by hospital staff upon ED arrival (ESCAPE-NA1). Alteplase, which is administered after hospital arrival, also requires weight-based dosing. Here we evaluated the accuracy of the body weight estimated by paramedics and by hospital staff prior to administering study drug (NA-1 or placebo) as compared to the actual subject weight collected using in-hospital scales during the subsequent in-hospital stay. Methodology: In both these studies, FRONTIER and ESCAPE-NA1, paramedics in the field and Hospital staff will be determining weight by first asking the subject, second asking a family member or third by estimation. Subsequently, in each trial, in-hospital scales are used during the subject’s admission to measure body weight accurately. The subject’s actual weight will be measured in hospital using standard hospital scales (i.e., stand up or in-bed scales if the subject is not ambulatory), as soon as possible, but within five days. Data were obtained from the trial database. Results: As of August 1 st 2018, 264 subjects were enrolled in FRONTIER of which 206 had all body weight data available, and 444 subjects were enrolled in ESCAPE-NA1 of which 218 had all body weight data available. As compared with in-hospital scales, paramedics over estimated patient weight by an average of 2.57 kg (SD = 6.94 P< 0.001). In-hospital staff under estimated patient weight by an average of 1.82kg (SD = 8.93 P=0.003). The difference is statistically significant but not clinically meaningful. Overall, the weight estimated by paramedics and by hospital staff was 93% accurate, when compared to the actual weight collected. Conclusion: Both paramedics and hospital staff were mostly accurate when estimating patient weight in the acute care settings of FRONTIER and ESCAPE-NA1. This suggests that when time is of the essence, weight may be estimated effectively for the purpose of administering stroke drugs.

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)0.011
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.260
Threshold uncertainty score0.871

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.023
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0050.002
Open science0.0020.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.2600.109

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 head0.095
GPT teacher head0.363
Teacher spread0.269 · 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 designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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