Pleural fluid C-C class chemokines 22 and pleural effusion due to heart failure: a prospective and double-blind diagnostic accuracy test

胸腔积液CC类趋化因子22与心力衰竭引起的胸腔积液:一项前瞻性双盲诊断准确性试验

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Abstract

BACKGROUND: Previous studies have indicated that C-C class chemokine ligand 22 (CCL22) is involved in the pathogenesis of tuberculous pleural effusion and malignant pleural effusion. However, the diagnostic role of pleural fluid CCL22 levels in patients with undiagnosed pleural effusions remains to be elucidated. METHODS: We prospectively recruited patients with undiagnosed pleural effusion who visited two centres (Hohhot and Changshu) in China. Pleural biopsy, microbiological culture and effusion cytology were used to verify the cause of pleural effusion. Pleural fluid CCL22 levels were measured using an ELISA. The diagnostic accuracy of CCL22 for identifying heart failure (HF) was evaluated using a receiver operating characteristic (ROC) curve, and the net benefit of CCL22 was evaluated using decision curve analysis (DCA). Net benefit was defined as the benefit associated with true positives minus the harms associated with false positives at various threshold probabilities. RESULTS: We enrolled 153 and 58 patients in the Hohhot and Changshu cohorts, respectively. The cohort included 28 patients with HF and 183 patients with non-HF. Patients with HF had significantly lower pleural fluid CCL22 levels than non-HF patients. The area under the ROC curve (AUC) of CCL22 was 0.85 (95% CI: 0.77 to 0.93) in the Hohhot cohort and 0.87 (95% CI: 0.75 to 0.98) in the Changshu cohort. The AUC in the combined cohort was 0.85 (95% CI: 0.79 to 0.92), with a sensitivity of 0.82 (95% CI: 0.68 to 0.93) and a specificity of 0.73 (95% CI: 0.67 to 0.79) at the threshold of 150 ng/mL. DCA revealed a potential net benefit of pleural CCL22 determination in patients with undiagnosed pleural effusions. CONCLUSIONS: Pleural fluid CCL22 may be a potential diagnostic marker for HF-related pleural effusion. Owing to the small sample size of this study, further studies with larger sample sizes are needed to validate our findings.

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