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Published on: August 24, 2019
Identification of predictors for complicated acute appendicitis: A retrospective cohort study from a high-volume
Rui Li1, Xu Sun1, Zhiyuan Yu1
1School of Medicine, Nankai University, Tianjin, China; Medical School of Chinese PLA, Beijing, China; Department of General Surgery, The First Medical Center, Chinese PLA General Hospital, Beijing, China.
Background:
Acute appendicitis (AA) is the most prevalent cause of acute abdominal pain, with an incidence rate ranging from 96.5 to 100 per 100,000 adults. The rapid and accurate identification of the type and risk level of AA continues to pose a significant challenge. We aimed to develop a model for preoperative differentiation between complicated and uncomplicated AA.
Methods:
In this retrospective study, 1196 AA patients were selected. The preoperative and postoperative clinicopathological characteristics were analyzed retrospectively. Both univariate analysis and multivariate analyses were conducted using binary logistic regression to identify the predictive factor associated with complicated AA.
Results:
Among a total of 1196 AA patients, 465 (38.9 %) were identified as having complicated AA. Approximately 10 % of AA patients experienced postoperative complications. Multivariate logistic regression analysis indicated that several factors were associated with an increased risk of complicated AA, including male (P < 0.001, OR = 2.178), age (P < 0.001, OR = 1.028), days of abdominal pain before operation = 3 (P < 0.001, OR = 3.616), days of abdominal pain before operation = 4 (P < 0.001, OR = 7.528), temperature (P < 0.001, OR = 2.121), abdominal tension (P < 0.001, OR = 2.242), neutrophil (P < 0.001, OR = 1.053), fluid accumulates around the appendix (P = 0.002, OR = 2.010), appendiceal fecalith (P < 0.001, OR = 2.122), and the diameter of the appendix (P = 0.002, OR = 1.083).
Conclusions:
The results of this study significantly advance the understanding of preoperative differentiation between complicated and uncomplicated AA. The predictive nomogram offers a valuable tool for clinicians, enhancing decision-making and improving patient outcomes.
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