Effects of Vitamin D levels on asthma control and severity in pre-school children

OBJECTIVE: Prevalence of asthma and Vitamin D deficiency has been increasing and leading to significant morbidities. This study aimed to compare the Vitamin D levels in the pre-school children with asthma and in healthy controls and to assess the relationship between Vitamin D levels and asthma clinical parameters and control. PATIENTS AND METHODS: Vi tamin D [25(OH)D3] levels were measured in 102 preschool children, aged 1-4 years with asthma and 102 healthy controls in winter. The patients with asthma were grouped according to serum Vitamin D levels as sufficient, insufficient and deficient. Asthma control was classified according to the Global Initiative for Asthma (GINA) guidelines and the Test for Respiratory and Asthma Control in Kids (TRACK) in 1-4 years-old children. RESULTS: Serum Vitamin D levels were 22.64 (9.96) ng/ml in the asthma group and 32.11 (14.74) ng/ml in the control group (p = 0.001). Total number of exacerbations during the previous year were significantly lower in the Vitamin D sufficient group, compared to the deficient and insufficient groups (p = 0.03). Frequency of patients with controlled asthma was higher in the sufficient group compared to the deficient and insufficient groups (p = 0.001 and p = 0.001, respectively). There was a positive correlation between serum Vitamin D levels and asthma control. CONCLUSIONS: The frequency of Vitamin D deficiency and insufficiency was higher in children with asthma, compared to the controls. Therefore, we suggest that lower levels of Vitamin D are associated with poor asthma control and increased asthma severity

Evaluation of cognitive deficits in patients infected with COVID-19

OBJECTIVE: COVID-19 infection can cause impairments in many cognitive areas. The aim of the present study was to evaluate the cognitive functions of patients who had been infected with COVID-19. PATIENTS AND METHODS: The demographic and infection-related characteristics of patients who had been infected with COVID-19 were determined. Their cranial magnetic resonance imaging (MRI) and electroencephalography (EEG) findings were recorded. The Mini-Mental State Evaluation (MMSE). clock drawing test, forward and backward digit span tests. visual memory test. and Frontal Assessment Battery were applied to the patients. Finger agnosia and ideomotor apraxia were also determined. RESULTS: The study included 176 patients [100 female (56.8%). 76 male (43.2%), mean age 66.09 +/- 13.96 years]. About half of the patients were hospitalized for symptoms of COVID-19 infection (n=82, 46.6%). One third of these patients required intensive care (n=26. 14.8%). While 50 (45.9%) of the 109 patients diagnosed with dementia before infection were hospitalized. 32 (47.8%) of the 67 patients without a diagnosis of dementia required hospitalization (p=0.46). The most common neurological finding during COVID-19 infection was insomnia (n=36. 20.5%). The MMSE and visual memory test scores of the patients who were hospitalized for severe respiratory distress were lower than those whose treatment at home was completed (respectively 17.92 +/- 7.69/20.59 +/- 7.01, p=0.02; 2.53 +/- 1.73/3.69 +/- 2.80. p=0.01). The patients with moderate to severe cognitive impairment had significantly higher CRP levels at admission than the others (37.52 +/- 43.09/20.93 +/- 31.74, p=0.01, respectively). CONCLUSIONS: Cognitive damage in COVID-19 infection may be caused by ACE receptor density in the pial, hippocampal, and amygdala areas. In addition, the reason why people with severe dementia have a milder infection might be explained by the atrophy in these areas

Biosimilar filgrastim vs filgrastim: a multicenter nationwide observational bioequivalence study in patients with chemotherapy-induced neutropenia

Background: We studied the comparative effectiveness of biosimilar filgrastim vs original filgrastim in patients with chemotherapy-induced neutropenia.Patients and methods: This multicenter, observational study was conducted at 14 centers. The study included 337 patients experiencing neutropenia under chemotherapy. Patients were given either filgrastim 30 MIU or 48 MIU (Neupogen (R)) or biosimilar filgrastim 30 MIU (Leucostim (R)). Data regarding age, chemotherapeutic agents used, number of chemotherapy courses, previous diagnosis of neutropenia, neutrophil count of patients after treatment, medications used for the treatment of neutropenia, and duration of neutropenia were collected. Time to absolute neutrophil count (ANC) recovery was the primary efficacy measure.Results: Ambulatory and hospitalized patients comprised 11.3% and 45.1% of the enrolled patients, respectively, and a previous diagnosis of neutropenia was reported in 49.3% of the patients, as well. Neutropenia occurred in 13.7% (n=41), 45.5% (n=136), 27.4% (n=82), 11.4% (n=34), and 2.0% (n=6) of the patients during the first, second, third, fourth, and fifth cycles of chemotherapy, respectively. While the mean neutrophil count was 0.53 +/- 0.48 before treatment, a significant increase to 2.44 +/- 0.66 was observed after treatment (p=0.0001). While 90.3% of patients had a neutrophil count,1.49 before treatment, all patients had a neutrophil count >= 1.50 after treatment. Neutropenia resolved within <= 4 days of filgrastim therapy in 60.1%, 56.7%, and 52.6% of the patients receiving biosimilar filgrastim 30 MIU, original filgrastim 30 MIU, and original filgrastim 48 MIU, respectively. However, there was no significant difference between the three arms (p=0.468). Similarly, time to ANC recovery was comparable between the treatment arms (p=0.332).Conclusion: The results indicate that original filgrastim and biosimilar filgrastim have comparable efficacy in treating neutropenia. Biosimilar filgrastim provides a valuable alternative; however, there is need for further studies comparing the two products in different patient subpopulations

Residents' views about family medicine specialty education in Turkey

<p>Abstract</p> <p>Background</p> <p>Residents are one of the key stakeholders of specialty training. The Turkish Board of Family Medicine wanted to pursue a realistic and structured approach in the design of the specialty training programme. This approach required the development of a needs-based core curriculum built on evidence obtained from residents about their needs for specialty training and their needs in the current infrastructure. The aim of this study was to obtain evidence on residents' opinions and views about Family Medicine specialty training.</p> <p>Methods</p> <p>This is a descriptive, cross-sectional study. The board prepared a questionnaire to investigate residents' views about some aspects of the education programme such as duration and content, to assess the residents' learning needs as well as their need for a training infrastructure. The questionnaire was distributed to the Family Medicine Departments (n = 27) and to the coordinators of Family Medicine residency programmes in state hospitals (n = 11) by e-mail and by personal contact.</p> <p>Results</p> <p>A total of 191 questionnaires were returned. The female/male ratio was 58.6%/41.4%. Nine state hospitals and 10 university departments participated in the study. The response rate was 29%. Forty-five percent of the participants proposed over three years for the residency duration with either extensions of the standard rotation periods in pediatrics and internal medicine or reductions in general surgery. Residents expressed the need for extra rotations (dermatology 61.8%; otolaryngology 58.6%; radiology 52.4%). Fifty-nine percent of the residents deemed a rotation in a private primary care centre necessary, 62.8% in a state primary care centre with a proposed median duration of three months. Forty-seven percent of the participants advocated subspecialties for Family Medicine, especially geriatrics. The residents were open to new educational methods such as debates, training with models, workshops and e-learning. Participation in courses and congresses was considered necessary. The presence of a department office and the clinical competency of the educators were more favored by state residents.</p> <p>Conclusions</p> <p>This study gave the Board the chance to determine the needs of the residents that had not been taken into consideration sufficiently before. The length and the content of the programme will be revised according to the needs of the residents.</p

Theoretically-Efficient and Practical Parallel DBSCAN

The DBSCAN method for spatial clustering has received significant attention due to its applicability in a variety of data analysis tasks. There are fast sequential algorithms for DBSCAN in Euclidean space that take $O(n\log n)$ work for two dimensions, sub-quadratic work for three or more dimensions, and can be computed approximately in linear work for any constant number of dimensions. However, existing parallel DBSCAN algorithms require quadratic work in the worst case, making them inefficient for large datasets. This paper bridges the gap between theory and practice of parallel DBSCAN by presenting new parallel algorithms for Euclidean exact DBSCAN and approximate DBSCAN that match the work bounds of their sequential counterparts, and are highly parallel (polylogarithmic depth). We present implementations of our algorithms along with optimizations that improve their practical performance. We perform a comprehensive experimental evaluation of our algorithms on a variety of datasets and parameter settings. Our experiments on a 36-core machine with hyper-threading show that we outperform existing parallel DBSCAN implementations by up to several orders of magnitude, and achieve speedups by up to 33x over the best sequential algorithms

Rule-by-rule input significance analysis in fuzzy system modeling

Input or feature selection is one the most important steps of system modeling. Elimination of irrelevant variables can save time, money and can improve the precision of model that we are trying to discover. In Fuzzy System Modeling (FSM) approaches, input selection plays an important role too. The input selection algorithms that are under our investigation did not consider one crucial fact. An input variable may of may not be significant in a specific rule, not in overall system. In this paper, an input selection algorithm that takes this observation into account is proposed as an extension of the input selection algorithms found in the literature. The proposed algorithm is applied on a nonlinear function and successful results are achieved

Two step feature selection: Approximate functional dependency approach using membership values

Feature selection is one of the most important issues in fields such as system modelling and pattern recognition. In this study, a new feature selection algorithm that combines feature wrapper and feature filter approaches is proposed in order to identify the significant input variables in systems with continuous domains. The proposed method utilizes functional dependency concept and K-Nearest Neighbourhood method to implement the feature filter and feature wrapper, respectively. It is common to have outliers and noise in real-life data. In order to make the proposed feature selection algorithm noise and outlier resistant, approximate functional dependencies are used by utilizing membership values that inherently cope with uncertainty in the data