ArticleBioMed research international2021
Risk Factors for Gastric Cancer-Associated Thrombotic Diseases in a Han Chinese Population.
Article in BioMed research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Development and validation of a competing risk nomogram for predicting PICC-related venous thrombosis in patients with gastrointestinal malignancies.Frontiers in oncology · 2026Article
- Article
- Map of thrombogenesis in viral infections and viral-driven tumours.Discover oncology · 2023Review
- Menstrual and Reproductive Factors for Gastric Cancer in Postmenopausal Women: The 2007-2020 Korea National Health and Nutrition Examination Survey.International journal of environmental research and public health · 2022Article
- Partial thrombosis of the corpus cavernosum - a malignancy mimicker.BJR case reports · 2022Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present work was to investigate the risk factors for gastric cancer- (GC-) associated thrombotic diseases in a Han Chinese population. A total of 333 patients diagnosed with GC, 68 with thrombotic diseases included in the case group and the remaining 265 in the control group, were enrolled. The relevant data for the participants, including general information (gender, age, smoking, and drinking), comorbidities (diabetes, hypertension, and anemia), tumor-related data (tumor site, histology, degree of differentiation, and clinical stage), and treatment-related data (surgery, chemotherapy, hormones, transfusion, and peripherally inserted central venous catheter (PICC)), were collected. Statistically significant factors derived from univariate analyses were then subjected to multivariate logistic regression analyses. The results demonstrate a statistically significant difference in age, diabetes, hypertension, histology, surgery, chemotherapy, and PICC (
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