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QRS Width: Easily Obtained but Overlooked Parameter in Monitoring Algorithms in Implantable Devices

2023· preprint· en· W4383645548 on OpenAlexaff
Arjun K. Aggarwal, Ayana Nanthakumar, Bonnie Daba, Arulalan Veluppillai, Melanie Burg R, Kumaraswamy Nanthakumar

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsEjection fractionQRS complexMedicineCardiologyInternal medicineHeart failureCardiac resynchronization therapyCardiomyopathy

Abstract

fetched live from OpenAlex

Introduction We describe the progressive increase in the QRS durations (QRSd) and the subsequent decrease in the left ventricular ejection fractions (LVEF) of two patients post pacemaker implantation. We aim to highlight the need for contemporary cardiac implantable electronic devices (CIEDs) to include QRSd monitoring in the standard device data capture. This would ultimately allow for early interventions to be made to prevent chronic heart failure (CHF) hospitalizations. Methods The echocardiographic studies of two patients (pre and post pacemaker implantation) were analyzed, in order to determine changes in QRSd and LVEF data leading up to CHF hospitalization events. Results Patient 1 had a QRSd of 66 msec in June of 2018, one month before pacemaker implantation. Six months after implantation, Patient 1 had an increased QRSd of 156 msec. This was accompanied with a stark decrease in LVEF, from 55% at the time of implantation to below 35% in October of 2020. Patient 2 had a QRSd of 160 msec and a LVEF of 43% prior to the implantation of a pacemaker in 2016. Patient 2 similarly showed a progressive increase in their QRSd and was found to have a significantly decreased LVEF of 17% when hospitalized for decompensated heart failure around 5 years after pacemaker insertion. Conclusion Chronic RV apical pacing can be associated with adverse effects, leading to compromised cardiac function and resulting in pacing-induced cardiomyopathy (PICM). Progressive paced QRS widening can be indicative of CHF development and correlates with a decline in ejection fraction. The addition of device based QRS width monitoring to the current trend toolkit in implantable devices could alert electrophysiologists and patients of the potential for PICM, in the absence of serial 12 lead comparisons. This pre-emptive alert is essential in an era where remedy in the form of cardiac resynchronization and physiological pacing therapy is readily available.

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)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.085
GPT teacher head0.351
Teacher spread0.266 · 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 designObservational
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

Citations0
Published2023
Admission routes1
Has abstractyes

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