BACKGROUND: Acute appendicitis is the most common surgical condition presented in emergency departments worldwide. Clinical scoring systems, such as the Alvarado and modified Alvarado scoring systems, were developed with the goal of reducing the negative appendectomy rate to 5%–10%. The Raja Isteri Pengiran Anak Saleha Appendicitis (RIPASA) scoring system was established in 2008 specifically for Asian populations. The aim of this study was to compare the modified Alvarado with the RIPASA scoring system in Kuwait population. METHODS: This study included 180 patients who underwent appendectomies and were documented as having "acute appendicitis" or "abdominal pain" in the operating theatre logbook (unit B) from November 2014 to March 2016. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, predicted negative appendectomy and receiver operating characteristic (ROC) curve of the modified Alvarado and RIPASA scoring systems were derived using SPSS statistical software. RESULTS: A total of 136 patients were included in this study according to our criteria. The cut-off threshold point of the modified Alvarado score was set at 7.0, which yielded a sensitivity of 82.8% and a specificity of 56%. The PPV was 89.3% and the NPV was 42.4%. The cut-off threshold point of the RIPASA score was set at 7.5, which yielded a 94.5% sensitivity and an 88% specificity. The PPV was 97.2% and the NPV was 78.5%. The predicted negative appendectomy rates were 10.7% and 2.2% for the modified Alvarado and RIPASA scoring systems, respectively. The negative appendectomy rate decreased significantly, from 18.4% to 10.7% for the modified Alvarado, and to 2.2% for the RIPASA scoring system, which was a significant difference (P<0.001) for both scoring systems. CONCLUSION: Based on the results of this study, the RIPASA score is a simple scoring system with better sensitivity and specificity than the modified Alvarado scoring system in Asian populations. It consists of 14 clinical parameters that can be obtained from a good patient history, clinical examination and laboratory investigations. The RIPASA scoring system is more accurate and specific than the modified Alvarado scoring system for Kuwait population.

Diffusion Tensor Imaging (DTI) is an advanced magnetic resonance imaging (MRI) technique. DTI provides quantitative information at microstuructural level via its parameter indices e.g. mean diffusivity (MD) and fractional anisotropy (FA). It also allows for visualization of neuron fibres through a specific technique called fibre tractography. Leukoaraiosis is an asymptomatic pathological condition of the brain white matter which appears hyperintense on T2-weighted MRI images. Association of leukoaraiosis with age and ischemic heart disease have been previously reported. The objective of this study is to compare MD and FA values measured in various areas of the brain white matter (WM), grey matter (GM), and cerebrospinal fluid (CSF) in humans using DTI. 30 subjects with leukoaraiosis and 12 subjects without leukoaraiosis underwent brain scan using GE 1.5 Tesla MRI system. Region of interests were located in the CSF and various WM and GM areas. Comparison of MD and FA values was made between leukoaraiosis tissue (LA) and normal appearing brain tissue (NABT) measured within the same leukoaraiosis subjects, and with normal brain tissue (CONTROL) of healthy control subjects. LA demonstrated a significantly higher MD and lower FA compared to NABT and CONTROL in frontal and occipital WM areas. No differences were observed in MD in any brain region between NABT and CONTROL. Whereas no differences were observed in FA between NABT and CONTROL except in the occipital WM. Fibre tractography showed 31.7% to 56.1% lesser fibre tracts in LA subjects compared to CONTROL subjects. Significant differences were found between pathological tissue compared to normal appearing brain tissue and normal brain tissue. Fibre tractography exposed reduced number of neural fibres in leukoaraiosis subjects as compared to normal subjects.
Diffusion Tensor Imaging