ArticleESC heart failure2021
Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type.
Article in ESC heart failure, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Rechallenge of immunotherapy after rituximab-induced Takotsubo syndrome: a case report and review of the literature.European heart journal. Case reports · 2026Article
- Investigating the effect of cancer medication in the development of Takotsubo cardiomyopathy.American journal of cardiovascular disease · 2024Review
- Machine Learning in Cardio-Oncology: New Insights from an Emerging Discipline.Reviews in cardiovascular medicine · 2023Review
- "Obesity paradox" and takotsubo syndrome.International journal of cardiology. Cardiovascular risk and prevention · 2022Review
- Artificial intelligence-augmented analysis of contemporary procedural, mortality, and cost trends in carcinoid heart disease in a large national cohort with a focus on the "forgotten pulmonic valve".Frontiers in cardiovascular medicine · 2022Article
- Stress cardiomyopathy in hospitalized patients with cancer: machine learning analysis by primary malignancy type.ESC heart failure · 2021Article
- Cancer and Takotsubo syndrome: from rarity to clinical practice.ESC heart failure · 2021Article
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Authors and funding
15 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimsPrevious studies have shown that patients with stress (Takotsubo) cardiomyopathy (SC) and cancer have higher in-hospital mortality than patients with SC alone. No studies have examined outcomes in patients with active cancer and SC compared to patients with active cancer without SC. We aimed to assess the potential association between primary malignancy type and SC and their shared interaction with inpatient mortality. METHODS AND
resultsWe analysed SC by primary malignancy type with propensity score adjusted multivariable regression and machine learning analysis using the 2016 United States National Inpatient Sample. Of 30 195 722 adult hospitalized patients, 4 719 591 had active cancer, of whom 568 239 had SC. The mean age of patients with cancer and SC was 69.1, of which 74.7% were women. Among patients with cancer, those with SC were more likely to be female and have white race, Medicare insurance, hypertension, heart failure with reduced ejection fraction, obesity, cerebrovascular disease, anaemia, and chronic obstructive pulmonary disease (P < 0.003 for all). In machine learning-augmented, propensity score multivariable regression adjusted for age, race, and income, only lung cancer [OR 1.25; 95% CI: 1.08-1.46; P = 0.003] and breast cancer [OR 1.81; 95% CI: 1.62-2.02; P < 0.001] were associated with a significantly increased likelihood of SC. Neither SC alone nor having both SC and cancer was significantly associated with in-hospital mortality. The presence of concomitant SC and breast cancer was significantly associated with reduced mortality (OR 0.48; 95% CI: 0.25-0.94; P = 0.032).
conclusionsThis analysis demonstrates that primary malignancy type influences the likelihood of developing SC. Further studies will be necessary to delineate characteristics in patients with lung cancer and breast cancer which contribute to development of SC. Additional investigation should confirm lower mortality in patients with SC and breast cancer and determine possible explanations and protective factors.
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