The efficacy of functional gait training in children and young adults with cerebral palsy: a systematic review and meta-analysis.

AIM: The aim of this systematic review was to investigate the effects of functional gait training on walking ability in children and young adults with cerebral palsy (CP). METHOD: The review was conducted using standardized methodology, searching four electronic databases (PubMed, Embase, CINAHL, Web of Science) for relevant literature published between January 1980 and January 2017. Included studies involved training with a focus on actively practising the task of walking as an intervention while reporting outcome measures relating to walking ability. RESULTS: Forty-one studies were identified, with 11 randomized controlled trials included. There is strong evidence that functional gait training results in clinically important benefits for children and young adults with CP, with a therapeutic goal of improved walking speed. Functional gait training was found to have a moderate positive effect on walking speed over standard physical therapy (effect size 0.79, p=0.04). Further, there is weaker yet relatively consistent evidence that functional gait training can also benefit walking endurance and gait-related gross motor function. INTERPRETATION: There is promising evidence that functional gait training is a safe, feasible, and effective intervention to target improved walking ability in children and young adults with CP. The addition of virtual reality and biofeedback can increase patient engagement and magnify effects. WHAT THIS PAPER ADDS: Functional gait training is a safe, feasible, and effective intervention to improve walking ability. Functional gait training shows larger positive effects on walking speed than standard physical therapy. Walking endurance and gait-related gross motor function can also benefit from functional gait training. Addition of virtual reality and biofeedback shows promise to increase engagement and improve outcomes.

Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study.

The COVID-19 pandemic has created an urgent need for robust, scalable monitoring tools supporting stratification of high-risk patients. This research aims to develop and validate prediction models, using the UK Biobank, to estimate COVID-19 mortality risk in confirmed cases. From the 11,245 participants testing positive for COVID-19, we develop a data-driven random forest classification model with excellent performance (AUC: 0.91), using baseline characteristics, pre-existing conditions, symptoms, and vital signs, such that the score could dynamically assess mortality risk with disease deterioration. We also identify several significant novel predictors of COVID-19 mortality with equivalent or greater predictive value than established high-risk comorbidities, such as detailed anthropometrics and prior acute kidney failure, urinary tract infection, and pneumonias. The model design and feature selection enables utility in outpatient settings. Possible applications include supporting individual-level risk profiling and monitoring disease progression across patients with COVID-19 at-scale, especially in hospital-at-home settings.

Muscle Synergies in Response to Biofeedback-Driven Gait Adaptations in Children With Cerebral Palsy.

BACKGROUND: Children with cerebral palsy (CP) often show impaired selective motor control (SMC) that induces limitations in motor function. Children with CP can improve aspects of pathological gait in an immediate response to visual biofeedback. It is not known, however, how these gait adaptations are achieved at the neural level, nor do we know the extent of SMC plasticity in CP. AIM: Investigate the underlying SMC and changes that may occur when gait is adapted with biofeedback. METHODS: Twenty-three ambulatory children with CP and related (hereditary) forms of spastic paresis (Aged: 10.4 ± 3.1, 6-16 years, M: 16/F: 9) were challenged with real-time biofeedback to improve step length, knee extension, and ankle power while walking on an instrumented treadmill in a virtual reality environment. The electromyograms of eight superficial muscles of the leg were analyzed and synergies were further decomposed using non-negative matrix factorization (NNMF) using 1 to 5 synergies, to quantify SMC. Total variance accounted for (tVAF) was used as a measure of synergy complexity. An imposed four synergy solution was investigated further to compare similarity in weightings and timing patterns of matched paired synergies between baseline and biofeedback trials. RESULTS: Despite changes in walking pattern, changes in synergies were limited. The number of synergies required to explain at least 90% of muscle activation increased significantly, however, the change in measures of tVAF1 from baseline (0.75 ± 0.08) were less than ±2% between trials. In addition, within-subject similarity of synergies to baseline walking was high (>0.8) across all biofeedback trials. CONCLUSION: These results suggest that while gait may be adapted in an immediate response, SMC as quantified by synergy analysis is perhaps more rigidly impaired in CP. Subtle changes in synergies were identified; however, it is questionable if these are clinically meaningful at the level of an individual. Adaptations may be limited in the short term, and further investigation is essential to establish if long term training using biofeedback leads to adapted SMC.

Real-time feedback to improve gait in children with cerebral palsy.

Real-time feedback may be useful for enhancing information gained from clinical gait analysis of children with cerebral palsy (CP). It may also be effective in functional gait training, however, it is not known if children with CP can adapt gait in response to real-time feedback of kinematic parameters. Sixteen children with cerebral palsy (age 6-16; GMFCS I-III), walking with a flexed-knee gait pattern, walked on an instrumented treadmill with virtual reality in three conditions: regular walking without feedback (NF), feedback on hip angle (FH) and feedback on knee angle (FK). Clinically relevant gait parameters were calculated and the gait profile score (GPS) was used as a measure of overall gait changes between conditions. All children, except one, were able to improve hip and/or knee extension during gait in response to feedback, with nine achieving a clinically relevant improvement. Peak hip extension improved significantly by 5.1±5.9° (NF: 8.9±12.8°, FH: 3.8±10.4°, p=0.01). Peak knee extension improved significantly by 7.7±7.1° (NF: 22.2±12.0°, FK: 14.5±12.7°, p<0.01). GPS did not change between conditions due to increased deviations in other gait parameters. Responders to feedback were shown to have worse initial gait as measured by GPS (p=0.005) and functional selectivity score (p=0.049). In conclusion, ambulatory children with CP show adaptability in gait and are able to respond to real-time feedback, resulting in significant and clinically relevant improvements in peak hip and knee extension. These findings show the potential of real-time feedback as a tool for functional gait training and advanced gait analysis in CP.