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Record W2513785767 · doi:10.14740/cr495w

Fragmented QRS as a Marker of Electrical Dyssynchrony to Predict Inter-Ventricular Conduction Defect by Subsequent Echocardiographic Assessment in Symptomatic Patients of Non-Ischemic Dilated Cardiomyopathy

2016· article· en· W2513785767 on OpenAlexvenueno aff
Santosh Kumar Sinha, Kush Kumar Bhagat, Mohammad Asif, Karandeep Singh, Mohit Sachan, Vikas Mishra, Nasar Afdaali, Mukesh Jitendra Jha, Ashutosh Kumar, Shravan Singh, Rupesh Sinha, Dibbendhu Khanra, Ramesh Thakur, C. M. Varma, Vinay Krishna, Umeshwar Pandey

Bibliographic record

VenueCardiology Research · 2016
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCardiologyInternal medicineQRS complexDilated cardiomyopathyHeart failure

Abstract

fetched live from OpenAlex

BACKGROUND: Left ventricular (LV) dyssynchrony frequently occurs in patients with heart failure (HF). QRS ≥ 120 ms is a surrogate marker of electrical dyssynchrony, which occurs in only 30% of HF patients. In contrary, in those with normal QRS (nQRS) duration, LV dyssynchrony has been reported in 20-50%. This study was carried out to investigate the role of fragmented QRS (fQRS) on the surface electrocardiography (ECG) as a marker of electrical dyssynchrony to predict the presence of significant intraventricular dyssynchrony (IVD) by subsequent echocardiographic assessment. METHODS: A total of 226 consecutive patients with non-ischemic cardiomyopathy were assessed for fQRS on surface ECG as defined by presence of an additional R wave (R prime), notching in nadir of the S wave, notching of R wave, or the presence of more than one R prime (fragmentation) in two contiguous leads corresponding to a major myocardial segment. Tissue Doppler imaging (TDI) was performed in the apical views (four-chamber, two-chamber and long-axis) to analyze all 12 segments at both basal and middle levels. Time-to-peak myocardial sustained systolic (Ts) velocities were calculated. Significant systolic IVD was defined as Ts-SD > 32.6 ms as known as "Yu index". RESULT: Of the total patients, 112 had fQRS (49.5%), while 114 had nQRS (50.5%) with male dominance (M/F = 71:29). Majority of patients were in NYHA class II (n = 122, 54%) followed by class III (n = 83; 37%), and class IV (n = 21; 9%). There were no significant differences among both groups for baseline parameters except higher QRS duration (102.42 ± 14.05 vs. 91.10 ± 13.75 ms; P = 0.001), higher Yu index (35.64 ± 12.79 vs. 20.45 ± 11.17; P = 0.01) and number of patients with positive Yu index (78.6% vs. 21.1%; P = 0.04) in group with fQRS compared with group with nQRS. fQRS complexes had 84.61% sensitivity and 80.32% specificity with positive predictive value of 78.6% and negative predictive value of 85.9% to detect IVD. On detailed segmental analysis for fQRS distribution, inferior segment had maximum (37%), followed by anterior (23%), lateral (19%), inferior and lateral (11%), anterior and inferior (8%), and anterior and lateral (2%). Among 104 patients with significant dyssynchrony, 88 patients (84.6%) had fQRS in the dyssynchronic segment. CONCLUSION: Fragmentation of QRS complex is an important predictor of electro-mechanical dyssynchrony. It is also helpful in localizing the dyssynchronous segment. In future, larger studies may be carried out to investigate the role of fQRS as a predictor of response to cardiac resynchronization therapy (CRT) in this subgroup of HF patients with narrow QRS.

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.676

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
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 head0.019
GPT teacher head0.345
Teacher spread0.326 · 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 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

Citations9
Published2016
Admission routes1
Has abstractyes

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