A Clinical Risk Scoring Tool to Predict Readmission After Cardiac Surgery: A Methodological Issue

I read with interest the article by Verdial and colleagues 1 published in The Annals of Thoracic Surgery. The authors' aim was to develop a prediction model for nodal disease as a potential alternative approach to staging. For this purpose, they constructed a logistic regression model to estimate the probability of nodal disease in a very good manner, and they selected variables and parameterizations to maximize discrimination. In addition, for evaluation of the model performance, discrimination and calibration were used.This study is valuable and important, but some important comments are recommended in this regard. Validation is one of the most important stages in building the model prediction. In doing this, data should come from 2 different cohorts, but if it is from a single cohort, data should be divided into 2 parts. The first part is used for developing the prediction model and the second part is used for developing the validation model. The main results obtained from model development may be misleading if the validity of the model is not appropriate. [2][3][4] Given these comments about prediction models, the authors' results should be interpreted with caution.

show abstract

Methodological Issue in “Development of an Ultrasound Prediction Model to Discriminate between Malignant and Benign Liver Lesions”

Pilangorgi

Shahsavari

2020

Ultrasound in Medicine & Biology

View full text Add to dashboard Cite

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

A Clinical Risk Scoring Tool to Predict Readmission After Cardiac Surgery: A Methodological Issue

Cited by 4 publications

References 3 publications

A Methodological Issue in Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features

A Methodological Issue in Prediction of Cancer Masking in Screening Mammography Using Density and Textural Features

Methodological Issue in Prediction Model for Nodal Disease Among Patients With Lung Cancer

Methodological Issue in “Development of an Ultrasound Prediction Model to Discriminate between Malignant and Benign Liver Lesions”

Contact Info

Product

Resources

About