Spring cleaning as a safety risk: results of a population-based study in two consecutive years

<p>Abstract</p> <p>Background</p> <p>Spring cleaning is a popular tradition in Iran as well as in many other countries. The purpose of our study was to determine the pattern and compare the incidence of spring cleaning related injuries in Tehran, in the years 2007 and 2008.</p> <p>Methods</p> <p>In the year 2007, a household survey was performed in Tehran by random cluster sampling. The survey was repeated in May 2008 with the same clusters and starting points, but different households. The incidence of spring cleaning related injuries, the age and sex of injured person(s), the mechanism, type and cost of injuries were recorded through semi-structured interviews. The incidence rates of injuries and injuries leading to health visits (severe) according to sex and age groups were calculated. Data were analyzed using SPSS and STATA statistical softwares.</p> <p>Results</p> <p>The incidence of all and severe spring cleaning related injuries were 3.8 (3.0 - 4.8) and 1.6 (1.1-2.3) per 1000, respectively. The most common mechanisms of injuries were falls, followed by cutting and lifting heavy objects or overexertion. Falls were also the main mechanism of severe injuries. The most common injuries were open wounds, followed by superficial injuries (including contusions) and sprain and strain. Among severe injuries, the most frequent injuries were open wounds and contusions, followed by dislocations. The injuries were most common among women with an incidence of about 8.4 per 1000 in women older than 18 years of age (severe injuries: 3.4 per 1000 (2.2-5.1)).</p> <p>Conclusion</p> <p>The incidence of spring cleaning related injuries is high enough to raise concern in health system authorities. It could be estimated that about 23,927 to 38,283 persons get injured during the spring cleaning in Tehran at the beginning of every Persian new year. In addition, about 8,773-18,344 of these cases are expected to be severe enough to lead to medical attention (considering 7,975,679 as the population of Tehran at the time of study). Improving awareness of families, especially young women, regarding the scope and importance of spring cleaning safety can be suggested as the first population-based strategy to decrease the incidence of these injuries.</p

Mini-Mental State Examination (MMSE) for the detection of dementia in clinically unevaluated people aged 65 and over in community and primary care populations

BACKGROUND: The Mini Mental State Examination (MMSE) is a cognitive test that is commonly used as part of the evaluation for possible dementia. OBJECTIVES: To determine the diagnostic accuracy of the Mini‐Mental State Examination (MMSE) at various cut points for dementia in people aged 65 years and over in community and primary care settings who had not undergone prior testing for dementia. SEARCH METHODS: We searched the specialised register of the Cochrane Dementia and Cognitive Improvement Group, MEDLINE (OvidSP), EMBASE (OvidSP), PsycINFO (OvidSP), LILACS (BIREME), ALOIS, BIOSIS previews (Thomson Reuters Web of Science), and Web of Science Core Collection, including the Science Citation Index and the Conference Proceedings Citation Index (Thomson Reuters Web of Science). We also searched specialised sources of diagnostic test accuracy studies and reviews: MEDION (Universities of Maastricht and Leuven, www.mediondatabase.nl), DARE (Database of Abstracts of Reviews of Effects, via the Cochrane Library), HTA Database (Health Technology Assessment Database, via the Cochrane Library), and ARIF (University of Birmingham, UK, www.arif.bham.ac.uk). We attempted to locate possibly relevant but unpublished data by contacting researchers in this field. We first performed the searches in November 2012 and then fully updated them in May 2014. We did not apply any language or date restrictions to the electronic searches, and we did not use any methodological filters as a method to restrict the search overall. SELECTION CRITERIA: We included studies that compared the 11‐item (maximum score 30) MMSE test (at any cut point) in people who had not undergone prior testing versus a commonly accepted clinical reference standard for all‐cause dementia and subtypes (Alzheimer disease dementia, Lewy body dementia, vascular dementia, frontotemporal dementia). Clinical diagnosis included all‐cause (unspecified) dementia, as defined by any version of the Diagnostic and Statistical Manual of Mental Disorders (DSM); International Classification of Diseases (ICD) and the Clinical Dementia Rating. DATA COLLECTION AND ANALYSIS: At least three authors screened all citations.Two authors handled data extraction and quality assessment. We performed meta‐analysis using the hierarchical summary receiver‐operator curves (HSROC) method and the bivariate method. MAIN RESULTS: We retrieved 24,310 citations after removal of duplicates. We reviewed the full text of 317 full‐text articles and finally included 70 records, referring to 48 studies, in our synthesis. We were able to perform meta‐analysis on 28 studies in the community setting (44 articles) and on 6 studies in primary care (8 articles), but we could not extract usable 2 x 2 data for the remaining 14 community studies, which we did not include in the meta‐analysis. All of the studies in the community were in asymptomatic people, whereas two of the six studies in primary care were conducted in people who had symptoms of possible dementia. We judged two studies to be at high risk of bias in the patient selection domain, three studies to be at high risk of bias in the index test domain and nine studies to be at high risk of bias regarding flow and timing. We assessed most studies as being applicable to the review question though we had concerns about selection of participants in six studies and target condition in one study. The accuracy of the MMSE for diagnosing dementia was reported at 18 cut points in the community (MMSE score 10, 14‐30 inclusive) and 10 cut points in primary care (MMSE score 17‐26 inclusive). The total number of participants in studies included in the meta‐analyses ranged from 37 to 2727, median 314 (interquartile range (IQR) 160 to 647). In the community, the pooled accuracy at a cut point of 24 (15 studies) was sensitivity 0.85 (95% confidence interval (CI) 0.74 to 0.92), specificity 0.90 (95% CI 0.82 to 0.95); at a cut point of 25 (10 studies), sensitivity 0.87 (95% CI 0.78 to 0.93), specificity 0.82 (95% CI 0.65 to 0.92); and in seven studies that adjusted accuracy estimates for level of education, sensitivity 0.97 (95% CI 0.83 to 1.00), specificity 0.70 (95% CI 0.50 to 0.85). There was insufficient data to evaluate the accuracy of the MMSE for diagnosing dementia subtypes.We could not estimate summary diagnostic accuracy in primary care due to insufficient data. AUTHORS' CONCLUSIONS: The MMSE contributes to a diagnosis of dementia in low prevalence settings, but should not be used in isolation to confirm or exclude disease. We recommend that future work evaluates the diagnostic accuracy of tests in the context of the diagnostic pathway experienced by the patient and that investigators report how undergoing the MMSE changes patient‐relevant outcomes

Global Education - Helene-Lange-Schule Wiesbaden (UNESCO Associated School) and their project in Nepal. A qualitative analysis.

In der Arbeit wird der Fragestellung nachgegangen, ob und in inwiefern ein groß angelegtes Schulprojekt von den aktiv Beteiligten als eine Lernmöglichkeit gesehen wird. Zunehmend beschäftigen sich Schulen mit der Frage der Förderung des Globalen Lernens im Schulalltag und wie dies zu realisieren ist. In der vorliegenden Arbeit wird das Nepalprojekt der Helene-Lange-Schule in Hinblick auf Lernmomente und Lernmöglichkeiten in Hinblick auf Globales Lernen untersucht. Die anfängliche Analyse der Frage „Globales Lernen im Kontext nachhaltiger Entwicklung“ leitet schließlich in die Vorstellung der Schule über und schließlich in den empirischen Teil der Arbeit. Die Frage nach den nötigen Kompetenzen die es zu erreichen gilt, zieht sich durch die Arbeit und wird kritisch diskutiert.In this diploma thesis the question of global education is discussed. Helene-Lange-Schule Wiesbaden has a evolving project in Nepal.This project is part of the every day life in school. The question is, how far the students learn by taking part in this projectand which responsibilities they appropriate

Effect of Missing Data Imputation on Deep Learning Prediction Performance for Vesicoureteral Reflux and Recurrent Urinary Tract Infection Clinical Study

Ozgur, Su/0000-0002-8993-674X;WOS: 000556223500008PubMed: 32733929Missing observations are always a challenging problem that we have to deal with in diseases that require follow-up. in hospital records for vesicoureteral reflux (VUR) and recurrent urinary tract infection (rUTI), the number of complete cases is very low on demographic and clinical characteristics, laboratory findings, and imaging data. on the other hand, deep learning (DL) approaches can be used for highly missing observation scenarios with its own missing ratio algorithm. in this study, the effects of multiple imputation techniques MICE and FAMD on the performance of DL in the differential diagnosis were compared. the data of a retrospective cross-sectional study including 611 pediatric patients were evaluated (425 with VUR, 186 with rUTI, 26.65% missing ratio) in this research. CNTK and R 3.6.3 have been used for evaluating different models for 34 features (physical, laboratory, and imaging findings). in the differential diagnosis of VUR and rUTI, the best performance was obtained by deep learning with MICE algorithm with its values, respectively, 64.05% accuracy, 64.59% sensitivity, and 62.62% specificity. FAMD algorithm performed withaccuracy = 61.52,sensitivity = 60.20, and specificity was found out to be 61.00 with 3 principal components on missing imputation phase. DL-based approaches can evaluate datasets without doing preomit/impute missing values from datasets. Once DL method is used together with appropriate missing imputation techniques, it shows higher predictive performance.TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [114S011]This work was supported by TUBITAK with Project No. 114S011

The Use of Artificial Neural Networks for Differential Diagnosis between Vesicoureteral Reflux and Urinary Tract Infection in Children

Ozgur, Su/0000-0002-8993-674XWOS: 000544838900009Aim: Vesicoureteral reflux (VUR) and urinary tract infection (UTI) are common problems in children. Our goal is to use different models for the clinical decision of differential diagnosis of VUR and UTI in children. Materials and Methods: This was a retrospective cross-sectional study with 611 pediatric patients enrolled. Detailed information for the patients was obtained from hospital records and patient files. Three models including different variables were evaluated via an artificial neural network for the differential diagnosis of VUR and recurrent UTI. Clinical findings were included in Model 1, clinical and laboratory findings were included in Model 2, and clinical, laboratory and detailed urinary ultrasonography (USG) findings were included in Model 3. A cross-validation technique was used to evaluate predictive models by partitioning the original sample into a training set to train the model, and a test set to evaluate it. Results: of the 611 children, 425 (69.6%) had VUR and 186 (30.4%) had UTI. the sensitivity of Model 1 and Model 2 were 0.682 and 0.856, respectively. Also, Model 3 showed the best performance and highest sensitivity with 0.939 for differential diagnosis. Conclusion: Differential diagnosis between VUR and UTI in children can be predicted by using clinical, laboratory and USG variables via an Artificial Neural Network. Model 3, which included clinical, laboratory and USG variables together, showed the best performance and highest sensitivity.TUBITAKTurkiye Bilimsel ve Teknolojik Arastirma Kurumu (TUBITAK) [114S011]This article was written based on a project supported by TUBITAK with project number 114S011

The effect of recurrent urinary tract infections on somatic growth in children [Çocuklarda tekrarlayan idrar yolu enfeksiyonlarinin büyüme üzerine etkisi (ön çalişma)]

Aim: Urinary tract infection is one of the common bacterial infections in children and may lead to substantial morbidity. In this study, the effect of recurrent urinary tract infections on the growth of children aged between 0-12 years was investigated. Material and Method: In this prospective study, 72 children who had the definite diagnosis of recurrent urinary tract infections and followed up for at least 6 months, in a period of one year in the outpatient clinic of nephrology were included. The infection was evaluated with urine culture and growth charts. Data were analyzed with Pearson and Mc Nemar chi-square tests, t-test, Mann Whitney U test and corelation analysis. Results: The mean age of the children was 42.9 months, 66.7% of those were females. Height for age and weight for age were found to be lower in 16.7% and 22.2%, respectively. Escherischia coli was the most common pathogen found in urine cultures. Renal scarring was determined in 20.8% of the subjects. While the attack numbers of urinary trcat infections were increasing, height and weight measurements for age were significantly decreasing. Weight for age was significantly low in boys at the beginning of the study. Weight for age score improved after a 6-month follow-up period. Conclusions: The treatment and the prophylaxy of the recurrent urinary tract infections resulted in a positive effect on growth of the children

HYPERTENSION IN THE PEDIATRIC KIDNEY TRANSPLANT RECIPIENTS

WOS:000443998400464[No Abstract Available