Pacemaker Longevity: Are We Getting What We Are Promised?
Bibliographic record
Abstract
BACKGROUND: Although pacemaker manufacturers provide projections on longevity, these projections cannot be relied upon due to the assumptions of output parameters being far in excess of those programmed in clinical practice. OBJECTIVE: The purpose of this review was to compare the actual longevity to the calculated longevity of pacemakers based on battery cell characteristics taking into account individual programmed parameters, mode, degree of usage, and percent pacing. This was also compared to the manufacturers' own projected longevities. METHODS: Patients who had a pacemaker replaced between 1998 and 2003 were included (n = 124). Cell characteristics were obtained from manufacturers and programmed parameters were obtained at each visit. Stepwise calculations were done for each visit to find current drain during each interval, and then were used in a weighted average to find the total average lifetime current drain. This was subsequently used to find a calculated longevity for each pacemaker to be compared to the actual longevity observed. RESULTS: The pacemakers lasted 491+/-92 days (mean+/-SEM) less than calculated. There was also a difference between dual- and single-chamber devices (though not statistically significant). Moreover, it was found that there were significant differences between manufacturers. CONCLUSIONS: There appears to be a significant discrepancy between calculated and actual longevities, confirming that battery depletion occurs earlier than expected. This suggests that current drain expended for ancillary functions may be considerable. Another factor may be pre-implantation drain. Vigilance with programming of outputs, modes, sensors, heart rates, and ancillary functions could potentially extend longevity and postpone/obviate the need for costly repeat surgery with its attended risk of complications. Furthermore, the differences between manufacturers seem to parallel the clinical impressions.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".