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The aim of this prospective study was to examine predictors of SBP in order to develop a noninvasive method to identify or exclude an episode of SBP, for starting early treatment with antibiotics, so decrease morbidity and mortality in these patients.
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Spontaneous bacterial peritonitis (SBP) is a bacterial infection of ascitic fluid without any intra-abdominal, surgically treatable cause.
SBP is the most common bacterial infection in patients with cirrhosis, with a mortality rate exceeding 90% in untreated cases. However, inpatient mortality has been reduced to about 20% with early diagnosis and effective treatment.
Delayed diagnosis increases in-hospital mortality; with each hour of delay in performing paracentesis for SBP diagnosis, mortality increases by approximately 3.3%.
A study conducted in the United States reported that paracentesis was performed within the first 24 hours of admission in only 66% of cirrhotic patients with ascites.
Another study noted that routine paracentesis cannot be performed in all patients with liver cirrhosis. Therefore, delaying diagnosis increases mortality, and it is necessary to find a non-invasive and accurate method for predicting SBP.
Important risk factors for the development of SBP in cirrhotic patients include a history of SBP, variceal hemorrhage, and the use of proton pump inhibitors Several laboratory parameters have been evaluated as early predictors of SBP, including C-reactive protein (CRP), neutrophil-to-lymphocyte ratio (NLR), mean platelet volume (MPV), platelet count, and serum creatinine level. However, the data remain inconsistent.
Recently, the Mansoura Scoring System was developed at Mansoura University and retrospectively applied to cirrhotic patients with ascites for early SBP diagnosis without waiting for peritoneal fluid analysis.
The Mansoura score includes four components: age, MPV, and NLR (1 point each), and CRP (2 points), yielding a total score of 0 to 5. SBP is diagnosed when the score is equal to or greater than 4.
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Amira M Abdelmawgod, Lecturer, Trop Med
Data sourced from clinicaltrials.gov
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