Implementation of Generic and Efficient Architecture of Elliptic Curve Cryptography over Various GF(p) for Higher Data Security

Elliptic Curve Cryptography (ECC) has recognized much more attention over the last few years and has time-honored itself among the renowned public key cryptography schemes. The main feature of ECC is that shorter keys can be used as the best option for implementation of public key cryptography in resource-constrained (memory, power, and speed) devices like the Internet of Things (IoT), wireless sensor based applications, etc. The performance of hardware implementation for ECC is affected by basic design elements such as a coordinate system, modular arithmetic algorithms, implementation target, and underlying finite fields. This paper shows the generic structure of the ECC system implementation which allows the different types of designing parameters like elliptic curve, Galois prime finite field GF(p), and input type. The ECC system is analyzed with performance parameters such as required memory, elapsed time, and process complexity on the MATLAB platform. The simulations are carried out on the 8th generation Intel core i7 processor with the specifications of 8 GB RAM, 3.1 GHz, and 64-bit architecture. This analysis helps to design an efficient and high performance architecture of the ECC system on Application Specific Integrated Circuit (ASIC) and Field Programmable Gate Array (FPGA).Elliptic Curve Cryptography (ECC) has recognized much more attention over the last few years and has time-honored itself among the renowned public key cryptography schemes. The main feature of ECC is that shorter keys can be used as the best option for implementation of public key cryptography in resource-constrained (memory, power, and speed) devices like the Internet of Things (IoT), wireless sensor based applications, etc. The performance of hardware implementation for ECC is affected by basic design elements such as a coordinate system, modular arithmetic algorithms, implementation target, and underlying finite fields. This paper shows the generic structure of the ECC system implementation which allows the different types of designing parameters like elliptic curve, Galois prime finite field GF(p), and input type. The ECC system is analyzed with performance parameters such as required memory, elapsed time, and process complexity on the MATLAB platform. The simulations are carried out on the 8th generation Intel core i7 processor with the specifications of 8 GB RAM, 3.1 GHz, and 64-bit architecture. This analysis helps to design an efficient and high performance architecture of the ECC system on Application Specific Integrated Circuit (ASIC) and Field Programmable Gate Array (FPGA)

SARS-COV-ATE risk assessment model for arterial thromboembolism in COVID-19

Patients with SARS-CoV-2 infection are at an increased risk of cardiovascular and thrombotic complications conferring an extremely poor prognosis. COVID-19 infection is known to be an independent risk factor for acute ischemic stroke and myocardial infarction (MI). We developed a risk assessment model (RAM) to stratify hospitalized COVID-19 patients for arterial thromboembolism (ATE). This multicenter, retrospective study included adult COVID-19 patients admitted between 3/1/2020 and 9/5/2021. Among 3531 patients from the training cohort, 15.5% developed acute in-hospital ATE, including stroke, MI, and other ATE, compared to 13.4% in the validation cohort. The 16-item final score was named SARS-COV-ATE (Sex: male = 1, Age [40-59 = 2, \u3e 60 = 4], Race: non-African American = 1, Smoking = 1 and Systolic blood pressure elevation = 1, Creatinine elevation = 1; Over the range: leukocytes/lactate dehydrogenase/interleukin-6, B-type natriuretic peptide = 1, Vascular disease (cardiovascular/cerebrovascular = 1), Aspartate aminotransferase = 1, Troponin-I [\u3e 0.04 ng/mL = 1, troponin-I \u3e 0.09 ng/mL = 3], Electrolytes derangement [magnesium/potassium = 1]). RAM had a good discrimination (training AUC 0.777, 0.756-0.797; validation AUC 0.766, 0.741-0.790). The validation cohort was stratified as low-risk (score 0-8), intermediate-risk (score 9-13), and high-risk groups (score ≥ 14), with the incidence of ATE 2.4%, 12.8%, and 33.8%, respectively. Our novel prediction model based on 16 standardized, commonly available parameters showed good performance in identifying COVID-19 patients at risk for ATE on admission

Data of atrial arrhythmias in hospitalized COVID-19 and influenza patients

Atrial arrhythmias (AA) are common in hospitalized COVID-19 patients with limited data on their association with COVID-19 infection, clinical and imaging outcomes. In the related research article using retrospective research data from one quaternary care and five community hospitals, patients aged 18 years and above with positive SARS-CoV-2 polymerase chain reaction test were included. 6927 patients met the inclusion criteria. The data in this article provides demographics, home medications, in-hospital events and COVID-19 treatments, multivariable generalized linear regression regression models using a log link with a Poisson distribution (multi-parameter regression [MPR]) to determine predictors of new-onset AA and mortality in COVID-19 patients, computerized tomography chest scan findings, echocardiographic findings, and International Classification of Diseases-Tenth Revision codes. The clinical outcomes were compared to a propensity-matched cohort of influenza patients. For influenza, data is reported on baseline demographics, comorbid conditions, and in-hospital events. Generalized linear regression models were built for COVID-19 patients using demographic characteristics, comorbid conditions, and presenting labs which were significantly different between the groups, and hypoxia in the emergency room. Statistical analysis was performed using R programming language (version 4, ggplot2 package). Multivariable generalized linear regression model showed that, relative to normal sinus rhythm, history of AA (adjusted relative risk [RR]: 1.38; 95% CI: 1.11-1.71; p = 0.003) and newly-detected AA (adjusted RR: 2.02 95% CI: 1.68-2.43; p \u3c 0.001) were independently associated with higher in-hospital mortality. Age in increments of 10 years, male sex, White race, prior history of coronary artery disease, congestive heart failure, end-stage renal disease, presenting leukocytosis, hypermagnesemia, and hypomagnesemia were found to be independent predictors of new-onset AA in the MPR model. The dataset reported is related to the research article entitled Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19 [Jehangir et al. Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19, American Journal of Cardiology] [1]

Venous thromboembolism in COVID-19 patients and prediction model: a multicenter cohort study

BACKGROUND: Patients with COVID-19 infection are commonly reported to have an increased risk of venous thrombosis. The choice of anti-thrombotic agents and doses are currently being studied in randomized controlled trials and retrospective studies. There exists a need for individualized risk stratification of venous thromboembolism (VTE) to assist clinicians in decision-making on anticoagulation. We sought to identify the risk factors of VTE in COVID-19 patients, which could help physicians in the prevention, early identification, and management of VTE in hospitalized COVID-19 patients and improve clinical outcomes in these patients. METHOD: This is a multicenter, retrospective database of four main health systems in Southeast Michigan, United States. We compiled comprehensive data for adult COVID-19 patients who were admitted between 1st March 2020 and 31st December 2020. Four models, including the random forest, multiple logistic regression, multilinear regression, and decision trees, were built on the primary outcome of in-hospital acute deep vein thrombosis (DVT) and pulmonary embolism (PE) and tested for performance. The study also reported hospital length of stay (LOS) and intensive care unit (ICU) LOS in the VTE and the non-VTE patients. Four models were assessed using the area under the receiver operating characteristic curve and confusion matrix. RESULTS: The cohort included 3531 admissions, 3526 had discharge diagnoses, and 6.68% of patients developed acute VTE (N = 236). VTE group had a longer hospital and ICU LOS than the non-VTE group (hospital LOS 12.2 days vs. 8.8 days, p \u3c 0.001; ICU LOS 3.8 days vs. 1.9 days, p \u3c 0.001). 9.8% of patients in the VTE group required more advanced oxygen support, compared to 2.7% of patients in the non-VTE group (p \u3c 0.001). Among all four models, the random forest model had the best performance. The model suggested that blood pressure, electrolytes, renal function, hepatic enzymes, and inflammatory markers were predictors for in-hospital VTE in COVID-19 patients. CONCLUSIONS: Patients with COVID-19 have a high risk for VTE, and patients who developed VTE had a prolonged hospital and ICU stay. This random forest prediction model for VTE in COVID-19 patients identifies predictors which could aid physicians in making a clinical judgment on empirical dosages of anticoagulation

Changes in Plasma Renin Activity After Renal Artery Sympathetic Denervation.

The renin-angiotensin-aldosterone system plays a key role in blood pressure (BP) regulation and is the target of several antihypertensive medications. Renal denervation (RDN) is thought to interrupt the sympathetic-mediated neurohormonal pathway as part of its mechanism of action to reduce BP. Objectives The purpose of this study was to evaluate plasma renin activity (PRA) and aldosterone before and after RDN and to assess whether these baseline neuroendocrine markers predict response to RDN. Methods Analyses were conducted in patients with confirmed absence of antihypertensive medication. Aldosterone and PRA levels were compared at baseline and 3 months post-procedure for RDN and sham control groups. Patients in the SPYRAL HTN-OFF MED Pivotal trial were separated into 2 groups, those with baseline PRA ≥0.65 ng/ml/h (n = 110) versus <0.65 ng/ml/h (n = 116). Follow-up treatment differences between RDN and sham control groups were adjusted for baseline values using multivariable linear regression models. Results Baseline PRA was similar between RDN and control groups (1.0 ± 1.1 ng/ml/h vs. 1.1 ± 1.1 ng/ml/h; p = 0.37). Change in PRA at 3 months from baseline was significantly greater for RDN compared with control subjects (-0.2 ± 1.0 ng/ml/h; p = 0.019 vs. 0.1 ± 0.9 ng/ml/h; p = 0.14), p = 0.001 for RDN versus control subjects, and similar differences were seen for aldosterone: RDN compared with control subjects (-1.2 ± 6.4 ng/dl; p = 0.04 vs. 0.4 ± 5.4 ng/dl; p = 0.40), p = 0.011. Treatment differences at 3 months in 24-h and office systolic blood pressure (SBP) for RDN versus control patients were significantly greater for patients with baseline PRA ≥0.65 ng/ml/h versus <0.65 ng/ml/h, despite similar baseline BP. Differences in office SBP changes according to baseline PRA were also observed earlier at 2 weeks post-RDN. Conclusions Plasma renin activity and aldosterone levels for RDN patients were significantly reduced at 3 months when compared with baseline as well as when compared with sham control. Higher baseline PRA levels were associated with a significantly greater reduction in office and 24-h SBP. (SPYRAL PIVOTAL - SPYRAL HTN-OFF MED Study; NCT02439749)

A NOVEL HYBRID SCHEME FOR CONTENTION MINIMIZATION IN OPTICAL BURST SWITCHED NETWORK

In Optical Burst Switched (OBS) Networks, data is transported in a bufferless network and hence there is fair amount of possibility of contention among the data bursts. This occurs when multiple bursts contend for the same link. The existing reactive contention resolution schemes attempt to address issue of contention without making any efforts to minimize the occurrences of contention in the network. Also, the existing proactive contention minimization schemes fail to provide improvement in contention loss at a very high load. Therefore, we are presenting new scheme for reducing the occurrence of contention in OBS network and it is known as Dynamic Hybrid Cluster and Deflection Feedback (DHCF) scheme. In proposed DHCF scheme entire OBS network is partitioned into many small clusters. In each cluster, one node acts as cluster head for gathering the information of resources in the network. The contention is minimized using clustering approach and it can be further improved with the help of deflection feedback mechanism. A performance metrics is considered to evaluate merits of the proposed DHCF scheme and its effects on overall network performance. Also, the comparison of the performance of the DHCF scheme with limited hybrid deflection and retransmission (LHDR) scheme and dynamic hybrid retransmission in deflection routing (DHRD) scheme is made. The simulation results show that the proposed scheme gives improvement in Burst Loss Probability (BLP) in the range of 31% to 38% and delay improvement in the range of 64% to 74% on vBSN network. The vBSN is network topology

3D-PAST: Risk Assessment Model for Predicting Venous Thromboembolism in COVID-19

Hypercoagulability is a recognized feature in SARS-CoV-2 infection. There exists a need for a dedicated risk assessment model (RAM) that can risk-stratify hospitalized COVID-19 patients for venous thromboembolism (VTE) and guide anticoagulation. We aimed to build a simple clinical model to predict VTE in COVID-19 patients. This large-cohort, retrospective study included adult patients admitted to four hospitals with PCR-confirmed SARS-CoV-2 infection. Model training was performed on 3531 patients hospitalized between March and December 2020 and validated on 2508 patients hospitalized between January and September 2021. Diagnosis of VTE was defined as acute deep vein thrombosis (DVT) or pulmonary embolism (PE). The novel RAM was based on commonly available parameters at hospital admission. LASSO regression and logistic regression were performed, risk scores were assigned to the significant variables, and cutoffs were derived. Seven variables with assigned scores were delineated as: DVT History = 2; High D-Dimer (&gt;500&ndash;2000 ng/mL) = 2; Very High D-Dimer (&gt;2000 ng/mL) = 5; PE History = 2; Low Albumin (&lt;3.5 g/dL) = 1; Systolic Blood Pressure &lt;120 mmHg = 1, Tachycardia (heart rate &gt;100 bpm) = 1. The model had a sensitivity of 83% and specificity of 53%. This simple, robust clinical tool can help individualize thromboprophylaxis for COVID-19 patients based on their VTE risk category

Incidence, Mortality, and Imaging Outcomes of Atrial Arrhythmias in COVID-19

Atrial arrhythmias (AAs) are common in hospitalized patients with COVID-19; however, it remains uncertain if AAs are a poor prognostic factor in SARS-CoV-2 infection. In this retrospective cohort study from 2014 to 2021, we report in-hospital mortality in patients with new-onset AA and history of AA. The incidence of new-onset congestive heart failure (CHF), hospital length of stay and readmission rate, intensive care unit admission, arterial and venous thromboembolism, and imaging outcomes were also analyzed. We further compared the clinical outcomes with a propensity-matched influenza cohort. Generalized linear regression was performed to identify the association of AA with mortality and other outcomes, relative to those without an AA diagnosis. Predictors of new-onset AA were also modeled. A total of 6,927 patients with COVID-19 were included (626 with new-onset AA, 779 with history of AA). We found that history of AA (adjusted relative risk [aRR] 1.38, confidence interval [CI], 1.11 to 1.71, p = 0.003) and new-onset AA (aRR 2.02, 95% CI 1.68 to 2.43, p \u3c0.001) were independent predictors of in-hospital mortality. The incidence of new-onset CHF was 6.3% in history of AA (odds ratio 1.91, 95% CI 1.30 to 2.79, p \u3c0.001) and 11.3% in new-onset AA (odds ratio 4.01, 95% CI 3.00 to 5.35, p \u3c0.001). New-onset AA was shown to be associated with worse clinical outcomes within the propensity-matched COVID-19 and influenza cohorts. The risk of new-onset AA was higher in patients with COVID-19 than influenza (aRR 2.02, 95% CI 1.76 to 2.32, p \u3c0.0001), but mortality associated with new-onset AA was higher in influenza (aRR 12.58, 95% CI 4.27 to 37.06, p \u3c0.0001) than COVID-19 (aRR 1.86, 95% CI 1.55 to 2.22, p \u3c0.0001). In a subset of the patients with COVID-19 for which echocardiographic data were captured, abnormalities were common, including valvular abnormalities (40.9%), right ventricular dilation (29.6%), and elevated pulmonary artery systolic pressure (16.5%); although there was no evidence of a difference in incidence among the 3 groups. In conclusion, new-onset AAs are associated with poor clinical outcomes in patients with COVID-19

Risk Stratification for Acute Arterial and Venous Thromboembolism using CHA 2DS 2-VASc Score in Hospitalized COVID-19 Patients: A Multicenter Study

Introduction: Arterial and venous thromboembolism are common complications in COVID-19. Micro-macro thrombosis-related organ dysfunction can confer an increased risk for mortality. The optimal dosage of anticoagulation (AC) in COVID-19 patients remains unclear. Interim data from adaptive randomized control trials (ATTACC, REMAP-CAP, and ACTIV-4a) showed divergent results of therapeutic AC (TAC) versus usual care AC for the primary outcome of organ support free days in hospitalized COVID-19 patients. Components of CHA 2DS 2-VASc, a model originally built for predicting ischemic stroke in atrial fibrillation, are consistent with independent risk factors for COVID-19 severity and mortality. Herein, we analyzed the performance of the CHA 2DS 2-VASc model in hospitalized COVID-19 patients for predicting arterial and venous thromboembolic events, which could potentially aid in risk stratification of hospitalized patients and guide AC dosing. Methods: This is a large, retrospective, multicenter cohort study that included all adult patients from one tertiary care and five community hospitals with PCR-proven SARS-CoV-2 infection between 3/1/2020 and 12/1/2020. The primary composite outcome was acute arterial thromboembolism (ATE) and venous thromboembolism (VTE). We identified patients with ATE [cerebrovascular accident (CVA), myocardial infarction (MI) including both ST-segment elevation MI and non-ST-segment elevation MI], and VTE [deep vein thrombosis (DVT) and pulmonary embolism (PE)] using ICD -10 codes. Mean and standard deviation were reported for continuous variables; proportions were reported for categorical variables. To compare the groups, the Chi-square test was used for categorical variables, and the t-test was used for continuous variables. CHA 2DS 2-VASc scores were calculated on admission and were used as a measure of the predictive accuracy of the scoring system. Sensitivity and specificity with different cut-offs of CHA 2DS 2-VASc scores were calculated. All statistical tests were 2-sided with an α (significance) level of 0.05. All data were analyzed using R version 4.0.5. Results: Among 3526 patients, a total of 619 patients had thromboembolic events: 383 had ATE and 236 had VTE. Of 383 patients who had ATE, 350 patients were found to have acute MI, 48 had CVA, and 15 had both MI and CVA. In patients with VTE, 134 had DVT, 168 had PE, and 66 had both DVT and PE (Figure 1). We analyzed the primary composite outcome of ATE and VTE (group 1) vs no ATE and VTE (group 2). Baseline characteristics are included in Table 1. The in-patient all-cause mortality rate was 28.4% in group 1 vs 12.6% in group 2 (p\u3c0.001). The mean hospital length of stay was 12.3 days in group 1 vs 8.8 days in group 2 (p\u3c0.001). Group 1 had a mean CHA 2DS 2-VASc score of 3.3 ±1.6. vs 2.7±1.7 in group 2 (p\u3c0.001) (Figure 2). At CHA 2DS 2-VASc scores of 3 and 4, the model had a specificity of 46% and 67% and sensitivity of 68% and 42% respectively for predicting ATE/VTE. The CHA 2DS 2-VASc score of 5 had a specificity of 86% and sensitivity of 25%. The score of 7 had 98% specificity but 3% sensitivity (Table 2). Conclusion: Our results suggest that the CHA 2DS 2-VASc model for arterial and venous thromboembolism has a moderate performance. The CHA 2DS 2-VASc score of 5 has a high specificity, though low sensitivity, for predicting thromboembolism. The CHA 2DS 2-VASc score can be used as an adjunct risk stratification tool to initiate TAC