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Record W3092254727 · doi:10.4103/aian.aian_639_19

Systematic development of structured semi-interactive stroke prevention package for secondary stroke prevention

2020· article· en· W3092254727 on OpenAlexaff
Deepti Arora, Rohit Bhatia, Dheeraj Khurana, Arvind Sharma, Vishnu Renjith, S Jabeen, Meenakshi Sharma

Bibliographic record

VenueAnnals of Indian Academy of Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicAcute Ischemic Stroke Management
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsWorkbookMedicineStroke (engine)Formative assessmentPatient educationRandomized controlled trialPhysical therapyFamily medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Lack of compliance to medication and uncontrolled risk factors are associated with increased risk of recurrent stroke and acute coronary syndrome in patients with recent stroke. Multimodal patient education may be a strategy to improve the compliance to medication and early adoption of nonpharmacological measures to reduce the vascular risk factor burden in patients with stroke. We thus aim to develop multilingual short messaging services (SMS), print, and audio-visual secondary stroke prevention patient education package. The efficacy of the package will be tested in a randomized control trial to prevent major cardiovascular and cerebrovascular events. METHODS: stage). RESULTS: = 2) noted no implementation issues at the end of 1 month. CONCLUSION: An implementable complex multilingual patient education material could be developed in a stepwise manner. The efficacy of the package to prevent major adverse cardiovascular events is being tested in the SPRINT INDIA study.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.167
Threshold uncertainty score0.917

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.051
GPT teacher head0.336
Teacher spread0.285 · 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

Citations11
Published2020
Admission routes1
Has abstractyes

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