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Record W2766227684 · doi:10.1016/j.jalz.2017.06.677

[P2–029]: GLOBAL STATISTICAL ANALYSIS OF OUTCOMES FROM THE ‘PREVENTION OF DECLINE IN COGNITION AFTER STROKE TRIAL’ (PODCAST)

2017· article· en· W2766227684 on OpenAlexaboutno aff
Polly Scutt, Philip M. Bath, Jason P. Appleton, Nikola Sprigg

Bibliographic record

VenueAlzheimer s & Dementia · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal Cognitive AssessmentStroke (engine)GuidelineCognitionMedicinePhysical therapyPsychologyPsychiatryCognitive impairment

Abstract

fetched live from OpenAlex

The ‘Prevention of Decline in Cognition After Stroke Trial’ (PODCAST) was a multicentre partial factorial randomised controlled trial to assess the effect of intensive versus guideline blood pressure lowering and intensive versus guideline lipid lowering on cognitive outcomes in patients with a recent stroke. The Wei-Lachin test is a multivariate generalization of the Wilcoxon–Mann– Whitney test and can be used to combine multiple outcomes to produce an average estimate of overall recovery from stroke. The effect of intensive versus guideline lipid lowering on multiple combined primary and secondary outcomes was assessed using the Wei-Lachin test. Analyses using multiple linear regression were also performed on primary and secondary outcomes individually. Cognition outcomes analysed were the Addenbrooke's Cognitive Examination-R (ACE-r), Mini-Mental State Examination (MMSE), Montreal Cognitive assessment (MoCA), Telephone Interview Cognition Scale (TICS), Trail making B (time and correct answers), Informant (IQ code), verbal fluency (animal naming) and Stroop interference (accuracy and time). Other outcomes analysed were the Modified Rankin Scale (mRS), Barthel Index (BI), EuroQoL-Health Utility Status (EQ-5D HUS), Zung Depression Scale (ZDS) and telephone MMSE (t-MMSE). Eighty three patients were randomised into the PODCAST trial, 77 into the intensive versus guideline lipid lowering comparison. For the intensive versus guideline lipid comparison, the primary outcome, ACE-r, was neutral. However, for a number of secondary outcomes, a statistically significant difference was found between treatment groups in favour of intensive lipid lowering. Results from analyses of individual outcomes are given in Table 1. The Wei-Lachin test showed a statistically significant difference in favour of intensive lipid lowering for a global cognition outcome (Mann-Whitney statistic=4.3, p=0.023) and for a global outcome consisting of measures of dependency, disability, quality of life, mood and cognition (Mann-Whitney statistic=2.14, p=0.023). Intensive lipid lowering improves cognition and overall recovery on global aggregate outcomes. Global outcomes are more statistically efficient than individual tests and provide an overall estimate of treatment effect encompassing a range of outcomes of relevance after stroke. Global outcomes could be of interest to patients involved in clinical trials as it gives an estimate of overall recovery as opposed to recovery in one specific domain.

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)0.008
metaresearch head score (Gemma)0.015
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.119

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.004
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0360.002

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 head0.042
GPT teacher head0.357
Teacher spread0.315 · 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 designMeta-analysis
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

Citations0
Published2017
Admission routes1
Has abstractyes

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