Bullying girls - Changes after brief strategic family therapy: A randomized, prospective, controlled trial with one-year follow-up

Background: Many girls bully others. They are conspicuous because of their risk-taking behavior, increased anger, problematic interpersonal relationships and poor quality of life. Our aim was to determine the efficacy of brief strategic family therapy (BSFT) for bullying-related behavior, anger reduction, improvement of interpersonal relationships, and improvement of health-related quality of life in girls who bully, and to find out whether their expressive aggression correlates with their distinctive psychological features. Methods: 40 bullying girls were recruited from the general population: 20 were randomly selected for 3 months of BSFT. Follow-up took place 12 months after the therapy had ended. The results of treatment were examined using the Adolescents' Risk-taking Behavior Scale (ARBS), the State-Trait Anger Expression Inventory (STAXI), the Inventory of Interpersonal Problems (IIP-D), and the SF-36 Health Survey (SF-36). Results: In comparison with the control group (CG) (according to the intent-to-treat principle), bullying behavior in the BSFT group was reduced (BSFT-G from n = 20 to n = 6; CG from n = 20 to n = 18, p = 0.05) and statistically significant changes in all risk-taking behaviors (ARBS), on most STAXI, IIP-D, and SF-36 scales were observed after BSFT. The reduction in expressive aggression (Anger-Out scale of the STAXI) correlated with the reduction on several scales of the ARBS, IIP-D, and SF-36. Follow-up a year later showed relatively stable events. Conclusions: Our findings suggest that bullying girls suffer from psychological and social problems which may be reduced by the use of BSFT. Expressive aggression in girls appears to correlate with several types of risk-taking behavior and interpersonal problems, as well as with health-related quality of life. Copyright (c) 2006 S. Karger AG, Basel

Diagnoses and mortality among prehospital emergency patients calling 112 with unclear problems:a population-based cohort study from Denmark

BACKGROUND: Patients calling for an emergency ambulance and assessed as presenting with ‘unclear problem’ account for a considerable part of all emergency calls. Previous studies have demonstrated that these patients are at increased risk for unfavourable outcomes. A deeper insight into the underlying diagnoses and outcomes is essential to improve prehospital treatment. We aimed to investigate which of these diagnoses contributed most to the total burden of diseases in terms of numbers of deaths together with 1- and 30-day mortality. METHODS: A historic regional population-based observational cohort study from the years 2016 to 2018. Diagnoses were classified according to the World Health Organisation ICD-10 System (International Statistical Classification of Diseases and Related Health Problems, 10th edition). The ICD-10 chapters, R (‘symptoms, signs and abnormal clinical and laboratory findings, not elsewhere classified)’ and Z (‘factors influencing health status and contact with health services”) were combined and designated “non-specific diagnoses”. Poisson regression with robust variance estimation was used to estimate proportions of mortality in percentages with 95% confidence intervals, crude and adjusted for age, sex and comorbidities. RESULTS: Diagnoses were widespread among the ICD-10 chapters, and the most were ‘non-specific diagnoses’ (40.4%), ‘circulatory diseases’ (9.6%), ‘injuries and poisonings’ (9.4%) and ‘respiratory diseases’ (6.9%). The diagnoses contributing most to the total burden of deaths (n = 554) within 30 days were ‘circulatory diseases’ (n = 148, 26%) followed by ‘non-specific diagnoses’ (n = 88, 16%) ‘respiratory diseases’ (n = 85, 15%), ‘infections’ (n = 54, 10%) and ‘digestive disease’ (n = 39, 7%). Overall mortality was 2.3% (1-day) and 7.1% (30-days). The risk of mortality was highly associated with age. CONCLUSION: This study found that almost half of the patients brought to the hospital after calling 112 with an ‘unclear problem’ were discharged with a ‘non-specific diagnosis’ which might seem trivial but should be explored more as these contributed the second-highest to the total number of deaths after 30 days only exceeded by ‘circulatory diseases’. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13049-022-01052-y

Incidental CT Findings in the Elderly with Low-Energy Falls: Prevalence and Implications

Background: Computed tomography (CT) is commonly used in trauma care, with increasing implementation during the emergency work-up of elderly patients with low-energy falls (LEF). The prevalence of incidental findings (IFs) resulting from CT imaging and requiring down-stream actions in this patient cohort is unknown. We have investigated the prevalence and urgency of IFs from emergency CT examinations in these patients. Methods: A total of 2871 patients with LEF and emergency CT examinations were consecutively included in this retrospective cohort study. The primary endpoint was the prevalence of IFs;the secondary endpoint was their urgency. Results: The median age was 82 years (64.2% were women). IFs were identified in 73.9% of patients, with an average of 1.6 IFs per patient. Of all IFs, 16.4% were classified as urgent or relevant, predominantly in the abdomen, chest and neck. Increasing age was associated with the prevalence of an IF (odds ratio: 1.053, 95% confidence interval: 1.042-1.064). Significantly more IFs were found in female patients (75.2% vs. 71.5%). Conclusion: IFs resulting from CT examinations of the elderly are frequent, but in more than 8 out of 10, they are harmless or currently asymptomatic. For the benefit of an accurate diagnosis of traumatic lesions, concerns about IFs with respect to disease burden, further work-up and resource utilisation might be disregarded

EphA kinase activation regulates HGF-induced epithelial branching morphogenesis

Eph kinases and their ephrin ligands are widely expressed in epithelial cells in vitro and in vivo. Our results show that activation of endogenous EphA kinases in Madin-Darby canine kidney (MDCK) cells negatively regulates hepatocyte growth factor/scatter factor (HGF)–induced branching morphogenesis in collagen gel. Cotreatment with HGF and ephrin-A1 reduced sprouting of cell protrusions, an early step in branching morphogenesis. Moreover, addition of ephrin-A1 after HGF stimulation resulted in collapse and retraction of preexisting cell protrusions. In a newly developed assay that simulates the localized interactions between Ephs and ephrins in vivo, immobilized ephrin-A1 suppressed HGF-induced MDCK cell scattering. Ephrin-A1 inhibited basal ERK1/2 mitogen-activated protein kinase activity; however, the ephrin-A1 effect on cell protrusion was independent of the mitogen-activated protein kinase pathway. Ephrin-A1 suppressed HGF-induced activation of Rac1 and p21-activated kinase, whereas RhoA activation was retained, leading to the preservation of stress fibers. Moreover, dominant-negative RhoA or inhibitor of Rho-associated kinase (Y27632) substantially negated the inhibitory effects of ephrin-A1. These data suggest that interfering with c-Met signaling to Rho GTPases represents a major mechanism by which EphA kinase activation inhibits HGF-induced MDCK branching morphogenesis

Pregnant women with bronchial asthma benefit from progressive muscle relaxation: A randomized, prospective, controlled trial

Background: Asthma is a serious medical problem in pregnancy and is often associated with stress, anger and poor quality of life. The aim of this study was to determine the efficacy of progressive muscle relaxation (PMR) on change in blood pressure, lung parameters, heart rate, anger and health-related quality of life in pregnant women with bronchial asthma. Methods: We treated a sample of 64 pregnant women with bronchial asthma from the local population in an 8-week randomized, prospective, controlled trial. Thirty-two were selected for PMR, and 32 received a placebo intervention. The systolic blood pressure, forced expiratory volume in the first second, peak expiratory flow and heart rate were tested, and the State-Trait Anger Expression Inventory and Health Survey (SF-36) were employed. Results: According to the intend-to-treat principle, a significant reduction in systolic blood pressure and a significant increase in both forced expiratory volume in the first second and peak expiratory flow were observed after PMR. The heart rate showed a significant increase in the coefficient of variation, root mean square of successive differences and high frequency ranges, in addition to a significant reduction in low and middle frequency ranges. A significant reduction on three of five State-Trait Anger Expression Inventory scales, and a significant increase on seven of eight SF-36 scales were observed. Conclusions: PMR appears to be an effective method to improve blood pressure, lung parameters and heart rate, and to decrease anger levels, thus enhancing health-related quality of life in pregnant women with bronchial asthma. Copyright (c) 2006 S. Karger AG, Basel

Identifying Appropriate Nursing Home Resources to Reduce Fall-Related Emergency Department Transfers.

OBJECTIVES To describe potentially avoidable fall-related transfers to the emergency department (ED), and to identify infrastructure, training needs, and resources deemed appropriate for implementation in nursing homes (NHs) to decrease fall-related transfers to EDs. DESIGN A multi-method design, including (1) in-depth case review by an expert panel, (2) structured discussion with NH stakeholders, and (3) appropriateness rating. SETTING AND PARTICIPANTS Fall-related transfers were identified from the prospective reporting of every unplanned hospital transfer occurring within 21 months, collected during the INTERCARE study in 11 Swiss NHs. METHODS Eighty-one fall-related transfers were rated for avoidability by a 2-round expert panel. NH stakeholders were consulted to discuss key implementable resources for NHs to mitigate potentially avoidable fall-related transfers. A questionnaire composed of 21 contextually adapted resources was sent to a larger group of stakeholders, to rate the appropriateness for implementation in NHs. χ2 tests were used to assess whether avoidability was associated with an ED visit and to describe transfers. The RAND/UCLA method for appropriateness was used to determine appropriate resources. RESULTS One of 4 fall-related transfers were rated as potentially avoidable. A positive association was found between an ED visit and a rating of avoidability (χ2 (1, N = 81) = 18.0, P < .001). Fourteen resources, including developing partnerships with outpatient clinics to access imaging services and strengthening geriatric expertise in nursing homes through clinical training and advanced nurse practitioners, were rated as appropriate by NH stakeholders for NH implementation to reduce potentially avoidable fall-related ED transfers. CONCLUSIONS AND IMPLICATIONS Access to diagnostic equipment, geriatric expertise, and clinical training is essential to reduce fall-related potentially avoidable transfers from NHs. Implementing and supporting advanced practice nurses or nurses in extended roles provides NH directors, policymakers, and health care institutions with the possibility of re-engineering resources to limit unnecessary transfers, which are detrimental for resident quality of care and costly for the health system

Development and External Validation of the International Early Warning Score for Improved Age- and Sex-Adjusted In-Hospital Mortality Prediction in the Emergency Department

Objectives: Early Warning Scores (EWSs) have a great potential to assist clinical decision-making in the emergency department (ED). However, many EWS contain methodological weaknesses in development and validation and have poor predictive performance in older patients. The aim of this study was to develop and externally validate an International Early Warning Score (IEWS) based on a recalibrated National Early warning Score (NEWS) model including age and sex and evaluate its performance independently at arrival to the ED in three age categories (18-65, 66-80, &gt; 80 yr). Design: International multicenter cohort study. Setting: Data was used from three Dutch EDs. External validation was performed in two EDs in Denmark. Patients: All consecutive ED patients greater than or equal to 18 years in the Netherlands Emergency department Evaluation Database (NEED) with at least two registered vital signs were included, resulting in 95,553 patients. For external validation, 14,809 patients were included from a Danish Multicenter Cohort (DMC). Measurements and Main Results: Model performance to predict in-hospital mortality was evaluated by discrimination, calibration curves and summary statistics, reclassification, and clinical usefulness by decision curve analysis. In-hospital mortality rate was 2.4% (n = 2,314) in the NEED and 2.5% (n = 365) in the DMC. Overall, the IEWS performed significantly better than NEWS with an area under the receiving operating characteristic of 0.89 (95% CIs, 0.89-0.90) versus 0.82 (0.82-0.83) in the NEED and 0.87 (0.85-0.88) versus 0.82 (0.80-0.84) at external validation. Calibration for NEWS predictions underestimated risk in older patients and overestimated risk in the youngest, while calibration improved for IEWS with a substantial reclassification of patients from low to high risk and a standardized net benefit of 5-15% in the relevant risk range for all age categories. Conclusions: The IEWS substantially improves in-hospital mortality prediction for all ED patients greater than or equal to18 years.</p

Machine learning for developing a prediction model of hospital admission of emergency department patients:Hype or hope?

Objective: Early identification of emergency department (ED) patients who need hospitalization is essential for quality of care and patient safety. We aimed to compare machine learning (ML) models predicting the hospitalization of ED patients and conventional regression techniques at three points in time after ED registration. Methods: We analyzed consecutive ED patients of three hospitals using the Netherlands Emergency Department Evaluation Database (NEED). We developed prediction models for hospitalization using an increasing number of data available at triage, similar to 30 min (including vital signs) and similar to 2 h (including laboratory tests) after ED registration, using ML (random forest, gradient boosted decision trees, deep neural networks) and multivariable logistic regression analysis (including spline transformations for continuous predictors). Demographics, urgency, presenting complaints, disease severity and proxies for comorbidity, and complexity were used as covariates. We compared the performance using the area under the ROC curve in independent validation sets from each hospital. Results: We included 172,104 ED patients of whom 66,782 (39 %) were hospitalized. The AUC of the multi-variable logistic regression model was 0.82 (0.78-0.86) at triage, 0.84 (0.81-0.86) at similar to 30 min and 0.83 (0.75-0.92) after similar to 2 h. The best performing ML model over time was the gradient boosted decision trees model with an AUC of 0.84 (0.77-0.88) at triage, 0.86 (0.82-0.89) at similar to 30 min and 0.86 (0.74-0.93) after similar to 2 h. Conclusions: Our study showed that machine learning models had an excellent but similar predictive performance as the logistic regression model for predicting hospital admission. In comparison to the 30-min model, the 2-h model did not show a performance improvement. After further validation, these prediction models could support management decisions by real-time feedback to medical personal