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Sex differences in cardiovascular complications after allogeneic hematopoietic stem cell transplantation

2025· article· en· W4412806026 on OpenAlexaff
Terezinha Valim Oliver Gonçalves, B. Sibilia, Lue Ping Zhao, Mathilde Baudet, Solenn Toupin, Madhu Singh, Aliénor Xhaard, Régis Peffault de Latour, Damien Logeart, Alain Cohen Solal, J G Dillinger, P. Henry, Théo Pezel, Marie Robin

Bibliographic record

VenueEuropean Heart Journal Supplements · 2025
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsMedicineStem cellTransplantationHematopoietic stem cell transplantationHaematopoiesisImmunologyHematopoietic cellInternal medicineGenetics

Abstract

fetched live from OpenAlex

Abstract Background Allogeneic hematopoietic stem cell transplantation (AHSCT) represents a major therapeutic challenge in the treatment of hematologic malignancies. However, the conditioning regimens, including chemotherapy and radiotherapy, are associated with both short- and long-term cardiotoxicity, increasing the risk of major adverse cardiovascular events (MACE). While sex-based differences in cardiovascular disease (CVD) have been extensively documented in the general population, their impact on AHSCT outcomes and the development of subsequent CVD remains poorly known. Purpose To study sex differences in AHSCT outcomes and identify predictors of MACE by sex in a large cohort of AHSCT patients. Methods Between 2011 and 2020, we conducted a retrospective, single-centre longitudinal cohort study including all consecutive patients with hematologic malignancies undergoing AHSCT. The primary composite outcome was MACE, including cardiovascular death, heart failure (HF), rhythm/conduction disorders, acute arterial events, venous thromboembolism (VTE), and myopericarditis. A propensity score matching was performed to balance characteristics between males and females. Predictors of MACE were analysed using Cox proportional hazards regression and Fine-and-Gray subdistribution hazard models. Results In the propensity-score matched population (N=786 patients, 50% males and 50% females, mean age 44±16 years), 30% patients experienced MACE after a median (IQR) follow-up of 4 (1-7) years. The cumulative incidence of early MACE (≤100 days) was similar between men and women (12.6% versus 13.8%, p=0.67), with the primary causes being HF and supraventricular arrhythmia in men, and HF and pericardial disease in women. At 4 years, the cumulative incidence of late MACE remained comparable between men and women (17.3% vs. 18.1%, p=0.91), with HF, VTE, and pericardial disease as the predominant causes. Among men, the following variables were identified as significant predictors of early MACE: history of hypertension (HR: 2.16; 95% CI: 1.07–4.33; p=0.031), smoking status (HR: 1.90; 95% CI: 1.08–3.35; p=0.026), history of supraventricular arrhythmia (HR: 3.43; 95% CI: 1.07–11.0; p=0.039), history of cancer-therapy related cardiac dysfunction (HR: 5.51; 95% CI: 2.18–13.9; p<0.001), previous use of liposomal anthracyclines (HR: 2.83; 95% CI: 1.02–7.89; p=0.046), age (HR: 1.02; 95% CI: 1.00–1.04; p=0.022), and haploidentical donor transplant (HR: 3.18; 95% CI: 1.40–7.22; p=0.006). In women, predictors of early MACE included history of hypertension (HR: 2.34; 95% CI: 1.23–4.45; p=0.009), history of HF (HR: 3.70; 95% CI: 1.34–10.3; p=0.012), and left ventricular ejection fraction (HR: 0.96; 95% CI: 0.92–1.00; p=0.039). Conclusion After propensity score matching, the risk of early and late MACE was similar between men and women following AHSCT. However, sex-specific differences in predictors may suggest the need for sex-specific risk stratification prior to AHSCT.

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)0.001
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 score0.054
Threshold uncertainty score0.498

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.280
Teacher spread0.250 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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