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Record W2565300330 · doi:10.1136/hrt.2010.195958.10

036 In-hospital outcomes of very elderly patients (over 85 years old) undergoing percutaneous coronary intervention:

2010· article· en· W2565300330 on OpenAlexaff
Clare Appleby, Joan Ivanov, Karen Mackie, Vladimír Džavík, C.B. Overgaard

Bibliographic record

VenueHeart · 2010
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsToronto General Hospital
Fundersnot available
KeywordsMedicineConventional PCIMacePercutaneous coronary interventionTertiary referral hospitalComorbidityCohortInternal medicinePropensity score matchingEmergency medicineRetrospective cohort studySurgeryMyocardial infarction

Abstract

fetched live from OpenAlex

<h3>Background</h3> Interventionists are often reluctant to undertake PCI in very elderly patients due to the perception of poor outcome in a high risk cohort. Paradoxically however, elderly patients may benefit most from revascularisation because of their higher baseline risk compared to younger patients. The prognostic significance of advanced age itself is not clear. <h3>Objective</h3> An observational study determining the in-hospital outcomes of very elderly patients (age&gt;85) undergoing percutaneous coronary intervention (PCI) for all indications at a tertiary cardiac referral centre. <h3>Methods</h3> Baseline clinical, angiographic and procedural variables and in-hospital outcome data were entered into a prospective registry of 17 572 consecutive patients undergoing PCI at the University Health Network between April 2000 and December 2008. Patients were stratified according to age (&lt;85 years, n=17 168, or ≥85 years, n=404) and in-hospital mortality, major adverse cardiac event (MACE) and complication rates were calculated. Logistic regression-analysis identified independent predictors of unadjusted mortality and MACE. Very elderly patients were propensity matched (1:2 ratio) with younger patients, and the analysis repeated. <h3>Results</h3> Very elderly patients had a mean age of 87.5±2.9 (range 85 to 97) vs 62.8±11.1 years for the younger cohort and had greater comorbidity. The very elderly were more likely to present as a primary or urgent PCI, and PCI was less likely to be undertaken electively. Left main stem and complex lesion-type intervention was greater, and angiographic success less likely. Unadjusted mortality and post procedure MI were significantly higher (6.93% vs 1.20%, p&lt;0.0001 and 4.46% vs 2.74%, p=0.04), but CABG rates did not significantly differ (0.25% vs 0.47%, p=0.5). Length of stay, renal, neurological and access-site complications were all greater in the very elderly cohort. Though age≥85 years was a significant independent predictor of both mortality (OR 2.62, CI 1.44 to 4.78, p=0.0016) and MACE (OR 1.94, CI 1.25 to 3.01, p=0.003), its effect was not as great as other well documented variables such as cardiogenic shock and urgency of procedure. After propensity matching, mortality remained significantly higher in the very elderly patients (7.0% vs 3.25%, p=0.003). MACE rates were also significantly higher (9.75% vs 5.88%, p=0.014). Advanced age remained a strong predictor of worse outcomes (mortality OR 2.90, CI 1.38 to 6.06, p=0.005, MACE OR 2.01, CI 1.17 to 3.46, p=0.011). <h3>Conclusion</h3> Very elderly patients represent a high risk cohort in terms of comorbidity and complications post-PCI. Although in-hospital mortality was significantly increased compared with younger patients, death occurred predominantly in very elderly patients undergoing non-elective PCI. Decisions to proceed with PCI in very elderly patients should be based on other prognostic variables and these patients should not be excluded from revascularization based on age alone.

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)0.002
metaresearch head score (Gemma)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.001

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 head0.080
GPT teacher head0.363
Teacher spread0.283 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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