Study on the Red Blood Cell Distribution Width in Connective Tissue Disease Associated with Interstitial Lung Disease

Biomed Res Int. 2020 Jan 24:2020:8130213. doi: 10.1155/2020/8130213. eCollection 2020.

Abstract

Background: Connective tissue disease (CTD) associated with interstitial lung disease (ILD) affects the lungs and can lead to considerable morbidity and shortened survival. Red blood cell distribution width (RDW) is a readily available parameter that is routinely reported with complete blood cell count (CBC) This study aimed to investigate the predictive value of RDW in CTD-ILD.

Methods: A retrospective analysis was performed on 180 patients with CTD-ILD and 202 patients with CTD but without ILD between April 2016 and December 2018. Baseline demographics, laboratory results, imaging examinations, and results of ultrasound scans were analysed.

Results: In comparison with patients without ILD, patients with CTD-ILD displayed a larger RDW (14.65 ± 2.08 vs. 14.17 ± 1.63, P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (r = 0.349; P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (r = 0.349; P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (r = 0.349; P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (P=0.002), and RDW shared positive relationships with pulmonary artery systolic pressure (.

Conclusions: RDW was significantly increased in patients with CTD-ILD under various CTD backgrounds and may be a promising biomarker that may help physicians predict CTD-ILD risk.

MeSH terms

  • Adult
  • Biomarkers
  • Blood Cell Count
  • Connective Tissue Diseases / complications*
  • Connective Tissue Diseases / physiopathology*
  • Erythrocyte Indices*
  • Erythrocytes
  • Female
  • Humans
  • Logistic Models
  • Lung
  • Lung Diseases, Interstitial / complications*
  • Male
  • Middle Aged
  • Retrospective Studies

Substances

  • Biomarkers