Thrombo-vera：一种使用现代变量选择方法的新型真性红细胞增多症血栓风险模型

数据集获取（Figshare）

• 源站标题：Thrombo-vera: a new thrombosis risk model for polycythemia vera using modern variable selection methods
• DOI：10.6084/m9.figshare.29328694.v1
• 发布日期：2025-06-16
• 文件数：5 个
• 文件总体积：77.76 KB
• 源站页面：https://tandf.figshare.com/articles/dataset/Thrombo-vera_a_new_thrombosis_risk_model_for_polycythemia_vera_using_modern_variable_selection_methods/29328694

命令行下载

curl -L -o "ierr_a_2521401_sm1987.docx" "https://ndownloader.figshare.com/files/55412221"
curl -L -o "ierr_a_2521401_sm1986.docx" "https://ndownloader.figshare.com/files/55412224"
curl -L -o "ierr_a_2521401_sm1985.docx" "https://ndownloader.figshare.com/files/55412227"
curl -L -o "ierr_a_2521401_sm1984.docx" "https://ndownloader.figshare.com/files/55412230"
curl -L -o "ierr_a_2521401_sm1983.docx" "https://ndownloader.figshare.com/files/55412233"

文件清单

• ierr_a_2521401_sm1987.docx（14.35 KB）
• ierr_a_2521401_sm1986.docx（14.21 KB）
• ierr_a_2521401_sm1985.docx（15.74 KB）
• ierr_a_2521401_sm1984.docx（15.74 KB）
• ierr_a_2521401_sm1983.docx（17.71 KB）

文件总体积 77.76 KB（源站 API 实测）。

数据加载示例（图像类）

from PIL import Image
import glob, os

files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
       + glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)

# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path)  # 要求 子目录=类别

目录组织与标注格式以源站说明和下载后实际文件为准。

数据说明

Thrombosis is a major complication in polycythemia vera (PV), contributing to significant morbidity and mortality. This retrospective study aimed to develop a predictive model for thrombosis risk in PV patients using advanced statistical techniques.
The study included 817 consecutive PV patients, with a median follow-up of 59 months. A Bayesian logistic regression model with sparsity-inducing R2D2 priors was used to predict thrombosis.
Thrombotic events occurred in 13.2% of patients. The thrombosis group had significantly higher median neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), splenomegaly, cardiovascular risk factors, microvascular symptoms, pruritus, previous thrombosis, and Charlson Comorbidity Index (CCI) compared to the no-thrombosis group. Both groups were comparable in age. Multivariate regression analysis identified CCI, PLR, splenomegaly, and microvascular symptoms as key predictors of thrombosis. A clinical score, ThromboVera CS, was developed based on these predictors, classifying patients into low, moderate, or high-risk groups. In the low-risk group, 6.94% experienced thrombosis, compared to 15.76% in moderate-risk group and 48.78% in the high-risk group.
The ThromboVera CS score is a reliable, easy-to-use tool for predicting thrombosis in PV patients. It can help clinicians identify those at high risk, enabling early intervention that could significantly improve patient outcomes by targeting nearly 50% of high-risk patients.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.29328694.v1（source: https://tandf.figshare.com/articles/dataset/Thrombo-vera_a_new_thrombosis_risk_model_for_polycythemia_vera_using_modern_variable_selection_methods/29328694）。