Implantable cardiac defibrillators in octogenarians
Bibliographic record
Abstract
<sec><strong>OBJECTIVE</strong> Implantable cardiac defibrillators (ICD) implantation in the very elderly remains controversial. We aimed to describe the experience and outcome of patients over 80 years old implanted with an ICD in Belgium. </sec><sec><strong>METHODS</strong> Data were extracted from the national QERMID-ICD registry. All implantations performed in octogenarians between February 2010 and March 2019 were analysed. Data on baseline patient characteristics, type of prevention, device configuration and all-cause mortality were available. To determine predictors of mortality, multivariable Cox proportional hazard regression modelling was performed. </sec><sec><strong>RESULTS</strong> Nationwide, 704 primo ICD implantations were performed in octogenarians (median age 82, IQR 81-83 years; 83% male and 45% secondary prevention). During a mean follow-up of 3.1 ± 2.3 years, 249 (35%) patients died, of which 76 (11%) within the first year after implantation. In multivariable Cox regression analysis age (HR = 1.15, <i>P</i> = 0.004), oncological history (HR = 2.43, <i>P</i> = 0.027) and secondary prevention (HR = 2.23, <i>P</i> = 0.001) were independently associated with 1-year mortality. A better preserved left ventricular ejection fraction (LVEF) was associated with a better outcome (HR = 0.97, <i>P</i> = 0.002). Regarding overall mortality multivariable analysis withheld age, history of atrial fibrillation, centre volume and oncological history as significant predictors. Higher LVEF was again protective (HR = 0.99, <i>P</i> = 0.008). </sec><sec><strong>CONCLUSIONS</strong> Primary ICD implantation in octogenarians is not often performed in Belgium. Among this population, 11% died within the first year after ICD implantation. Advanced age, oncological history, secondary prevention and a lower LVEF were associated with an increased one-year mortality. Age, low LVEF, atrial fibrillation, centre volume and oncological history were indicative of higher overall mortality. </sec>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".