Israel Medical Association Journal

Background: Acute mesenteric ischemia (AMI) is a medical condition with high levels of morbidity and mortality. However, most patients suspected of AMI will eventually have a different diagnosis. Nevertheless, these patients have a high risk for co-morbidities.

Objectives: To analyze patients with suspected AMI with an alternative final diagnosis, and to evaluate a machine learning algorithm for prognosis prediction in this population.

Methods: In a retrospective search, we retrieved patient charts of those who underwent computed tomography angiography (CTA) for suspected AMI between January 2012 and December 2015. Non-AMI patients were defined as patients with negative CTA and a final clinical diagnosis other than AMI. Correlation of past medical history, laboratory values, and mortality rates were evaluated. We evaluated gradient boosting (XGBoost) model for mortality prediction.

Results: The non-AMI group comprised 325 patients. The two most common groups of diseases included gastrointestinal (33%) and biliary-pancreatic diseases (27%). Mortality rate was 24.6% for the entire cohort. Medical history of chronic kidney disease (CKD) had higher risk for mortality (odds ratio 2.2). Laboratory studies revealed that lactate dehydrogenase (LDH) had the highest diagnostic ability for predicting mortality in the entire cohort (AUC 0.70). The gradient boosting model showed an area under the curve of 0.82 for predicting mortality.

Conclusions: Patients with suspected AMI with an alternative final diagnosis showed a 25% mortality rate. A past medical history of CKD and elevated LDH were associated with increased mortality. Non-linear machine learning algorithms can augment single variable inputs for predicting mortality.

Background: Magnetic resonance imaging (MRI) is the most sensitive imaging modality for the detection of sacroiliitis. Diagnosing sacroiliitis on MRI is not always straightforward and can be challenging in some cases.

Objectives: To evaluate the prevalence of alternative diagnoses suggested by MRI and characterize the MR appearance of the most common ones.

Methods: Consecutive MRI examinations of the sacroiliac joints (SIJ) performed between 2005 and 2012 were retrospectively evaluated for the presence of structural and active sacroiliitis findings according to the Assessment of SpondyloArthritis International Society guidelines. Alternative diagnoses, including degenerative changes, diffuse idiopathic skeletal hyperostosis (DISH), Osteitis condensans ilii (OCI), septic sacroiliitis/discitis, stress reaction as well as anatomic variants, were registered

Results: We evaluated 281 MRI examinations, 116 males, 165 females, average age 44 ± 15 years. Sacroiliitis was found in 71 examinations (25%) and alternative diagnoses were suggested in 87 (31%) (OCI 8.9%, anatomic variants 5.3%, septic sacroiliitis 5.3%, degenerative findings 4.3%, diffuse idiopathic skeletal hyperostosis [DISH] 1.5%, stress reaction 0.7%, tumor 0.3%). A normal examination was found in the remaining 123 examinations. Patients with alternative diagnoses were older than those with sacroiliitis (62 vs. 47 years of age, respectively, P > 0.05). Alternative pathologies in the SIJ were significantly more common in females (66) than males (21), P < 0.05.

Conclusions: A substantial proportion of patients with suspected sacroiliitis had normal SIJ while the rest were more commonly diagnosed with other pathologies. A referral by an experienced rheumatologist may improve the sensitivity and specificity of this important examination.