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CRASH: CONVERSATIONS AND REACTIONS AROUND SEVERE HYPOGLYCEMIA: A GLOBAL STUDY

2017· other· en· W6964909708 on OpenAlexaboutno aff

Bibliographic record

VenueBiblioBoard Library Catalog (Open Research Library) · 2017
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)Suicide preventionDiabetic ketoacidosisType 1 diabetesDescriptive researchType 2 diabetesPoison controlMEDLINE

Abstract

fetched live from OpenAlex

Background and Aims: There is little known about the experience of persons with diabetes (PWD) and their caregiversu2019 (CG) knowledge of a severe hypoglycemic event (SHE), and the use of glucagon to treat such an event. The CRASH (Conversations and Reactions Around Severe Hypoglycemia) cross-sectional survey was developed to address this research gap.Method: Medical research panels were used to identify and recruit 400 participants (200 PWD and 200 CG, evenly divided between type 1 and type 2 diabetes) in each of six countries: Canada, Germany, China, Spain, UK, and US. All participants were age u226518 years old. Inclusion criteria for PWD included self-report of insulin therapy and having had experienced a SHE within the past 3 years. CG inclusion required self-report of caring for a PWD u22654 years old on insulin therapy, who had experienced a SHE within the past 3 years. Participants completed a 30-minute online survey that examined their understanding of a SHE and its treatment, their actions during the SHE, and finally, what precautionary actions occurred after the SHE in terms of prevention and emergency preparedness. Descriptive analyses were conducted. Management and impact of a SHE were analyzed by subgroups including: diabetes type, participant type, age, glucagon use. Results: Data from 400 UK participants were analyzed. Findings describe symptom recognition, knowledge and use of self-management strategies and professional emergency medical assistance. Conclusion: Results provide much needed insights of the impact SHE (both personal and societal perspectives) and current glucagon treatment have on PWD and their CG.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.077
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0070.010
Open science0.0040.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0280.003

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 head0.082
GPT teacher head0.341
Teacher spread0.259 · 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; both teacher heads agree on what is shown here.

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".

Quick stats

Citations0
Published2017
Admission routes1
Has abstractyes

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