Postoperative plasma presepsin as a biomarker of postoperative infectious complications in different surgical departments : A meta-analysis and systematic review
Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved..
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.
METHOD: 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.
CONCLUSION: 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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:229 |
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| Enthalten in: |
American journal of surgery - 229(2024) vom: 06. März, Seite 65-75 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
You, Pan [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 01.03.2024 Date Revised 05.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.amjsurg.2023.11.024 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM365565393 |
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| 245 | 1 | 0 | |a Postoperative plasma presepsin as a biomarker of postoperative infectious complications in different surgical departments |b A meta-analysis and systematic review |
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| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved. | ||
| 520 | |a 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 | ||
| 520 | |a METHOD: 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 | ||
| 520 | |a 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 | ||
| 520 | |a CONCLUSION: 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Meta-Analysis | |
| 650 | 4 | |a Systematic Review | |
| 650 | 4 | |a Diagnostic biomarker | |
| 650 | 4 | |a Meta-analysis | |
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| 650 | 4 | |a Presepsin | |
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| 700 | 1 | |a Zhang, Xiao-Ke |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Wen-Xiong |e verfasserin |4 aut | |
| 700 | 1 | |a Huang, Li-Feng |e verfasserin |4 aut | |
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