Decision tools for diagnosing spontaneous bacterial peritonitis: a systematic review and meta-analysis
-
Khazar Garjani
,
Elnaz Vahidi
,
Mehrad Aghili
,
Amir Abbas Azimi Nezhad
,
Parinaz Dadlani
,
Hadi Mirfazaelian
Abstract
Backgound: Approximately one-third of the spontaneous bacterial peritonitis (SBP) are missed due to the absence of paracentesis, and any delay in antibiotic initiation significantly increases mortality. Clinical decision tools may help to rule out or rule in the diagnosis without paracentesis. This study systematically reviewed the performance of available decision tools for diagnosing SBP in adult patients with cirrhosis. Methods: We included all original studies that evaluated clinical decision tools for SBP diagnosis. Search was conducted in MEDLINE, Embase, Scopus, and Web of Science Core Collection from inception to September 2024. Study quality was evaluated using Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS 2). Results: From 2038 records, 44 articles were scrutinized in full text. Twenty-four studies ultimately met eligibility criteria. Most of the studies were at low risk of bias. Several tools relied on laboratory findings with clinical features. In meta-analysis the Mansoura scoring system (cut-off of 4) showed a pooled sensitivity of 70.96% (95% CI: 42.06%,99.86%) and a negative predictive value 92.27% (95% CI: 88.80%,95.74%). The Wehmeyer’s scoring system achieved pooled specificity and positive predictive value of 98.43% (95% CI: 95.29,101.58%) and 90.26% (95% CI: 70.28,110.23%). A MELD score >15 yielded had pooled sensitivity of 83.85% (95% CI: 78.50%,89.20%) and negative predictive value of 87.56% (95% CI: 81.29%,93.84%). Conclusion: Several decision tools, particularly laboratory-based (e.g. procalcitonin) tools, showed high sensitivity to potentially rule out SBP. Some other tools (e.g. Mansoura, Wehmeyer rules) can reliably rule in the diagnosis. However, tools all the tools need further validation before widespread adoption.
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2. European Association for the Study of the Liver. EASL clinical practice guidelines on the management of ascites, spontaneous bacterial peritonitis, and hepatorenal syndrome in cirrhosis. J Hepatol. 2010;53(3):397-417.
3. Deutsch-Link S, Campbell PT, Shah ND. PRO: ascitic fluid cell count should be routinely sent with every therapeutic paracentesis to assess for spontaneous bacterial peritonitis. Clin Liver Dis (Hoboken). 2023;22(4):140-142.4. Long B, and Gottlieb M. Emergency medicine updates: spontaneous bacterial peritonitis. Am J Emerg Med. 2023;70:84-9.
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6. Alhumaid S, Al Mutair A, Al Alawi Z, et al. Proton pump inhibitors use and risk of developing spontaneous bacterial peritonitis in cirrhotic patients: a systematic review and meta-analysis. Gut Pathog. 2021;13(1):17.7. Thalheimer U, Triantos CK, Samonakis DN, Patch D, Burroughs AK. Infection, coagulation, and variceal bleeding in cirrhosis. Gut. 2005;54(4):556-63.
8. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-36. 9. McGuinness LA, Higgins JPT. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021;12(1):55-61.10. Abdel-Razik A, Mousa N, Abdel-Aziz M, et al. Mansoura simple scoring system for prediction of spontaneous bacterial peritonitis: lesson learnt. Eur J Gastroenterol Hepatol. 2019;31(8):1017-24.
11. Abdo G, Nir U, Rawajdey R, et al. A novel score-based approach by using routine laboratory tests for accurate diagnosis of spontaneous bacterial peritonitis (SBP) in cirrhotic patients. EJIFCC. 2023;34(4):297-304.
12. Huynh NC, Vo TD. Validation of a new simple scoring system to predict spontaneous bacterial peritonitis in patients with cirrhosis and ascites. BMC Gastroenterol. 2023;23(1):272.
13. Wehmeyer MH, Krohm S, Kastein F, Lohse AW, Lüth S. Prediction of spontaneous bacterial peritonitis in cirrhotic ascites by a simple scoring system. Scand J Gastroenterol. 2014;49(5):595-603.
14. Xiang S, Tan J, Tan C, et al. Establishment and validation of a non-invasive diagnostic nomogram to identify spontaneous bacterial peritonitis in patients with decompensated cirrhosis. Front Med (Lausanne). 2022;8:797363..
15. Würstle S, Hapfelmeier A, Karapetyan S, et al. A novel machine learning-based point-score model as a non-invasive decision-making tool for identifying infected ascites in patients with hydropic decompensated liver cirrhosis: a retrospective multicentre study. Antibiotics (Basel). 2022;11(11):1610.
16. Shi KQ, Fan YC, Ying L, et al. Risk stratification of spontaneous bacterial peritonitis in cirrhosis with ascites based on classification and regression tree analysis. Mol Biol Rep. 2012;39(5):6161-9.
17. Yin X, Qin E, Song R, et al. Diagnostic model for spontaneous bacterial peritonitis in cirrhotic patients with ascites: a multicenter cohort study. Eur J Gastroenterol Hepatol. 2024;36(11):1319-28.
18. Zhou Z, Lv H, Lv J, et al. Alterations of gut microbiota in cirrhotic patients with spontaneous bacterial peritonitis: A distinctive diagnostic feature. Front Cell Infect Microbiol. 2022;12:999418.
19. Hu Y, Chen R, Gao H, et al. Explainable machine learning model for predicting spontaneous bacterial peritonitis in cirrhotic patients with ascites. Sci Rep. 2021;11(1):21639.
20. Elsadek HM, Elhawari SA, Mokhtar A. A novel serum index for accurate diagnosis of spontaneous bacterial peritonitis in cirrhotic patients without other infections. 2020.
21. Wang H, Li Y, Zhang F, et al. Combination of PCT, sNFI and dCHC for the diagnosis of ascites infection in cirrhotic patients. BMC Infect Dis. 2018;18(1):389.
22. Obstein KL, Campbell MS, Reddy KR, Yang YX. Association between model for end-stage liver disease and spontaneous bacterial peritonitis. Am J Gastroenterol. 2007;102(12):2732-6.
23. Kamal A. Evaluation of a novel index that incorporates both neutrophil- lymphocyte ratio and c-reactive protein for the detection of spontaneous bacterial peritonitis. The Egyptian Journal of Hospital Medicine. 2024; 94: 950-6 .
24. Popoiag RE, Suceveanu AI, Suceveanu AP, et al. Predictors of spontaneous bacterial peritonitis in Romanian adults with liver cirrhosis: Focus on the neutrophil-to-lymphocyte ratio. Exp Ther Med. 2021;22(3):983.
25. Mousa N, Besheer T, Abdel-Razik A, et al. Can combined blood neutrophil to lymphocyte ratio and C-reactive protein be used for diagnosis of spontaneous bacterial peritonitis?. Br J Biomed Sci. 2018;75(2):71-5.
26. Silvey S, Patel N, Liu J, et al. A Machine learning algorithm avoids unnecessary paracentesis for exclusion of sbp in cirrhosis in resource-limited settings. Clin Gastroenterol Hepatol. 2024;22(12):2442-50.e8.27. Cai ZH, Fan CL, Zheng JF, et al. Measurement of serum procalcitonin levels for the early diagnosis of spontaneous bacterial peritonitis in patients with decompensated liver cirrhosis. BMC Infect Dis. 2015;15:55.28. Metwally K, Fouad T, Assem M, Abdelsameea E, Yousery M. Predictors of Spontaneous Bacterial Peritonitis in Patients with Cirrhotic Ascites. J Clin Transl Hepatol. 2018;6(4):372-6.29. Gayatri AA, Suryadharma IG, Purwadi N, Wibawa ID. The relationship between a model of end stage liver disease score (MELD score) and the occurrence of spontaneous bacterial peritonitis in liver cirrhotic patients. Acta Med Indones. 2007;39(2):75-8.
30. Kraja B, Sina M, Mone I, et al. Predictive value of the model of end-stage liver disease in cirrhotic patients with and without spontaneous bacterial peritonitis. Gastroenterol Res Pract. 2012;2012:539059.
31. Elghoneimy, R.I.E.S.M. Predictive value of neutrophil to lymphocyte ratio combined with c-reactive protein for diagnosis of spontaneous bacterial peritonitis among cirrhotic patients. The Egyptian Journal of Hospital Medicine. 2023; 91: 4380-6.
32. Abudeif A, Elbadry MI, Ahmed NM. Validation of the diagnostic accuracy of neutrophil to lymphocyte ratio (NLR) and mean platelet volume (MPV) in cirrhotic patients with spontaneous bacterial peritonitis. Egypt Liver Journal. 2023;13. (2023).
33. Du T, Li QP, Jiang GX, et al. Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes. BMC Infect Dis. 2023;23(1):786.
34. Pieri G, Agarwal B, Burroughs AK. C-reactive protein and bacterial infection in cirrhosis. Ann Gastroenterol. 2014;27(2):113-20.
35. Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ. 2004;329(7458):168-9.
36. Qin N, Yang F, Li A, et al. Alterations of the human gut microbiome in liver cirrhosis. Nature. 2014;513(7516):59-64.
37. Lv LX, Fang DQ, Shi D, et al. Alterations and correlations of the gut microbiome, metabolism and immunity in patients with primary biliary cirrhosis. Environ Microbiol. 2016;18(7):2272-86..
38. Wiesner R, Edwards E, Freeman R, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology. 2003;124(1):91-6.
2. European Association for the Study of the Liver. EASL clinical practice guidelines on the management of ascites, spontaneous bacterial peritonitis, and hepatorenal syndrome in cirrhosis. J Hepatol. 2010;53(3):397-417.
3. Deutsch-Link S, Campbell PT, Shah ND. PRO: ascitic fluid cell count should be routinely sent with every therapeutic paracentesis to assess for spontaneous bacterial peritonitis. Clin Liver Dis (Hoboken). 2023;22(4):140-142.4. Long B, and Gottlieb M. Emergency medicine updates: spontaneous bacterial peritonitis. Am J Emerg Med. 2023;70:84-9.
5. Orman ES, Hayashi PH, Bataller R, Barritt AS 4th. Paracentesis is associated with reduced mortality in patients hospitalized with cirrhosis and ascites. Clin Gastroenterol Hepatol. 2014;12(3):496-503.e1..
6. Alhumaid S, Al Mutair A, Al Alawi Z, et al. Proton pump inhibitors use and risk of developing spontaneous bacterial peritonitis in cirrhotic patients: a systematic review and meta-analysis. Gut Pathog. 2021;13(1):17.7. Thalheimer U, Triantos CK, Samonakis DN, Patch D, Burroughs AK. Infection, coagulation, and variceal bleeding in cirrhosis. Gut. 2005;54(4):556-63.
8. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529-36. 9. McGuinness LA, Higgins JPT. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021;12(1):55-61.10. Abdel-Razik A, Mousa N, Abdel-Aziz M, et al. Mansoura simple scoring system for prediction of spontaneous bacterial peritonitis: lesson learnt. Eur J Gastroenterol Hepatol. 2019;31(8):1017-24.
11. Abdo G, Nir U, Rawajdey R, et al. A novel score-based approach by using routine laboratory tests for accurate diagnosis of spontaneous bacterial peritonitis (SBP) in cirrhotic patients. EJIFCC. 2023;34(4):297-304.
12. Huynh NC, Vo TD. Validation of a new simple scoring system to predict spontaneous bacterial peritonitis in patients with cirrhosis and ascites. BMC Gastroenterol. 2023;23(1):272.
13. Wehmeyer MH, Krohm S, Kastein F, Lohse AW, Lüth S. Prediction of spontaneous bacterial peritonitis in cirrhotic ascites by a simple scoring system. Scand J Gastroenterol. 2014;49(5):595-603.
14. Xiang S, Tan J, Tan C, et al. Establishment and validation of a non-invasive diagnostic nomogram to identify spontaneous bacterial peritonitis in patients with decompensated cirrhosis. Front Med (Lausanne). 2022;8:797363..
15. Würstle S, Hapfelmeier A, Karapetyan S, et al. A novel machine learning-based point-score model as a non-invasive decision-making tool for identifying infected ascites in patients with hydropic decompensated liver cirrhosis: a retrospective multicentre study. Antibiotics (Basel). 2022;11(11):1610.
16. Shi KQ, Fan YC, Ying L, et al. Risk stratification of spontaneous bacterial peritonitis in cirrhosis with ascites based on classification and regression tree analysis. Mol Biol Rep. 2012;39(5):6161-9.
17. Yin X, Qin E, Song R, et al. Diagnostic model for spontaneous bacterial peritonitis in cirrhotic patients with ascites: a multicenter cohort study. Eur J Gastroenterol Hepatol. 2024;36(11):1319-28.
18. Zhou Z, Lv H, Lv J, et al. Alterations of gut microbiota in cirrhotic patients with spontaneous bacterial peritonitis: A distinctive diagnostic feature. Front Cell Infect Microbiol. 2022;12:999418.
19. Hu Y, Chen R, Gao H, et al. Explainable machine learning model for predicting spontaneous bacterial peritonitis in cirrhotic patients with ascites. Sci Rep. 2021;11(1):21639.
20. Elsadek HM, Elhawari SA, Mokhtar A. A novel serum index for accurate diagnosis of spontaneous bacterial peritonitis in cirrhotic patients without other infections. 2020.
21. Wang H, Li Y, Zhang F, et al. Combination of PCT, sNFI and dCHC for the diagnosis of ascites infection in cirrhotic patients. BMC Infect Dis. 2018;18(1):389.
22. Obstein KL, Campbell MS, Reddy KR, Yang YX. Association between model for end-stage liver disease and spontaneous bacterial peritonitis. Am J Gastroenterol. 2007;102(12):2732-6.
23. Kamal A. Evaluation of a novel index that incorporates both neutrophil- lymphocyte ratio and c-reactive protein for the detection of spontaneous bacterial peritonitis. The Egyptian Journal of Hospital Medicine. 2024; 94: 950-6 .
24. Popoiag RE, Suceveanu AI, Suceveanu AP, et al. Predictors of spontaneous bacterial peritonitis in Romanian adults with liver cirrhosis: Focus on the neutrophil-to-lymphocyte ratio. Exp Ther Med. 2021;22(3):983.
25. Mousa N, Besheer T, Abdel-Razik A, et al. Can combined blood neutrophil to lymphocyte ratio and C-reactive protein be used for diagnosis of spontaneous bacterial peritonitis?. Br J Biomed Sci. 2018;75(2):71-5.
26. Silvey S, Patel N, Liu J, et al. A Machine learning algorithm avoids unnecessary paracentesis for exclusion of sbp in cirrhosis in resource-limited settings. Clin Gastroenterol Hepatol. 2024;22(12):2442-50.e8.27. Cai ZH, Fan CL, Zheng JF, et al. Measurement of serum procalcitonin levels for the early diagnosis of spontaneous bacterial peritonitis in patients with decompensated liver cirrhosis. BMC Infect Dis. 2015;15:55.28. Metwally K, Fouad T, Assem M, Abdelsameea E, Yousery M. Predictors of Spontaneous Bacterial Peritonitis in Patients with Cirrhotic Ascites. J Clin Transl Hepatol. 2018;6(4):372-6.29. Gayatri AA, Suryadharma IG, Purwadi N, Wibawa ID. The relationship between a model of end stage liver disease score (MELD score) and the occurrence of spontaneous bacterial peritonitis in liver cirrhotic patients. Acta Med Indones. 2007;39(2):75-8.
30. Kraja B, Sina M, Mone I, et al. Predictive value of the model of end-stage liver disease in cirrhotic patients with and without spontaneous bacterial peritonitis. Gastroenterol Res Pract. 2012;2012:539059.
31. Elghoneimy, R.I.E.S.M. Predictive value of neutrophil to lymphocyte ratio combined with c-reactive protein for diagnosis of spontaneous bacterial peritonitis among cirrhotic patients. The Egyptian Journal of Hospital Medicine. 2023; 91: 4380-6.
32. Abudeif A, Elbadry MI, Ahmed NM. Validation of the diagnostic accuracy of neutrophil to lymphocyte ratio (NLR) and mean platelet volume (MPV) in cirrhotic patients with spontaneous bacterial peritonitis. Egypt Liver Journal. 2023;13. (2023).
33. Du T, Li QP, Jiang GX, et al. Systematically analysis of decompensated cirrhotic patients with spontaneous bacterial peritonitis to identify diagnostic and prognostic indexes. BMC Infect Dis. 2023;23(1):786.
34. Pieri G, Agarwal B, Burroughs AK. C-reactive protein and bacterial infection in cirrhosis. Ann Gastroenterol. 2014;27(2):113-20.
35. Deeks JJ, Altman DG. Diagnostic tests 4: likelihood ratios. BMJ. 2004;329(7458):168-9.
36. Qin N, Yang F, Li A, et al. Alterations of the human gut microbiome in liver cirrhosis. Nature. 2014;513(7516):59-64.
37. Lv LX, Fang DQ, Shi D, et al. Alterations and correlations of the gut microbiome, metabolism and immunity in patients with primary biliary cirrhosis. Environ Microbiol. 2016;18(7):2272-86..
38. Wiesner R, Edwards E, Freeman R, et al. Model for end-stage liver disease (MELD) and allocation of donor livers. Gastroenterology. 2003;124(1):91-6.
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| Issue | In press | |
| Section | Systematic review / Meta-analysis | |
| Keywords | ||
| Cirrhosis Decision Tool Diagnosis Spontaneous Bacterial Peritonitis | ||
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How to Cite
1.
Garjani K, Vahidi E, Aghili M, Azimi Nezhad AA, Dadlani P, Mirfazaelian H. Decision tools for diagnosing spontaneous bacterial peritonitis: a systematic review and meta-analysis. Front Emerg Med. 2025;.
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