Persistent symptoms and decreased health-related quality of life after symptomatic pediatric COVID-19: A prospective study in a Latin American tertiary hospital

OBJECTIVES: To prospectively evaluate demographic, anthropometric and health-related quality of life (HRQoL) in pediatric patients with laboratory-confirmed coronavirus disease 2019 (COVID-19) METHODS: This was a longitudinal observational study of surviving pediatric post-COVID-19 patients (n=53) and pediatric subjects without laboratory-confirmed COVID-19 included as controls (n=52) was performed. RESULTS: The median duration between COVID-19 diagnosis (n=53) and follow-up was 4.4 months (0.8-10.7). Twenty-three of 53 (43%) patients reported at least one persistent symptom at the longitudinal follow-up visit and 12/53 (23%) had long COVID-19, with at least one symptom lasting for >12 weeks. The most frequently reported symptoms at the longitudinal follow-up visit were headache (19%), severe recurrent headache (9%), tiredness (9%), dyspnea (8%), and concentration difficulty (4%). At the longitudinal follow-up visit, the frequencies of anemia (11% versus 0%, p=0.030), lymphopenia (42% versus 18%, p=0.020), C-reactive protein level of >30 mg/L (35% versus 0%, p=0.0001), and D-dimer level of >1000 ng/mL (43% versus 6%, p=0.0004) significantly reduced compared with baseline values. Chest X-ray abnormalities (11% versus 2%, p=0.178) and cardiac alterations on echocardiogram (33% versus 22%, p=0.462) were similar at both visits. Comparison of characteristic data between patients with COVID-19 at the longitudinal follow-up visit and controls showed similar age (p=0.962), proportion of male sex (p=0.907), ethnicity (p=0.566), family minimum monthly wage (p=0.664), body mass index (p=0.601), and pediatric pre-existing chronic conditions (p=1.000). The Pediatric Quality of Live Inventory 4.0 scores, median physical score (69 [0-100] versus 81 [34-100], p=0.012), and school score (60 [15-100] versus 70 [15-95], p=0.028) were significantly lower in pediatric patients with COVID-19 at the longitudinal follow-up visit than in controls. CONCLUSIONS: Pediatric patients with COVID-19 showed a longitudinal impact on HRQoL parameters, particularly in physical/school domains, reinforcing the need for a prospective multidisciplinary approach for these patients. These data highlight the importance of closer monitoring of children and adolescents by the clinical team after COVID-19

Health-related quality of life and functionality in primary caregiver of surviving pediatric COVID-19

ObjectivesTo prospectively assess health-related quality of life (HRQoL), global functionality, and disability in primary caregivers of surviving children and adolescents after COVID-19.MethodsA longitudinal observational study was carried out on primary caregivers of surviving pediatric post-COVID-19 patients (n = 51) and subjects without COVID-19 (n = 60). EuroQol five-dimension five-level questionnaire (EQ-5D-5L) and 12-question WHO Disability Assessment Schedule 2.0 (WHODAS 2.0) were answered for both groups. The univariate regression analysis was carried out using SPSS (v 20) and significance was established at 5%.ResultsThe median duration between COVID-19 diagnosis in children and adolescents and longitudinal follow-up visits was 4.4 months (0.8–10.7). The median age of children and adolescents caregivers with laboratory-confirmed COVID-19 was similar to primary caregivers of subjects without laboratory-confirmed COVID-19 [43.2 (31.6–60.9) vs. 41.5 (21.6–54.8) years, p = 0.08], as well as similar female sex (p = 1.00), level of schooling (p = 0.11), social assistance program (p = 0.28), family income/month U$ (p = 0.25) and the number of household’s members in the residence (p = 0.68). The frequency of slight to extreme problems (level ≥ 2) of the pain/discomfort domain according to EQ-5D-5L score was significantly higher in the former group [74% vs. 52.5%, p = 0.03, OR = 2.57 (1.14–5.96)]. The frequency of disability according to WHODAS 2.0 total score was similar to those without disability and unknown (p = 0.79); however, with a very high disability in both groups (72.5% and 78.3%). Further analysis of primary caregivers of children and adolescents with post-COVID-19 condition (PCC) [n = 12/51 (23%)] compared to those without PCC [n = 39/51(77%)] revealed no differences between demographic data, EQ-5D-5L and WHODAS 2.0 scores in both groups (p > 0.05).ConclusionWe longitudinally demonstrated that pain/discomfort were predominantly reported in approximately 75% of primary caregiver of COVID-19 patients, with high disability in approximately three-quarters of both caregiver groups. These data emphasized the prospective and systematic caregiver burden evaluation relevance of pediatric COVID-19

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART): Study protocol for a randomized controlled trial

Background: Acute respiratory distress syndrome (ARDS) is associated with high in-hospital mortality. Alveolar recruitment followed by ventilation at optimal titrated PEEP may reduce ventilator-induced lung injury and improve oxygenation in patients with ARDS, but the effects on mortality and other clinical outcomes remain unknown. This article reports the rationale, study design, and analysis plan of the Alveolar Recruitment for ARDS Trial (ART). Methods/Design: ART is a pragmatic, multicenter, randomized (concealed), controlled trial, which aims to determine if maximum stepwise alveolar recruitment associated with PEEP titration is able to increase 28-day survival in patients with ARDS compared to conventional treatment (ARDSNet strategy). We will enroll adult patients with ARDS of less than 72 h duration. The intervention group will receive an alveolar recruitment maneuver, with stepwise increases of PEEP achieving 45 cmH(2)O and peak pressure of 60 cmH2O, followed by ventilation with optimal PEEP titrated according to the static compliance of the respiratory system. In the control group, mechanical ventilation will follow a conventional protocol (ARDSNet). In both groups, we will use controlled volume mode with low tidal volumes (4 to 6 mL/kg of predicted body weight) and targeting plateau pressure <= 30 cmH2O. The primary outcome is 28-day survival, and the secondary outcomes are: length of ICU stay; length of hospital stay; pneumothorax requiring chest tube during first 7 days; barotrauma during first 7 days; mechanical ventilation-free days from days 1 to 28; ICU, in-hospital, and 6-month survival. ART is an event-guided trial planned to last until 520 events (deaths within 28 days) are observed. These events allow detection of a hazard ratio of 0.75, with 90% power and two-tailed type I error of 5%. All analysis will follow the intention-to-treat principle. Discussion: If the ART strategy with maximum recruitment and PEEP titration improves 28-day survival, this will represent a notable advance to the care of ARDS patients. Conversely, if the ART strategy is similar or inferior to the current evidence-based strategy (ARDSNet), this should also change current practice as many institutions routinely employ recruitment maneuvers and set PEEP levels according to some titration method.Hospital do Coracao (HCor) as part of the Program 'Hospitais de Excelencia a Servico do SUS (PROADI-SUS)'Brazilian Ministry of Healt

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

STATIC BALANCE MEASUREMENTS IN STABLE AND UNSTABLE CONDITIONS DO NOT DISCRIMINATE GROUPS OF YOUNG ADULTS ASSESSED BY THE FUNCTIONAL MOVEMENT SCREEN™ (FMS™)

BACKGROUND: The Functional Movement Screen™ (FMS™) has been the focus of recent research related to movement profiling and injury prediction. However, there is a paucity of studies examining the associations between physical performance tasks such as balance and the FMS™ screening system.PURPOSE: The purpose of this study was to compare measures of static balance in stable and unstable conditions between different groups divided by FMS™ scores. A secondary purpose was to discern if balance indices discriminate the groups divided by FMS™ scores.STUDY DESIGN: Cross-sectional study.METHODS: Fifty-seven physically active subjects (25 men and 32 women; mean age of 22.9 ± 3.1 yrs) participated. The outcome was unilateral stance balance indices, composed by: Anteroposterior Index; Medial-lateral Index, and Overall Balance Index in stable and unstable conditions, as provided by the Biodex balance platform. Subjects were dichotomized into two groups, according to a FMS™ cut-off score of 14: FMS1 (score &gt; 14) and FMS2 (score ≤ 14). The independent Students t-test was used to verify differences in balance indices between FMS1 and FMS2 groups. A discriminant analysis was applied in order to identify which of the balance indices would adequately discriminate the FMS™ groups.RESULTS: Comparisons between FMS1 and FMS2 groups in the stable and unstable conditions demonstrated a higher unstable Anteroposterior index for FMS2 (p=0.017). No significant differences were found for other comparisons (p&gt;0.05). The indices did not discriminate the FMS™ groups (p &gt; 0.05).CONCLUSIONS: The balance indices adopted in this study were not useful as a parameter for identification and discrimination of healthy subjects assessed by the FMS™.LEVEL OF EVIDENCE: 2c.</p

Static Balance Measurements in Stable and Unstable Conditions Do Not Discriminate Groups of Young Adults Assessed By the Functional Movement Screen™ (fms™)

BACKGROUND: The Functional Movement Screen™ (FMS™) has been the focus of recent research related to movement profiling and injury prediction. However, there is a paucity of studies examining the associations between physical performance tasks such as balance and the FMS™ screening system.PURPOSE: The purpose of this study was to compare measures of static balance in stable and unstable conditions between different groups divided by FMS™ scores. A secondary purpose was to discern if balance indices discriminate the groups divided by FMS™ scores.STUDY DESIGN: Cross-sectional study.METHODS: Fifty-seven physically active subjects (25 men and 32 women; mean age of 22.9 ± 3.1 yrs) participated. The outcome was unilateral stance balance indices, composed by: Anteroposterior Index; Medial-lateral Index, and Overall Balance Index in stable and unstable conditions, as provided by the Biodex balance platform. Subjects were dichotomized into two groups, according to a FMS™ cut-off score of 14: FMS1 (score &gt; 14) and FMS2 (score ≤ 14). The independent Students t-test was used to verify differences in balance indices between FMS1 and FMS2 groups. A discriminant analysis was applied in order to identify which of the balance indices would adequately discriminate the FMS™ groups.RESULTS: Comparisons between FMS1 and FMS2 groups in the stable and unstable conditions demonstrated a higher unstable Anteroposterior index for FMS2 (p=0.017). No significant differences were found for other comparisons (p&gt;0.05). The indices did not discriminate the FMS™ groups (p &gt; 0.05).CONCLUSIONS: The balance indices adopted in this study were not useful as a parameter for identification and discrimination of healthy subjects assessed by the FMS™.LEVEL OF EVIDENCE: 2c.</p

Assessment of a Hardware-Implemented Machine Learning Technique under Neutron Irradiation

International audienceHardware-implemented intelligent systems running autonomous functions and decisions are today becoming more and more ubiquitous in many fields of applications, demanding reliable operation even under harsh conditions as in nuclear power plants and avionics altitudes. Support vector machine (SVM) is a prominent machine learning solution to optimize hardware-implemented autonomous systems. This paper is the first to assess the operation of a field-programmable gate array (FPGA)-designed SVM architecture under radiation effects. A fault emulation campaign along with radiation test experiments with a 14-MeV neutron generator has been performed, and the results show that 27% of the neutron radiation-induced errors in the target SVM architecture provoked critical failures