Wang Yuan, Wang Tingting, Hu Shouqin, Cheng Yuntao, Du Chongyue, Xu Guolong
Department of Emergency, Jiashan County Traditional Chinese Medicine Hospital, No. 38 Gujiadai, Weitang Street, Jiashan County, Jiaxing, Zhejiang Province, 314100, China.
BMC Pulm Med. 2025 Jun 9;25(1):286. doi: 10.1186/s12890-025-03750-6.
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.
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.
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.
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.
卒中相关性肺炎（SAP）是卒中后常见且严重的并发症，对恢复和预后有显著影响。早期识别生物标志物并开发预测模型对于SAP的诊断和预防至关重要。本研究系统评估了降钙素原（PCT）和其他生物标志物对SAP的诊断价值，并探讨了将它们纳入预测模型的情况。
通过检索PubMed、Web of Science和CNKI数据库，对截至2023年3月发表的研究进行系统评价和荟萃分析。纳入标准侧重于报告SAP诊断生物标志物和预测模型的研究。使用RevMan 5.4和R软件进行统计分析，包括合并敏感性、特异性、诊断比值比（DOR）和受试者工作特征曲线下面积（AUC）。
这项荟萃分析纳入了11项研究，共1478例患者，发现SAP患者的PCT水平显著升高，尤其是缺血性卒中患者（标准化均数差[SMD]=2.89，95%置信区间[CI]=1.74 - 4.04）。PCT显示出较高的诊断准确性，合并敏感性为0.84，特异性为0.89，DOR为48.78，AUC为0.91，优于CRP和IL - 6等其他生物标志物。纳入生物标志物的预测模型改善了风险分层，不过研究之间的异质性强调了标准化的必要性。
PCT是用于SAP诊断的可靠生物标志物，具有高敏感性和特异性。将PCT与预测模型相结合可增强对SAP的风险评估和早期检测。有必要进一步研究以完善预测模型，并在不同人群中验证生物标志物的临床应用。本研究强调了生物标志物在指导SAP预防和管理策略方面的重要性。
