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Cardiovascular events among recipients of hematopoietic stem cell transplantation

2021· article· en· W4386660684 on OpenAlexaff
Nazanin Aghel, Macy Mei‐Sze Lui, Hira Mian, Dina Khalaf, Christopher Hillis, J. Petropoulos, V Wang, Brian Leber, Jeffrey H. Lipton, I. Walker, Darryl P. Leong

Bibliographic record

VenueEuropean Heart Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicChemotherapy-induced cardiotoxicity and mitigation
Canadian institutionsPrincess Margaret Cancer CentreHamilton Health SciencesPopulation Health Research InstituteMcMaster University
Fundersnot available
KeywordsMedicineHematopoietic stem cell transplantationCumulative incidenceIncidence (geometry)TransplantationInternal medicinePopulationStroke (engine)Cause of deathCohortPediatricsIntensive care medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background Allogeneic and autologous hematopoietic stem cell transplantation (HSCT) are potential curative treatments for several hematological malignancies (1). Survival after HSCT has improved over the last decade, but survivors remain at risk for health issues after transplantation. Cardiovascular complications after HSCT are increasingly recognized (2). Cardiovascular diseases may be an important cause of mortality and morbidity in patients after HSCT owing to the toxicities of the cancer therapies; however, the incidence of cardiovascular events (CVEs) in this population has not been completely characterized. The objective of this systematic review is to summarize the evidence on the incidence of CVEs in HSCT recipients. Methods Medline and Embase were searched from inception to December 2020 without language restriction. Two authors independently screened the titles and abstracts. Inclusion criteria were: cohort studies and phase 3 randomized controlled trials that reported CVEs (i.e., heart failure, arrythmias, acute coronary syndrome, and stroke) or cardiovascular death among adults who underwent HSCT for a hematological malignancy. All-cause mortality, relapse-related mortality, and non-relapse-related mortality (NRM) were also collected. Studies in which the follow up period was not started immediately after HSCT were excluded due to the risk of immortal bias. Results Of 8151 nonduplicate articles, 30 studies including 14019 individuals post autologous HSCT, and 22 studies including 31049 individuals post allogeneic HSCT met the inclusion criteria. The cumulative incidence of CVEs in the first 100 days post autologous HSCT was 9% and arrhythmia (i.e., atrial fibrillation) was the most common CVE. In recipients of allogeneic HSCT, the 100-day cumulative incidence of CVEs was 3%, and heart failure (HF) was the most common reported CVE. In recipients of autologous and allogeneic HSCT, cardiovascular death was responsible for 43% and 10% of NRM within 100 days, respectively (Table 1). The incidence of CVEs was 4.96 per 1000-person years (95% CI; 4.21–5.80) in long-term survivors (beyond 100-days) of autologous HSCT, and HF was the most common CVE in this population. In long-term survivors of allogeneic HSCT, the incidence of CVEs was 1.90 per 1000-person years (95% CI: 1.59–2.24). Cardiovascular death was the most frequently reported CVE in long-term survivors of allogeneic HSCT (Table 2). Conclusion CVEs remain a major cause of non relapse morbidity and mortality in recipients of HSCT, especially recipients of autologous HSCT within the first 100 days. Future studies are needed to identify the risk factors for CVEs that are specific to HSCT recipients. Funding Acknowledgement Type of funding sources: None.

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)0.003
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0040.003
Bibliometrics0.0060.007
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.027
GPT teacher head0.255
Teacher spread0.228 · 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 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
Published2021
Admission routes1
Has abstractyes

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