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Goal: The experimental study of the stumble phenomena is essential to develop novel technological solutions to limit harmful effects in at-risk populations. A versatile platform to deliver realistic and unanticipated tripping perturbations, controllable in their strength and timing, would be beneficial for this field of study. Methods: We built a modular tripping-eliciting system based on multiple compliant trip blocks that deliver unanticipated tripping perturbations. The system was validated with a study with 9 healthy subjects. Results: The system delivered 33 out of 34 perturbations (a minimum of 3 per subject) during the desired gait phase, and 31 effectively induced a tripping event. The recovery strategies adopted after the perturbations were qualitatively consistent with the literature. The analysis of the inertial motion unit signals and the questionnaires suggests a limited adaptation to the perturbation throughout experiments. Conclusions: The platform succeeded in providing realistic trip perturbations, concurrently limiting subjects’ adaptation. The presence of multiple compliant obstacles, tunable regarding position and perturbation strength, represents a novelty in the field, allowing the study of stumbling phenomena caused by obstacles with different levels of sturdiness. The overall system is modular and can be easily adapted for different applications.

Abstract Good data quality is vital for personalising plans in rehabilitation. Machine learning (ML) improves prognostics but integrating it with Multiple Imputation (MImp) for dealing missingness is an unexplored field. This work aims to provide post-stroke ambulation prognosis, integrating MImp with ML, and identify the prognostic influential factors. Stroke survivors in intensive rehabilitation were enrolled. Data on demographics, events, clinical, physiotherapy, and psycho-social assessment were collected. An independent ambulation at discharge, using the Functional Ambulation Category scale, was the outcome. After handling missingness using MImp, ML models were optimised, cross-validated, and tested. Interpretability techniques analysed predictor contributions. Pre-MImp, the dataset included 54.1% women, 79.2% ischaemic patients, median age 80.0 (interquartile range: 15.0). Post-MImp, 368 non-ambulatory patients on 10 imputed datasets were used for training, 80 for testing. The random forest (the validation best-performing algorithm) obtained 75.5% aggregated balanced accuracy on the test set. The main predictors included modified Barthel index, Fugl-Meyer assessment/motricity index, short physical performance battery, age, Charlson comorbidity index/cumulative illness rating scale, and trunk control test. This is among the first studies applying ML, together with MImp, to predict ambulation recovery in post-stroke rehabilitation. This pipeline reliably exploits the potential of incomplete datasets for healthcare prognosis, identifying relevant predictors.

Reducing energy consumption during walking is a critical goal for transtibial amputees. The study presents the evaluation of a semi-active prosthesis with five transtibial amputees. The prosthesis has a low-power actuator integrated in parallel into an energy-storing-and-releasing foot. The actuator is controlled to compress the foot during the stance phase, supplementing the natural compression due to the user’s dynamic interaction with the ground, particularly during the ankle dorsiflexion phase, and to release the energy stored in the foot during the push-off phase, to enhance propulsion. The control strategy is adaptive to the user’s gait patterns and speed. The clinical protocol to evaluate the system included treadmill and overground walking tasks. The results showed that walking with the semi-active prosthesis reduced the Physiological Cost Index of transtibial amputees by up to 16% compared to walking using the subjects’ proprietary prosthesis. No significant alterations were observed in the spatiotemporal gait parameters of the participants, indicating the module’s compatibility with users’ natural walking patterns. These findings highlight the potential of the mechatronic actuator in effectively reducing energy expenditure during walking for transtibial amputees. The proposed prosthesis may bring a positive impact on the quality of life, mobility, and functional performance of individuals with transtibial amputation.

BackgroundIntensive treadmill training (TT) has been documented to improve gait parameters and functional independence in Parkinson’s Disease (PD), but the optimal intervention protocol and the criteria for tailoring the intervention to patients’ performances are lacking. TT may be integrated with augmented virtual reality (AVR), however, evidence of the effectiveness of this combined treatment is still limited. Moreover, prognostic biomarkers of rehabilitation, potentially useful to customize the treatment, are currently missing. The primary aim of this study is to compare the effects on gait performances of TT + AVR versus TT alone in II-III stage PD patients with gait disturbance. Secondary aims are to assess the effects on balance, gait parameters and other motor and non-motor symptoms, and patient’s satisfaction and adherence to the treatment. As an exploratory aim, the study attempts to identify biomarkers of neuroplasticity detecting changes in Neurofilament Light Chain concentration T0-T1 and to identify prognostic biomarkers associated to blood-derived Extracellular Vesicles.MethodsSingle-center, randomized controlled single-blind trial comparing TT + AVR vs. TT in II-III stage PD patients with gait disturbances. Assessment will be performed at baseline (T0), end of training (T1), 3 (T2) and 6 months (T3, phone interview) from T1. The primary outcome is difference in gait performance assessed with the Tinetti Performance-Oriented Mobility Assessment gait scale at T1. Secondary outcomes are differences in gait performance at T2, in balance and spatial–temporal gait parameters at T1 and T2, patients’ satisfaction and adherence. Changes in falls, functional mobility, functional autonomy, cognition, mood, and quality of life will be also assessed at different timepoints. The G*Power software was used to estimate a sample size of 20 subjects per group (power 0.95, α

In stroke survivors, persistent seizure activity could be associated with poor functional outcomes. At the same time, antiepileptic over-treatment could hamper post-stroke recovery. We systematically investigated the occurrence of seizures, the prevalence of epileptic discharges, and delta slow waves on electroencephalogram (EEG) and anti-seizure medication (ASM) management in relation to clinical manifestations and EEG abnormalities. This was a multi-centre prospective study involving two intensive rehabilitation units (IRUs). Clinical and EEG data were acquired at admission to the IRU, discharge (T1), and six-month follow-up (T2). A total of 163 patients underwent EEG recording upon admission to the IRU, while 149 were available for analysis at discharge from the IRU. Eighteen patients were treated with ASMs upon IRU admission despite only five of these patients having early seizures. Among the 145 patients not treated upon admission to the IRU, eight had late seizures, of which six were during the IRU stay, while two were after discharge from the IRU. During IRU stay, ASMs were generally discontinued in patients with no early seizures reported and were started in patients with late seizures. Among the 18 patients treated with ASMs at admission to the IRU, only six maintained the therapy also at T2. Our results suggest that post-acute inpatient rehabilitation is a proper setting to observe patients treated with ASMs after stroke and provide personalized post-stroke epilepsy management.

Abstract Background Rehabilitation treatments and services are essential for the recovery of post-stroke patients’ functions; however, the increasing number of available therapies and the lack of consensus among outcome measures compromises the possibility to determine an appropriate level of evidence. Machine learning techniques for prognostic applications offer accurate and interpretable predictions, supporting the clinical decision for personalised treatment. The aim of this study is to develop and cross-validate predictive models for the functional prognosis of patients, highlighting the contributions of each predictor. Methods A dataset of 278 post-stroke patients was used for the prediction of the class transition, obtained from the modified Barthel Index. Four classification algorithms were cross-validated and compared. On the best performing model on the validation set, an analysis of predictors contribution was conducted. Results The Random Forest obtained the best overall results on the accuracy (76.2%), balanced accuracy (74.3%), sensitivity (0.80), and specificity (0.68). The combination of all the classification results on the test set, by weighted voting, reached 80.2% accuracy. The predictors analysis applied on the Support Vector Machine, showed that a good trunk control and communication level, and the absence of bedsores retain the major contribution in the prediction of a good functional outcome. Conclusions Despite a more comprehensive assessment of the patients is needed, this work paves the way for the implementation of solutions for clinical decision support in the rehabilitation of post-stroke patients. Indeed, offering good prognostic accuracies for class transition and patient-wise view of the predictors contributions, it might help in a personalised optimisation of the patients’ rehabilitation path.

A domain-specific perspective to cognitive functioning in stroke patients may predict their cognitive recovery over time and target stroke rehabilitation intervention. However, data about domain-specific cognitive impairment after stroke are still scarce. This study prospectively investigated the domain-specific pattern of cognitive impairments, using the classification proposed by the Montreal Cognitive Assessment (MoCA), in a cohort of 49 stroke patients at admission (T0), discharge (T1), and six-month follow-up (T2) from subacute intensive rehabilitation. The predictive value of T0 cognitive domains cognitive impairment at T1 and T2 was also investigated. Patients’ cognitive functioning at T0, T1, and T2 was assessed through the MoCA domains for executive functioning, attention, language, visuospatial, orientation, and memory. Different evolutionary trends of cognitive domain impairments emerged across time-points. Patients’ impairments in all domains decreased from T0 to T1. Attention and executive impairments decreased from T0 to T2 (42.9% and 26.5% to 10.2% and 18.4%, respectively). Conversely, altered visuospatial, language, and orientation increased between T1 and T2 (16.3%, 36.7%, and 40.8%, respectively). Additionally, patients’ global cognitive functioning at T1 was predicted by the language and executive domains in a subacute phase (p = 0.031 and p = 0.001, respectively), while in the long term, only attention (p = 0.043) and executive (p = 0.019) domains intervened. Overall, these results confirm the importance of a domain-specific approach to target cognitive recovery across time in stroke patients.

Abstract Background Life expectancy has increased over the last century and a growing number of people is reaching age 90 years and over. However, data on nonagenarians’ health trends are scarce due to difficulties in investigating this specific population. This study aims to identify risk factors for one-year mortality in nonagenarians using data collected within the “Mugello Study”. Methods Complete information on sociodemographic data, cognitive and functional status, lifestyle, medical history, and drug use was collected from 433 nonagenarians, as well as information about survival after 1 year from the interview. Results The sample included 314 women (72.5%) and 119 men (27.5%) with a median age of 92 years (range 90-99 years). The mortality rate was 20.3% (88 deaths). After adjustment for age and sex, a significantly higher risk of dying within 12 months was observed in individuals with more severe cognitive impairment (HR = 5.011, p

Patients with Disorder of Consciousness (DoC) entering Intensive Rehabilitation Units after a severe Acquired Brain Injury have a highly variable evolution of the state of consciousness which is a complex aspect to predict. Besides clinical factors, electroencephalography has clearly shown its potential into the identification of prognostic biomarkers of consciousness recovery. In this retrospective study, with a dataset of 271 patients with DoC, we proposed three different Elastic-Net regressors trained on different datasets to predict the Coma Recovery Scale-Revised value at discharge based on data collected at admission. One dataset was completely EEG-based, one solely clinical data-based and the last was composed by the union of the two. Each model was optimized, validated and tested with a robust nested cross-validation pipeline. The best models resulted in a median absolute test error of 4.54 [IQR = 4.56], 3.39 [IQR = 4.36], 3.16 [IQR = 4.13] for respectively the EEG, clinical and hybrid model. Furthermore, the hybrid model for what concerns overcoming an unresponsive wakefulness state and exiting a DoC results in an AUC of 0.91 and 0.88 respectively. Small but useful improvements are added by the EEG dataset to the clinical model for what concerns overcoming an unresponsive wakefulness state. Data-driven techniques and namely, machine learning models are hereby shown to be capable of supporting the complex decision-making process the practitioners must face.

Abstract Objectives This study aims to evaluate the diagnostic performance of NIHSS extinction and inattention item, compared to the results of the Oxford Cognitive Screen (OCS) heart subtest. Additionally, the possible role of the NIHSS visual field subtest on the NIHSS extinction and inattention subtest performance is explored and discussed. Methods We analysed scores on NIHSS extinction and inattention subtest, NIHSS visual field subtest, and OCS heart subtest on a sample of 118 post-stroke patients. Results Compared to OCS heart subtest, the results on NIHSS extinction and inattention subtest showed an accuracy of 72.9% and a moderate agreement level (Cohen’s kappa = 0.404). Furthermore, a decrease in NIHSS accuracy detecting neglect (61.1%) was observed in patients with pathological scores in NIHSS visual field item. Conclusions Extreme caution is recommended for the diagnostic performance of extinction and inattention item of NIHSS. Signs of neglect may not be detected by NIHSS, and may be confused with visual field impairment. Trial registration This study refers to an observational study protocol submitted to ClinicalTrials.gov with identifier: NCT03968627 . The name of the registry is “Development of a National Protocol for Stroke Rehabilitation in a Multicenter Italian Institution” and the date of the registration is the 30th May 2019.

BackgroundStroke represents the second preventable cause of death after cardiovascular disease and the third global cause of disability. In countries where national registries of the clinical quality of stroke care have been established, the publication and sharing of the collected data have led to an improvement in the quality of care and survival of patients. However, information on rehabilitation processes and outcomes is often lacking, and predictors of functional outcomes remain poorly explored. This paper describes a multicenter study protocol to implement a Stroke rehabilitation Registry, mainly based on a multidimensional assessment proposed by the Italian Society of Physical and Rehabilitation Medicine (PMIC2020), in a pilot Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation, to provide a systematic assessment of processes and outcomes and develop data-driven prediction models of functional outcomes.MethodsAll patients with a diagnosis of ischemic or haemorrhagic stroke confirmed by clinical assessment, admitted to intensive rehabilitation units within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled. Measures will be taken at admission (T0), at discharge (T1), and at follow-up, 3 months (T2) and 6 months (T3) after the stroke. Assessment variables include anamnestic data, clinical and nursing complexity information and measures of body structures and function, activity and participation (PMIC2020), rehabilitation interventions, adverse events and discharge data. The modified Barthel Index will be our primary outcome. In addition to classical biostatistical analysis, learning algorithms will be cross-validated to achieve data-driven prognosis prediction models.ConclusionsThis study will test the feasibility of a stroke rehabilitation registry in the Italian health context and provide a systematic assessment of processes and outcomes for quality assessment and benchmarking. By the development of data-driven prediction models in stroke rehabilitation, this study will pave the way for the development of decision support tools for patient-oriented therapy planning and rehabilitation outcomes maximization.Clinical tial registrationThe registration on ClinicalTrials.gov is ongoing and under review. The identification number will be provided when the review process will be completed.

Abstract Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status.

Abstract Background and aims Reduced sleep quality is common in advanced age. Poor sleep quality is associated with adverse outcomes, chiefly cardiovascular, in young and middle-aged subjects, possibly because of its association with metabolic syndrome (MetS). However, the correlates of sleep quality in oldest populations are unknown. We evaluated the association of sleep quality with MetS in a cohort of subjects aged 90+. Methods and results We analysed data of 343 subjects aged 90+ living in the Mugello area (Tuscany, Italy). Quality of sleep was assessed using the Pittsburgh Sleep Quality Assessment Index (PSQI). Good quality of sleep was defined by a PSQI score .050). However, an increasing number of MetS components was associated with increasing probability of good quality of sleep (P for trend = .002), and of PSQI below the median (P for trend = .007). Generalized Additive Model analysis documented no smoothing function suggestive of nonlinear association between PSQI and MetS. Conclusion Our results confirm a high prevalence of poor sleep quality in oldest age; however, in these subjects, MetS seems to be associated with better sleep quality. Additional larger, dedicated studies are required to confirm our results, and, if so, to identify the subsystems involved and the potential therapeutic implications of such an association.

BackgroundDue to continuous advances in intensive care technology and neurosurgical procedures, the number of survivors from severe acquired brain injuries (sABIs) has increased considerably, raising several delicate ethical issues. The heterogeneity and complex nature of the neurological damage of sABIs make the detection of predictive factors of a better outcome very challenging. Identifying the profile of those patients with better prospects of recovery will facilitate clinical and family choices and allow to personalize rehabilitation. This paper describes a multicenter prospective study protocol, to investigate outcomes and baseline predictors or biomarkers of functional recovery, on a large Italian cohort of sABI survivors undergoing postacute rehabilitation.MethodsAll patients with a diagnosis of sABI admitted to four intensive rehabilitation units (IRUs) within 4 months from the acute event, aged above 18, and providing informed consent, will be enrolled. No additional exclusion criteria will be considered. Measures will be taken at admission (T0), at three (T1) and 6 months (T2) from T0, and follow-up at 12 and 24 months from onset, including clinical and functional data, neurophysiological results, and analysis of neurogenetic biomarkers.StatisticsAdvanced machine learning algorithms will be cross validated to achieve data-driven prediction models. To assess the clinical applicability of the solutions obtained, the prediction of recovery milestones will be compared to the evaluation of a multiprofessional, interdisciplinary rehabilitation team, performed within 2 weeks from admission.DiscussionIdentifying the profiles of patients with a favorable prognosis would allow customization of rehabilitation strategies, to provide accurate information to the caregivers and, possibly, to optimize rehabilitation outcomes.ConclusionsThe application and validation of machine learning algorithms on a comprehensive pool of clinical, genetic, and neurophysiological data can pave the way toward the implementation of tools in support of the clinical prognosis for the rehabilitation pathways of patients after sABI.

Background: Autonomic Nervous System (ANS) activity, as cardiac, respiratory and electrodermal activity, has been shown to provide specific information on different consciousness states. Respiration rates (RRs) are considered indicators of ANS activity and breathing patterns are currently already included in the evaluation of patients in critical care. Objective: The aim of this work was to derive a proxy of autonomic functions via the RR variability and compare its diagnostic capability with known neurophysiological biomarkers of consciousness. Methods: In a cohort of sub-acute patients with brain injury during post-acute rehabilitation, polygraphy (ECG, EEG) recordings were collected. The EEG was labeled via descriptors based on American Clinical Neurophysiology Society terminology and the respiration variability was extracted by computing the Approximate Entropy (ApEN) of the ECG-derived respiration signal. Competing logistic regressions were applied to evaluate the improvement in model performances introduced by the RR ApEN. Results: Higher RR complexity was significantly associated with higher consciousness levels and improved diagnostic models’ performances in contrast to the ones built with only electroencephalographic descriptors. Conclusions: Adding a quantitative, instrumentally based complexity measure of RR variability to multimodal consciousness assessment protocols may improve diagnostic accuracy based only on electroencephalographic descriptors. Overall, this study promotes the integration of biomarkers derived from the central and the autonomous nervous system for the most comprehensive diagnosis of consciousness in a rehabilitation setting.

Background: The Token Test (TT) is widely used to examine comprehension disorders in aphasic patients, but abilities other than language may affect a patient’s performance. This study aims to explore the correlation between the TT subtest performances and the performances in extra-linguistic cognitive areas in a cohort of patients from the Intensive Rehabilitation Post-Stroke (RIPS) study with a first, right hemisphere stroke and without aphasia, prospectively enrolled at admission to intensive inpatient post-acute rehabilitation. Methods: The patients were administered the TT (50-item version), the forward and backward digit span (DST), and the Montreal Cognitive Assessment (MoCA). Spearman’s partial correlations adjusted by age were used to evaluate the association between the number of errors in the TT and the other tests’ corrected scores. Results: Of the 37 patients enrolled in this study, 29.7% made 3–11 errors on the TT, 27.0% more than 11 errors, mostly in parts IV and V. The forward and backward digit span scores showed correlations with errors in part V of the TT (r = −0.408, p = 0.013; r = −0.307, p = 0.027). The errors in part IV of the TT presented a correlation with a forward digit span too (r = −0.394, p = 0.017). With respect to MoCA domains, executive functioning, and orientation were related to the TT part V errors (r = −0.468, p = 0.007; r = −0.499, p = 0.003). The orientation also correlated with the TT part III (r = −0.504, p = 0.002). Conclusion: Our findings show that the TT performances in patients with right hemisphere stroke and without aphasia are related to impairments in auditory–verbal span/auditory working memory mostly for TT scores on subpart V as measured by the DST and to executive function and orientation, as measured by the MoCA subtests.

Background: Sporadic CAA is recognized as a major cause of sICH and sABI. Even if intensive rehabilitation is recommended to maximize functional recovery after sICH, no data are available on whether CAA may affect rehabilitation outcomes. In this observational prospective study, to explore the impact of CAA on rehabilitation results, functional outcomes after intensive rehabilitation have been compared between patients affected by sICH with and without a diagnosis of CAA. Methods: All adults affected by sABI due to sICH and admitted to the IRU of IRCCS-Don-Gnocchi-Foundation were consecutively enrolled for 12 months. Demographic and clinical data were recorded upon admission and discharge. Results: Among 102 sICH patients (age: 66 (IQR = 16), 53% female), 13% were diagnosed as probable/possible-CAA. TPO and functional assessment were comparable upon admission, but CAA patients were significantly older (p = 0.001). After a comparable LOS, CAA patients presented higher care burden (ERBI: p = 0.025), poorer functional recovery (FIM: p = 0.02) and lower levels of global independence (GOSE > 4: p = 0.03). In multivariate analysis, CAA was significantly correlated with a lower FIM (p = 0.019) and a lower likelihood of reaching GOS-E > 4, (p = 0.041) at discharge, independently from age. Conclusions: CAA seems to be independently associated with poorer rehabilitation outcomes, suggesting the importance of improving knowledge about CAA to better predict rehabilitation outcomes.

Background. The current literature does not furnish clear data concerning the relationship between thyroid function, sedentary time and daily physical activity (PA) in older adults with euthyroid condition. The aim of this study was to investigate the association of serum Thyrotropin-Stimulating Hormone (TSH), free Triiodothyronine (fT3) and free Thyroxine (fT4) with sedentary time and PA in a cohort of nonagenarians. Methods. A total of 108 nonagenarians (92.8 ± 3.2 years), participating in the Mugello Study, and with complete data on thyroid function, sedentary time, PA and sleeping (objectively collected through a multisensory device), were considered for the analysis. Results. Mainly, TSH negatively correlated with time spent lying down, and positively correlated with METs. fT4 levels were negatively associated with mean daily metabolic equivalents (METs) and with low-intensity PA practice (LIPAT), and positively associated with lying down and sleeping time. Similar results have been shown in the female sample. Mainly, participants with high-normal (third tertile) versus low-normal TSH (first tertile) had higher moderate-intensity PA (MIPAT) (p = 0.03). In the female sample, first TSH tertile had higher METs (p = 0.010), LIPAT (p = 0.02), MIPAT (p = 0.01) and lower time lying down (p = 0.04) than third TSH tertile. Conclusion. High-normal serum TSH and low-normal fT4 are associated with higher levels and intensity of daily PA, together with higher MIPAT continuity, in the oldest-old.

Background: The complex nature of stroke sequelae, the heterogeneity in rehabilitation pathways, and the lack of validated prediction models of rehabilitation outcomes challenge stroke rehabilitation quality assessment and clinical research. An integrated care pathway (ICP), defining a reproducible rehabilitation assessment and process, may provide a structured frame within investigated outcomes and individual predictors of response to treatment, including neurophysiological and neurogenetic biomarkers. Predictors may differ for different interventions, suggesting clues to personalize and optimize rehabilitation. To date, a large representative Italian cohort study focusing on individual variability of response to an evidence-based ICP is lacking, and predictors of individual response to rehabilitation are largely unexplored. This paper describes a multicenter study protocol to prospectively investigate outcomes and predictors of response to an evidence-based ICP in a large Italian cohort of stroke survivors undergoing post-acute inpatient rehabilitation.Methods: All patients with diagnosis of ischemic or hemorrhagic stroke confirmed both by clinical and brain imaging evaluation, admitted to four intensive rehabilitation units (adopting the same stroke rehabilitation ICP) within 30 days from the acute event, aged 18+, and providing informed consent will be enrolled (expected sample: 270 patients). Measures will be taken at admission (T0), at discharge (T1), and at follow-up 6 months after a stroke (T2), including clinical data, nutritional, functional, neurological, and neuropsychological measures, electroencephalography and motor evoked potentials, and analysis of neurogenetic biomarkers.Statistics: In addition to classical multivariate logistic regression analysis, advanced machine learning algorithms will be cross-validated to achieve data-driven prognosis prediction models.Discussion: By identifying data-driven prognosis prediction models in stroke rehabilitation, this study might contribute to the development of patient-oriented therapy and to optimize rehabilitation outcomes.Clinical Trial Registration:ClinicalTrials.gov, NCT03968627. https://www.clinicaltrials.gov/ct2/show/NCT03968627?term=Cecchi&cond=Stroke&draw=2&rank=2.

Background: Patients with Mild Cognitive Impairment (MCI) and Vascular Cognitive Impairment (VCI) are at a high risk of progressing to dementia. Recent guidelines indicate the importance of promoting multidimensional and multi-domain interventions to prevent further decline. Due to its growing effectiveness, comparable to conventional face-to-face interventions, the use of technology is gaining relevance. Tele-rehabilitation systems have the potential to engage patients in multi-dimensional activity programs and to guarantee a low-cost continuum of care through remote control. A possible limitation of such programs is represented by the lack of familiarization with technology and computers in elderly people. The purpose of this study is to describe the feasibility, adherence, and appreciation of the GOAL Tele-R system, administered by a web-application through remote control in patients with MCI/VCI.Methods: Feasibility of the Tele-R system was evaluated by means of distribution of patients' attrition along the study phases, controlling for potential systematic bias in drop-out rates due to the technological device. Adherence was evaluated analyzing drop-out rates and indexes of carried out activities. Patients' appreciation was analyzed through ad hoc satisfaction questionnaire items.Results: Out of 86 approached patients, 25 (29%) were not enrolled, 30 (35%) dropped-out after randomization, and 31 (36%) completed the study (standard care group n = 12, the tele-R group n = 19). Compared to the tele-R group, rates of drop-outs resulted significantly higher for the standard care group (34 vs. 62%, respectively, p = 0.029). Taking into account baseline characteristics, females resulted in a statistically significant higher rate of drop-outs compared to males (66 vs. 27%, respectively, p = 0.003). Overall adherence to the proposed activities was 84% (85% for cognitive module and 83% for physical activity module). Concerning satisfaction, participants provided a good mean level of appreciation (3.7 ± 0.8, range 1–5), a positive feedback for usability, and a subjective perception of cognitive, emotional, and physical benefits due to the training.Conclusion: The GOAL Tele-R system seems a feasible technological rehabilitation program, reaching an acceptable level of adherence and appreciation in patients with an MCI/VCI condition.Clinical Trial Registration:www.ClinicalTrials.gov, ID: NCT03383549 (registration date: 26/dec/2017).

Background: Disorders of consciousness (DoCs) include unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Critical illness polyneuropathy and myopathy (CIPNM) is frequent in severe acquired brain injuries and impacts functional outcomes at discharge from the intensive rehabilitation unit (IRU). We investigated the prevalence of CIPNM in DoCs and its relationship with the consciousness assessment. Methods: Patients with DoCs were retrospectively selected from the database including patients admitted to the IRU of the IRCCS Don Gnocchi Foundation, Florence, from August 2012 to May 2020. Electroneurography/electromyography was performed at admission. Consciousness was assessed using the Coma Recovery Scale-Revised (CRS-R) at admission and discharge. Patients transitioning from a lower consciousness state to a higher one were classified as improved responsiveness (IR). Results: A total of 177 patients were included (UWS: 81 (45.8%); MCS: 96 (54.2%); 78 (44.1%) women; 67 years (IQR: 20). At admission, 108 (61.0%) patients had CIPNM. At discharge, 117 (66.1%) patients presented an IR. In the multivariate analysis, CRS-R at admission (p = 0.006; OR: 1.462) and CIPNM (p = 0.039; OR: −1.252) remained significantly associated with IR only for the UWS patients. Conclusions: CIPNM is frequent in DoCs and needs to be considered during the clinical consciousness assessment, especially in patients with UWS.

Abstract Background Despite progress in surgery and care, hip fracture (HF) remains a catastrophic event, burdened with high risk of mortality and disability. This study aims at identifying predictors of recovering ambulation after intensive inpatient rehabilitation within the Tuscany Region HF rehabilitation pathway. Methods All HF patients referred from acute care to the two Massa-Carrara Rehabilitation facilities January 2015–June 2017 were enrolled. Comorbidity Total Score (CIRS) defined high- or low-care setting referral. Recovery of ambulation, with or without aid, (assessed by SAHFE) was the primary outcome. Personal data, comorbidity, cognitive (MMSe) and pre-fracture function (mRANKIN) were recorded on admission. Outcomes included hospital readmission, length of stay (LOS) and home discharge. Urinary catheter, bedsores, disability (modified Barthel Index-mBI), communication disability (CDS), trunk control (TCT), pain (NRS), and ambulation were recorded (admission-discharge). Results Of 352 patients enrolled (age 83.9 ± 7.1; 80% women), 1 died and 6 were readmitted to acute-care hospital; 97% patients referred to high-care, and 64% referred to low-care, presented moderate-high comorbidity on admission. Median LOS was 22 days; 95% patients were discharged back home; daily functional gain (mBIscore/LOS) was 1.3 ± 0.7. Patients who recovered ambulation on discharge were 84%. Older age, higher comorbidity, bladder catheter, impaired trunk control, worse cognitive and functional status on admission, and pre-fracture disability were associated to poor outcome, but only higher comorbidity and impaired communication on admission predicted failure to recover ambulation on discharge. Conclusion In HF patients entitled to intensive inpatient rehabilitation, moderate-high comorbidity and impaired communication are frequent findings and predict rehabilitation failure.

Quantitative and qualitative running gait analysis allows the early identification and the longitudinal monitoring of gait abnormalities linked to running-related injuries. A promising calibration- and marker-less video sensor-based technology (i.e., Graal), recently validated for walking gait, may also offer a time- and cost-efficient alternative to the gold-standard methods for running. This study aim was to ascertain the validity of an improved version of Graal for quantitative and qualitative analysis of running. In 33 healthy recreational runners (mean age 41 years), treadmill running at self-selected submaximal speed was simultaneously evaluated by a validated photosensor system (i.e., Optogait—the reference methodology) and by the video analysis of a posterior 30-fps video of the runner through the optimized version of Graal. Graal is video analysis software that provides a spectral analysis of the brightness over time for each pixel of the video, in order to identify its frequency contents. The two main frequencies of variation of the pixel’s brightness (i.e., F1 and F2) correspond to the two most important frequencies of gait (i.e., stride frequency and cadence). The Optogait system recorded step length, cadence, and its variability (vCAD, a traditional index of gait quality). Graal provided a direct measurement of F2 (reflecting cadence), an indirect measure of step length, and two indexes of global gait quality (harmony and synchrony index). The correspondence between quantitative indexes (Cadence vs. F2 and step length vs. Graal step length) was tested via paired t-test, correlations, and Bland–Altman plots. The relationship between qualitative indexes (vCAD vs. Harmony and Synchrony Index) was investigated by correlation analysis. Cadence and step length were, respectively, not significantly different from and highly correlated with F2 (1.41 Hz ± 0.09 Hz vs. 1.42 Hz ± 0.08 Hz, p = 0.25, r2 = 0.81) and Graal step length (104.70 cm ± 013.27 cm vs. 107.56 cm ± 13.67 cm, p = 0.55, r2 = 0.98). Bland–Altman tests confirmed a non-significant bias and small imprecision between methods for both parameters. The vCAD was 1.84% ± 0.66%, and it was significantly correlated with neither the Harmony nor the Synchrony Index (0.21 ± 0.03, p = 0.92, r2 = 0.00038; 0.21 ± 0.96, p = 0.87, r2 = 0.00122). These findings confirm the validity of the optimized version of Graal for the measurement of quantitative indexes of gait. Hence, Graal constitutes an extremely time- and cost-efficient tool suitable for quantitative analysis of running. However, its validity for qualitative running gait analysis remains inconclusive and will require further evaluation in a wider range of absolute and relative running intensities in different individuals.

Comparison studies on recovery outcomes in ischemic (IS) and hemorrhagic strokes (HS) have yielded mixed results. In this retrospective observational study of consecutive IS and HS patients, we aimed at evaluating functional outcomes at discharge from an intensive rehabilitation hospital, comparing IS vs. HS, analyzing possible predictors. Modified Rankin Scale (mRS) at discharge was the main outcome. Out of the 229 patients included (mean age 72.9 ± 13.9 years, 48% males), 81 had HS (35%). Compared with IS (n = 148), HS patients were significantly younger (75 ± 12.5 vs. 68.8 ± 15.4 years, p = 0.002), required longer hospitalizations both in acute (23.9 ± 36.7 vs. 35.2 ± 29.9 days, p = 0.019) and rehabilitation hospitals (41.5 ± 31.8 vs. 77.2 ± 51.6 days, p = 0.001), and had more severe initial clinical deficit (mean number of neurological impairments: 2.0 ± 1.1 vs. 2.6 ± 1.4, p = 0.001) and mRS scores at admission (p = 0.046). At discharge, functional status change, expressed as mRS, was not significantly different between IS and HS (F = 0.01, p = 0.902), nor was the discharge destination (p = 0.428). Age and clinical severity were predictors of functional outcome in both stroke types. On admission in an intensive rehabilitation hospital, HS patients presented a worse functional and clinical status compared to IS. Despite this initial gap, the two stroke types showed an overlapped trajectory of functional recovery, with age and initial stroke severity as the main prognostic factors.

Gait abnormalities such as high stride and step frequency/cadence (SF—stride/second, CAD—step/second), stride variability (SV) and low harmony may increase the risk of injuries and be a sentinel of medical conditions. This research aims to present a new markerless video-based technology for quantitative and qualitative gait analysis. 86 healthy individuals (mead age 32 years) performed a 90 s test on treadmill at self-selected walking speed. We measured SF and CAD by a photoelectric sensors system; then, we calculated average ± standard deviation (SD) and within-subject coefficient of variation (CV) of SF as an index of SV. We also recorded a 60 fps video of the patient. With a custom-designed web-based video analysis software, we performed a spectral analysis of the brightness over time for each pixel of the image, that reinstituted the frequency contents of the videos. The two main frequency contents (F1 and F2) from this analysis should reflect the forcing/dominant variables, i.e., SF and CAD. Then, a harmony index (HI) was calculated, that should reflect the proportion of the pixels of the image that move consistently with F1 or its supraharmonics. The higher the HI value, the less variable the gait. The correspondence SF-F1 and CAD-F2 was evaluated with both paired t-Test and correlation and the relationship between SV and HI with correlation. SF and CAD were not significantly different from and highly correlated with F1 (0.893 ± 0.080 Hz vs. 0.895 ± 0.084 Hz, p < 0.001, r2 = 0.99) and F2 (1.787 ± 0.163 Hz vs. 1.791 ± 0.165 Hz, p < 0.001, r2 = 0.97). The SV was 1.84% ± 0.66% and it was significantly and moderately correlated with HI (0.082 ± 0.028, p < 0.001, r2 = 0.13). The innovative video-based technique of global, markerless gait analysis proposed in our study accurately identifies the main frequency contents and the variability of gait in healthy individuals, thus providing a time-efficient, low-cost means to quantitatively and qualitatively study human locomotion.

Background: People living with Mild Cognitive Impairment (MCI) and Vascular Cognitive Impairment (VCI) are persons who do not fulfill a diagnosis of dementia, but who have a high risk of progressing to a dementia disorder. The most recent guidelines to counteract cognitive decline in MCI/VCI subjects suggest a multidimensional and multi-domain interventions combining cognitive, physical, and social activities. The purpose of this study is to test an innovative service that provides a multi-dimensional tele-rehabilitation program through a user-friendly web application. The latter has been developed through a participatory design involving MCI specialists, patients, and their caregivers. Particularly, the proposed tele-rehabilitation program includes cognitive, physical, and caregiver-supported social activities. The goal is to promote and preserve an active life style and counteract cognitive decline in people living with MCI/VCI.Methods:The study is a randomized controlled trial. Sixty subjects will be randomly assigned to the experimental group, who will receive the tele-rehabilitation program, or the control group, who will not receive any treatment. The trial protocol comprises three steps of assessment for the experimental group: at the baseline (T_0), after tele-rehabilitation program (T_1) and at follow-up after 12-months (T_2). Differently, the control group will be assessed twice: at the baseline and at 12-months follow-up. Both the experimental and the control group will be assessed with a multidimensional evaluation battery, including cognitive functioning, behavioral, functional, and quality of life measures. The tele-rehabilitation program lasts 8 weeks and includes cognitive exercises 3 days a week, physical activities 2 days a week, and social activities once a week. In addition, group will be given an actigraph (GENEActiv, Activisinghts Ltd., Cambridgshire, UK) to track physical and sleep activity.Discussion:Results of this study will inform on the efficacy of the proposed tele-rehabilitation to prevent or delay further cognitive decline in MCI/VCI subjects. The expected outcome is to counteract cognitive decline and improve both physical functioning and quality of life.Ethics and Dissemination:The study is approved by the Local Ethics Committee and registered in https://clinicaltrials.gov (NCT03383549). Dissemination will include submission to a peer-reviewed journal, patients, and healthcare magazines and congress presentations.Trial Registration: ClinicalTrials.gov ID: NCT03383549 (registration date: 26/dec/2017)Trial Funding: Bando FAS Salute 2014 Regione ToscanaVersion Identifier: ver 5—16/11/2018

Near-death experiences (NDEs) have been defined as any conscious perceptual experience occurring in individuals pronounced clinically dead or who came very close to physical death. They are frequently reported by patients surviving a critical injury and, intriguingly, they show common features across different populations. The tool traditionally used to assess NDEs is the NDE Scale, which is available in the original English version. The aim of this study was to develop the Italian version of the NDE Scale and to assess its reliability in a specific clinical setting. A process of translation of the original scale was performed in different stages in order to obtain a fully comprehensible and accurate Italian translation. Later, the scale was administered to a convenience sample of patients who had experienced a condition of coma and were, at the time of assessment, fully conscious and able to provide information as requested by the scale. Inter-rater and test–retest reliability, assessed by the weighted Cohen’s kappa (Kw), were estimated. A convenience sample of 20 subjects [mean age ± standard deviation (SD) 51.6 ± 17.1, median time from injury 3.5 months, interquartile range (IQR) 2–10] was included in the study. Inter-rater [Kw 0.77 (95% CI 0.67–0.87)] and test–retest reliability [Kw 0.96 (95% CI 0.91–1.00)] showed good to excellent values for the total scores of the Italian NDE Scale and for subanalyses of each single cluster of the scale. An Italian Version of the NDE Scale is now available to investigate the frequency of NDE, the causes for NDE heterogeneity across different life-threatening conditions, and the possible neural mechanisms underlying NDE phenomenology.

Objective. Comparing global postural reeducation (GPR) to a standard physiotherapy treatment (PT) based on active exercises, stretching, and massaging for improving pain and function in chronic low back pain (CLBP) patients. Design. Prospective controlled study. Setting. Outpatient rehabilitation facility. Participants. Adult patients with diagnosis of nonspecific, chronic (>6 months) low back pain. Interventions. Both treatments consisted of 15 sessions of one hour each, twice a week including patient education. Measures. Roland Morris Disability Questionnaire to evaluate disability, and Numeric Analog Scale for pain. A score change >30% was considered clinically significant. Past treatments, use of medications, smoking habits, height, weight, profession, and physical activity were also recorded on baseline, on discharge, and 1 year after discharge (resp., T0, T1, and T2). Results. At T0 103 patients with cLBP (51 cases and 52 controls) were recruited. The treatment (T1) has been completed by 79 (T1) of which 60 then carried out the 1-year follow-up (T2). Both GPR and PT at T1 were associated with a significant statistical and clinical improvement in pain and function, compared to T0. At T2, only pain in GPR still registered a statistically significant improvement.