Association and outcomes of bacterial infections with acute coronary syndrome; a cross-sectional study from a tertiary care hospital in Pakistan

Objective: To identify the association between acute infection and acute coronary syndrome, and to evaluate the outcomes in such cases.Methods: The cross-sectional, retrospective, analytical study was conducted at the Aga Khan University Hospital, Karachi, from July to December 2020, and comprised data from January to December 2019 of acute coronary syndrome patients aged \u3e18 years. Data related to demographics, comorbidities, smoking status and history of dyslipidaemia. Binary logistic regression was used to explore the association of infections with acute coronary syndrome. Data was analysed using SPSS 26.Results: Of the 1202 patients with acute coronary syndrome, 189(15.7%) had infection before the coronary event. The mean age of the patients was 68.5±12.4 years, and 97(51.3%) of them were females. Community-acquired pneumonia was found in 105(55.6%) patients, followed by urinary tract infection 64(33.9%) and cellulitis 8(4.2%). For pneumonia, the odds of having non-ST elevated myocardial infarction was 1.1 (95% confidence interval: 0.4-3.0). With urinary tract infections, unstable angina was associated with an odd ratio of 4.2 (95% confidence interval: 1-17.4), and ST elevated myocardial infarction was associated with odd ratio of 3.7 (95% confidence interval: 0.4-31).Conclusions: Bacterial infections were found to be associated with acute coronary syndrome. Bacterial infections with pneumonia and urinary tract infections showed a higher risk of myocardial ischaemia.

Distance Measurement Error Reduction Analysis for the Indoor Positioning System

This paper presents the DME (Distance Measurement Error) estimation analysis for the wireless indoor positioning channel. The channel model for indoor positioning is derived and implemented using 8 WLAN (Wireless Local Area Network) antennas system compliant to IEEE 802.11 a/b/g standard. Channel impairments are derived for the TDOA (Time Difference of Arrival) range estimation. DME calculation is performed over distinct experiments in the TDOA channel profiles using 1,2,4 and 8 antennas deployed system. Analysis for the DME for different antennas is presented. The spiral antenna achieves minimum DME in the range of 1m. Data demographics scattering for the error spread in TDOA channel profile is analyzed to show the error behavior. The effect of increase in number of recordings on DME is shown by the results. Transmitter antennas behavior for DME and their standard deviations are depicted through the results, which minimize the error floor to less than 1 m. This reduction is not achieved in the literature to the best of our knowledge

Distance Measurement Error Reduction Analysis for the Indoor Positioning System

ABSTRACT INTRODUCTION Sputnikovaya In the paper the introduction is followed by the section wireless communication channel model, which describes the model, its impairments and TOA/TDOA channel profile. In Section 3, the deployment of an indoor positioning system and experimental details are discussed. Section 4 includes the results obtained and finally the paper is concluded in Section 5. WIRELESS COMMUNICATION CHANNEL MODEL We can simply model the wireless channel in frequency where β is called phase factor and represented by: where c is the free space speed of light. The received signal will have a time delay τ which depends on range r. The relation between time delay and the distance can be written as follows: The electric field now can be written as: The signal is received through multiple number of paths in a typical wireless communication system. These paths, shown in A typical wireless channel generally comprises these paths and its CIR can be represented by a tapped delay module, shown i

Distribution of Cardiometabolic Risk Factors in School-Aged Children with Excess Body Weight in the Al Ain City, United Arab Emirates: A Cross-Sectional Study

(1) Background: This study aimed to examine the distribution of cardiometabolic risk factors (CMRF) in school-aged children with excess body weight (overweight and obese) in Al Ain City, United Arab Emirates and identify the factors associated with increased cardiovascular risk factors between boys and girls. (2) Methods: A cross-sectional survey of children aged 6–17 years was conducted in Al Ain from 1 August 2019 to 31 December 2020. Binary logistic regression analysis was performed to investigate the relationship between excess body weight and CMRF between the groups and reported odds ratios (OR) with 95% confidence intervals (CI). (3) Results: A total of 966 school-aged children (490 boys and 476 girls) participated in the study, and the mean age of the children was 11.8 ± 2.9 years. The proportions of overweight and obesity were 13.5% and 10.2% in boys and 11.1% and 10.3% in girls. Higher glucose of ≥100 mg/dL (26.4%), triglycerides of ≥150 mg/dL and low-density lipoprotein cholesterol: ≥130 mg/dL (23.2%) were more prevalent in children with excess body weight. These children were at least two times more likely to have higher triglycerides levels, high total cholesterol (≥200 mg/dL) in girls (OR:2.06, 95% CI: 1.01–4.21) and low high-density lipoprotein (<35 mg/dL) in boys (OR: 2.20; 95% CI: 1.12–4.31). (4) Conclusions: Excess body weight in school-aged children was associated with increased CMRF, particularly triglycerides

Role of Anterior Cervical Decompression Fusion (ACDF) and Plating in Patients with Lower Cervical Caries Spine

Objective:  We assessed the neurologic status of patients with cervical spine caries after anterior cervical decompression fusion and plating in terms of muscle power measured by MRC (medical research council) grade and functional status measured by Nurick grade. Materials and Methods:  A descriptive case series study was conducted and 36 subjects with lower cervical spine (C3 – C7) were included with cervical spine caries who needed anterior cervical decompression and plating operated by the department of Neurosurgery, KEMU/Mayo Hospital. The cervical spine TB was confirmed using an MRI plain and contrasted cervical spine. Post-surgical neurological examinations were performed on the 1st, 7th, 21st, and 42nd days and the 3rd and 6th months after surgery. The neurological state was measured in terms of muscle power measured by MRC grades and functional outcome was assessed from Nurick grades. Results:  The mean age of the patients was 37.0 ± 14.4 years. The majority of patients had C5 caries spine (28%) and the least had C7 caries spine (14%). Most of the patients had pre-operative MRC grade 3 (41.7%). The majority had Nurick’s grade 5 (55.6%). 17% of patients had post-operative hoarseness of voice. 31% of the patients had post-operative dysphasia which improved by 3 weeks. 3% developed a new neurological deficit in the form of deterioration of muscle power measured by MRC grade during 6 months’ follow-up time. Conclusion:  All follow-up improvements were statistically significant in terms of pre-operative status

Dyslipidemia, subclinical inflammation, hepatic cholestasis and endothelial dysfunction in schoolchildren with excess fat: A study from the United Arab Emirates.

BackgroundThe impact of obesity on cardiovascular health of young children is still to be fully illustrated. This study measured biomarkers for glycemic control, lipid metabolism, systemic inflammation, endothelial dysfunction, and hepatic cholestasis in schoolchildren. Its main purpose was to determine whether metabolic derangements could be detected in young children with excess fat.MethodThis cross-sectional study involved 967 children in the second, sixth, and tenth grades (median age, 7.3, 11.3, and 15.4 years, respectively). Using the International Obesity Task Force interpretation (IOTF) of body-mass-index (BMI), children were stratified as thin (ResultsPrevalence of BMI≥85th centile among the second graders was 13.1%, sixth graders 42.2%, and tenth graders 33.8%. BMI≥85th centile was associated with a tendency for higher hemoglobin A1c (p≥0.160) and higher blood glucose (p≥0.197). For the second graders, BMI≥85th centile was associated with higher high-sensitivity C-reactive protein (hs-CRP, pConclusionsThe studied children with excess fat had increased risks for developing systemic inflammation, dyslipidemia, endothelial dysfunction, cholestasis, and diabetes. These results suggest that metabolic biomarkers should be included in the routine assessment of children with an overweight problem

Automatic COVID-19 Lung Infection Segmentation through Modified Unet Model

The coronavirus (COVID-19) pandemic has had a terrible impact on human lives globally, with far-reaching consequences for the health and well-being of many people around the world. Statistically, 305.9 million people worldwide tested positive for COVID-19, and 5.48 million people died due to COVID-19 up to 10 January 2022. CT scans can be used as an alternative to time-consuming RT-PCR testing for COVID-19. This research work proposes a segmentation approach to identifying ground glass opacity or ROI in CT images developed by coronavirus, with a modified structure of the Unet model having been used to classify the region of interest at the pixel level. The problem with segmentation is that the GGO often appears indistinguishable from a healthy lung in the initial stages of COVID-19, and so, to cope with this, the increased set of weights in contracting and expanding the Unet path and an improved convolutional module is added in order to establish the connection between the encoder and decoder pipeline. This has a major capacity to segment the GGO in the case of COVID-19, with the proposed model being referred to as "convUnet." The experiment was performed on the Medseg1 dataset, and the addition of a set of weights at each layer of the model and modification in the connected module in Unet led to an improvement in overall segmentation results. The quantitative results obtained using accuracy, recall, precision, dice-coefficient, F1score, and IOU were 93.29%, 93.01%, 93.67%, 92.46%, 93.34%, 86.96%, respectively, which is better than that obtained using Unet and other state-of-the-art models. Therefore, this segmentation approach proved to be more accurate, fast, and reliable in helping doctors to diagnose COVID-19 quickly and efficiently