By using an accelerometer, a precise method, this study showed that KTRs are significantly more active in daily life than HD patients, and that daily physical activity increases with time since transplantation.

OBJECTIVES: To describe the changes in ventilator management over time in patients with neurologic disease at ICU admission and to estimate factors associated with 28-day hospital mortality. DESIGN: Secondary analysis of three prospective, observational, multicenter studies. SETTING: Cohort studies conducted in 2004, 2010, and 2016. PATIENTS: Adult patients who received mechanical ventilation for more than 12 hours. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Among the 20,929 patients enrolled, we included 4,152 (20%) mechanically ventilated patients due to different neurologic diseases. Hemorrhagic stroke and brain trauma were the most common pathologies associated with the need for mechanical ventilation. Although volume-cycled ventilation remained the preferred ventilation mode, there was a significant (p < 0.001) increment in the use of pressure support ventilation. The proportion of patients receiving a protective lung ventilation strategy was increased over time: 47% in 2004, 63% in 2010, and 65% in 2016 (p < 0.001), as well as the duration of protective ventilation strategies: 406 days per 1,000 mechanical ventilation days in 2004, 523 days per 1,000 mechanical ventilation days in 2010, and 585 days per 1,000 mechanical ventilation days in 2016 (p < 0.001). There were no differences in the length of stay in the ICU, mortality in the ICU, and mortality in hospital from 2004 to 2016. Independent risk factors for 28-day mortality were age greater than 75 years, Simplified Acute Physiology Score II greater than 50, the occurrence of organ dysfunction within first 48 hours after brain injury, and specific neurologic diseases such as hemorrhagic stroke, ischemic stroke, and brain trauma. CONCLUSIONS: More lung-protective ventilatory strategies have been implemented over years in neurologic patients with no effect on pulmonary complications or on survival. We found several prognostic factors on mortality such as advanced age, the severity of the disease, organ dysfunctions, and the etiology of neurologic disease.

Background Mechanical Ventilation (MV) is a complex and central treatment process in the care of critically ill patients. It influences acid–base balance and can also cause prognostically relevant biotrauma by generating forces and liberating reactive oxygen species, negatively affecting outcomes. In this work we evaluate the use of a Recurrent Neural Network (RNN) modelling to predict outcomes of mechanically ventilated patients, using standard mechanical ventilation parameters. Methods We performed our analysis on VENTILA dataset, an observational, prospective, international, multi-centre study, performed to investigate the effect of baseline characteristics and management changes over time on the all-cause mortality rate in mechanically ventilated patients in ICU. Our cohort includes 12,596 adult patients older than 18, associated with 12,755 distinct admissions in ICUs across 37 countries and receiving invasive and non-invasive mechanical ventilation. We carry out four different analysis. Initially we select typical mechanical ventilation parameters and evaluate the machine learning model on both, the overall cohort and a subgroup of patients admitted with respiratory disorders. Furthermore, we carry out sensitivity analysis to evaluate whether inclusion of variables related to the function of other organs, improve the predictive performance of the model for both the overall cohort as well as the subgroup of patients with respiratory disorders. Results Predictive performance of RNN-based model was higher with Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) of 0.72 (± 0.01) and Average Precision (AP) of 0.57 (± 0.01) in comparison to RF and LR for the overall patient dataset. Higher predictive performance was recorded in the subgroup of patients admitted with respiratory disorders with AUC of 0.75 (± 0.02) and AP of 0.65 (± 0.03). Inclusion of function of other organs further improved the performance to AUC of 0.79 (± 0.01) and AP 0.68 (± 0.02) for the overall patient dataset and AUC of 0.79 (± 0.01) and AP 0.72 (± 0.02) for the subgroup with respiratory disorders. Conclusion The RNN-based model demonstrated better performance than RF and LR in patients in mechanical ventilation and its subgroup admitted with respiratory disorders. Clinical studies are needed to evaluate whether it impacts decision-making and patient outcomes. Trial registration: NCT02731898 (https://clinicaltrials.gov/ct2/show/NCT02731898), prospectively registered on April 8, 2016.

BACKGROUND: Early exercise has been recommended in critically ill patients, but its impact on subject-ventilator interaction is still unclear. Therefore, the aim of this study was to evaluate the occurrence of subject-ventilator asynchrony during passive exercise in mechanically ventilated subjects. METHODS: This study included deeply sedated subjects who were under mechanical ventilation for < 72 h. Subjects were coupled to a cycle ergometer and maintained at rest for 5 min (baseline period). After this period, they started 20 min of passive exercise, followed by 10 min of rest (recovery period). The occurrence of asynchrony was monitored by the analysis of flow and airway pressure waveforms, registered throughout the protocol during the baseline, exercise, and recovery periods. Hemodynamic and respiratory parameters were registered at the end of each period. Finally, arterial blood gas analysis was performed twice, at the end of the baseline period and at the end of the recovery period. RESULTS: 8 subjects were enrolled (63.3 6 16.7 y old, 50% male). The asynchrony index increased during exercise (median 32.1% [interquartile range (IQR) 18.6-47.6%]), compared to baseline (median 6.6% [IQR 3.9-10.4%]), returning to initial levels during the recovery period (median 2.7% [IQR 0-12.2%]). The most frequent types of asynchrony were ineffective triggering (index of 11.8% [IQR 1.2-22.5%] during exercise, compared to 2.0% [IQR 1.4-4.4%] at baseline), and insufficient flow (index of 11.7% [IQR 4.7-19.3%] during exercise, compared to 2.0% [IQR 1.1 to 3.3%] at baseline). There were no significant changes in the hemodynamic and respiratory variables. CONCLUSIONS: Early cycle ergometer passive exercise in deeply sedated subjects can worsen subject-ventilator interaction, due to ineffective triggering and insufficient flow. Adjustments in the ventilatory parameters may be necessary to avoid asynchrony during exercise.

To evaluate the availability and characteristics of exercise training during hemodialysis in Brazil and to identify the reported barriers to exercise program implementation and maintenance. All dialysis units were assessed for eligibility using the database of the Brazilian Society of Nephrology. Each dialysis unit was contacted by telephone and the questions were administered. In dialysis units with exercise training, questions related to personnel involved, exercise components, and program delivery were included. Additionally, the barriers to exercise program implementation and maintenance were evaluated. This study included 261 dialysis units that responded to the survey. Forty‐one dialysis units reported exercise training during hemodialysis in Brazil (prevalence of 15.7%). We identified 66 physiotherapists and 10 exercise physiologists in dialysis units with exercise training. Resistance training was the most common program component (92.7%). Hypotension (90.5%) and muscle cramps (85.7%) were the most common adverse events reported. In dialysis units with exercise training, poor patients’ adherence to exercise was the most commonly reported barrier. The most prevalent barrier in dialysis units that tried or never tried to implement the exercise programs was a lack of resources. The number of dialysis units that have exercise training during hemodialysis in Brazil is low, and the most common program component is resistance training. A lack of resources was the most prevalent barrier in dialysis units that tried or never tried to implement the exercise programs.