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Predicting the risk of stroke in patients with late-onset epilepsy: A machine learning approach
CONCLUSION: The stroke risk in patients with epilepsy was relatively high and could be predicted based on comorbidities such as diabetes mellitus, hypertension, heart failure, and alcohol dependence. Knowing and addressing these factors may help reduce the risk of stroke in patients with epilepsy.PMID:34325155 | DOI:10.1016/j.yebeh.2021.108211
Source: Epilepsy and Behaviour - July 29, 2021 Category: Neurology Authors: Karel Kostev Tong Wu Yue Wang Kal Chaudhuri Christian Tanislav Source Type: research

Clinical code usage in UK general practice: a cohort study exploring 18 conditions over 14 years
Conclusions This is an under-reported research area and the findings suggest the codes’ usage diversity for most conditions remained overall stable throughout the study period. Generated mental health code lists can last for a long time unlike cardiometabolic conditions and cancer. Adopting more consistent and less diverse coding would help improve data quality in primary care. Future research is needed following the transfer to the Systematised Nomenclature of Medicine Clinical Terms (SNOMED CT) coding.
Source: BMJ Open - July 25, 2022 Category: General Medicine Authors: Zghebi, S. S., Reeves, D., Grigoroglou, C., McMillan, B., Ashcroft, D. M., Parisi, R., Kontopantelis, E. Tags: Open access, General practice / Family practice Source Type: research