2167Impact of dual-chamber pacing with closed loop stimulation on quality of life in patients with recurrent reflex vasovagal syncope: results from the SPAIN study
Bibliographic record
Abstract
Abstract Background Reflex vasovagal syncope (VVS) is one of the most common causes of syncope and, when recurrent, can have devastating consequences on the quality of life of patients despite pharmacological interventions. The closed loop stimulation (CLS) pacing algorithm converts, during an incipient VVS, variations in right intracardiac impedance into heart rate adaptation. The study SPAIN was the first randomized, double-blind trial robustly showing a strong reduction in syncopal recurrence in patients paced with dual-chamber (DDD)-CLS. (NCT01621464). Purpose To evaluate whether the differences observed in the SPAIN study regarding syncope burden and time to recurrence translate into improvements on quality of life. Methods This study analysed quality of life data from the SPAIN study: a randomized, prospective, double-blind, multicenter trial conducted in 10 Spanish and 1 Canadian centers. Ethics Committee approval was obtained at each participating center. Patients aged ≥40 years, with ≥5 VVS episodes and cardioinhibitory response to head-up tilt testing were included. After implant, patients were randomized 1:1 to active DDD-CLS mode for 12 months followed by sham DDI mode for the remaining 12 months or vice-versa. Quality of life was assessed via the Short Form-36 (SF-36) health survey before randomization (baseline), and at 12- and 24-month follow-up. The change in quality of life during the entire follow-up relative to baseline was compared between each pacing mode (DDD-CLS vs. DDI). Results Fifty-four patients were enrolled with a mean age of 56.3±10.6 years and a median of 12 syncopal episodes before randomization. Median SF-36 scores greatly increased from baseline in the DDD-CLS group across the 8 domains, whereas the response was variable in the DDI group. Comparing both pacing algorithms, median SF-36 scores were higher in the DDD-CLS group, with differences reaching statistical significance for “physical role” and “vitality” domains (p-value =0.006 and 0.014, respectively). Pacing sequence or treatment period did not significantly influence the response (p-value >0.05 for all the domains). Conclusions We demonstrated the beneficial effect of this physiological pacing algorithm on the quality of life of patients, as evidenced by the improvement in all the domains of the SF-36 when stimulated in DDD-CLS as compared to the sham DDI mode.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".