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Record W2321603993 · doi:10.1037/neu0000003

Decision-making deficits persist after aneurysmal subarachnoid hemorrhage.

2013· article· en· W2321603993 on OpenAlexfundno aff
Timour Al‐Khindi, R. Loch Macdonald, Tom A. Schweizer

Bibliographic record

VenueNeuropsychology · 2013
Typearticle
Languageen
FieldMedicine
TopicIntracranial Aneurysms: Treatment and Complications
Canadian institutionsnot available
FundersOntario Ministry of Research and Innovation
KeywordsSubarachnoid hemorrhageIowa gambling taskCognitionPerseverationCohortMedicinePsychologyGlasgow Outcome ScaleStroke (engine)Glasgow Coma ScaleInternal medicinePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: Effective decision-making is critical for resuming day-to-day activities after aneurysmal subarachnoid hemorrhage (aSAH). Little is known, however, about how decision-making is affected after aSAH, particularly under ambiguous conditions in which neither the outcome nor the outcome probabilities are known. METHOD: Here we examined the integrity of decision-making under ambiguity in a cohort of aSAH patients classified as having made a "good outcome" according to the Glasgow Outcome Scale. Thirty aSAH survivors and 33 healthy controls completed the Iowa Gambling Task (IGT) and the Balloon Analogue Risk Task (BART). Mean time of assessment poststroke was 30 months. RESULTS: Although patients and controls had similar decision-making strategies on the IGT, patients made significantly fewer switches between decks, suggesting perseveration and cognitive inflexibility. On the BART, aSAH patients demonstrated significantly enhanced risk-taking behavior relative to controls. Examination of effect sizes revealed cognitive inflexibility in 33% to 35% of aSAH patients and enhanced risk-taking behavior in 35% to 40% of aSAH patients. CONCLUSION: Approximately one third of "good outcome" aSAH patients experience cognitive inflexibility and enhanced risk-taking behavior over 2 years poststroke, illustrating the persistence of aSAH-associated cognitive impairment.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.765
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0030.004

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 head0.012
GPT teacher head0.271
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 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

Citations10
Published2013
Admission routes1
Has abstractyes

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