1,356 research outputs found
Relationship between platelet parameters and sudden sensorineural hearing loss: a systematic review and meta-analysis
Background: Sudden deafness or sudden sensorineural hearing loss (SSNHO is defined as sensorineural hearing loss of greater than 30 dB over 3 contiguous puretone frequencies occurring within 3 days' periodObjective: To investigate the relationship of some platelet parameters including platelet count (PC), mean platelet volume (MPV) and platelet distribution width (PDW) with the occurrence of SSNHL.Data source: A PubMed, Science Direct, Scopus, OVID, EMBASE and Google Scholar search (date last searchedApril2016) search was done. No restrictions of time, language and location were placed.Study selection: All case-control studies which have been studied the relationship of PC, MPV and PDW with the occurrence of SSNHL were included in the meta-analysis.Data extraction: The required data from selected studies including the title, authors, publication date, location of study, sample size of patients and control groups, number of withdrawals, the mean and standard deviation of PC, MPV and PDW for patients and control groups and the result of different tests were extracted and entered to EX CELL.Data synthesis: A total of 9 case-control studies were r found in our search from them 8 studies have reported mean PC, 7 studies have reported mean MPV and 4 studies have reported mean PDW. Our analysis showed that mean PC of patients is 0.03 (-0.14-0.20) unit higher than that of controls with 95% CI which is not statistically significant. Also, mean MPV of patients is 0.31 (-0.03-0.65) unit higher than that of controls with 95% CI which is statistically not significant too. Finally, mean PDW of patients is 0.70 (0.03- 1.37) unit higher than that of controls with 95% CI which is statistically significant.Conclusions: Our study confirmed only the probable relationship of PDW and SSNHL but due to the limited studies on this subject more studies is needed
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
In this work, we investigate the value of uncertainty modeling in 3D
super-resolution with convolutional neural networks (CNNs). Deep learning has
shown success in a plethora of medical image transformation problems, such as
super-resolution (SR) and image synthesis. However, the highly ill-posed nature
of such problems results in inevitable ambiguity in the learning of networks.
We propose to account for intrinsic uncertainty through a per-patch
heteroscedastic noise model and for parameter uncertainty through approximate
Bayesian inference in the form of variational dropout. We show that the
combined benefits of both lead to the state-of-the-art performance SR of
diffusion MR brain images in terms of errors compared to ground truth. We
further show that the reduced error scores produce tangible benefits in
downstream tractography. In addition, the probabilistic nature of the methods
naturally confers a mechanism to quantify uncertainty over the super-resolved
output. We demonstrate through experiments on both healthy and pathological
brains the potential utility of such an uncertainty measure in the risk
assessment of the super-resolved images for subsequent clinical use.Comment: Accepted paper at MICCAI 201
DESCRIPTION OF UTI IN PATIENTS WITH RENAL TRANSPLANTATION ADMITTED IN LABAFINEGAD HOSPITAL FROM 1384 TO 1385
Background: The renal transplantation is now the treatment of choice for ESRD. Urinary tract
is the most common site for infection after kidney transplantation. The different clinical &
microbiological aspects of UTl in renal transplantation. Materials and Methods: In this cross-
sectional study, the clinical manifestation at the time of admission, past medical history, the
time of transplantation & the result of laboratory data including U/A, U/C & CBC of patients
with kidney transplantation & probable UTl were collected & analysed in SPSS 11.5. ..
Development and Validation of a Reversed-Phase HPLC Method for the Estimation of Zolpidem in Bulk Drug and Tablets
In the present study an isocratic reversed-phase high-performance liquid chromatography method was developed for the estimation of zolpidem in bulk drug and pharmaceutical dosage forms. The quantification was carried out on C18 columns. A mixture of acetonitrile-ammonium acetate (pH=8.0, 0.02 M) (60 : 40 v/v) was used as the mobile phase, at flow rate of 1.0 mL/min and the determination wavelength at 245 nm. The retention time of zolpidem was found to be 3–5 min. The validation of the proposed method was carried out for specificity, linearity, accuracy, precision, limit of detection, limit of quantification, and robustness. The linear dynamic range was from 2.5 to 30 μg mL−1. Regression equation was found to be y=0.1416x+0.0183 with correlation coefficient r=0.9996. The percentage recovery obtained for zolpidem was greater than 96.5%. Limit of quantification and limit of detection were found to be 2.5 μg mL−1 and 0.83 μg mL−1, respectively. The developed method can be used for routine quality control analysis of zolpidem in tablet formulations
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Restriction Spectrum Imaging Differentiates True Tumor Progression From Immune-Mediated Pseudoprogression: Case Report of a Patient With Glioblastoma.
Immunotherapy is increasingly used in the treatment of glioblastoma (GBM), with immune checkpoint therapy gaining in popularity given favorable outcomes achieved for other tumors. However, immune-mediated (IM)-pseudoprogression is common, remains poorly characterized, and renders conventional imaging of little utility when evaluating for treatment response. We present the case of a 64-year-old man with GBM who developed pathologically proven IM-pseudoprogression after initiation of a checkpoint inhibitor, and who subsequently developed true tumor progression at a distant location. Based on both qualitative and quantitative analysis, we demonstrate that an advanced diffusion-weighted imaging (DWI) technique called restriction spectrum imaging (RSI) can differentiate IM-pseudoprogression from true progression even when conventional imaging, including standard DWI/apparent diffusion coefficient (ADC), is not informative. These data complement existing literature supporting the ability of RSI to estimate tumor cellularity, which may help to resolve complex diagnostic challenges such as the identification of IM-pseudoprogression
Passive smoking is associated with cognitive and emotional impairment in adolescent girls
It is well established that smoking is associated with impaired mental health and sleep problems. However, the possible effects of passive smoking on cognitive and emotional characteristics have not previously been evaluated in adolescents. We investigated the association between passive smoking and cognitive and emotional function, and sleep patterns in 940 adolescent girls. The girls were divided into 2 groups [305 exposed subjects and 635 non-exposed subjects (the controls)]. The passive smokers had a significantly lower cognitive function and higher depression, aggression, and insomnia scores compared to the control group (P <0.05). No significant difference was detected with respect to day-time sleepiness and sleep apnea. Logistic regression analyses showed that the passive smokers were more likely than the controls to have cognitive impairments, depressive mood, aggressive behavior and insomnia. Adolescent passive smokers had significant differences in their cognitive abilities and emotional function
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