Mathiasenwollesen6090

The 100% response rate confirmed ease of use. There were no redundant items. There were strong correlations between the 12-item and longer versions (>0.9). The HOOS-12 and KOOS-12 scores were reliable and valid 1) there were no ceiling or floor effects for pre- or postoperative KOOS-12 scores, although a ceiling effect was found for HOOS-12 postoperatively (20% of patients having maximum scores of 100); 2) internal consistency was confirmed, with Cronbach alpha>0.8; 3) external consistency between Oxford-12 and HOOS-12/KOOS-12 was excellent, with Pearson correlation coefficient>0.8. Sensitivity to pre-/postoperative change was confirmed, with effect size>0.8.

The present study confirmed the usefulness of this new 12-item form for HOOS and KOOS. Properties were identical between the French- and English-language versions, authorising everyday use of these simpler versions.

IV; prospective study without control group.

IV; prospective study without control group.

Preliminary evidence suggests that the COVID-19 pandemic has had a negative impact on children's mental health. Given these problems can have significant impacts throughout the lifespan, preventing the negative repercussions of COVID-19 on children's mental health is essential. Philosophy for children (P4C) and mindfulness-based interventions (MBIs) show promise in this regard.

The goal of the present study was to compare the impact of online MBI and P4C interventions on mental health, within the context of the COVID-19 pandemic. We used a randomized cluster trial to assess and compare the impact of both interventions on elementary school students' (N=37) anxiety and inattention symptoms as well as on their basic psychological need satisfaction (BPN).

ANCOVAs revealed a significant effect of the P4C intervention on mental health difficulties, controlling for baseline levels. Participants in the P4C group showed lower scores on the measured symptoms at post-test than participants in the MBI group. Signif support measures in elementary schools should consider an online modality, which has shown in this study to work well, be feasible, and yield positive results on youth mental health.

Practice Philosophy for children (P4C) and mindfulness-based interventions (MBIs) can be used to foster mental health in elementary school students, in the current COVID-19 context. Policy As we do not anticipate that facilitators will be allowed in schools during the 2020-2021 school year and that children will, most likely, be attending school in the current COVID-19 context, policymakers who want to implement psychological support measures in elementary schools should consider an online modality, which has shown in this study to work well, be feasible, and yield positive results on youth mental health.

Impaired clinical and cognitive insight are prevalent in schizophrenia and relate to poorer outcome. Good insight has been suggested to depend on social cognitive and metacognitive abilities requiring global integration of brain signals. Impaired insight has been related to numerous focal gray matter (GM) abnormalities distributed across the brain suggesting dysconnectivity at the global level. In this study, we test whether global integration deficiencies reflected in gray matter network connectivity underlie individual variations in insight.

We used graph theory to examine whether individual GM-network metrics relate to insight in patients with a psychotic disorder (n=114). Clinical insight was measured with the Schedule for the Assessment of Insight-Expanded and item G12 of the Positive and Negative Syndrome Scale, and cognitive insight with the Beck Cognitive Insight Scale. Individual GM-similarity networks were created from GM-segmentations of T1-weighted MRI-scans. Graph metrics were calculated usin critical perspective on one's symptoms (clinical insight) or views (cognitive insight) might depend especially on segregated specialized processing within distinct subnetworks.

Atrial fibrillation (AF) is the most encountered arrhythmia and has been associated with worse in-hospital outcomes.

This study was to determine the incidence of AF in patients hospitalized with coronavirus disease 2019 (COVID-19) as well as its impact on in-hospital mortality.

Patients hospitalized with a positive COVID-19 polymerase chain reaction test between March 1 and April 27, 2020, were identified from the common medical record system of 13 Northwell Health hospitals. Natural language processing search algorithms were used to identify and classify AF. Patients were classified as having AF or not. check details AF was further classified as new-onset AF vs history of AF.

AF occurred in 1687 of 9564 patients (17.6%). Of those, 1109 patients (65.7%) had new-onset AF. Propensity score matching of 1238 pairs of patients with AF and without AF showed higher in-hospital mortality in the AF group (54.3% vs 37.2%; P < .0001). Within the AF group, propensity score matching of 500 pairs showed higher in-hospital mortality in patients with new-onset AF as compared with those with a history of AF (55.2% vs 46.8%; P = .009). The risk ratio of in-hospital mortality for new-onset AF in patients with sinus rhythm was 1.56 (95% confidence interval 1.42-1.71; P < .0001). The presence of cardiac disease was not associated with a higher risk of in-hospital mortality in patients with AF (P = .1).

In patients hospitalized with COVID-19, 17.6% experienced AF. AF, particularly new-onset, was an independent predictor of in-hospital mortality.

In patients hospitalized with COVID-19, 17.6% experienced AF. AF, particularly new-onset, was an independent predictor of in-hospital mortality.

To identify life-long body mass index (BMI) trajectories across two related generations and estimate their associated mortality risks and population attributable deaths.

We use prospective cohort data from the Framingham Heart Study (1948-2011) original (4576 individuals, 3913 deaths) and offspring (3753 individuals, 967 deaths) cohorts and latent trajectory models to model BMI trajectories from age 31 to 80 years. Survival models are used to estimate trajectory-specific mortality risk.

We define seven BMI trajectories among original cohort and six among offspring cohort. Among original cohort, people who are normal weight at age 31 years and gradually move to overweight status in middle or later adulthood have the lowest mortality risk even compared to those who maintain normal weight throughout adulthood, followed by overweight stable, lower level of normal weight, overweight downward, class I obese upward, and class II/III upward trajectories. Mortality risks associated with obesity trajectories have declined across cohorts, while the prevalence of high-risk trajectories has increased.