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

Causality in Epidemiology01:21

Causality in Epidemiology

451
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
451
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

176
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
176
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

326
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:  
326
Convergent Evolution01:54

Convergent Evolution

27.8K
Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.
27.8K
Relative Risk01:12

Relative Risk

195
Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
195
Cancer Survival Analysis01:21

Cancer Survival Analysis

365
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...
365

You might also read

Related Articles

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

Sort by
Same author

Health-Related Quality of Life Changes in Patients with Digestive Cancers and Chronic Digestive Diseases: A Prospective, Multicenter Study.

Journal of clinical medicine·2026
Same author

Machine learning using PROFUND components for 30-day readmission prediction in multimorbid patients: a prospective multicentre study.

Scientific reports·2026
Same author

Impact of Visitor Restrictions Due to the COVID-19 Pandemic on the Occurrence of In-Hospital Delirium.

Journal of patient safety·2026
Same author

Rethinking readmission prediction in multiple chronic conditions: Clinical utility over accuracy.

European journal of internal medicine·2026
Same author

Hospitalization and referral for mental illness among people under 30 in Euskadi: a retrospective population-based cohort.

Gaceta sanitaria·2026
Same author

Frailty in COPD hospitalized patients: Associated factors from a multicentre cohort study.

Respiratory medicine and research·2026
Same journal

Interobserver agreement of the Out-of-Hospital Advanced Triage Model (META, 2020) using vignette cases among medical students.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
Same journal

Automated detection of sepsis in emergency departments and its clinical impact: a pre-post study.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
Same journal

Diagnostic performance of structured telephone triage for detecting priority 1 in suspected prehospital stroke: a population-based analysis in Andalusia (Spain).

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
Same journal

Pulmonary congestion assessed by ultrasound at discharge from the ED predicts early revisit or readmission after an acute heart failure episode more accurately than the MEESSI score.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
Same journal

Impact of health care reorganization on emergency process times.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
Same journal

Effect of beta-blockers on the diagnosis of pulmonary embolism in the emergency department.

Emergencias : revista de la Sociedad Espanola de Medicina de Emergencias·2026
See all related articles

Related Experiment Video

Updated: Jul 14, 2025

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
08:48

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19

Published on: February 16, 2022

2.9K

Nonadverse COVID-19 evolution predictors: the CoNAE scale.

Esther Pulido-Herrero1, Nere Larrea2, Susana García-Gutiérrez3

  • 1Servicio Vasco de Salud de Osakidetza, Unidad de Urgencias, Hospital Universitario Galdakao-Usansolo, Barakaldo, España. Grupo de Urgencias, Instituto de Investigación Sanitaria Biocruces Bizkaia, Barakaldo, España. Departamento de Medicina, Facultad de Ciencias de la Salud, Universidad de Deusto, España. Red de Investigación de Servicios Sanitarios en Enfermedades Crónicas (REDISSEC), Bizkaia, España. Red de Investigación en Cronicidad, Atención Primaria y Promoción de la Salud (RICAPPS).

Emergencias : Revista De La Sociedad Espanola De Medicina De Emergencias
|October 6, 2023
PubMed
Summary
This summary is machine-generated.

A new scale, the CoNAE scale, can predict non-adverse outcomes in COVID-19 patients. This tool aids emergency departments in identifying patients who may not require hospitalization, optimizing care.

Keywords:
Clinical decision-making.Cuidados sanitarios.Emergency department.Evaluación de resultados.Health services.Outcomes.Reglas de decisión clínica.SARS-CoV-2. COVID-19.Servicio de urgencias.

More Related Videos

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K
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

10.2K

Related Experiment Videos

Last Updated: Jul 14, 2025

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19
08:48

Dynamic Monitoring of Seroconversion using a Multianalyte Immunobead Assay for Covid-19

Published on: February 16, 2022

2.9K
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
07:31

Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

Published on: May 15, 2020

7.1K
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

10.2K

Area of Science:

  • Infectious Diseases
  • Public Health
  • Clinical Medicine

Background:

  • Lack of tools to identify mild to moderate COVID-19 cases in emergency settings.
  • Need for predictive models to guide patient management and resource allocation.

Purpose of the Study:

  • Identify factors associated with nonadverse outcomes in COVID-19 patients.
  • Develop a predictive scale (CoNAE scale) for nonadverse evolution in emergency departments.

Main Methods:

  • Retrospective cohort study of SARS-CoV-2 infected patients (July 2020 - July 2021).
  • Collected sociodemographic data, comorbidities, treatments, and vital signs.
  • Utilized multilevel multivariable logistic regression to identify predictors.

Main Results:

  • Nonadverse outcomes associated with younger age, female sex, and COVID-19 vaccination (2 doses).
  • Normal vital signs and absence of specific comorbidities (heart failure, hypertension, diabetes, etc.) were predictive.
  • Absence of corticosteroid or immunosuppressant therapy was also a key factor.
  • Model demonstrated strong predictive performance with an AUC of 0.840.

Conclusions:

  • The CoNAE scale effectively predicts nonadverse outcomes in COVID-19 patients.
  • The scale can aid in triage decisions within emergency departments.
  • Potential utility in primary care and out-of-hospital settings for patient assessment and care planning.