相关实验视频

Updated: Jun 12, 2025

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.1K

五个分数的比较,以预测恶性肺溢液死亡率

Merve Ayik Türk1, Gülru Polat2, Özer Özdemir2

  • 1Department of Pulmonology, İzmir Bozyaka Training and Research Hospital, Bahar, Saim Çıkrıkçı Street No:59, 35170, Izmir, Turkey.

Updates in surgery
|September 23, 2024
PubMed
概括

伦特得分是最有效的预测肺癌患者的死亡率恶性多叶流液 (MPE). 它在6个月和1年的生存预测中表现优于其他得分.

关键词:
恶性 恶性 恶性死亡率 死亡率 死亡率腹溢出 腹溢出 是一种风险评分 风险评分

更多相关视频

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery06:46

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

Published on: September 27, 2024

223
Implantation and Monitoring by PET/CT of an Orthotopic Model of Human Pleural Mesothelioma in Athymic Mice07:54

Implantation and Monitoring by PET/CT of an Orthotopic Model of Human Pleural Mesothelioma in Athymic Mice

Published on: December 21, 2019

6.8K

相关概念视频

Pleural Effusion II: Symptoms and Management01:28

Pleural Effusion II: Symptoms and Management

Pleural Effusion Overview
A pleural effusion is the abnormal collection of fluid between the parietal and visceral pleura layers of tissue that form the lining of the lungs and chest cavity. It can occur independently or due to surrounding parenchymal diseases, such as infection, malignancy, or inflammatory conditions.
Clinical Manifestations:
157
Pleural Effusion I: Introduction01:25

Pleural Effusion I: Introduction

Pleural effusion is an abnormal fluid accumulation in the pleural cavity, a narrow space between the lungs and the chest wall. It is not a disease per se but rather a symptom or indication of an underlying disease. In normal circumstances, this space contains a small amount of fluid (5 to 15 mL), a lubricant facilitating the non-frictional movement of the pleural surfaces.
There are two main types of pleural effusion: transudative and exudative. They are differentiated using Light's...
679
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
158
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
107
Cancer Survival Analysis01:21

Cancer Survival Analysis

Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
331