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Watson Adams posted an update 6 months, 3 weeks ago
Burnout is common among nurses and midwives. We examined whether an early career episode of burnout has long-term consequences on; a) cognitive functions, b) symptoms of depression, and/or c) insomnia for nurses a decade after graduation.
Symptoms of burnout were investigated in an observational longitudinal study of three national cohorts of registered nurses (RNs). Nursing students were recruited from all 26 of Sweden’s nursing programs. Burnout was subsequently measured through annual assessment over the first three years post graduation, with one long-term follow-up 11-15 years after graduation. A total of 2474 nurses (62%) consented to participate at follow-up. Burnout was measured using items from the Oldenburg Burnout Inventory, cognitive function by a study specific instrument, depressive symptoms by the Major Depression Inventory, and sleep problems using items from the Karolinska Sleep Questionnaire. We used logistic regression to identify factors associated with consequences of early career burnout, adjusting for concurrent levels at follow up.
The prevalence of nurses reporting high levels of burnout symptoms at least one of the first three years of working life was 299 (12·3%). High levels of burnout symptoms in early working life were significantly related to more frequent symptoms of cognitive dysfunction, depression, and impaired sleep a decade later when taking current burnout levels into account. After controlling for both current symptoms of burnout and the other outcome variables, nurses with early career burnout still reported more frequent problems with cognitive functions and sleep but not depression.
The results of this study show that the detrimental processes caused by overwhelming or chronic stress start early on in nurses’ careers and thus preventive efforts should preferably be introduced early on (e.g. as part of nursing education and onboarding programs).
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Preterm birth (PTB) and small for gestational age (SGA) are increasingly prevalent, with major consequences for health and development into later life. There is emerging evidence that some risk processes begin before pregnancy. selleck We report on associations between maternal and paternal common mental disorders (CMD) before and during pregnancy and offspring PTB and SGA.
398 women with 609 infants and 267 men with 421 infants were assessed repeatedly for CMD symptoms before pregnancy between age 14 and 29 and during pregnancy. Associations between preconception and antenatal CMD symptoms and offspring gestational age/PTB and size for gestational age/SGA were estimated using linear and Poisson regression.
In men, persistent preconception CMD across adolescence and young adulthood predicted offspring PTB after adjustment for ethnicity, education, BMI and adolescent substance use (adjusted RR 7·0, 95% CI 1·8,26·8), corresponding to a population attributable fraction of 31% of preterm births. In women, antenataldoch Children’s Research Institute, Australian Research Council.
The overall prognosis of oral cancer remains poor because over half of patients are diagnosed at advanced-stages. Previously reported screening and earlier detection methods for oral cancer still largely rely on health workers’ clinical experience and as yet there is no established method. We aimed to develop a rapid, non-invasive, cost-effective, and easy-to-use deep learning approach for identifying oral cavity squamous cell carcinoma (OCSCC) patients using photographic images.
We developed an automated deep learning algorithm using cascaded convolutional neural networks to detect OCSCC from photographic images. We included all biopsy-proven OCSCC photographs and normal controls of 44,409 clinical images collected from 11 hospitals around China between April 12, 2006, and Nov 25, 2019. We trained the algorithm on a randomly selected part of this dataset (development dataset) and used the rest for testing (internal validation dataset). Additionally, we curated an external validation dataset comprising clecialists and has the potential to be used as a clinical tool for fast screening, earlier detection, and therapeutic efficacy assessment of the cancer.
Automated detection of OCSCC by deep-learning-powered algorithm is a rapid, non-invasive, low-cost, and convenient method, which yielded comparable performance to that of human specialists and has the potential to be used as a clinical tool for fast screening, earlier detection, and therapeutic efficacy assessment of the cancer.
Soil-transmitted helminths (STHs) infect almost 1·5 billion people worldwide. The control of STH infections is based on preventive chemotherapy using either albendazole or mebendazole. Before being widely used, a sufficient body of evidence on efficacy, safety and acceptability is warranted for the new chewable child-friendly formulation of mebendazole that was recently developed.
We conducted a randomised controlled superiority trial in four primary schools and kindergartens on Pemba Island, Tanzania. We considered eligible children aged 3 to 12 years with a hookworm infection intensity of at least 50 eggs per gram (EPG) of stool and no chronic diseases. Participants were allocated to treatment arms (ratio 11) using a computer generated random sequence. Our primary outcome was geometric mean based egg reduction rate (ERR) against hookworm assessed 14-21 days post-treatment. This trial complete and is registered with ClinicalTrials.gov, number NCT03995680 (June 24, 2019).
397 children were eligible and , in particular in young children who may have swallowing difficulties. This might help increase compliance and, consequently, enhance the effect of preventive chemotherapy.
Chronic kidney disease (CKD) measures (estimated glomerular filtration rate and albuminuria) are frequently assessed in clinical practice and improve the prediction of incident cardiovascular disease (CVD), yet most major clinical guidelines do not have a standardized approach for incorporating these measures into CVD risk prediction. “CKD Patch” is a validated method to calibrate and improve the predicted risk from established equations according to CKD measures.
Utilizing data from 4,143,535 adults from 35 datasets, we developed several “CKD Patches” incorporating eGFR and albuminuria, to enhance prediction of risk of atherosclerotic CVD (ASCVD) by the Pooled Cohort Equation (PCE) and CVD mortality by Systematic COronary Risk Evaluation (SCORE). The risk enhancement by CKD Patch was determined by the deviation between individual CKD measures and the values expected from their traditional CVD risk factors and the hazard ratios for eGFR and albuminuria. We then validated this approach among 4,932,824 adults from 37 independent datasets, comparing the original PCE and SCORE equations (recalibrated in each dataset) to those with addition of CKD Patch.