Abstract：
BACKGROUND: High rates of postoperative infection persist after different surgical procedures, encompassing surgical site infections (SSIs), remote infections, sepsis, and septic shock. Our aim was to assess presepsin\'s diagnostic accuracy for postoperative infections in patients across surgical procedures.
METHODS: We conducted a comprehensive search in seven databases, extracting data independently. Using STATA 14.0, we calculated pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and Under the receiver operator curve and 95 % confidence interval (AUC, 95 % CI) as primary outcomes, with secondary outcomes involving sensitivity and specificity in subgroup analyses.
RESULTS: This meta-analysis of 14 studies (1891 cases) evaluated presepsin\'s diagnostic value for postoperative infectious complications. Results include sensitivity of 77 % (70-83), specificity of 81 % (71-88), DOR of 14 (8-26), AUC of 84 (80-87), PLR of 4 (3-6), and NLR of 0.28 (0.21-0.38). Presepsin exhibits promise as a diagnostic tool for postoperative infections.
CONCLUSIONS: In summary, compared to conventional markers like C-reactive protein (CRP) and procalcitonin (PCT), presepsin demonstrated superior sensitivity and specificity for detecting postoperative infectious complications across various surgical procedures.
METHODS: We conducted a comprehensive search in seven databases, extracting data independently. Using STATA 14.0, we calculated pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and Under the receiver operator curve and 95 % confidence interval (AUC, 95 % CI) as primary outcomes, with secondary outcomes involving sensitivity and specificity in subgroup analyses.
RESULTS: This meta-analysis of 14 studies (1891 cases) evaluated presepsin\'s diagnostic value for postoperative infectious complications. Results include sensitivity of 77 % (70-83), specificity of 81 % (71-88), DOR of 14 (8-26), AUC of 84 (80-87), PLR of 4 (3-6), and NLR of 0.28 (0.21-0.38). Presepsin exhibits promise as a diagnostic tool for postoperative infections.
CONCLUSIONS: In summary, compared to conventional markers like C-reactive protein (CRP) and procalcitonin (PCT), presepsin demonstrated superior sensitivity and specificity for detecting postoperative infectious complications across various surgical procedures.
摘要：
背景：不同外科手术后，术后感染率高，包括手术部位感染(SSIs)，远程感染,脓毒症,和感染性休克。我们的目的是评估presepsin对手术患者术后感染的诊断准确性。
方法：我们在七个数据库中进行了全面搜索，独立提取数据。使用STATA14.0，我们计算了合并灵敏度，特异性，正似然比(PLR)，负似然比(NLR)，诊断优势比(DOR)，在接受者算子曲线和95%置信区间(AUC，95%CI)作为主要结果，次要结局涉及亚组分析的敏感性和特异性。
结果：这项对14项研究（1891例）的荟萃分析评估了presepsin对术后感染并发症的诊断价值。结果包括77%(70-83)的灵敏度，特异性为81%(71-88)，DOR为14（8-26），AUC为84（80-87），PLR为4(3-6),NLR为0.28（0.21-0.38）。Presepsin有望作为术后感染的诊断工具。
结论：总之，与C反应蛋白（CRP）和降钙素原（PCT）等常规标志物相比，presepsin在检测各种外科手术的术后感染并发症方面表现出优异的敏感性和特异性.
方法：我们在七个数据库中进行了全面搜索，独立提取数据。使用STATA14.0，我们计算了合并灵敏度，特异性，正似然比(PLR)，负似然比(NLR)，诊断优势比(DOR)，在接受者算子曲线和95%置信区间(AUC，95%CI)作为主要结果，次要结局涉及亚组分析的敏感性和特异性。
结果：这项对14项研究（1891例）的荟萃分析评估了presepsin对术后感染并发症的诊断价值。结果包括77%(70-83)的灵敏度，特异性为81%(71-88)，DOR为14（8-26），AUC为84（80-87），PLR为4(3-6),NLR为0.28（0.21-0.38）。Presepsin有望作为术后感染的诊断工具。
结论：总之，与C反应蛋白（CRP）和降钙素原（PCT）等常规标志物相比，presepsin在检测各种外科手术的术后感染并发症方面表现出优异的敏感性和特异性.
