BACKGROUND: To investigate the factors predicting acute appendicitis (AAp) and perforated AAp in patients who underwent surgery with a preliminary diagnosis of AAp. METHODS: Between May 2009 and December 2018, 1316 patients underwent appendectomy with a presumed diagnosis of AAp. To investigate the factors predicting AAp, patients were divided into two groups considering the histopathological presence of inflammatory changes in the appendix: AAp positive (AAp group; n=1043) and AAp negative (Non-AAp group; n=273). Also, to investigate the factors predicting appendiceal perforation, patients with AAp were divided into two groups considering the presence of perforation: non-perforated AAp (n=850) and perforated AAp (n=193). ROC curve analysis was used to identify optimum cut-off values of quantitative variables. The groups were compared using univariate analysis methods and parameters with a p≤ 0.20 were taken into a multivariate logistic regression model. RESULTS: Multivariate analysis method related to factors predicting AAp showed that gender (male; p=0.034; OR=1.4), WBC (≥10.900; p=0.022; OR=1.5), MPV (≥29.1; p=0.006; OR=1.6), TBil (≥0.61; p=0.034; OR=1.4), CRP (≥0.725; p=0.002; OR=1.7), NLR (≥5.13; p=0.034; OR=1.5), PNR (<24.04; p=0.001; OR=1.9) and US findings (AAp+; p<0.001; OR=2.9) were independent factors for predicting AAp. Multivariate analysis method related to factors predicting appendiceal perforation showed that age (≥32 years; p<0.001; OR=2.5), TBil (≥0.67; p=0.046; OR=1.5), CRP (≥3.75; p<0.001; OR=3.0) and NLR (≥5.69; p=0.006; OR=1.8) were independent factors for predicting perforated AAp. CONCLUSION: We believe that predicting both AAp and perforation will help the clinician evaluate patients who applied to the emergency unit with presumed diagnosis AAp. This approach will also contribute to reducing the negative appendectomy and perforation rates.
BACKGROUND: To investigate the factors predicting acute appendicitis (AAp) and perforated AAp in patients who underwent surgery with a preliminary diagnosis of AAp. METHODS: Between May 2009 and December 2018, 1316 patients underwent appendectomy with a presumed diagnosis of AAp. To investigate the factors predicting AAp, patients were divided into two groups considering the histopathological presence of inflammatory changes in the appendix: AAp positive (AAp group; n=1043) and AAp negative (Non-AAp group; n=273). Also, to investigate the factors predicting appendiceal perforation, patients with AAp were divided into two groups considering the presence of perforation: non-perforated AAp (n=850) and perforated AAp (n=193). ROC curve analysis was used to identify optimum cut-off values of quantitative variables. The groups were compared using univariate analysis methods and parameters with a p≤ 0.20 were taken into a multivariate logistic regression model. RESULTS: Multivariate analysis method related to factors predicting AAp showed that gender (male; p=0.034; OR=1.4), WBC (≥10.900; p=0.022; OR=1.5), MPV (≥29.1; p=0.006; OR=1.6), TBil (≥0.61; p=0.034; OR=1.4), CRP (≥0.725; p=0.002; OR=1.7), NLR (≥5.13; p=0.034; OR=1.5), PNR (<24.04; p=0.001; OR=1.9) and US findings (AAp+; p<0.001; OR=2.9) were independent factors for predicting AAp. Multivariate analysis method related to factors predicting appendiceal perforation showed that age (≥32 years; p<0.001; OR=2.5), TBil (≥0.67; p=0.046; OR=1.5), CRP (≥3.75; p<0.001; OR=3.0) and NLR (≥5.69; p=0.006; OR=1.8) were independent factors for predicting perforated AAp. CONCLUSION: We believe that predicting both AAp and perforation will help the clinician evaluate patients who applied to the emergency unit with presumed diagnosis AAp. This approach will also contribute to reducing the negative appendectomy and perforation rates.