16 research outputs found

    Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

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    Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

    SVD-BASED SIGNATURE VERIFICATION TECHNIQUE USING DATA GLOVE

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    Data glove is a new dimension in the field of virtual reality environments, initially designed to satisfy the stringent requirements of modern motion capture and animation professionals. In this paper, we try to shift the implementation of data glove from motion animation towards signature verification problem, making use of the offered multiple degrees of freedom for each finger and for the hand as well. The proposed technique is based on the Singular Value Decomposition (SVD) in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, and thus account for most of the variation in the original data, so the effective dimensionality of the data can be reduced. Having identified data glove signature through its rth principal subspace, the authenticity can then be obtained by calculating the angles between the different subspaces. The SVD-signature verification technique is tested with large number of authentic and forged signatures, showing remarkable level of accuracy in finding the similarities between genuine samples as well as those differentiated between genuine-forgery trials

    Subspace Techniques for Brain Signal Enhancement

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    Enhancement of Glove-Based Approach to Dynamic Signature Verification by Reducing Number of Sensors

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    Data glove is a new dimension in the field of virtual reality environments, initially designed to satisfy the stringent requirements of modern motion capture and animation professionals. Utilizing the multiple degrees of freedom offered by the data glove for each finger and the hand, a novel online signature verification technique using Singular Value Decomposition (SVD) for signature classification and verification is presented The proposed technique is based on the S VD in finding r-singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, and thus account for most of the variation in the original data, so the effective dimensionality of the data can be reduced. Having identified data glove signature through its r-principal subspace, the authenticity is then can be obtained by calculating the angles between the different subspaces. In this paper we try to ponder a significant analysis of accuracy and performance of dynamic signature identification and verification using data glove with reduced number of sensors from 14 to 5 to achieve a significant level of accuracy. The SVD-based signature verification technique is appears to be promising with the best combination of selected 5 prominent sensors instead of select all the 14-seonsor based data sets and the best performance is shown to be able to produce 2.33% of Equal Error Rate (EER)

    Virtual Reality Based Dynamic Signature Verification Using Data glove

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    Data glove is a new dimension in the field of virtual reality environments, initially designed to satisfy the stringent requirements of modern motion capture and animation professionals. In this paper we try to shift the implementation of data glove from motion animation towards signature verification problem, making use of the offered multiple degrees of freedom for each finger and for the hand as well. The proposed technique is based on the Singular Value Decomposition (SVD) in finding r singular vectors sensing the maximal energy of glove data matrix A, called principal subspace, and thus account for most of the variation in the original data, so the effective dimensionality of the data can be reduced. Having identified data glove signature through its r-th principal subspace, the authenticity is then can be obtained by calculating the angles between the different subspaces. The SVD-signature verification technique is tested with large number of authentic and forgery signatures and shows remarkable level of accuracy in finding the similarities between genuine samples as well as the differenced between genuine-forgery trials

    EEG spectral analysis during complex cognitive task at occipital

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    Factors Associated with Health-Related Quality of Life among Jordanian Patients with Diabetic Foot Ulcer

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    Objective. This study is aimed at determining factors associated with the quality of life among Jordanian diabetic patients with foot ulcers. Methods. 144 consecutive patients with diabetic foot ulcers aged ≥ 18 years who were attending the diabetic foot clinic at a diabetes-specialized center were included in this study. Health-related quality of life was assessed using two self-administered questionnaires: Diabetic Foot Scale-Short Form (DFS-SF) and Short Form-8 (SF-8). Results. Patients with diabetic foot ulcer had low mean DFS-SF score and low mean scores on physical and mental component summary scales (PCS8 and MCS8). Males had significantly higher DFS-SF score indicating better health-related quality of life than females (P value 0.038). A patient with stressful life events had significantly lower health-related quality of life using DFS-SF scale and SF-8 summary scales. Patients with peripheral vascular disease (PVD) and patients with obesity had lower DFS-SF and PCS8 quality of life. Conclusion. Patients with diabetic foot ulcer had low quality of life. Female gender, obesity, presence of PVD, and stressful life events were the most important factors associated with lower quality of life in patients with diabetic foot ulcer
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