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Record W4402644355 · doi:10.4081/monaldi.2024.3084

How effective is disopyramide in treating pediatric hypertrophic cardiomyopathy? State of the art and future directions

2024· review· en· W4402644355 on OpenAlexaff
Karin Del Vecchio, Caterina Rizzardi, Alice Pozza, Francesco Prati, Longying Ye, Alessia Fattoretto, Elena Reffo, Giovanni Di Salvo

Bibliographic record

VenueMonaldi Archives for Chest Disease · 2024
Typereview
Languageen
FieldMedicine
TopicCardiomyopathy and Myosin Studies
Canadian institutionsChildren's & Women's Health Centre of British Columbia
Fundersnot available
KeywordsDisopyramideMedicineHypertrophic cardiomyopathyVentricular outflow tract obstructionCardiomyopathyInotropeCardiologyInternal medicinePopulationIntensive care medicinePediatricsHeart failure

Abstract

fetched live from OpenAlex

Pediatric hypertrophic cardiomyopathy (HCM) has a wide range of clinical manifestations. Left ventricular outflow tract obstruction (LVOTO) at rest is present in up to one-third of children with HCM, with a further 50-60% of symptomatic children developing a gradient under exertion. Treatment options are limited, and there is a relative lack of data on the pediatric population. Disopyramide is a sodium channel blocker with negative inotropic properties. This therapy effectively reduces LVOTO in adults with HCM and delays surgical interventions, but it is not licensed for use in children. We aimed to review and analyze the influence of disopyramide over the pathophysiological, clinical, electrocardiographic, and echocardiographic characteristics of patients with HCM in infancy, childhood, adolescence, and adult age. While disopyramide remains a cornerstone in the management of pediatric HCM, the advent of mavacamten and aficamten heralds a new era of potential advancements. These emerging therapies could significantly improve the quality of life and prognosis for young patients with HCM.

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)0.001
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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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 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

Citations0
Published2024
Admission routes1
Has abstractyes

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