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Related Concept Videos

Endocarditis IV: Nursing Management01:29

Endocarditis IV: Nursing Management

Infective endocarditis (IE) is a chronic infection of the heart's endocardium, primarily affecting the heart valves. A detailed nursing assessment for a patient with IE involves collecting subjective and objective data to ensure an accurate diagnosis and timely intervention.Subjective DataThe nurse gathers information about the patient's symptoms and complaints during the subjective assessment. Patients with infective endocarditis often report non-specific symptoms that can mimic other...
Radiological Investigation III: Pulmonary Angiogram and PET Scan01:13

Radiological Investigation III: Pulmonary Angiogram and PET Scan

Radiological investigations are paramount in the diagnosis and management of various pulmonary diseases. Two essential investigations are the Pulmonary Angiogram and the Positron Emission Tomography (PET) Scan.
Pulmonary Angiogram
A Pulmonary Angiogram is an invasive procedure involving injecting a contrast medium through a catheter threaded into the pulmonary artery or the right side of the heart to visualize the pulmonary vasculature. Computed Tomography (CT) scans have mainly replaced this...

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Related Experiment Video

Updated: Jun 18, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Risk Factors and Development of a Risk Prediction Model for PICC-Related Thrombosis in Radiotherapy Inpatients: A

Qin-Mei Lin1, Qin-Lin Guo2, Zhuang-Bin Lin3

  • 1Department of Outpatient Nursing, Fujian Medical University Union Hospital, Fuzhou, Fujian, 350001, People's Republic of China.

Risk Management and Healthcare Policy
|June 17, 2026
PubMed
Summary
This summary is machine-generated.

This study identified cumulative radiation dose and prior thrombosis history as key risks for peripherally inserted central catheter-related venous thrombosis (PICC-RVT) in radiotherapy patients. The developed model shows promise for preliminary screening but requires further validation due to low specificity.

Keywords:
PICC-related thrombosisinfluencing factorsprediction modelsradiotherapy

Related Experiment Videos

Last Updated: Jun 18, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Area of Science:

  • Oncology
  • Vascular Medicine
  • Radiotherapy

Background:

  • Peripherally inserted central catheters (PICCs) are crucial for radiotherapy but increase venous thrombosis risk.
  • Identifying risk factors for PICC-related venous thrombosis (PICC-RVT) is essential for patient safety during cancer treatment.

Purpose of the Study:

  • To identify independent risk factors for PICC-RVT in patients undergoing radiotherapy.
  • To develop and validate a predictive model for early identification of patients at high risk for PICC-RVT.

Main Methods:

  • A retrospective cohort study of 335 patients with malignant tumors receiving PICC placement.
  • Univariate and multivariate logistic regression analyses to identify independent risk factors.
  • Development and validation of a risk prediction model using ROC curve analysis.

Main Results:

  • The incidence of PICC-RVT was 20.89%, with most cases being asymptomatic.
  • Independent risk factors identified were total cumulative radiation dose and a history of thrombosis.
  • The predictive model demonstrated moderate sensitivity but low specificity.

Conclusions:

  • Cumulative radiation dose and prior thrombosis history are significant predictors of PICC-RVT in radiotherapy patients.
  • The current model is suitable for preliminary screening but requires optimization for clinical utility.
  • Larger, multicenter studies are recommended to enhance the model's predictive performance.