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Record W4321606085 · doi:10.1101/2023.02.15.23286004

DOC screen completion time reflects executive function, speed of processing and fluency in an observational cohort study

2023· preprint· en· W4321606085 on OpenAlexaff
Alisia Southwell, Sajeevan Sujanthan, Tera Armel, Elaine Xing, Arunima Kapoor, Xiao Yu Eileen Liu, Krista L. Lanctôt, Nathan Herrmann, Brian J. Murray, Kevin E. Thorpe, Megan L. Cayley, Michelle N. Sicard, Karen Lien, Demetrios J. Sahlas, Richard H. Swartz

Bibliographic record

VenuemedRxiv · 2023
Typepreprint
Languageen
FieldMedicine
TopicObstructive Sleep Apnea Research
Canadian institutionsMcMaster UniversityUniversity of TorontoHamilton Health SciencesHamilton General HospitalHealth Sciences CentreHeart and Stroke FoundationSunnybrook Health Science Centre
Fundersnot available
KeywordsVerbal fluency testCognitionReceiver operating characteristicNeuropsychologyMedicineCohortNeuropsychological assessmentFluencyEffects of sleep deprivation on cognitive performanceAudiologyPsychologyPsychiatryInternal medicine

Abstract

fetched live from OpenAlex

Abstract Background The DOC screen was developed to identify Depression, Obstructive sleep apnea, and Cognitive impairment (“DOC” comorbidities) after stroke. Each component has its own score, but additional information may be gained from the time to complete the screen. Cognitive screening completion time is rarely used as an outcome measure. We assessed the added value of using DOC screen completion time as a predictor of impairment on detailed cognitive assessments. Methods Consecutive English-speaking new referrals to the stroke prevention clinic were consented to participate in detailed neuropsychological testing (n=437). DOC screen scores and times were compared to cognitive test scores using multiple linear regression and receiver operating characteristic (ROC) analysis. All linear regression analyses controlled for age, sex, years of education, and functional outcome as assessed by the modified Rankin score. Results Average completion time for the DOC screen was 3.8 ± 1.3 minutes. After accounting for age, sex and cognitive screen score, completion time was a significant independent predictor, of speed of processing (p = .002, 95% CI: -0.016 to -0.004), verbal fluency (p < .001, CI: -0.012 to -0.006) and executive (p = .004, CI: -0.006 to -0.001), but not memory, function. Completion time above 5.5 minutes (332.5 seconds) was associated with a high likelihood of impairment on gold standard executive (likelihood ratios 3.9-5.2) and speed of processing (likelihood ratio = 5.2) tasks. Conclusions DOC screen completion time is easy to collect in routine care and is independently associated with speed of processing, language and executive dysfunctions after stroke. People who take more than 5.5 minutes to complete the DOC screen are likely to have deficits in executive functioning and speed of processing. These domains can be challenging to screen for in stroke survivors, and this measure provides a simple, clinically feasible method to screen for these under-appreciated concerns. Clinical Trials Registration Identifier: NCT02363114 Clinical Trials URL: https://clinicaltrials.gov/ct2/show/NCT02363114

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)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.138
GPT teacher head0.389
Teacher spread0.251 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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