ArticleScientific reports2017
Nomogram predicted risk of peripherally inserted central catheter related thrombosis.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 31 citations in OpenAlex.
- Pooled it
- Clinical factors of PICC-RVT in cancer patients: a meta-analysis.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2023Pooled it
- Machine learning survival model for personalised prevention of catheter-related thrombosis in tumour patients.Communications medicine · 2026Article
- A predictive model for PICC-related thrombosis in sepsis patients using XGBoost algorithm.Scientific reports · 2026Article
- Development and validation of a nomogram for predicting unplanned PICC removal in preterm infants with gestational age <32 weeks.Frontiers in pediatrics · 2026Article
- Development and validation of a risk prediction model for PICC-related venous thrombosis in patients with cancer: a prospective cohort study.Scientific reports · 2025Article
- Establishment and validation of a predictive nomogram for central venous catheter-related thrombosis in cancer patients: a retrospective nested case-control study.Frontiers in oncology · 2024Article
- Risk Factors and Predictive Models for Peripherally Inserted Central Catheter Unplanned Extubation in Patients With Cancer: Prospective, Machine Learning Study.Journal of medical Internet research · 2023Article
- Biomarkers Associated with Thrombosis in Patients with Peripherally Inserted Central Catheter: A Systematic Review and Meta-Analysis.Journal of clinical medicine · 2023Review
- Conditional catheter-related thrombosis free probability and risk-adapted choices of catheter for lung cancer.Thoracic cancer · 2022Article
- A model to assess the risk of peripherally inserted central venous catheter-related thrombosis in patients with breast cancer: a retrospective cohort study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2022Article
- Plasminogen activator inhibitor-1 gene promoter 4G/5G polymorphism and risks of peripherally inserted central catheter-related venous thrombosis in patients with lung cancer: a prospective cohort study.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2021Article
- Catheter-related bloodstream infection associated with multiple insertions of the peripherally inserted central catheter in patients with hematological disorders.Scientific reports · 2021Article
- Development and Validation of a New Clinical Prediction Model of Catheter-Related Thrombosis Based on Vascular Ultrasound Diagnosis in Cancer Patients.Frontiers in cardiovascular medicine · 2020Article
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of peripherally inserted central catheters (PICCs) is increasing rapidly worldwide. A number of patient-related, clinical-related and device-related characteristics might be risk factors for PICC-related thrombosis. We retrospectively reviewed a database of 320 consecutive patients who underwent PICC insertion between December 2014 and December 2015 at the First Affiliated Hospital of Xi'an Jiaotong University to explore the potential associations between risk factors and PICC-associated thrombosis. A novel nomogram for predicting risk was developed based on the data. The nomogram prediction model included ten risk factors that were derived from different relevant estimates. The nomogram prediction model showed good discriminatory power (Harrell's C-index, 0.709) and a high degree of similarity to actual thrombosis occurring after calibration. Furthermore, principal component analysis was performed to identify the factors that most influence PICC-related thrombosis. Our novel nomogram thrombosis risk prediction model was accurate in predicting PICC-related thrombosis. Karnofsky performance scores, D-dimer and blood platelet levels and previous chemotherapy were principal components. Our findings might help clinicians predict thrombosis risk in individual patients, select proper therapeutic strategies and optimize the timing of anticoagulation therapy.
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