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The association of the advanced lung cancer inflammation index with postoperative complications in patients undergoing lung resection for bronchiectasis

  • 0Department of Thoracic Surgery, Beijing Institute of Respiratory Medicine and Beijing Chao-Yang Hospital, Capital Medical University, Beijing, China.
Journal of Thoracic Disease +

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July 21, 2025

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July 21, 2025

View abstract on PubMed

Summary

This summary is machine-generated.

The advanced lung cancer inflammation index (ALI) predicts postoperative complications in bronchiectasis patients. This index, along with BMI and operation time, helps assess surgical risk.

Area Of Science

  • Pulmonary Medicine
  • Surgical Oncology
  • Biomarker Research

Background

  • Bronchiectasis patients often face systemic inflammation and malnutrition, impacting prognosis.
  • The advanced lung cancer inflammation index (ALI) is a novel biomarker for inflammation and nutritional status.
  • Evaluating ALI's predictive capacity for postoperative complications in bronchiectasis is crucial.

Purpose Of The Study

  • To assess the predictive value of the advanced lung cancer inflammation index (ALI) for postoperative complications.
  • To identify independent risk factors for postoperative complications in patients with localized bronchiectasis undergoing surgery.
  • To develop and validate a predictive nomogram for postoperative complications.

Main Methods

  • Retrospective study of 191 localized bronchiectasis patients (Jan 2013 - Nov 2023).
  • Determined optimal ALI cutoff using ROC curve analysis.
  • Multivariate logistic regression and nomogram construction for risk prediction.

Main Results

  • Optimal ALI cutoff identified as 43.1.
  • ALI (OR: 3.006), low BMI (OR: 0.868), and operation time (OR: 1.010) were independent predictors of complications.
  • Developed nomogram showed good predictive performance (AUC = 0.776).

Conclusions

  • Preoperative ALI is a significant independent predictor of postoperative complications in localized bronchiectasis.
  • The ALI-based predictive model offers a valuable tool for risk assessment in surgical patients.
  • This research aids clinicians in managing bronchiectasis patients undergoing surgical resection.

Keywords:

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