Clinical, sociodemographic and environmental factors impact post-COVID-19 syndrome.

Background: Sociodemographic and environmental factors are associated with incidence, severity, and mortality of COVID-19. However, little is known about the role of such factors in persisting symptoms among recovering patients. We designed a cohort study of hospitalized COVID-19 survivors to describe persistent symptoms and identify factors associated with post-COVID-19 syndrome. Methods: We included patients hospitalized between March to August 2020 who were alive six months after hospitalization. We collected individual and clinical characteristics during hospitalization and at follow-up assessed ten symptoms with standardized scales, 19 yes/no symptoms, a functional status and a quality-of-life scale and performed four clinical tests. We examined individual exposure to greenspace and air pollution and considered neighbourhood´s population density and socioeconomic conditions as contextual factors in multilevel regression analysis. Results: We included 749 patients with a median follow-up of 200 (IQR = 185-235) days, and 618 (83%) had at least one of the ten symptoms measured with scales. Pain (41%), fatigue (38%) and posttraumatic stress disorder (35%) were the most frequent. COVID-19 severity, comorbidities, BMI, female sex, younger age, and low socioeconomic position were associated with different symptoms. Exposure to ambient air pollution was associated with higher dyspnoea and fatigue scores and lower functional status. Conclusions: We identified a high frequency of persistent symptoms among COVID-19 survivors that were associated with clinical, sociodemographic, and environmental variables. These findings indicate that most patients recovering from COVID-19 will need post-discharge care, and an additional burden to health care systems, especially in LMICs, should be expected.

Slow Versus Fast Robot-Assisted Locomotor Training After Severe Stroke: A Randomized Controlled Trial.

BACKGROUND AND PURPOSE: Robot-assisted locomotor training on a bodyweight-supported treadmill is a rehabilitation intervention that compels repetitive practice of gait movements. Standard treadmill speed may elicit rhythmic movements generated primarily by spinal circuits. Slower-than-standard treadmill speed may elicit discrete movements, which are more complex than rhythmic movements and involve cortical areas. OBJECTIVE: Compare effects of fast (i.e., rhythmic) versus slow (i.e., discrete) robot-assisted locomotor training on a bodyweight-supported treadmill in subjects with chronic, severe gait deficit after stroke. METHODS: Subjects (N = 18) were randomized to receive 30 sessions (5 d/wk) of either fast or slow robot-assisted locomotor training on a bodyweight-supported treadmill in an inpatient setting. Functional ambulation category, time up and go, 6-min walk test, 10-m walk test, Berg Balance Scale, and Fugl-Meyer Assessment were administered at baseline and postintervention. RESULTS: The slow group had statistically significant improvement on functional ambulation category (first quartile-third quartile, P = 0.004), 6-min walk test (95% confidence interval [CI] = 1.8 to 49.0, P = 0.040), Berg Balance Scale (95% CI = 7.4 to 14.8, P < 0.0001), time up and go (95% CI = -79.1 to 5.0, P < 0.0030), and Fugl-Meyer Assessment (95% CI = 24.1 to 45.1, P < 0.0001). The fast group had statistically significant improvement on Berg Balance Scale (95% CI = 1.5 to 10.5, P = 0.02). CONCLUSIONS: In initial stages of robot-assisted locomotor training on a bodyweight-supported treadmill after severe stroke, slow training targeting discrete movement may yield greater benefit than fast training.