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Record W4214872395 · doi:10.5770/cgj.25.525

The Ottawa 3DY Predicts Mortality in a Prospective Cohort Study

2022· article· en· W4214872395 on OpenAlexafffundvenueabout
Philip D. St. John, Frank Molnar

Bibliographic record

VenueCanadian Geriatrics Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsUniversity of ManitobaUniversity of Ottawa
FundersHealth Canada
KeywordsMedicineConfidence intervalLogistic regressionReceiver operating characteristicCohortOdds ratioDemographyMini–Mental State ExaminationStatisticProspective cohort studyPopulationCohort studyStatisticsInternal medicineCognitive impairmentDisease

Abstract

fetched live from OpenAlex

Background: The Ottawa 3DY (O3DY) is a simple measure of cognition. Objectives: 1) To determine if the O3DY predicts mortality; and 2) To compare the discrimination of the O3DY to the Mini-Mental State Examination (MMSE) and Modified MMSE (3MS). Methods: Analyses of a population based cohort study of 1,751 participants aged 65+; conducted in 1991/2 with follow-up over five years. The O3DY, age, sex, education, comorbid conditions, the MMSE, and the 3MS were measured: 4.5% of the participants had missing data for the O3DY; 42.8% were considered as positive (one or more errors), and 52.7% were considered as negative (no errors). Logistic regression models were constructed with the outcome of death at time 2. A Receiver Operator Curve (ROC) was constructed and the Area Under the ROC (AUROC) was calculated using a c-statistic. Results: The unadjusted odds ratio (OR) and 95% confidence interval (CI) for mortality was 1.96 (1.56, 2.47); and the adjusted OR was 1.33 (1.02, 1.72). The AUROC was 0.66 for the 3MS, 0.65 for the MMSE, and 0.60 for the O3DY. Conclusions: The O3DY predicts mortality over a long time frame, although the discrimination is less than that of longer measures of cognition.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.104
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.015
GPT teacher head0.296
Teacher spread0.281 · 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 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

Citations2
Published2022
Admission routes4
Has abstractyes

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