112 research outputs found
Delay in Diagnosis of Cervical Cancer in Afghanistan: A Pilot Cross-Sectional Survey
No full textObjectives: The present study aimed to investigate the potential delays in healthcare seeking and diagnosis of women with cervical cancer (CC) in Afghanistan. Methods: Clinical records of three hospitals in Kabul were searched for CC cases, and the women identified were interviewed by a trained physician using a semi-structured questionnaire. The main outcomes were the prevalence of potential delays over 90 days (1) from symptoms onset to healthcare seeking (patient delay), and (2) from first healthcare visit to CC diagnosis (healthcare delay). Information was also collected on: type and stage of CC, diagnostic test utilized, familiarity for CC, signs and symptoms, treatment type, and potential reasons for delaying healthcare seeking. Results: 31 women with CC were identified, however only 11 continued their treatment in the study hospitals or were reachable by telephone, and accepted the interview. The mean age was 51 ± 14 years, and only 18.2% had a previous history of seeking medical care. Patient delay was seen in 90.9% of the women (95% CI: 58.7–99.8), with a median of 304 ± 183 days. Instead, healthcare delay was found in 45.4% (95% CI: 16.7–76.6), with a median of 61 ± 152 days. The main reasons for patient delays were unawareness of the seriousness of the symptoms (70.0%) and unwillingness to consult a healthcare professional (30.0%). None of the women ever underwent cervical screening or heard of the HPV vaccination. Conclusions: Given the global effort to provide quality health care to all CC patients, Afghanistan needs interventions to reduce the delays in the diagnosis of this cancer, for instance by improving all women's awareness of gynecological signs and symptoms
A Narrative Review of Personal Protective Equipment Uses in Coronavirus Disease 2019 and Its Disposable Practices
No full textSince severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for causing coronavirus disease 2019 (COVID-19), is transmitted through close contact and droplets, people, especially those at risk of infection, must follow preventive measures in the community and healthcare settings. Healthcare personnel (HCP) must appropriately select and use personal protective equipment (PPE) with sensible donning and doffing and disposal practices. A narrative review of the existing literature was conducted, in which articles from Scopus, PubMed, Google Scholar, ScienceDirect, and Web of Science were collected. The primary findings of the retained articles were reviewed according to official recommendations on PPE use. The World Health Organization (WHO), US Centers for Disease Control and Prevention (CDC), and European Center for Disease Control and Prevention (ECDC) recommend standard precautions for contact transmission, respiratory transmission, and droplet precautions among HCPs caring for patients with COVID-19. Indeed, healthcare workers working in high-risk areas, as well as the public, when social distancing cannot be assured, must wear PPE such as face mask and protective eyewear to prevent the transmission of SARS-CoV-2 infection. Due to the increased use of PPE, the potentially infectious waste stream has been rapidly increasing, requiring safe and adequate solid waste management. The proper use of PPE and management of waste generated from COVID-19 care centers can reduce the risk of COVID-19 infection. These measures should be implemented to counter the rapid spread and any long-term impacts of the current pandemic
Analysis of oxygen binding by hemoglobin on the basis of mean intrinsic thermodynamic quantities
No full textThe binding data for oxygenation of human hemoglobin, Hb, at various temperatures and in the absence and presence of 2,3-diphosphoglycerate, DPG, and inositol hexakis phosphate, IHP, were analyzed for extraction of mean intrinsic Gibbs free energy, ΔGo, enthalpy, ΔHo, and entropy, ΔSo, of binding at various partial oxygen pressures. This method of analysis considers all the protein species present such as dimer and tetramer forms which were not considered by Imai et al. (Imai K et al., 1970, Biochim Biophys Acta 200: 189 - 196) , in their analysis which was based on Adair equation. In this regard, the values of Hill equation parameters were estimated with high precision at all points of the binding curve and used for calculation of ΔGo, ΔHo and ΔSo were also calculated by analysis of ΔGo values at various temperatures using van't Hoff equation. The results represent the enthalpic nature of the cooperativity in Hb oxygenation and the compensation effect of intrinsic entropy. The interpretation of results also to be, into account the decrease of the binding affinity of sites for oxygen in the presence of DPG and IHP without any considerable changes in the site - site interaction (extent of cooperativity). In other words, the interactions between bound ligands, organic phosphates and oxygen, are more due to a decreasing binding affinity and not to the reduction of the cooperative interaction between sites. The results also document the more heterotropic effect of IHP compared to DPG
A novel one-layer recurrent neural network for the l<sub>1</sub>-regularized least square problem
No full textThe l1-regularized least square problem has been considered in diverse fields. However, finding its solution is exacting as its objective function is not differentiable. In this paper, we propose a new one-layer neural network to find the optimal solution of the l1-regularized least squares problem. To solve the problem, we first convert it into a smooth quadratic minimization by splitting the desired variable into its positive and negative parts. Accordingly, a novel neural network is proposed to solve the resulting problem, which is guaranteed to converge to the solution of the problem. Furthermore, the rate of the convergence is dependent on a scaling parameter, not to the size of datasets. The proposed neural network is further adjusted to encompass the total variation regularization. Extensive experiments on the l1 and total variation regularized problems illustrate the reasonable performance of the proposed neural network.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Information and Communication Technolog
Generalized Variant Support Vector Machine
No full textWith the advancement in information technology, datasets with an enormous amount of data are available. The classification task on these datasets is more time- and memory-consuming as the number of data increases. The support vector machine (SVM), which is arguably the most popular classification technique, has disappointing performance in dealing with large datasets due to its constrained optimization problem. To deal with this challenge, the variant SVM (VSVM) has been utilized which has the fraction ({1}/{2})b{2} in its primal objective function, where b is the bias of the desired hyperplane. The VSVM has been solved with different optimization techniques in more time- and memory-efficient fashion. However, there is no guarantee that its optimal solution is the same as the standard SVM. In this paper, we introduce the generalized VSVM (GVSVM) which has the fraction ({1}/{2t})b{2} in its primal objective function, for a fixed positive scalar t. Further, we present the thorough theoretical insights that indicate the optimal solution of the GVSVM tends to the optimal solution of the standard SVM as t rightarrow infty . One vital corollary is to derive a closed-form formula to obtain the bias term in the standard SVM. Such a formula obviates the need of approximating it, which is the modus operandi to date. An efficient neural network is then proposed to solve the GVSVM dual problem, which is asymptotically stable in the sense of Lyapunov and converges globally exponentially to the exact solution of the GVSVM. The proposed neural network has less complexity in architecture and needs fewer computations in each iteration in comparison to the existing neural solutions. Experiments confirm the efficacy of the proposed recurrent neural network and the proximity of the GVSVM and the standard SVM solutions with more significant values of t. Information and Communication Technolog
Treatment outcomes for maculopathy secondary to retinal vein occlusion in Afghanistan
No full textOBJECTIVES: The objective of this study was to investigate the efficacy of intravitreal antivascular endothelial growth factor (VEGF) therapy in the treatment of macular edema secondary to retinal vein occlusion (RVO) in Afghanistan.
METHODS: A retrospective analysis was conducted of all RVO cases that underwent intravitreal ant-VEGF injection at the two leading hospitals in Kabul. The main outcome measures were visual acuity and central retinal thickness as determined by optical coherence tomography. Information was also collected on the distance traveled by each patient and the frequency of injections.
RESULTS: One hundred and twenty-five eyes of 121 patients (86 males) with RVO were identified as having undergone treatment, with a mean age of 53.1 years (range 20–80). The only agent used was bevacizumab. The mean central retinal thickness reduced from 624.2 ± 24.9 μm at the baseline to 257.8 ± 5.7 μm following treatment (P < 0.001). There was a small increase in visual acuity from 1.33 LogMAR at the baseline to 1.13 LogMAR following the most recent injection (P = 0.03, paired t-test). The mean distance traveled by patients was 173.9 km (range 2–447 km).
CONCLUSION: Despite the challenges of health-care provision in Afghanistan, this review shows that the use of intravitreal bevacizumab has provided an effective treatment for macular edema after RVO
Prevalence and Risk Factors of Hepatitis B, Hepatitis C and HIV Viruses Among People Who Use Drugs (PWUD) in Kabul, Health Care Facilities
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The spatial assessment of suitable areas for medicinal species of Astragalus (Astragalus hypsogeton Bunge) using the Analytic Hierarchy Process (AHP) and Geographic Information System (GIS)
No full textClimatic variation and different ecological conditions is led to the species diversity and richness of medicinal plants throughout the country. In this study, the effective criteria were identified in determining suitable areas for the Astragalus; including the six main criteria of precipitation, temperature, slope, altitude, soil texture and orientation, based on the purpose of the study and regional characteristics, field surveys, local information and expertise opinions. The Analytic Hierarchy Process (AHP), Pair comparison method and expert choice “11” software were used to determine the incompatibility rate of the criteria based on the questionnaire. The basic researches and integration of informative layers were done using GIS. Therefore, suitable areas were obtained for Astragalus hypsogeton Bunge in the Bahar Mountains catchment, using overlaying of maps. The results showed that the class of more than 2400 m height with relative importance of 0.5172 and 2100–2400 m, and the relative importance of 0.2702 are located on the first and second priority to locate Astragalus hypsogeton Bunge in Bahar Mountain catchment. Furthermore, the tree main criteria of altitude, precipitation and temperature have been allocated the most relative importance of 0.33, 0.22 and 0.16, respectively and located on the top three priorities. 1354.3 ha of the total area of Bahar Mountain catchment was identified as a suitable area for Astragalus hypsogeton Bunge. The study could ultimately show that it can be obtained an optimal locality to identify medicinal plants in different areas using modern technology, GIS and AHP with minimal cost and time. Keywords: Spatial assessment, Astragalus hypsogeton Bunge, Geographic Information System (GIS), Bahar Mountain catchmen
Understanding Care-Seeking Behavior for Reproductive Tract Infections Among Afghan Women: A Cross-Sectional Study
No full textBackground: In Afghanistan, providing care for reproductive tract infections (RTIs) is challenging, among other factors, due to the extreme scarcity of reliable data. To address this gap, the present study investigates symptoms, potential risk factors, knowledge, and care-seeking behavior in the largest sample of women to date. Methods: From September 16, 2022 to November 26, 2022, a structured questionnaire was administered to women presenting at multi-specialist clinics in the major cities of Afghanistan. Signs and symptoms of RTIs were investigated, together with reproductive history, hygiene practices, and sociodemographic characteristics. Logistic regression, adjusted for selected covariates, was used to assess predictors of delays (over 1 month) from symptoms onset to care-seeking, and of a history of RTI. Results: A total of 601 responses were analyzed (80.2%). Mean age was 31.3 years (standard deviation [SD] 11.5). Signs symptoms related to RTIs were reported by 79.2%, knowledge of RTIs by only 23.0%, and care-seeking delays by up to 39.5%. Care-seeking delays were positively associated with abnormal vaginal discharge (odds ratios [OR] 4.12; 95% confidence intervals (CI) 2.01–8.45), lower abdominal pain (2.62; 1.44–4.77), and fever (1.93; 1.25–2.98) and negatively associated with being sedentary (0.38; 0.22–0.64), hand washing (0.61; 0.40–0.95), and knowledge about RTI, although borderline significant. A history of RTI (reported by 44.1%) was predicted by abnormal vaginal discharge, fever, irregular menstruations, and use of sanitary pads but not by the husbands’ history of RTI. Conclusions: The majority of women presenting at clinics in Afghanistan reported symptoms related to RTIs, delayed care-seeking, and lack of knowledge about RTI. Healthcare providers should inform the population about RTIs and their standard care pathway, while adopting a multi-dimensional approach accounting for the cultural background of the women
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