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Optimal Pacing for Symptomatic AV Block:

2004· article· en· W3196429390 on OpenAlexaff
Max T. Huang, Andrew D. Krahn, Raymond Yee, George J. Klein, Allan C. Skanes

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2004
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsWestern University
Fundersnot available
KeywordsMedicineImplantAtrioventricular blockCardiologyComplicationInternal medicineSurgery

Abstract

fetched live from OpenAlex

VDD pacing provides the physiological benefits of atrioventricular synchronous pacing with the convenience of a single lead system, but is hampered by uncertainty regarding long term atrial sensing and potential development of sinus node disease. To examine the long-term reliability and complication rates of VDD pacing, we compared the outcome of 112 consecutive patients (age 70 +/- 13 years, 59% men) with symptomatic AV block who received a single pass bipolar VDD system, to 80 patients (age 63 +/- 16 years, 70% men) who received DDD pacing for the same indication. All patients were judged to have intact sinus node function based on submitted ECGs and monitoring results at the time of implant. Implant time was reduced in VDD patients compared to DDD patients (63 +/- 20 vs 97 +/- 36 minutes, P < 0.0001). Implant complications occurred in 5 (6%) DDD patients compared to 3 (3%) VDD patients (P = 0.15). The implant P wave was lower with VDD pacing compared to DDD patients (2.91 +/- 1.48 vs 4.0 +/- 1.7 mv, P < 0.0001), but remained stable during long-term follow-up in both groups. During 17.7 +/- 10.0 months of follow-up in the VDD group, only two VDD patients were reprogrammed to VVIR mode, compared to three DDD patients. Physiological atrioventricular activation was maintained in 94%-99% of beats throughout the follow-up period in the VDD group. VDD pacing is an excellent strategy for treatment of patients with symptomatic AV block. The lower cost, high reliability, and abbreviated implantation time suggest that VDD pacing is a viable alternative to DDD pacing in patients with high degree AV block and normal sinus node function.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.542

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.025
GPT teacher head0.355
Teacher spread0.330 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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".

Quick stats

Citations33
Published2004
Admission routes1
Has abstractyes

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