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Record W6981917108

Frailty assessment before cardiac surgery

2010· dissertation· en· W6981917108 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2010
Typedissertation
Languageen
FieldEarth and Planetary Sciences
TopicMineralogy and Gemology Studies
Canadian institutionsnot available
FundersInstitut de Cardiologie de MontréalJewish General Hospital
KeywordsDiseaseStressorHeart failureCardiac surgeryFrailty syndromeCardiovascular eventPathogenesis
DOInot available

Abstract

fetched live from OpenAlex

Background: Frailty is a geriatric syndrome of increased vulnerability to stressors which has been implicated as an etiologic and prognostic factor in patients with cardiovascular disease.The American Heart Association and the Society of Geriatric Cardiology have called for a better understanding of frailty as it pertains to cardiac care in the elderly.Methods: We sought to systematically review studies of frailty in patients with cardiovascular disease.We searched Ovid MEDLINE, EMBASE, Cochrane Database, and unpublished sources.Inclusion criteria were assessment of frailty using systematically defined criteria and a study population with prevalent or incident cardiovascular disease.Results: Nine studies were included encompassing 54,250 elderly patients with a mean weighted follow-up of 6.2 years.Among community-dwelling elders, cardiovascular disease was associated with an odds ratio (OR) of 2.7-4.1 for prevalent frailty, and an OR of 1.5 for incident frailty among those who were not frail at baseline.Gait speed (a measure of frailty) was associated with an OR of 1.6 for incident cardiovascular disease.Among elderly patients with documented severe coronary artery disease or heart failure, the prevalence of frailty was 50-54% and this was associated with an OR of 1.6-4.0 for all-cause mortality after adjusting for potential confounders.Conclusion: There exists a relation between frailty and cardiovascular disease; frailty may lead to cardiovascular disease, just like cardiovascular disease may lead to frailty.The presence of frailty confers an incremental increase in mortality.The role of frailty assessment in clinical practice may be to refine estimates of cardiovascular risk which tend to be less accurate in the heterogeneous elderly patient population.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.250
Teacher spread0.231 · 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
Published2010
Admission routes1
Has abstractyes

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