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Record W2765235190 · doi:10.1111/anec.12514

Clinical applications of <scp>QT</scp>/<scp>RR</scp> hysteresis assessment: A systematic review

2017· review· en· W2765235190 on OpenAlexafffund
Hugo Gravel, Vincent Jacquemet, Nagib Dahdah, Daniel Curnier

Bibliographic record

VenueAnnals of Noninvasive Electrocardiology · 2017
Typereview
Languageen
FieldMedicine
TopicCardiac electrophysiology and arrhythmias
Canadian institutionsCentre Hospitalier Universitaire Sainte-JustineUniversité de Montréal
FundersFonds de Recherche du Québec - Santé
KeywordsMedicineInternal medicineBioinformatics

Abstract

fetched live from OpenAlex

BACKGROUND: QT/RR hysteresis (QT-hys) is an index of the time accommodation of ventricular repolarization to heart rate changes. This report comprehensively reviews studies addressing QT-hys as a biomarker of medical conditions. METHODS: This is a secondary analysis of data from a recent systematic review pertaining to methods of assessment of QT-hys. Articles included in the former review were filtered in order to select original articles investigating the association of QT-hys with medical conditions in humans. RESULTS: Nineteen articles fulfilled our inclusion criteria. Given the heterogeneity of the methods and investigated conditions, no pooled analysis of data could be implemented. QT-hys was mostly studied as a risk marker of severe arrhythmias, as a predictor of the long QT syndrome (LQTS) phenotypes and genotypes and as a marker of exercise-induced ischemia. An increased QT-hys appears to be implicated in arrhythmogenesis, although the evidence in this regard relies on few human studies. An augmented QT-hys was reported in the LQTS, predominantly in the LQT2 genotype, but conflicting results were obtained between studies using different methods of assessment. In addition, QT-hys appears to be a useful marker of stress-induced myocardial ischemia in patients suspected of coronary artery disease. CONCLUSIONS: QT-hys evaluation has potential clinical utility in at least some clinical conditions. Further studies of the clinical validity of QT-hys assessment are warranted, particularly condition specific studies based on QT-hys evaluation methods that provide separate estimates of QT-hys and QT/RR dependency.

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)0.003
metaresearch head score (Gemma)0.010
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Meta-epidemiology (broad), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0190.007
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0020.002
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 head0.110
GPT teacher head0.445
Teacher spread0.335 · 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.

Study designSystematic review
Domainnot available
GenreReview

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

Citations31
Published2017
Admission routes2
Has abstractyes

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