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

Regression Toward the Mean01:52

Regression Toward the Mean

7.0K
Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when...
7.0K
Appendicitis-I: Introduction01:22

Appendicitis-I: Introduction

2.5K
The appendix, a small, narrow, blind tube extending from the inferior part of the cecum, is widely regarded as a vestigial organ, having lost much of its original function through evolution. Despite its diminished role, the appendix can become inflamed, a condition known as appendicitis.
Etiology: Appendicitis can arise from various causes, primarily rooted in the obstruction of the appendix lumen. Factors contributing to this obstruction include fecal accumulation, lymphoid hyperplasia and, in...
2.5K
Multiple Regression01:25

Multiple Regression

4.0K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
4.0K
Appendicitis-II: Diagnostic Studies and Management01:29

Appendicitis-II: Diagnostic Studies and Management

577
Diagnosing and managing appendicitis requires a structured and comprehensive approach that spans from initial assessment to postoperative care. Here is an overview of the process:
Diagnosing Appendicitis
It requires a multifaceted approach, starting with a detailed physical examination to pinpoint the location and nature of the pain and identify any associated symptoms. Laboratory tests play a crucial role. A complete Blood Count (CBC) typically reveals leukocytosis (an increased number of...
577
Correlation and Regression00:53

Correlation and Regression

3.4K
In statistics, correlation describes the degree of association between two variables. In the subfield of linear regression, correlation is mathematically expressed by the correlation coefficient, which describes the strength and direction of the relationship between two variables. The coefficient is symbolically represented by 'r' and ranges from -1 to +1. A positive value indicates a positive correlation where the two variables move in the same direction. A negative value suggests a...
3.4K
Regression Analysis01:11

Regression Analysis

8.4K
Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
8.4K

You might also read

Related Articles

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

Sort by
Same author

[Comprehensive analysis of unplanned reoperations in colorectal cancer surgery].

Zhonghua zhong liu za zhi [Chinese journal of oncology]·2018
Same author

Management of acute Achilles tendon ruptures: A review.

Bone & joint research·2018
Same author

Investigation of combined kV/MV CBCT imaging with a high-DQE MV detector.

Medical physics·2018
Same author

Association of serum galectin-3 with risks of death and vascular events in acute ischaemic stroke patients: the role of hyperglycemia.

European journal of neurology·2018
Same author

Hemorrhagic transformation after stroke: inter- and intrarater agreement.

European journal of neurology·2018
Same author

Ultrastructural changes of Trichophyton rubrum in tinea unguium after itraconazole therapy in vivo observed using scanning electron microscopy.

Clinical and experimental dermatology·2018

Related Experiment Video

Updated: Feb 4, 2026

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

10.9K

Logistic regression model to predict acute uncomplicated and complicated appendicitis.

Mmr Eddama1,2, K C Fragkos2, S Renshaw2

  • 1Division of Surgery and Interventional Science, University College London , London , UK.

Annals of the Royal College of Surgeons of England
|October 6, 2018
PubMed
Summary

This study developed a logistic regression equation to predict the likelihood of acute uncomplicated appendicitis versus complicated appendicitis. The equation, available online, helps clinicians determine the need for urgent surgery in suspected appendicitis cases.

Keywords:
Acute abdomenAcute appendicitisComplicated appendicitisEmergency surgeryRight iliac fossa pain

More Related Videos

Utilizing Percutaneous Ventricular Assist Devices in Acute Myocardial Infarction Complicated by Cardiogenic Shock
06:10

Utilizing Percutaneous Ventricular Assist Devices in Acute Myocardial Infarction Complicated by Cardiogenic Shock

Published on: June 12, 2021

3.7K
Development of an Uncomplicated Mild Traumatic Brain Injury Model Modified by Weight-Drop Method and Evidenced by Magnetic Resonance Imaging
08:27

Development of an Uncomplicated Mild Traumatic Brain Injury Model Modified by Weight-Drop Method and Evidenced by Magnetic Resonance Imaging

Published on: April 11, 2025

992

Related Experiment Videos

Last Updated: Feb 4, 2026

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

10.9K
Utilizing Percutaneous Ventricular Assist Devices in Acute Myocardial Infarction Complicated by Cardiogenic Shock
06:10

Utilizing Percutaneous Ventricular Assist Devices in Acute Myocardial Infarction Complicated by Cardiogenic Shock

Published on: June 12, 2021

3.7K
Development of an Uncomplicated Mild Traumatic Brain Injury Model Modified by Weight-Drop Method and Evidenced by Magnetic Resonance Imaging
08:27

Development of an Uncomplicated Mild Traumatic Brain Injury Model Modified by Weight-Drop Method and Evidenced by Magnetic Resonance Imaging

Published on: April 11, 2025

992

Area of Science:

  • Medical Diagnostics
  • Surgical Decision Support
  • Predictive Analytics in Medicine

Background:

  • Acute appendicitis diagnosis can be challenging, with uncomplicated cases managed conservatively and complicated cases requiring surgery.
  • Differentiating between uncomplicated and complicated appendicitis is crucial for appropriate patient management.
  • Emergency department presentations with suspected appendicitis necessitate accurate diagnostic tools.

Purpose of the Study:

  • To develop and validate a logistic regression equation for predicting the likelihood of acute uncomplicated appendicitis and complicated appendicitis.
  • To provide clinicians with a tool to estimate the probability of appendicitis severity.
  • To aid in determining the necessity of urgent surgical intervention for complicated appendicitis.

Main Methods:

  • Retrospective analysis of 895 patients who underwent appendicectomy.
  • Classification of patients into three groups: normal appendix, acute uncomplicated appendicitis, and complicated appendicitis based on histology.
  • Application of univariate and multivariate logistic regression models to identify predictive variables.

Main Results:

  • Key predictors for complicated appendicitis included age, female gender, elevated white cell count, C-reactive protein, and bilirubin levels.
  • Odds ratios indicated significant associations between these variables and appendicitis severity.
  • The study identified significant independent variables for predicting both acute uncomplicated and complicated appendicitis.

Conclusions:

  • A logistic regression equation has been established to calculate the likelihood of acute uncomplicated and complicated appendicitis.
  • The predictive equations are accessible via a web application (www.appendistat.com) for clinical use.
  • This tool assists clinicians in assessing appendicitis probability and guiding surgical decisions.