Correlation Between Systemic Inflammatory Physiology and Severity of Appendicitis in Patients Undergoing Appendectomy
Inflammatory Physiology as a Predictor of Appendicitis Severity
DOI:
https://doi.org/10.69750/dmls.03.01.0184Keywords:
appendicitis, systemic inflammation, CRP, procalcitonin, NLR, PLR, leukocytosis, severity, appendectomy, histopathologyAbstract
Background: Appendicitis is a common surgical emergency that has a spectrum of mild cases of inflammation, gangrene, and perforation. Systemic inflammatory markers could play a significant role in predicting disease severity before surgery.
Objectives: To determine the relationship between the healthcare objective of appraising systemic inflammatory physiology and the severity of appendicitis in patients who have undergone appendectomy.
Methods: A cross-sectional study was conducted on 89 patients who underwent appendectomy. Preoperative laboratory investigations, including TLC, neutrophil count, CRP, ESR, PCT, NLR, and PLR—along with clinical examination and imaging findings were documented. The severity of appendicitis was categorized intraoperatively and histopathologically into simple, suppurative, gangrenous, and perforated types. Associations between inflammatory biomarkers and disease severity were assessed using statistical comparisons and correlation analyses.
Results: The majority of patients (64%) reported within 24-48 hours of symptom onset. The distribution of severity of appendicitis was straightforward (36.0%), suppurative (30.3%), gangrenous (20.2%), and perforated (13.5%). CRP, PCT, NLR, PLR, and TLC demonstrated a progressive tendency in increasing by the severity. A correlation was greater with CRP (r = 0.71, p < 0.001) than with PCT (r = 0.66), NLR (r = 0.62), and TLC (r = 0.54).
Conclusion: CRP, PCT, and NLR are systemic inflammatory biomarkers with strong associative relationships to the severity of appendicitis and can be useful predictors of complicated disease. By introducing these parameters into clinical assessment, early detection, risk assessments, and operations could become better and more notable in resource-limited environments.
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