Can Gait Features Help in Differentiating Parkinson's Disease Medication States and Severity Levels? A Machine Learning Approach.

Parkinson's disease (PD) is one of the most prevalent neurological diseases, described by complex clinical phenotypes. The manifestations of PD include both motor and non-motor symptoms. We constituted an experimental protocol for the assessment of PD motor signs of lower extremities. Using a pair of sensor insoles, data were recorded from PD patients, Elderly and Adult groups. Assessment of PD patients has been performed by neurologists specialized in movement disorders using the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS)-Part III: Motor Examination, on both ON and OFF medication states. Using as a reference point the quantified metrics of MDS-UPDRS-Part III, severity levels were explored by classifying normal, mild, moderate, and severe levels of PD. Elaborating the recorded gait data, 18 temporal and spatial characteristics have been extracted. Subsequently, feature selection techniques were applied to reveal the dominant features to be used for four classification tasks. Specifically, for identifying relations between the spatial and temporal gait features on: PD and non-PD groups; PD, Elderly and Adults groups; PD and ON/OFF medication states; MDS-UPDRS: Part III and PD severity levels. AdaBoost, Extra Trees, and Random Forest classifiers, were trained and tested. Results showed a recognition accuracy of 88%, 73% and 81% for, the PD and non-PD groups, PD-related medication states, and PD severity levels relevant to MDS-UPDRS: Part III ratings, respectively.

The role of the sequential organ failure assessment score in evaluating the outcome in dogs with parvoviral enteritis.

SCIENTIFIC BACKGROUND: The aim of this prospective study was to assess whether the Sequential Organ Failure Assessment (SOFA) score could be indicative of outcome (survival to discharge) in dogs with parvoviral enteritis. METHODS: In 35 naturally infected dogs, the SOFA score and clinical score were calculated and the presence of systemic inflammatory response syndrome was verified on admission and during the first four days of hospitalization. RESULTS: 26 dogs survived, and out of the 9 non-survivors, 6 dogs had positive blood cultures. Mean SOFA scores and clinical scores between survivors and non-survivors and between septic and non-septic dogs on admission and on each hospitalization day were significantly different. Trends in SOFA score indicated that in non-survivors and septic dogs there was an increase in SOFA score during the first four days of hospitalization and a decrease occurred in survivors and non-septic dogs. The area under the curve (ROC curve analysis) for SOFA score predicting the outcome was 0.797 and predicting sepsis was 0.834. The best cut-off point of SOFA score for predicting the final outcome was 3.5 and the best cut-off of SOFA score for predicting sepsis was also 3.5. CONCLUSIONS: Either single values or trends in SOFA score can assist in suspecting sepsis and reaching prognosis in parvoviral enteritis.