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Record W2232301969 · doi:10.1136/ebmed-2015-110285

Intermediate and long-term cognitive effects in older adults secondary to cardiovascular procedures is uncommon but current evidence is insufficient

2015· letter· en· W2232301969 on OpenAlexaff
Lesley Charles

Bibliographic record

VenueEvidence-Based Medicine · 2015
Typeletter
Languageen
FieldMedicine
TopicCardiac, Anesthesia and Surgical Outcomes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicinePopulationAtrial fibrillationCognitive impairmentRandomized controlled trialCardiologyStroke (engine)Cognitive declineWeb of scienceInternal medicineCognitionPediatricsSurgeryMeta-analysisDementiaPsychiatry

Abstract

fetched live from OpenAlex

Commentary on: Fink HA, Hemmy LS, MacDonald R, et al. Intermediate- and long-term cognitive outcomes after cardiovascular procedures in older adults: a systematic review. Ann Intern Med 2015;163:107–17[OpenUrl][1][CrossRef][2][PubMed][3]. Cardiovascular procedures are common in the older population.1 There is suspicion that these procedures may have a negative outcome on cognition.2 However, further research has indicated that there may have been pre-existing cognitive deficits as cognitive impairment is common in the older population.3 This systematic review examines the evidence of the relationship of coronary and carotid revascularisation, cardiac valve replacement and repair and ablation for atrial fibrillation on intermediate-term and long-term cognitive outcomes in adults 65 years or above, including the effects of procedure related stroke or transient ischaemic attack. This was a systematic review of randomised controlled trials (RCTs) and prospective cohort studies of adults aged 65 years … [1]: {openurl}?query=rft.jtitle%253DAnn%2BIntern%2BMed%26rft.volume%253D163%26rft.spage%253D107%26rft_id%253Dinfo%253Adoi%252F10.7326%252FM14-2793%26rft_id%253Dinfo%253Apmid%252F26192563%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/external-ref?access_num=10.7326/M14-2793&link_type=DOI [3]: /lookup/external-ref?access_num=26192563&link_type=MED&atom=%2Febmed%2F20%2F6%2F221.atom

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Other designhigh
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.440
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.310
Teacher spread0.276 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
Domainnot available
GenreEmpirical · Commentary

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
Published2015
Admission routes1
Has abstractyes

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