Evaluation of newborns with vitamin D deficiency: A single-center experience

Aim: To evaluate the demographic, clinical, and laboratory characteristics (primarily phosphorus, calcium (Ca), and alkaline phosphatase (ALP) levels of newborns with low 25-OHD levels. Methods: In this retrospective study, babies whose 25-OHD levels were determined during hospitalization were evaluated. The newborns were classified as stated by their serum 25-OHD levels as follows: severely deficient, <5 ng/mL (group 1); deficient, 5–20 ng/mL (group 2); and insufficient, 20 to 30 ng/mL (group 3). In addition to the newborns' serum 25-OHD levels, their serum Ca, phosphorus, parathormone (PTH), and alkaline phosphatase levels and their mothers' 25-OHD levels were also measured. Results: A total of 568 newborns were included. Serum 25-OHD level was severely deficient in 112 patients (19.7%). The mothers of the babies in group 1 were younger than those of the babies in the other groups. First PTH level (F3,1, p = 0.04) and maternal ALP level were highest in group 1. In all the groups, the maternal 25-OHD level was <30 ng/mL. Vitamin D supplementation rate during pregnancy was found to be significantly lower in the severely deficient and deficient groups than in the insufficient group (F1,84, p = 0.01). Conclusion: 25-OHD deficiency continues to be a problem among pregnant women and their babies in Turkey despite the introduction of a supplementation program. This study emphasizes the need to improve maternal 25-OHD status to support maternal and infant health. &nbsp

Pregnancy and Crimean-Congo haemorrhagic fever

AbstractCrimean-Congo Hemorrhagic fever (CCHF) is a potentially fatal viral infection with reported case fatality rates of 5–30%. Humans become infected through tick bites, by contact with a patient with CCHF during the acute phase of infection, or by contact with blood or tissues from viraemic livestock. In this first report in the literature, we present the characteristics of three pregnant women with CCHF infection and the outcome of their babies. Transmission of the CCHF infection could be either intrauterine or perinatal. In endemic regions, CCHF infection should be considered in the differential diagnosis of HELLP syndrome (haemolytic anaemia, elevated liver enzymes, low platelet count), and obstetricians should be familiar with the characteristics of CCHF infection. In the aetiology of necrotising enterocolitis, CCHF should be considered

Arterial Thrombosis Secondary to Cardiac Catheterization in Neonates

Objective: Cardiac catheterization is one of the basic procedures applied in the diagnosis and treatment of cardiovascular diseases. Development of thrombosis is a serious complication of catheterization. In this study, the frequency and the factors affecting the development of arterial thrombosis were prospectively evaluated in neonates who were subjected to diagnostic or interventional cardiac catheterization. Methods: Twenty newborns that received femoral artery catheterization within 6-month period were enrolled in this study. Blood samples were taken for complete blood count, prothrombin, activated partial thromboplastin time, INR ratio and mutations of factorV Leiden, prothrombin 20210A, methylenetetrahydrofolate reductase C667T and A1298 before the procedure. 100 U/kg bolus of heparin was infused during catheterization. 28 U/kg/hour infusion of heparin was given to the patients with clinically suspected thrombosis during first few hours after catheterization. Doppler ultrasonography was performed in all patients within 6 hours after catheterization. Results: The gestational age of patients ranged from 31 to 40 weeks (median 39). Mean birth weight was 2996 ± 589 (1880-4000 gr). Arterial thrombosis was detected in 10 patients by Doppler USG. On development of arterial thrombosis, patient age, gender, diagnosis, treatments, platelet count, hemoglobin, prothrombin and activated partial thromboplastin time values, FactorV Leiden, prothrombin 20210A, methylenetetrahydrofolate reductase C667T and A1298 mutations were found as not impacting (p>0.05). Those who were found to have thrombosis in Doppler ultrasonography had lower INR levels compared to others (p= 0.023). Conclusions: The rate of femoral arterial thrombosis in newborns after catheterization detected by Doppler ultrasonography was 50% in this study. Our data suggest that early clinical assessment for the diagnosis of thrombosis may be misleading but Doppler ultrasonography may be helpful early detection. Further studies are needed to prediction appropriate drugs and/or doses for prevention of thrombosis after arterial catheterization in newborns

Comparing Non-Bayesian Uncertainty Evaluation Methods in Chromosome Classification by Using Deep Neural Networks

Chromosome classification is one of the essential tasks in karyotyping to diagnose genetic abnormalities like some types of cancers and Down syndrome. Deep convolutional neural networks have been widely used in this task, and the accuracy of classification models is exceptionally critical to such sensitive medical diagnoses. However, it is not always possible to meet the expected accuracy rates for diagnosis. So, it is vital to tell how certain or uncertain a model is with its decision. In our work, we use two metrics, entropy and variance, as uncertainty measurements. Moreover, three additional metrics, fail rate, workload, and tolerance range, are used to measure uncertainty metrics’ quality. Four different non-Bayesian methods: deep ensembles, snapshot ensembles, Test Time Augmentation, and Test Time Dropout, are used in experiments. A negative correlation is observed between the accuracy and the uncertainty estimation; the higher the accuracy of the model, the lower the uncertainty. Densenet121 with deep ensembles as the uncertainty evaluation method and variance as the uncertainty metric gives the best outcomes. Densenet121 provides a wider tolerance range and better separation between uncertain and certain predictions. Kromosomklassificering är en av de viktigaste uppgifterna i Karyotyping för att diagnostisera genetiska abnormiteter som vissa typer av cancer och Downs syndrom. Deep Convolutional Neural Networks har använts i stor utsträckning i denna uppgift, och noggrannheten hos klassificeringsmodeller är exceptionellt kritisk för sådana känsliga medicinska diagnoser. Det är dock inte alltid möjligt att uppfylla de förväntade noggrannhetsgraderna för diagnos. Så det är viktigt att berätta hur säker eller osäker en modell är med sitt beslut. Forskning har gjorts för att uppskatta osäkerheten med bayesiska metoder och icke-bayesiska neurala nätverk, medan lite är känt om kvaliteten på osäkerhetsuppskattningar. I vårt arbete använder vi två mått, entropi och varians, som osäkerhetsmätningar. Dessutom används ytterligare tre mätvärden, felfrekvens, arbetsbelastning och toleransintervall för att mäta osäkerhetsmätarnas kvalitet. Fyra olika icke-bayesiska metoder: djupa ensembler, ögonblicksbilder, Test Time Augmentation (TTA) och Test Time Dropout (TTD) används i experiment. En negativ korrelation observeras mellan noggrannheten och osäkerhetsuppskattningen; ju högre noggrannhet modellen är, desto lägre är osäkerheten. Densenet121 med djupa ensembler som osäkerhetsutvärderingsmetod och varians som osäkerhetsmätvärdet ger de bästa resultaten. De ger ett bredare toleransintervall och bättre separation mellan osäkra och vissa förutsägelser

Comparing Non-Bayesian Uncertainty Evaluation Methods in Chromosome Classification by Using Deep Neural Networks

Chromosome classification is one of the essential tasks in karyotyping to diagnose genetic abnormalities like some types of cancers and Down syndrome. Deep convolutional neural networks have been widely used in this task, and the accuracy of classification models is exceptionally critical to such sensitive medical diagnoses. However, it is not always possible to meet the expected accuracy rates for diagnosis. So, it is vital to tell how certain or uncertain a model is with its decision. In our work, we use two metrics, entropy and variance, as uncertainty measurements. Moreover, three additional metrics, fail rate, workload, and tolerance range, are used to measure uncertainty metrics’ quality. Four different non-Bayesian methods: deep ensembles, snapshot ensembles, Test Time Augmentation, and Test Time Dropout, are used in experiments. A negative correlation is observed between the accuracy and the uncertainty estimation; the higher the accuracy of the model, the lower the uncertainty. Densenet121 with deep ensembles as the uncertainty evaluation method and variance as the uncertainty metric gives the best outcomes. Densenet121 provides a wider tolerance range and better separation between uncertain and certain predictions. Kromosomklassificering är en av de viktigaste uppgifterna i Karyotyping för att diagnostisera genetiska abnormiteter som vissa typer av cancer och Downs syndrom. Deep Convolutional Neural Networks har använts i stor utsträckning i denna uppgift, och noggrannheten hos klassificeringsmodeller är exceptionellt kritisk för sådana känsliga medicinska diagnoser. Det är dock inte alltid möjligt att uppfylla de förväntade noggrannhetsgraderna för diagnos. Så det är viktigt att berätta hur säker eller osäker en modell är med sitt beslut. Forskning har gjorts för att uppskatta osäkerheten med bayesiska metoder och icke-bayesiska neurala nätverk, medan lite är känt om kvaliteten på osäkerhetsuppskattningar. I vårt arbete använder vi två mått, entropi och varians, som osäkerhetsmätningar. Dessutom används ytterligare tre mätvärden, felfrekvens, arbetsbelastning och toleransintervall för att mäta osäkerhetsmätarnas kvalitet. Fyra olika icke-bayesiska metoder: djupa ensembler, ögonblicksbilder, Test Time Augmentation (TTA) och Test Time Dropout (TTD) används i experiment. En negativ korrelation observeras mellan noggrannheten och osäkerhetsuppskattningen; ju högre noggrannhet modellen är, desto lägre är osäkerheten. Densenet121 med djupa ensembler som osäkerhetsutvärderingsmetod och varians som osäkerhetsmätvärdet ger de bästa resultaten. De ger ett bredare toleransintervall och bättre separation mellan osäkra och vissa förutsägelser

Investigating Teachers' Attitude and Beliefs about Classroom Management through Their Perceptions of the Quality of the School Life

WOS: 000430725900005This research investigating teachers' attitude and beliefs about classroom management through their perceptions of the quality of school life is a descriptive survey study. A total of 198 teachers (32 from primary schools, 98 from secondary schools and 68 from high schools) working in the Tercan District of Erzincan participated in the study. The data was collected through the "The Quality of School Life Scale (QSLS)" developed by Sari (2007) and "Attitudes and Beliefs on Classroom Control (ABCC) Inventory" developed by Martin, Yin and Baldwin (1998), adopted into Turkish by Ekici (2008). Besides descriptive statistics, the Mann Whitney U-Test and the Kruskal Wallis Test were used for the data analysis. At the end of the study, it was found that the teachers' perceptions about the quality of the school life range in the mid-level. The teachers' perceptions about "Status" and "School Administration" were found to be more positive while their perceptions about students were more negative. With regard to different study cycles, primary school and high school teachers' perceptions and, with regard to different subjects, social science teachers' perceptions about the quality of school life were found to be more positive. The variables of gender and years of experience did not make a significant difference in the teachers' perceptions about the quality of school life. The teachers' attitudes about instructional management were found to be interventionist, while attitudes about people and behavior management were found to be interactionist; with gender, years of experience, study cycles and subjects not causing significant differences in these behaviors. The perception of the quality of school life did not make a significant difference for their attitudes about instruction and behavior management while teachers were detected to be more interactionist towards people management at schools where the quality of life was perceived to be better

De novo translocation t(5;6)(q35;q21) in an infant with Walker-Warburg syndrome

WOS: 000174702900010PubMed: 11932995