Benefit of Pacemaker Therapy in Patients With Presumed Neurally Mediated Syncope and Documented Asystole Is Greater When Tilt Test Is Negative
Bibliographic record
Abstract
BACKGROUND: In the Third International Study on Syncope of Uncertain Etiology (ISSUE-3), cardiac pacing was effective in reducing recurrence of syncope in patients with presumed neurally mediated syncope (NMS) and documented asystole but syncope still recurred in 25% of them at 2 years. We have investigated the role of tilt testing (TT) in predicting recurrences. METHODS AND RESULTS: In 136 patients enrolled in the ISSUE-3, TT was positive in 76 and negative in 60. An asystolic response predicted a similar asystolic form during implantable loop recorder monitoring, with a positive predictive value of 86%. The corresponding values were 48% in patients with non-asystolic TT and 58% in patients with negative TT (P=0.001 versus asystolic TT). Fifty-two patients (26 TT+ and 26 TT-) with asystolic neurally mediated syncope received a pacemaker. Syncope recurred in 8 TT+ and in 1 TT- patients. At 21 months, the estimated product-limit syncope recurrence rates were 55% and 5%, respectively (P=0.004). The TT+ recurrence rate was similar to that seen in 45 untreated patients (control group), which was 64% (P=0.75). The recurrence rate was similar between 14 patients with asystolic and 12 with non-asystolic responses during TT (P=0.53). CONCLUSIONS: Cardiac pacing was effective in neurally mediated syncope patients with documented asystolic episodes in whom TT was negative; conversely, there was insufficient evidence of efficacy from this data set in patients with a positive TT even when spontaneous asystole was documented. Present observations are unexpected and need to be confirmed by other studies. Clinical Trial Registration- URL: http://www.clinicaltrials.gov. Unique identifier: NCT01463358.
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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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".