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Record W4410621029 · doi:10.1093/europace/euaf085.763

Sensing and detection performance of the novel, small-diameter omniasecure defibrillation lead: leadr trial analysis

2025· article· en· W4410621029 on OpenAlexaff
Prashanthan Sanders, Pamela Mason, Bert Hansky, Paolo De Filippo, Mukesch Shah, Darius P. Sholevar, John S. Zakaib, François Philippon, B. Tsang, Rajeev K. Pathak, Travis D. Richardson, M Friedman, Katherine Arias, Chad A. Bounds, George H. Crossley

Bibliographic record

VenueEP Europace · 2025
Typearticle
Languageen
FieldChemical Engineering
TopicAnalytical Chemistry and Sensors
Canadian institutionsSouthlake Regional Health CenterInstitut universitaire de cardiologie et de pneumologie de Québec
Fundersnot available
KeywordsDefibrillationLead (geology)MedicineInternal medicineComputer scienceCardiologyGeology

Abstract

fetched live from OpenAlex

Abstract Introduction The Lead EvaluAtion for Defibrillation and Reliability (LEADR) trial evaluated the small-diameter (4.7Fr), integrated bipolar OmniaSecure defibrillation lead. The trial exceeded primary safety and efficacy endpoint thresholds, demonstrating favorable performance and zero fractures through ~12 mo; patients remain in ongoing follow-up. Purpose To report on chronic electrical performance of the OmniaSecure lead through midterm follow-up of the LEADR trial. Methods Patients with indication for de novo ICD/CRT-D were implanted with the OmniaSecure lead in standard RV locations and followed at prespecified intervals along with CareLink. Results As reported, a total of 643 patients were implanted with the OmniaSecure lead; the lead continues to show favorable safety, efficacy, and reliability with zero fractures through midterm follow-up (18.2 ± 5.5 mo). Electrical measurements (Pacing capture threshold, pacing impedance, and R-wave amplitude) were chronically stable through follow-up; average R-wave amplitudes were >10mV throughout (Figure 1). Nineteen patients had reports of P-wave oversensing (PWOS), however there were zero inappropriate shocks due to PWOS. Among those with associated adverse events, 3 resulted in system modification and 1 in reprogramming. The remaining 15 patients had instances of PWOS noted by physicians via monitoring that were not associated with an adverse event; resolved via repositioning at implant (1) and reprogramming (14). Thirty-eight patients had reports of T-wave oversensing (TWOS). Among these, 1 patient had a system modification and 3 patients had reprogramming after inappropriate shock after which no further IAS was reported. The remaining 34 patients had instances of TWOS noted by physicians at device checks that were not associated with an adverse event; 1 resulted in unsuccessful implant and 1 had no action taken for lack of clinical concern, the others were resolved via repositioning at implant (1) and reprogramming (31). Additionally, 1 patient reported both TWOS and PWOS; both resolved via reprogramming with no further reports of TWOS/PWOS. During induced VF sensing at implant, 98% (119/122) of patients showed appropriate detection at the least sensitive setting (1.2mV) and the remaining were successful at more sensitive settings. There were 670 ambulatory VT/VF episodes appropriately treated in 94 patients, all of which were successfully detected across a variety of programmed sensitivities (Table 1) with no reported undersensing. Conclusion Chronic sensing performance of the OmniaSecure defibrillation lead demonstrated R-wave stability with a low rate of PWOS and TWOS, predominantly resolved by reprogramming RV sensitivity. Furthermore, VT/VF detection was successful in all patients and was not impacted when reprogrammed to less sensitive settings. The OmniaSecure lead shows a robustness of sensing and detection performance and programmability.Figure 1:Chronic electrical stability o Table 1:Proportion of successfully trea

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.013
GPT teacher head0.218
Teacher spread0.204 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

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Citations1
Published2025
Admission routes1
Has abstractyes

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