Publications by authors named "Hrishikesh A Lokhande"
Background: Contrast-enhancing magnetic resonance imaging (MRI) lesions (CELs) indicate acute multiple sclerosis inflammation. Serum biomarkers, neurofilament light (sNfL), and glial fibrillary acidic protein (sGFAP) may increase in the presence of CELs, and indicate a need to perform MRI.
Objective: We assessed the accuracy of biomarkers to detect CELs.
Background: Early risk-stratification in multiple sclerosis (MS) may impact treatment decisions. Current predictive models have identified that clinical and imaging characteristics of aggressive disease are associated with worse long-term outcomes. Serum biomarkers, neurofilament (sNfL) and glial fibrillary acidic protein (sGFAP), reflect subclinical disease activity through separate pathological processes and may contribute to predictive models of clinical and MRI outcomes.
View Article and Find Full Text PDFThe bioinformatics analysis of miRNA is a complicated task with multiple operations and steps involved from processing of raw sequence data to finally identifying accurate microRNAs associated with the phenotypes of interest. A complete analysis process demands a high level of technical expertise in programming, statistics, and data management. The goal of this chapter is to reduce the burden of technical expertise and provide readers the opportunity to understand crucial steps involved in the analysis of miRNA sequencing data.
View Article and Find Full Text PDFYounger age at multiple sclerosis onset is associated with worse outcomes at age 50.
J Neurol Neurosurg Psychiatry
August 2022
Article Synopsis
- Older people tend to do worse with multiple sclerosis (MS) if they had symptoms start at a younger age.
- The study looked at 661 MS patients over 10 years and found that those with earlier symptoms had more severe problems at age 50, like worse disability scores and higher chances of job loss.
- It suggests doctors should pay attention to a patient's age when their MS started, as it can help predict how serious the disease might get in the future.
Objective: The objective of this study was to identify predictors in common between different clinical and magnetic resonance imaging (MRI) outcomes in multiple sclerosis (MS) by comparing predictive models.
Methods: We analyzed 704 patients from our center seen at MS onset, measuring 37 baseline demographic, clinical, treatment, and MRI predictors, and 10-year outcomes. Our primary aim was identifying predictors in common among clinical outcomes: aggressive MS, benign MS, and secondary-progressive (SP)MS.