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Record W2078972913 · doi:10.1186/1745-6215-9-13

From multidimensional neuropsychological outcomes to a cognitive complication rate: The International Subarachnoid Aneurysm Trial

2008· article· en· W2078972913 on OpenAlexfundno aff
Richard B. Scott, Fiona Eccles, Andrew Lloyd, Katherine Carpenter

Bibliographic record

VenueTrials · 2008
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
FundersMedical Research CouncilCanadian Institutes of Health ResearchUniversity of Oxford
KeywordsNeuropsychologyMedicineCognitionClinical psychologyPhysical therapyPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

BACKGROUND: The neuropsychological arm of the International Subarachnoid Aneurysm Trial (N-ISAT) evaluated the cognitive outcome of 573 patients at 12 months following subarachnoid haemorrhage (SAH). The assessment included 29 psychometric measures, yielding a substantial and complex body of data. We have explored alternative and optimal methodologies for analysing and summarising these data to enable the estimation of a cognitive complication rate (CCR). Any differences in cognitive outcome between the two arms of the trial are not however reported here. METHODS: All individual test scores were transformed into z-scores and a 5th percentile cut-off for impairment was established. A principal components analysis (PCA) was applied to these data to mathematically transform correlated test scores into a smaller number of uncorrelated principal components, or cognitive 'domains'. These domains formed the basis for grouping and weighting individual patients' impaired scores on individual measures. In order to increase the sample size, a series of methods for handling missing data were applied. RESULTS: We estimated a 34.1% CCR in all those patients seen face-to-face, rising to 37.4% CCR with the inclusion of patients who were unable to attend assessment for reason related to the index SAH. This group demonstrated significantly more self and carer/relative rated disability on a Health Related Quality of Life questionnaire, than patients classified as having no functionally significant cognitive deficits. CONCLUSION: Evaluating neuropsychological outcome in a large RCT involves unique methodological and organizational challenges. We have demonstrated how these problems may be addressed by re-classifying interval data from 29 measures into a dichotomous CCR. We have presented a 'sliding scale' of undifferentiated individual cognitive impairments, and then on the basis of PCA-derived cognitive 'domains', included consideration of the distribution of impairments in these terms. In order to maximize sample size we have suggested ways for patients who did not complete the entire protocol to be included in the overall CCR. ISAT TRIAL REGISTRATION: ISRCTN49866681.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.871
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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)0.0010.001

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 head0.150
GPT teacher head0.393
Teacher spread0.243 · 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.

Study designObservational
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

Citations20
Published2008
Admission routes1
Has abstractyes

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