A retrospective analysis of the relationship between dermatomyositis-associated interstitial lung disease and disease duration, age, arterial blood gas pH, and serum Cl− levels

Abstract

Background

Dermatomyositis-associated interstitial lung disease (DM-ILD) represents a severe and insidious complication of dermatomyositis (DM). The study aimed to investigate the association between DM-ILD and arterial blood gas indices, serum ion levels, and the timing of interstitial lung disease onset, with the goal of identifying potential predictors for DM-ILD.

Methods

The investigation involved the collection of basic data from 89 patients with DM hospitalized at the Chinese PLA General Hospital between January 2019 and April 2022, and 43 normal control patients hospitalized for physical examinations during the same period. Analyses were conducted to explore the relationship between DM-ILD, arterial blood gas indices, disease duration, and serum ions. A regression model to predict DM-ILD was developed using these indices, and a receiver operating characteristic curve was generated.

Results

Significant differences were observed in pH and PaO₂ between the control group and the disease group (p < 0.05). The DM group exhibited higher levels of pH, actual bicarbonate, and base excess (BE) compared with the control group. In contrast, pH and BE levels were lower in the DM-ILD group than in the DM group, with these differences being statistically significant (p < 0.05). Interstitial lung disease was correlated with the duration of the disease and pH levels (p < 0.05). The cutoff values for age, disease duration, pH, and Cl⁻ were 55.5 years, 5.5 years, 7.432, and 101.5 mmol/L, respectively. The model demonstrated a prediction sensitivity and specificity for DM-ILD of 0.809 and 0.722, respectively, with an area under the curve of 0.809.

Conclusion

Arterial blood gas analysis and serum Cl⁻ levels may assist in predicting DM-ILD. A combined monitoring approach involving arterial blood gas pH, disease duration, age, and serum Cl⁻ levels could enhance the accuracy of DM-ILD predictions and hold significant clinical evaluation potential.