Background: Acute appendicitis stands out as a frequently encountered surgical emergency. Despite decades of experience and research, the diagnosis remains a formidable challenge, particularly in young females experiencing acute abdominal pain, where the assessment requires consideration of a broader spectrum of potential causes. An overarching concern lies in the risk of over-treatment, leading to an escalation in unnecessary surgeries, known as the negative appendectomy rate (NAR). This elevated NAR is associated with postoperative complications, prolonged hospital stays, and avoidable healthcare expenditures. Despite international guidelines recommending the routine use of risk prediction models for patients with acute abdominal pain, reported NAR values have reached as high as 28.2% in females and 12.1% in males. Aim: The primary study aim is to identify optimal risk prediction models for acute RIF pain in Turkey. The secondary aims are to audit the normal appendicectomy rate, assess whether these scores have similar efficacy in immigrants, and demonstrate nationwide clinical trends to discuss possible improvements.
Study Type
OBSERVATIONAL
Enrollment
3,358
Gazi University
Ankara, Turkey (Türkiye)
Best classification performance among 4 appendicitis scoring systems (for Turkish population)
Data is used to calculate the four most commonly used adult risk prediction models: Alvarado, the Appendicitis Inflammatory Response (AIR), Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA), and Adult Appendicitis Score (AAS). Then, the performance of each scoring system will be compared with one another to find the best scoring system among them.
Time frame: During admission
Normal Appendicectomy Rate (NAR)
The NAR value is calculated as the percentage of patients with normal appendix histology who had undergone appendectomy. Patients with appendix pathology other than appendicitis (such as appendix tumor) were included in the denominator but not the numerator.
Time frame: All patients are followed up for 60 days, and data being utilized for NAR calculation is collected within that timeframe.
Best classification performance among 4 appendicitis scoring systems (for immigrant population)
Data is used to calculate the four most commonly used adult risk prediction models: Alvarado, the Appendicitis Inflammatory Response (AIR), Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA), and Adult Appendicitis Score (AAS). Then, the performance of each scoring system will be compared with one another to find the best scoring system among them.
Time frame: During admission
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