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Related Concept Videos

COPD: Management Using Bronchodilators and Corticosteroids01:26

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Chronic obstructive pulmonary isease (COPD) involves a group of progressive lung disorders characterized by persistent airflow limitation and chronic respiratory symptoms. Asthma-COPD Overlap Syndrome (ACOS), encompassing features of both asthma and Chronic obstructive pulmonary disease (COPD), is a group of progressive lung disorders that includes chronic bronchitis, emphysema, and refractory (non-reversible) asthma. ACOS leads to complex clinical presentations that combine the inflammatory...
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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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Inhaled corticosteroids (ICS) are anti-inflammatory drugs used primarily in treating persistent asthma and providing long-term maintenance. They target the bronchial mucosa, the lining of the airways, to control inflammation, a critical factor in asthma progression and exacerbation.
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Lower respiratory tract disorders present challenges that often require skilled and nuanced approaches for effective management. Common ailments, such as asthma and chronic obstructive pulmonary disease (COPD), have prompted the development of intricate treatment strategies involving bronchodilators and anti-inflammatory drugs, each tailored to ease breathing and revitalize the lungs.
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Comprehensive Nomograms Using Routine Biomarkers Beyond Eosinophil Levels: Enhancing Predictability of Corticosteroid

Lin Feng1, Jiachen Li1, Zhenbei Qian2

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|March 13, 2024
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Summary

Predicting corticosteroid treatment success in acute exacerbation of chronic obstructive pulmonary disease (AECOPD) can be improved by combining blood eosinophil counts with other clinical factors. New scoring systems offer modest enhancement for predicting treatment outcomes in AECOPD patients.

Keywords:
chronic obstructive pulmonary diseaseglucocorticoidsleast absolute shrinkage and selection operatorprediction model

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Area of Science:

  • Pulmonary Medicine
  • Clinical Biomarkers
  • Predictive Modeling

Background:

  • Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) shows varied responses to corticosteroid therapy.
  • Predicting treatment success is crucial for optimizing patient management.

Purpose of the Study:

  • To assess if combining blood eosinophil levels with routine clinical indicators improves prediction of corticosteroid treatment outcomes in AECOPD.
  • To develop a scoring system for predicting treatment failure in AECOPD.

Main Methods:

  • Retrospective analysis of 3254 AECOPD patients treated with corticosteroids.
  • Utilized LASSO and logistic regression for predictor selection and developed predictive nomograms.
  • Assessed nomogram performance using AUC, calibration plots, bootstrap validation, and decision curve analysis.

Main Results:

  • Treatment failure observed in 24.7% of patients.
  • Developed distinct nomograms for smokers and non-smokers, incorporating eosinophils, platelets, CRP, LDL cholesterol, PNI, prior AECOPD hospitalizations, ischemic heart disease, and chronic hepatic disease.
  • Nomograms showed modest predictive superiority over eosinophil levels alone (AUCs 0.644-0.647).

Conclusions:

  • Developed user-friendly nomograms using accessible biomarkers for inflammation, nutrition, and immunity.
  • These nomograms offer a modest improvement in predicting treatment outcomes for corticosteroid-treated AECOPD patients.
  • Further research with novel biomarkers and additional data is needed to enhance predictive accuracy.