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Record W4414516254 · doi:10.1016/j.jhlto.2025.100394

Heart transplantation in special patient populations

2025· article· en· W4414516254 on OpenAlexaff
Kathryn Armstrong, Anne I. Dipchand

Bibliographic record

VenueJHLT Open · 2025
Typearticle
Languageen
FieldMedicine
TopicTransplantation: Methods and Outcomes
Canadian institutionsHospital for Sick ChildrenBC Children's Hospital
Fundersnot available
KeywordsPsychosocialQuality of life (healthcare)Heart transplantationLung transplantationHeart diseaseTransplantationHeart failure

Abstract

fetched live from OpenAlex

In this review of heart transplantation (HTx) in special patient populations, the indications for HTx for patients with underlying genetic conditions, myopathies, mitochondrial conditions, connective tissue disorders (CTDs), and intellectual developmental delay will be explored along with the outcomes and survival. A key principle for cardiologists looking after these patients who may develop end-stage heart failure and require HTx evaluation is to determine what is in the child's best interest from a medical, physical, emotional, developmental, and psychosocial perspective with a goal of providing the child not only survival but an acceptable quality of life within their underlying circumstances. This review highlights that much like clinicians do for any pediatric patient put forward for HTx and as the International Society of Heart Lung Transplantation (ISHLT) endorses an evaluation of the patient's cardiopulmonary status, comorbidities and psychosocial factors that may affect graft/patient survival should be considered for patients with underlying genetic conditions, myopathies, CTDs, and intellectual delays prior to transplantation. More research is required to better understand the risk and long-term outcomes of HTx in those with underlying mitochondrial conditions where HTx has accelerated the progression of disease in other organ systems and in conditions such as Noonan's syndrome, where patients have a higher risk of developing post-transplant complications such as post-transplant lymphoproliferative disorder.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.100
Threshold uncertainty score0.230

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.066
GPT teacher head0.428
Teacher spread0.362 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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