Evaluation of the Appropriateness of Pacemaker Mode Selection in Bradycardia Pacing:
Bibliographic record
Abstract
Although guidelines for selection of the appropriate pacing mode have been published, little data is available on how closely these are followed in the clinical setting. All 738 patients (men 412, women 326; age 73.4 +/- 0.46 years; range 19-101 years) who underwent pacemaker implantation from 1996 to 2000 were reviewed to determine if the appropriate mode was selected based on the ACC/AHA guidelines with the data collected prospectively. Demographic, investigational, and implantation data including the presence of sinus disease and/or atrioventricular block, diagnosis, indication for pacing, ACC/AHA class indication for device therapy, recommended ACC/AHA mode, implanted mode, and reason for not using the recommended mode were entered into an SPSS data base. Of 738 patients, 708 were cross-tabulated for a match to the guidelines of which 358 (50.6%) had a mode selected that did not conform. The reasons were advanced physical disability (16%), physician choice without identifiable reason (21%), rate modulation selected without identifiable indication (16%), DDD implanted instead of VDD (25%), advanced age (9%), rare need for pacing (6%), a need for specific device features (5%), and unstable stimulation thresholds or difficult venous access (2%). In the treatment of bradyarrhythmias, deviation from the ACC/AHA indicated mode occurred in a substantial proportion of pacing system implantations. However, in many, the deviation appeared appropriate considering the patient's clinical status. Nevertheless, in a smaller proportion of patients the deviation appeared inappropriate requiring rectification. The two outstanding categories were: (1) elderly denied a dual chamber system with no clinical explanation and (2) selection of rate-modulated devices without any indication of chronotropic incompetence.
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 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 | 0.008 | 0.051 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".