Evidence map›Paper›PMID 38746151›Full record

ArticlemedRxiv : the preprint server for health sciences2024

Genome Sequencing is Critical for Forecasting Outcomes Following Congenital Cardiac Surgery.

W Scott Watkins, E Javier Hernandez, Thomas Miller, Nathan Blue, Raquel Zimmerman, Eric Griffiths, Erwin Frise, Daniel Bernstein, Marko Boskovski, Martina Brueckner and 16 more

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

26 authors.

W Scott Watkins
E Javier Hernandez
Thomas Miller
Nathan Blue
Raquel Zimmerman
Eric Griffiths
Erwin Frise
Daniel Bernstein
Marko Boskovski
Martina Brueckner
Wendy Chung
J William Gaynor
Bruce Gelb
Elizabeth Goldmuntz
Peter Gruber
Jane Newburger
Amy Roberts
John Mayer
Christine Seidman
Jonathan Seidman
Yufeng Shen
Michael Wagner
Mark Yandell
Martin Tristani-FirouziORCID 0000-0001-5916-442X

Funding

RESEARCH METHODS IN PEDIATRICS HEART DISEASET32HL007572 · NHLBI · CHILDREN'S HOSPITAL BOSTON · PI Sarah D DE FERRANTI, Jane W. Newburger · 1985 to 2026
$13.0M
Identifying unrecognized genetic causes of congenital heart diseaseR01HL162356 · NHLBI · BRIGHAM AND WOMEN'S HOSPITAL · PI William Tswenching Pu, CHRISTINE E SEIDMAN · 2024 to 2026
$2.3M
NHLBI NIH HHS R01 HL162356NHLBI NIH HHS T32 HL007572
6 · The paper itself

Abstract

While exome and whole genome sequencing have transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we used artificial intelligence (AI) technologies to explore the predictive value of genome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a cohort of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes were associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes was further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes was also informative, reducing the risk for adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.

Identifiers

PMID38746151
PMCPMC11092705

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.