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Residuals and Least-Squares Property01:11

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The vertical distance between the actual value of y and the estimated value of y. In other words, it measures the vertical distance between the actual data point and the predicted point on the line
If the observed data point lies above the line, the residual is positive, and the line underestimates the actual data value for y. If the observed data point lies below the line, the residual is negative, and the line overestimates the actual data value for y.
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Calcium-Scoring CT ScanA calcium-scoring CT scan, also known as coronary artery calcium (CAC) scan, detects calcium deposits in the coronary arteries. This test assesses the risk of coronary artery disease (CAD), which can lead to cardiovascular events such as angina, heart failure, and sudden cardiac arrest.A calcium-scoring CT scan is generally recommended for individuals at intermediate risk of CAD without symptoms. It includes:Men aged 40-75 and women aged 50-75: Especially those with a...
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Pareto Chart00:52

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A Pareto chart is a bar graph or a combination of both line and bar graphs. The bar lengths represent the individual values or the frequency, while the lines represent the cumulative total values. In this chart, the longest bars are arranged on the left and the shortest bars on the right, which makes it easier to read and interpret the data. It can also be called a Pareto diagram or Pareto analysis.
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Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
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Receiver Operating Characteristic Plot01:15

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A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
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A pie chart (or a pie graph) is a circular graphical chart or a pictorial representation of categorical data. It is divided into slices of pie each indicating numerical proportions. It is also used to show the relative sizes of data in a single chart.
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Related Experiment Video

Updated: Sep 21, 2025

Comparing Objective Conjunctival Hyperemia Grading and the Ocular Surface Disease Index Score in Dry Eye Syndrome During COVID-19
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Predicting progression to severe COVID-19 using the PAINT score.

Ming Wang1,2, Dongbo Wu1,2, Chang-Hai Liu1

  • 1Center of Infectious Diseases, West China Hospital, Sichuan University, 37 Guoxue Lane, Chengdu, Sichuan Province, 610041, People's Republic of China.

BMC Infectious Diseases
|May 26, 2022
PubMed
Summary

A new predictive score, the PAINT score, helps identify patients with COVID-19 at high risk of severe disease progression. This tool aids clinicians in early intervention for coronavirus disease 2019 patients.

Keywords:
COVID-19NK cellPredictionSARS-CoV-2

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Area of Science:

  • Infectious Diseases
  • Clinical Medicine
  • Biostatistics

Background:

  • Predicting the severity of coronavirus disease 2019 (COVID-19) is crucial for effective patient management.
  • Early identification of patients likely to progress from mild/moderate to severe disease is a significant clinical challenge.

Purpose of the Study:

  • To develop and validate a novel predictive score for identifying COVID-19 patients at high risk of disease progression.
  • To establish a reliable tool for clinical decision-making in managing COVID-19.

Main Methods:

  • Retrospective analysis of 239 hospitalized COVID-19 patients from two Chinese medical centers.
  • Utilized Cox proportional hazards model and Kaplan-Meier methods to identify independent predictors of disease progression.
  • Developed the PAINT score based on five key prognostic factors: pulmonary disease, age > 75, IgM, CD16+/CD56+ NK cells, and aspartate aminotransferase.

Main Results:

  • A total of 23 patients (9.62%) progressed to severe COVID-19.
  • The PAINT score demonstrated high predictive accuracy with a C-index of 0.91.
  • Validation through nomogram, bootstrap analysis, calibration curves, and decision curves confirmed the score's robust predictive value.

Conclusions:

  • The PAINT score is a valuable tool for predicting progression from mild/moderate to severe COVID-19.
  • This score can assist clinicians in identifying high-risk individuals, enabling timely and targeted interventions.