COPD is a frequently diagnosed chronic disease, with high mortality and morbidity. AECOPD refers the acute situation of COPD featured by the worsening of the patient’s respiratory symptoms [16]. Bacterial infection is a leading reason for AECOPD, and antibiotic treatment is necessary for the patients. In addition to antibacterial treatment, the appropriate NIPPV treatment could shorten the hospitalization time, improve the pain, and reduce the need of endotracheal intubation [17]. However, there are no credible indicators for application of NIPPV among AECOPD patients. In this study, we estimated the predictive value of serum PCT for NIPPV treatment in AECOPD patients. The results suggested that serum PCT levels were significantly different between the cases in NIPPV group and control group. Serum PCT was independently correlated with NIPPV treatment, which might be employed as an indicator for NIPPV treatment in AECOPD patients.
For COPD patients, the long-term airflow obstruction could impair their immune lung defense systems, which make the patients are more easily to be infected by bacteria, leading to AECOPD [18]. Bacterial infection and inflammation play important roles in progression of AECOPD. Circulating PCT level is considered to be a specific indicator for bacterial infection, and its levels are closely correlated with infection severity [19]. In the current study, 220 AECOPD patients were divided into NIPPV group and control group according to the routine standards and physicians’ experience. The comparison analysis suggested that compared to those in control group, the individuals in NIPPV group were more likely to show high RR, PaO2, PaCO2, ESR, neutrophil, CRP and PCT levels, as well as low pH and oxygenation index. All the results demonstrated the aggressive inflammation, severe infection, and poor pulmonary function of NIPPV cases. Logistic regression analysis suggested that PCT, CRP, PaCO2, RR, and neutrophil were independently correlated with NIPPV treatment in AECOPD. The study carried out by Sarika et al. suggested that PCT level was significantly elevated in AECOPD patients, compared to stable COPD patients [20]. Hamid Borsi et al. reported that serum PCT might be employed as a biomarker for the differentiation of AECOPD patients from stable COPD patients [21]. All the data revealed the close relationship between serum PCT and COPD progression.
The appropriate application of NIPPV treatment could help improve the clinical prognosis of AECOPD patients, but the abuse of NIPPV may lead to some serious complications, such as pneumothorax, hypotension, aspiration pneumonia, and so on [22, 23]. Therefore, the specific indicators are necessary to guide NIPPV treatment in AECOPD patients. In our study, ROC curve demonstrated that PCT, CRP, PaCO2, RR, and neutrophil could distinguish between NIPPV group and control group. Moreover, compared to other indicators, PCT showed superior values, with better AUC, sensitivity and specificity. Serum PCT might be adopted as an indicator to guide NIPPV treatment among AECOPD patients. Serum PCT had been confirmed as an indicator for antibiotic treatment of AECOPD. A meta-analysis carried out by Li et al. demonstrated that the antibiotic treatment guided by PCT showed similar efficacy and safety with standard antibiotic treatment, and has fewer antibiotic prescriptions [24]. Moreover, the AECOPD patients with high serum PCT levels were more likely to undergo NIPPV failure [25]. The present study might be the first study to explore the predictive value of serum PCT for NIPPV treatment in COPD patients.
Several limitations in current study should be stated. Firstly, the sample size was relatively small that might reduce the statistical power of our analysis. Secondly, due to the selection criteria, the selection bias might be introduced, and the conclusion was limited by the studied subjects. Thirdly, NIPPV treatment was performed based on routine standards and the physicians’ experience that might influence the analysis results. Therefore, the well-designed prospective studies with large sample size are required to improve our analysis.