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Prediction of clinical deterioration within one year in chronic obstructive pulmonary disease using the systemic

Ling Hou1, Ming Min2, Rui Hou3

  • 1Department of Central Hospital of Tujia and Miao Autonomous Prefecture, Hubei University of Medicine, Hubei, China.

Peerj
|March 3, 2025
PubMed
Summary
This summary is machine-generated.

The systemic coagulation-inflammation (SCI) index is significantly higher in patients with chronic obstructive pulmonary disease (COPD) experiencing clinical deterioration. Machine learning models, particularly SVM, can reliably predict clinical deterioration in COPD patients using the SCI index.

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Area of Science:

  • Pulmonary Medicine
  • Biomedical Engineering
  • Computational Biology

Background:

  • The inflammatory response and coagulation system are key factors in the progression of chronic obstructive pulmonary disease (COPD).
  • Clinical deterioration in COPD is often linked to the interplay between inflammation and coagulation.
  • The systemic coagulation-inflammation (SCI) index offers a potential marker for assessing this interplay.

Purpose of the Study:

  • To investigate the association between the systemic coagulation-inflammation (SCI) index and clinical deterioration in patients with COPD.
  • To evaluate the performance of various machine learning models in predicting clinical deterioration in COPD.
  • To identify key predictors of clinical deterioration in COPD.

Main Methods:

  • A cohort of 957 COPD patients was analyzed between January 2018 and December 2021.
  • Six machine learning models (XGBoost, logistic regression, Random Forest, elastic net, SVM, and KNN) were compared using standard performance metrics (accuracy, precision, recall, F1-score, AUC-ROC).
  • The SCI index and other clinical/laboratory parameters were assessed for their predictive value.

Main Results:

  • Out of 957 patients, 171 experienced clinical deterioration (cd-COPD).
  • Significant differences were observed in age, comorbidities, C-reactive protein, lymphocyte count, RDW, SCI, PCT, and D-dimer between cd-COPD and non-cd-COPD groups.
  • The Support Vector Machine (SVM) model demonstrated superior performance in predicting cd-COPD. The SCI index was the most influential predictor, with a median of 93.08 in cd-COPD versus 81.67 in non-cd-COPD patients.

Conclusions:

  • The SCI index is significantly elevated in COPD patients with clinical deterioration.
  • The SVM model shows reliable performance for predicting clinical deterioration in COPD.
  • The SCI index is a valuable biomarker for identifying COPD patients at risk of clinical deterioration.