PREDICTIVE MODEL FOR THE DETECTION OF INFLAMMATORY APPENDICITIS. A CROSS-SECTIONAL OBSERVATIONAL STUDY.
DOI:
https://doi.org/10.61164/hv81sn43Keywords:
Appendicitis, Histology, Radiology, Tomography, X-Ray ComputedAbstract
Introduction: The overuse and isolated interpretation of laboratory tests, such as white blood cell (WBC) count, are recognized sources of diagnostic errors and unnecessary interventions, driven by factors like defensive medicine. The evaluation of acute appendicitis exemplifies this challenge. Objective: This study aimed to assess the isolated utility of WBC count for differentiating inflammatory from non-inflammatory appendiceal disease, comparing it to a combined approach incorporating the Alvarado score and computed tomography (CT). Methods: A cross-sectional observational study was conducted with 140 patients who underwent appendectomy (125 inflammatory, 15 non-inflammatory). The diagnostic performance of WBC count, the Alvarado score, and the degree of periappendiceal fat stranding on CT was evaluated individually and in combination using ROC curves and multivariate logistic regression analysis, with histopathology as the gold standard. Results: Isolated WBC count did not differ significantly between groups (p=0.527), and its predictive capability was no better than chance (AUC=0.525). The Alvarado score also showed low accuracy (AUC=0.397). In contrast, the degree of fat stranding on CT demonstrated excellent performance (AUC=0.934). In the multivariate analysis, only fat stranding was a significant independent predictor (p<0.001), with the combined model achieving the highest accuracy (AUC=0.957). Conclusion: Isolated WBC count is insufficient to differentiate inflammatory appendiceal disease. Optimal diagnostic accuracy is achieved by an integrated model, in which CT findings, particularly periappendiceal fat stranding, are the most robust component.
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