Epidemiological and clinical profile of amyotrophic lateral sclerosis in Ethiopia: a 5-year multicenter retrospective study.

Background: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease that results in progressive weakness of skeletal muscles including respiratory muscles. Epidemiological and clinical aspects of ALS are derived from a few world regions with very little representation of low- and middle-income countries. We therefore set out to determine the epidemiological and clinical phenotype of individuals with ALS in Ethiopia. Methods: Multicenter retrospective analysis was conducted using clinical records from ALS patients seen in Ethiopia at Tikur Anbessa Specialized Hospital and Yehuleshet specialty clinic between January 2016 and August 2021. The data collected included clinical characteristics, disease-related symptoms, a revised ALS functional rating scale, and medications. Results: Patients in Ethiopia had a younger age of onset with a mean age of disease onset of 51.9 years. 2.9% of patients had juvenile ALS, and the male-to-female ratio was almost 2:1. 4.9% had a positive family history of the disease. 68% of patients had spinal region involvement at onset, while 32% had bulbar region involvement at onset. Riluzole was used by 31% of ALS patients. 20.6% of patients had some respiratory symptoms, but none received a standard respiratory function assessment. 33.3% of patients were wheelchair-bound. Conclusion: In this retrospective study spanning 5 years, we examined the clinical phenotype of ALS in Ethiopian patients. Our findings suggest that most patients had clinically definite ALS with spinal region involvement. Further research, including genetic and epigenetic information, is necessary to understand the early onset of the disease in Ethiopia.

Development of Deep Learning Technique of Features for the Analysis of Clinical Images Integrated with CANN.

Computer tomography is an extensively used method for the detection of the disease in the subjects. Basically, computer-aided tomography depending on the artificial intelligence reveals its significance in smart health care monitoring system. Owing to its security and the private issue, analyzing the computed tomography dataset has become a tedious process. This study puts forward the convolutional autoencrypted deep learning neural network to assist unsupervised learning technique. By carrying out various experiments, our proposed method produces better results comparative to other traditional methods, which efficaciously solves the issues related to the artificial image description. Hence, the convolutional autoencoder is widely used in measuring the lumps in the bronchi. With the unsupervised machine learning, the extracted features are used for various applications.

Prevalence and burden of primary headache disorders among a local community in Addis Ababa, Ethiopia.

BACKGROUND: Headache disorders are the most common complaints worldwide. Migraine, tension type and cluster headaches account for majority of primary headaches and improvise a substantial burden on the individual, family or society at large. There is a scanty data on the prevalence of primary headaches in sub-Saharan Africa in general and Ethiopia in particular. Moreover there is no population based urban study in Ethiopia. The purpose of this study is to determine the prevalence and burden of primary headaches in local community in Addis Ababa, Ethiopia. METHODS: Cross-sectional sample survey was carried out in Addis Ketema sub city, Kebele 16/17/18 (local smallest administrative unit). Using systematic random sampling, data were collected by previously used headache questionnaire, over a period of 20 days. RESULTS: The study subjects were 231 of which 51.5% were males and 48.5% were females. The overall one year prevalence of primary headache disorders was 21.6% and that for migraine was 10%, migraine without aura 6.5% migraine with aura was 2.6% and probable migraine was 0.9%. The prevalence of tension type of headache was found to be 10.4%, frequent episodic tension type headache was 8.2% followed by infrequent tension type headache of 2.2%. The prevalence of cluster headache was 1.3%. The burden of primary headache disorders in terms of missing working, school or social activities was 68.0%. This was 78.3% for migraineurs and 66.7% for tension type headache. Majority 92.0% of primary headache cases were not using health services and 66.0% did not use any drug or medications during the acute attacks and none were using preventive therapy. CONCLUSION: Prevalence and burden of primary headache disorders was substantial in this community. Health service utilization of the community for headache treatment was poor.