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Enregistrement W4200196470 · doi:10.1182/blood-2021-152223

Cardiac Arrhythmias and Mortality after Hematopoietic Stem Cell Transplant (HSCT): A Systematic Review and Meta-Analysis

2021· review· en· W4200196470 sur OpenAlexaboutno aff
Saad Ullah Malik, Zachary Braunstein, Sumithira Vasu, Sam Penza, Ayman Saad, Nathan Denlinger, Marcos J.G. De Lima, Ajay Vallakati, Ragavendra R. Baliga, Samantha Jaglowski, Jonathan E. Brammer, Daniel Addison

Notice bibliographique

RevueBlood · 2021
Typereview
Langueen
DomaineMedicine
ThématiqueChemotherapy-induced cardiotoxicity and mitigation
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésMedicineInternal medicineIncidence (geometry)Atrial fibrillationMeta-analysisHematopoietic stem cell transplantationTransplantation

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction Hematopoietic stem cell transplant (HSCT) is commonly performed for the treatment of advanced hematological malignancies. Emerging data suggest non-relapse related events, including cardiac arrhythmias, increasingly limit anticancer outcomes and non-relapse mortality after initially successful HSCT. Yet, the relationship between HSCT and increased risk of arrhythmias after transplant remains controversial and unclear. Our aim was to evaluate the incidence and effect on mortality risk of arrhythmia development after HSCT. Materials and methods Leveraging the PubMed, Embase, Cochrane, Scopus and Clinicaltrials.gov databases, we identified all published studies evaluating the incidence and impacts of early arrhythmias after HSCT from January 1995 to July 2021 using PRISMA guidelines. We included all available observational studies (case-control, and cohort) and clinical trials without restriction of language or country of publication. The primary outcome was incidence of atrial fibrillation (AF) at 1 year of follow-up after HSCT. Secondary outcomes included the incidence of any arrhythmia across follow-up, the incidence of left atrium (LA) dilation, and non-relapse mortality associated with HSCT induced AF. Subgroup analysis based on type of HSCT treatment employed, allogenic (Allo-HSCT) or autologous (Auto-HSCT), was also performed. Variance weighted random effects modeling (DerSimonian and Laird) was used to define the associations between HSCT and AF and mortality events. Outcomes were reported as event rates, and relative risks (RR). Medians were reported with corresponding standard errors (SE). Heterogeneity was assessed using Cochrane Q-statistic which was quantified with I 2test (>75% was considered high heterogeneity). Publication bias was assessed using Eager's test where applicable. Further, the quality of included studies was assessed using the New-Castle Ottawa scale. Results Overall, from 769 articles, 12 cohort studies inclusive of 6,371 patients meeting study-criteria were identified. The mean incidence of AF was 8.8% (I 2:97%, P<0.001), including 5.2% (I 2:65%, P=0.05) within 1-year of any HSCT. The overall incidence of any type of arrhythmia was 11.2% (I 2 =95%, P≤0.001); Figure. Median time to AF onset was 10.3 days (SE= 1.2), but was longer in those treated with Allo-HSCT, at 71 days (SE=68.4); P<0.05. Among those treated with Allo-HSCT, 8.2% (I 2:73%, P<0.001) developed AF, including 6.5% (I 2:72%, P<0.01) at 1 year; the event rate for any type of arrhythmia was 8.3% (I 2:52%, P<0.001). In those treated with Auto-HSCT, the rate of AF was 8.7% (I 2=97%, P≤0.001) across follow-up. Among those with AF following HSCT therapy, LA dilatation was observed in 37.2% (I 2 =61.5%, P=0.1) among available studies. Similarly, mortality was higher among patients who developed AF vs. those without AF after HSCT (RR: 7.4, P=0.008, I 2 = 92.87). There was low risk of publication bias as assessed by visual inspection of funnel plot and Egger's regression test (P= 0.21); and low risk of bias within the included studies. Conclusion Atrial fibrillation is increasingly common after HSCT therapy, and associates with increased mortality. The presence of LA remodeling, reflected by atrial dilation, appears to portend AF risk. Further research into the mechanisms and predictors of AF after HSCT are needed. Figure 1 Figure 1. Disclosures Vasu: Kiadis, Inc.: Research Funding; Boehringer Ingelheim: Other: Travel support; Seattle Genetics: Other: travel support; Omeros, Inc.: Membership on an entity's Board of Directors or advisory committees. Saad: Incyte Pharmaceuticals: Consultancy; careDx: Consultancy; Amgen: Research Funding; Kadmon: Research Funding; OrcaBio: Research Funding; Magenta Therapeutics: Consultancy. de Lima: Miltenyi Biotec: Research Funding; BMS: Membership on an entity's Board of Directors or advisory committees; Pfizer: Membership on an entity's Board of Directors or advisory committees; Incyte: Membership on an entity's Board of Directors or advisory committees. Jaglowski: Juno: Consultancy; Novartis: Consultancy, Research Funding; Kite, a Gilead Company: Consultancy, Research Funding; Takeda: Consultancy; CRISPR Therapeutics: Consultancy.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,010
score de la tête « metaresearch » (Gemma)0,025
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Méta-analyse · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,014
Score d'incertitude au seuil0,050

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,025
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0140,031
Bibliométrie0,0060,008
Études des sciences et des technologies0,0010,001
Communication savante0,0030,001
Science ouverte0,0020,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0030,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,048
Tête enseignante GPT0,304
Écart entre enseignants0,256 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeMéta-analyse
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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