Ilias ThomasÖrebro University | oru · School of Medical Sciences
Ilias Thomas
PhD Micro-data analysis
About
15
Publications
2,084
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183
Citations
Citations since 2017
Publications
Publications (15)
Complex metabolic disruption is a crucial aspect of the pathophysiology of traumatic brain injury (TBI). Associations between this and systemic metabolism and their potential prognostic value are poorly understood. Here, we aimed to describe the serum metabolome (including lipidome) associated with acute TBI within 24 h post-injury, and its relatio...
Weather Normalized Models (WNMs) are modeling methods used for assessing air contaminants under a business-as-usual (BAU) assumption. Therefore, WNMs are used to assess the impact of many events on urban pollution. Recently, different approaches have been implemented to develop WNMs and quantify the lockdown effects of COVID-19 on air quality, incl...
Recent evidence suggests that patients with traumatic brain injuries (TBIs) have a distinct circulating metabolic profile. However, it is unclear if this metabolomic profile corresponds to changes in brain morphology as observed by magnetic resonance imaging (MRI). The aim of this study was to explore how circulating serum metabolites, following TB...
Aim:
To construct a Treatment Response Index from Multiple Sensors (TRIMS) for quantification of motor state in patients with Parkinson's disease (PD) during a single levodopa dose. Another aim was to compare TRIMS to sensor indexes derived from individual motor tasks.
Method:
Nineteen PD patients performed three motor tests including leg agilit...
Objective
Dosing schedules for oral levodopa in advanced stages of Parkinson’s disease (PD) require careful tailoring to fit the needs of each patient. This study proposes a dosing algorithm for oral administration of levodopa and evaluates its integration into a sensor-based dosing system (SBDS).
Materials and methods
In collaboration with two mo...
Introduction
A treatment response objective index (TRIS) was previously developed based on sensor data from pronation-supination tests. This study aimed to examine the performance of TRIS for medication effects in a new population sample with Parkinson's disease (PD) and its usefulness for constructing individual dose-response models.
Methods
Twen...
The objective of this study is to investigate the effects of feature selection methods on the performance of machine learning methods for quantifying motor symptoms of Parkinson’s disease (PD) patients. Different feature selection methods including step-wise regression, Lasso regression and Principal Component Analysis (PCA) were applied on 88 spat...
Objective
The aim of this retrospective study was to investigate if patients with PD, who are treated with levodopa‐carbidopa intestinal gel (LCIG), clinically worsen during the afternoon hours and if so, to evaluate whether this occurs in all LCIG‐treated patients or in a sub‐group of patients.
Methods
Three published studies were identified and...
Background and Objective
To achieve optimal effect with continuous infusion treatment in Parkinson’s disease (PD), the individual doses (morning dose and continuous infusion rate) are titrated by trained medical personnel. This study describes an algorithmic method to derive optimized dosing suggestions for infusion treatment of PD, by fitting indi...
Aim: This four-week open-label observational study describes the effect of introducing a microtablet dose dispenser and adjusting doses based on objective free-living motor symptom monitoring in individuals with Parkinson’s disease (PD).
Methods: 28 outpatients with PD on stable levodopa treatment with dose intervals of ≤ 4h had their daytime dose...
The goal of this study was to develop an algorithm that automatically quantifies motor states (off,on,dyskinesia) in Parkinson's disease (PD), based on accelerometry during a hand pronation-supination test. Clinician's ratings using the Treatment Response Scale (TRS), ranging from -3 (very Off) to 0 (On) to +3 (very dyskinetic), was used as target....
The objective of this study was to investigate the validity of an objective gait measure for assessment of different motor states of advanced Parkinson's disease (PD) patients. Seven PD patients performed a gait task up to 15 times while wearing sensors on their upper and lower limbs. Each task was performed at specific points during a test day, fo...
Projects
Projects (2)
Traumatic brain injury (TBI) is associated with a complex metabolic disruption that results in energy crisis, which is a consequence of multiple mechanisms including classical ischaemia, diffusion hypoxia, mitochondrial dysfunction and increased energy needs. The broad assumption has been that these metabolic changes are the consequence of metabolic failure. Our studies so far show that TBI associated with a specific metabolic profile, which is exacerbated proportionally to the severity of TBI. We hypothesize that these and potentially other metabolites reflect TBI pathophysiology and they may exhibit diagnostic potential in the full spectrum of TBI.
EU project CENTER-TBI currently prospectively collects clinical data including records from 5400 patients, files of imaging workup as well as blood samples from TBI patients from 60 sites of 18 countries. Our overall objective is to apply metabolic profiling of serum in the CENTER-TBI cohort to study the utility of the existing as well as to identify novel biomarkers of TBI which are also predictive of patient outcomes. These studies will be complemented by functional studies aiming to elucidate the underlying metabolic pathways in TBI. The project will be a major step forward in the disease detection and prognosis. We will combine innovative blood-based molecular biomarkers to conventional clinical biomarkers, not only to detect TBI, but also to detect and classify the underlying pathophysiological processes.
