Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
Survival Curves01:18

Survival Curves

Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Life Histories01:29

Life Histories

Overview
Survival Tree01:19

Survival Tree

Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
 Building a Survival Tree
Constructing a survival tree begins...
Competition02:34

Competition

When organisms require the same limited resources within an environment, they may have to compete for them. Competition is a net-negative interaction. Even if two competing individuals or populations do not interact directly, the overall fitness of both competitors is lowered as a result of not having full access to the limited resource.
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time until a...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Finerenone as a Third-Line Therapy for Persistent Proteinuria in Diabetic Kidney Transplant Recipients.

International journal of molecular sciences·2026
Same author

Inflammatory biomarkers in the assessment of kidney function decline in Long Covid syndrome.

Kidney & blood pressure research·2026
Same author

[Rufus of Ephesus, On gout].

Giornale italiano di nefrologia : organo ufficiale della Societa italiana di nefrologia·2026
Same author

Triglyceride-glucose index and its derived anthropometric indices: a comparative analysis for mortality prediction in the population cohort of the URRAH study.

Nutrition, metabolism, and cardiovascular diseases : NMCD·2026
Same author

Potential role of Aliskiren in cancer modulation compared to other Renin-Angiotensin inhibitors: an in-depth review.

European journal of pharmacology·2025
Same author

Gout in the "Anonymus Parisinus".

Journal of nephrology·2025

Related Experiment Video

Updated: May 26, 2026

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy
07:02

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

Published on: January 19, 2019

Survival is not enough.

Natale Gaspare De Santo1, Alessandra Perna, Aziz El Matri

  • 1Nephrology, Second University of Naples, Naples, Italy. nataleg.desanto@unina2.it

Journal of Renal Nutrition : the Official Journal of the Council on Renal Nutrition of the National Kidney Foundation
|December 28, 2011
PubMed
Summary
This summary is machine-generated.

The "Survival is not enough" event addresses renal patient needs and quality of life. It focuses on balancing healthcare costs, promoting prevention, and advancing clinical research for better patient outcomes.

More Related Videos

Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions
05:18

Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions

Published on: July 22, 2016

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

Related Experiment Videos

Last Updated: May 26, 2026

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy
07:02

Monitoring Neuronal Survival via Longitudinal Fluorescence Microscopy

Published on: January 19, 2019

Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions
05:18

Measurement of Survival Time in Brachionus Rotifers: Synchronization of Maternal Conditions

Published on: July 22, 2016

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

Area of Science:

  • Healthcare Management
  • Nephrology
  • Public Health

Background:

  • The annual 'Survival is not enough' event, established in 2007, convenes experts to address the challenges faced by renal patients.
  • This international gathering focuses on enhancing the quality of life for patients dependent on life-sustaining medical technology.
  • Discussions center on maintaining high-quality care and service quantity while managing healthcare resources effectively.

Purpose of the Study:

  • To explore strategies for balancing healthcare finances without compromising patient care quality or service availability.
  • To identify and promote effective resource management and waste reduction in healthcare systems.
  • To advocate for the advancement of clinical and translational research in renal patient care.

Main Methods:

  • Multidisciplinary dialogue involving renal patients, associations, philosophers, economists, nephrologists, and healthcare managers.
  • Analysis of current healthcare system changes and the influence of the medical-industrial complex.
  • Focus on innovative management approaches for sustainable healthcare provision.

Main Results:

  • Emergence of a need for specialized managers skilled in financial balancing and waste reduction.
  • Emphasis on prevention as a key long-term cost-containment strategy.
  • Recognition of the critical role of clinical and translational research in improving patient outcomes.

Conclusions:

  • Healthcare systems must adapt to evolving challenges, including the expanding medical-industrial complex.
  • A balanced approach integrating financial prudence, preventative care, and robust research is essential for renal patient well-being.
  • Continuous dialogue and innovation are crucial for ensuring the sustainability and quality of renal patient care.