Procalcitonin and biomarkers for stroke-associated pneumonia: a systematic review and meta-analysis - Yuan Wang; Tingting Wang; Shouqin Hu; Yuntao Cheng; Chongyue Du; Guolong Xu (BMC Pulmonary Medicine)
Abstract Background Stroke-associated pneumonia (SAP) is a common and severe complication following stroke, significantly impacting recovery and outcomes. Early identification of biomarkers and development of predictive models are essential for SAP diagnosis and prevention. This study systematically evaluated the diagnostic value of procalcitonin (PCT) and other biomarkers for SAP and explored their integration into predictive models. Methods A systematic review and meta-analysis were conducted by searching PubMed, Web of Science, and CNKI databases for studies published up to March 2023. Inclusion criteria focused on studies reporting biomarkers for SAP diagnosis and predictive models. Statistical analyses included pooled sensitivity, specificity, diagnostic odds ratio (DOR), and area under the receiver operating characteristic curve (AUC) using RevMan 5.4 and R software. Results This meta-analysis included 11 studies with 1,478 patients and found that PCT levels were significantly elevated in SAP patients, particularly those with ischemic stroke (standardized mean difference [SMD] = 2.89, 95% confidence interval [CI] = 1.74–4.04). PCT demonstrated high diagnostic accuracy, with a pooled sensitivity of 0.84, specificity of 0.89, DOR of 48.78, and AUC of 0.91, outperforming other biomarkers like CRP and IL-6. Predictive models incorporating biomarkers improved risk stratification, though heterogeneity among studies underscores the need for standardization. Conclusions PCT is a reliable biomarker for SAP diagnosis, offering high sensitivity and specificity. Combining PCT with predictive models can enhance risk assessment and early detection of SAP. Further research is necessary to refine prediction models and validate the clinical application of biomarkers across diverse populations. This study underscores the importance of biomarkers in guiding SAP prevention and management strategies.