関連する実験動画

Updated: Sep 9, 2025

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry
12:36

Single-cell Analysis of Immunophenotype and Cytokine Production in Peripheral Whole Blood via Mass Cytometry

Published on: June 26, 2018

9.6K

1999年から2020年までの米国における全身性白血病患者の死亡場所の格差に関するCDC WONDER研究

Aruna Anantharaj1, Dr Rohit Rao Yelagapuri2, Parth Vikram Singh3

  • 1Internal Medicine, Wuhan University School of Medicine, Hubei, CHN.

Cureus
|September 5, 2025
PubMed
まとめ

50歳以上の全身性狼症 (SLE) 患者,男性,アメリカン・インディアン/アラスカ先住民,および南米の患者は,自宅またはホスピスで死亡する確率が高くなります. 将来の傾向は,SLE患者の自宅/ホスピスでの死亡率の増加を予測しています.

キーワード:
自己免疫性ホスピスケア死亡率の傾向神経精神疾患による全身性赤血性狼 (npsle)全身性赤血性狼

さらに関連する動画

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease04:44

Imaging Features of Systemic Sclerosis-Associated Interstitial Lung Disease

Published on: June 16, 2020

20.2K
Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index06:55

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

14.6K

関連する概念動画

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...
279
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.4K
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...
445
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
525
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
666
Actuarial Approach01:20

Actuarial Approach

The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
131