In Heart Failure Patients with Left Bundle Branch Block Single Lead MultiSpot Left Ventricular Pacing Does Not Improve Acute Hemodynamic Response To Conventional Biventricular Pacing. A Multicenter Prospective, Interventional, Non-Randomized Study
Bibliographic record
Abstract
INTRODUCTION: Recent efforts to increase CRT response by multiSPOT pacing (MSP) from multiple bipols on the same left ventricular lead are still inconclusive. AIM: The Left Ventricular (LV) MultiSPOTpacing for CRT (iSPOT) study compared the acute hemodynamic response of MSP pacing by using 3 electrodes on a quadripolar lead compared with conventional biventricular pacing (BiV). METHODS: Patients with left bundle branch block (LBBB) underwent an acute hemodynamic study to determine the %change in LV+dP/dtmax from baseline atrial pacing compared to the following configurations: BiV pacing with the LV lead in a one of lateral veins, while pacing from the distal, mid, or proximal electrode and all 3 electrodes together (i.e. MSP). All measurements were repeated 4 times at 5 different atrioventricular delays. We also measured QRS-width and individual Q-LV durations. RESULTS: Protocol was completed in 24 patients, all with LBBB (QRS width 171±20 ms) and 58% ischemic aetiology. The percentage change in LV+dP/dtmax for MSP pacing was 31.0±3.3% (Mean±SE), which was not significantly superior to any BiV pacing configuration: 28.9±3.2% (LV-distal), 28.3±2.7% (LV-mid), and 29.5±3.0% (LV-prox), respectively. Correlation between LV+dP/dtmax and either QRS-width or Q-LV ratio was poor. CONCLUSIONS: In patients with LBBB MultiSPOT LV pacing demonstrated comparable improvement in contractility to best conventional BiV pacing. Optimization of atrioventricular delay is important for the best performance for both BiV and MultiSPOT pacing configurations. TRIAL REGISTRATION: ClinicalTrials.gov NTC01883141.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".