Increase In Number Of Cases Research Articles

Effects of Varicocele on Serum Testosterone Levels and Changes of Testosterone Levels after Varicocelectomy among Infertile Men: A Prospective Controlled Study

Background: Varicocele repair has been advocated as an option to prevent and treat low serum testosterone, even in men with normal semen quality. The association between clinical varicocele and impaired testosterone production is less clearly understood. Although, the conceptions of the negative impact of clinical varicocele on Leydig cell functions and the beneficial effect of varicocele repair on testosterone production have been proposed for decades. Objective: To examine the hypotheses that clinical varicoceles affect baseline serum total testosterone levels and to study the effects of varicocelectomy on serum testosterone levels and semen quality in infertile men who suffer from varicocele. Patients and Methods: This study included 100 patients (50 control and 50 cases) presented to the General Surgery and Endocrine Surgery Unit Outpatient Clinic at Mansoura University Hospitals with clinical varicocele for primary infertility. The study was conducted during the period between 1st April 2020 and end of March 2021. Results: Regarding preoperative and postoperative testosterone level among the intervention group, there were highly statistically significant increases in total testosterone as well as significant improvement in gonadal functions (significant increase in number of cases with euogonadism) after the operation among the intervention group (P < 0.001). however the percent of improvement was more than among hypogonadal compared to euogonadal. Conclusion: Varicocelectomy was demonstrated to significantly improve both sperm quality (in terms of volume, count, motility and morphology) as well as serum testosterone in infertile men, especially in cases with hypogonadism.

Integrated vaccination and non-pharmaceutical interventions based strategies in Ontario, Canada, as a case study: a mathematical modelling study.

Recently, two coronavirus disease 2019 (COVID-19) vaccine products have been authorized in Canada. It is of crucial importance to model an integrated/combined package of non-pharmaceutical (physical/social distancing) and pharmaceutical (immunization) public health control measures. A modified epidemiological, compartmental SIR model was used and fit to the cumulative COVID-19 case data for the province of Ontario, Canada, from 8 September 2020 to 8 December 2020. Different vaccine roll-out strategies were simulated until 75% of the population was vaccinated, including a no-vaccination scenario. We compete these vaccination strategies with relaxation of non-pharmaceutical interventions. Non-pharmaceutical interventions were supposed to remain enforced and began to be relaxed on 31 January, 31 March or 1 May 2021. Based on projections from the data and long-term extrapolation of scenarios, relaxing the public health measures implemented by re-opening too early would cause any benefits of vaccination to be lost by increasing case numbers, increasing the effective reproduction number above 1 and thus increasing the risk of localized outbreaks. If relaxation is, instead, delayed and 75% of the Ontarian population gets vaccinated by the end of the year, re-opening can occur with very little risk. Relaxing non-pharmaceutical interventions by re-opening and vaccine deployment is a careful balancing act. Our combination of model projections from data and simulation of different strategies and scenarios, can equip local public health decision- and policy-makers with projections concerning the COVID-19 epidemiological trend, helping them in the decision-making process.

Religion and COVID 19 pandemic in India: Risks and Opportunities

As of May 8th, 2020, in India, more than fifty thousand positive cases have been reported. India, with the second largest population in the world will have difficulty in controlling the transmission of SARS-CoV-2 among its population. The Ministry of Health and Family Welfare of India has raised serious issue about the recent outbreak and continuously taking necessary actions to check the rapid ongoing spread of COVID-19. Being a federal nation, both the central as well as state governments are taking many positive measures towards formulating several protocols to achieve this much required goal. In India first SARS-CoV-2 case was reported in state of Kerala on January 30th, 2020 followed by a drastic increase in number of cases. India in now facing double as well as triple mutation of the virus in few cases in second wave of pandemic. Between October 2020 and September 2021, over 5,00,000 deaths are projected by various studies in India. It means that India must need serious additional mitigation measures to prevent huge number of additional deaths [1]

A modelling analysis of the effectiveness of second wave COVID-19 response strategies in Australia

There is a significant challenge in responding to second waves of COVID-19 cases, with governments being hesitant in introducing hard lockdown measures given the resulting economic impact. In addition, rising case numbers reflect an increase in coronavirus transmission some time previously, so timing of response measures is highly important. Australia experienced a second wave from June 2020 onwards, confined to greater Melbourne, with initial social distancing measures failing to reduce rapidly increasing case numbers. We conducted a detailed analysis of this outbreak, together with an evaluation of the effectiveness of alternative response strategies, to provide guidance to countries experiencing second waves of SARS-Cov-2 transmission. An individual-based transmission model was used to (1) describe a second-wave COVID-19 epidemic in Australia; (2) evaluate the impact of lockdown strategies used; and (3) evaluate effectiveness of alternative mitigation strategies. The model was calibrated using daily diagnosed case data prior to lockdown. Specific social distancing interventions were modelled by adjusting person-to-person contacts in mixing locations. Modelling earlier activation of lockdown measures are predicted to reduce total case numbers by more than 50%. Epidemic peaks and duration of the second wave were also shown to reduce. Our results suggest that activating lockdown measures when second-wave case numbers first indicated exponential growth, would have been highly effective in reducing COVID-19 cases. The model was shown to realistically predict the epidemic growth rate under the social distancing measures applied, validating the methods applied. The timing of social distancing activation is shown to be critical to their effectiveness. Data showing exponential rise in cases, doubling every 7–10 days, can be used to trigger early lockdown measures. Such measures are shown to be necessary to reduce daily and total case numbers, and the consequential health burden, so preventing health care facilities being overwhelmed. Early control of second wave resurgence potentially permits strict lockdown measures to be eased earlier.

Coronavirus disease 2019: fundamentals, chronology and vaccine evolution

The coronavirus disease 2019 (COVID-19) is caused by a novel coronavirus, which is recognized as Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The recent pandemic caused by SARS-CoV-2 is a concern of major public health emergency globally. The virus is highly contagious, enters through nasopharyngeal route into lungs and infects respiratory tracts and later disseminate to other organs in the body. If body immune response fails to eliminate or over responds to infection in affected persons, the condition turns to severe acute respiratory syndrome or pneumonia, multiple organ failure, septic shock and finally end-up with life in critical cases. Currently, there are no antiviral drugs available to eradicate the complete infection and the only treatment available to patients with critical illness is providing oxygen supply through ventilators along with few antiviral and anti-inflammatory drugs to relieve from the symptoms. Recently developed COVID-19 vaccines are available to the public in several countries for protecting against SARS-CoV-2. Further, researchers are vigorously being focused on development of novel vaccines, recombinant interferons, monoclonal antibodies against virus, finding of antiviral drugs to block coronaviral specific structural proteins or multiplication in infected persons, drugs for suppression of over production of pro-inflammatory cytokines by the human body and disease mechanisms of virus. However, because of combined treatment strategies and reduced pathogenicity of SARS-CoV-2, the current mortality rate has been reduced to less than 1-1.5% globally from 5 to 6% of initial COVID-19 pandemic. Unfortunately, sudden increase in number of cases in several countries and evolution of new pathogenic strains of SARS-CoV-2 variants from existing strains make another challenging task both for public and scientific communities. Hence, public health officials are recommending public to continue social distancing, avoid contact with infected persons, isolation and quarantine of exposed persons till COVID-19 prevention is under control. Copyright (C) 2021 Wolters Kluwer Health, Inc. All rights reserved.

P0826 - Treatment trends for muscle-invasive bladder cancer in Germany from 2006 to 2018: Increasing case numbers facilitate more high-volume centers

P0826 - Treatment trends for muscle-invasive bladder cancer in Germany from 2006 to 2018: Increasing case numbers facilitate more high-volume centers

Surveillance for SARS-CoV-2 variants of concern in the Australian context.

Surveillance for SARS-CoV-2 variants of concern in the Australian context.

Learning curve of robotic distal and total gastrectomy.

This study aims to assess the learning curve of robotic distal gastrectomy (RDG) and robotic total gastrectomy (RTG) for gastric cancer. Data on consecutive patients who underwent robotic gastrectomy for gastric cancer by five surgeons between March 2010 and August 2019 at two high-volume institutions were collected. The learning curve was determined based on the analyses of operation time and postoperative complications within 30 days. Cumulative sum analysis (CUSUM) and risk-adjusted-CUSUM (RA-CUSUM) were applied to identify the turning points (TPs). A total of 899 consecutive patients were included. The mean number of patients needed to overcome the learning curve for operation time of RDG and RTG were 22 and 20, respectively. The number of patients needed to overcome the learning curve for postoperative complications after RDG and RTG were 23 and 18, respectively. The surgical outcomes in the post-TP group were better than in the pre-TP group and improved as surgeons' experience increased. Also, increased case numbers in RDG promoted the RTG learning process. The present study demonstrated a substantial influence of surgical cumulative volume on improved surgical outcomes in robotic gastrectomy. Increased experience in RDG may help surgeons to achieve proficiency faster in RTG.

Threatening incidence trends of genitourinary small cell cancer.

e17059 Background: Genitourinary localization (GU) is the most frequent extrapulmonary localization of small cell cancer (SCC). The goal of our study was to evaluate incidence trends of GU SCC (bladder (BC) and prostate (PC) in recent years, compare odds ratio (OR) and survival trends. Methods: SEER research data 18 registries, November 2019 Submission (2000-2017) was assessed for SCC histology codes 8041-8043. Patients 20 years and older were included. Age adjusted ratio for 2000 US standard population were used to calculate trends. Race groups were defined as Caucasians (White), African Americans (Black) and Other (included Asians and Native Americans). Stages were defined as localized, regional and distant. Linear regression, chi-square, log-rank test were used to estimate linear trends, OR and hazard ratios (HR). GraphPad Prism 9 (San Diego, CA) was used for analysis. Results: 1423 BC, 544 PC cases were identified. Both BC (R2 0.6151, p 0.0001) and PC (R2 0.8409, p &lt; 0.0001) showed statistically significant (SS) growth of cases. Annual percent change (APC) was 7.2% for PC and 6.8% for BC (p &lt; 0.05 for both groups). PC showed increase number of cases among Caucasians (R2 0.6236, p &lt; 0.0001) and African-Americans (R2 0.3293, p 0.0128). BC showed increase number of cases only among Caucasians (R2 0.8556, p &lt; 0.0001). Caucasian had SS increased OR compared to African Americans and Other for BC (3,503, p 0.0021 and 3.277, p 0.018 respectively). Trend analysis among the disease extend showed that in BC has SS growth was among localized (R2 0.7337, p &lt; 0.0001), regional (R2 0.4212, p 0.0036) and distant (R2 0.7801, &lt; 0.0001). For PC SS growth in number of cases was observed only in regional (R2 0.34565, 0.0109), and distant stage (R2 0.565, p 0.0003). Patients with BC had SS better survival compared to BC (HR 0.69, p &lt; 0.0001). The analysis within both groups showed worse survival with more advanced stage (HR 1.52, p 0.0236 in regional, HR 2.28, p &lt; 0.0001 in distant for PC; HR 1.27, p 0.0038 in regional, HR 2.93, p &lt; 0.0001 in distant for BC). Differentiation of the tumor grade was associated with worse survival in PC group (HR 4.46, p &lt; 0.0001 for poorly differentiated and HR 4.8, P &lt; 0.0001 for undifferentiated compared to moderately differentiated). African American and Other races had better survival compared to Caucasians in patients with BC (HR 0.29, p 0.0021 and HR 0.31, p 0.0018 respectively). Conclusions: GU SCC is a rare type of cancer, that is rapidly growing (APC 7.2% (PC) and 6.8% (BC). The number of cases is growing among Caucasians (BC and PC) and African Americans (PC). Caucasian is a risk factor for developing BC SCC, as well as worse outcomes compared to the other racial groups. The analysis showed that increase of distant stage of GU SCC at the time of diagnosis increase among both BC and PC. Patients with PC had worse survival compared to the BC. Survival tend to be worse in more advanced stages in both groups, but differentiation of the tumor affect survival only in PC patients.

Pakistan Oral Cancer Collaborative: analyzing barriers and obstacles to oral cancer diagnosis, treatment, and prevention in Pakistan

Oral cancer is a global health problem with increasing case numbers worldwide and no significant improvement in prognosis over the last few decades. It is one of the most common cancers and a leading cause of death in Pakistan, although the number reported is significantly underreported owing to the lack of a national cancer repository, and the true magnitude of this challenge is not known. Bilateral discussions and workshops funded by the Global Challenges Research Fund brought together a number of like-minded researchers and clinicians from the United Kingdom and Pakistan to analyze the status quo and plan the future course. This article reviews some of these discussions as well as barriers to oral cancer diagnosis in Pakistan and makes recommendations to investigate the magnitude and develop measures that may help tackle this devastating disease.

A Clinic-Based Quality Improvement Initiative to Increase Screening for Gonorrhea and Chlamydia in Adolescents

BackgroundUniversal screening is a strategy for addressing the limitations of risk-based screening for gonorrhea and chlamydia (GC/CT). This quality improvement (QI) initiative aimed to improve GC/CT screening by implementing universal annual screening for all adolescents ≥ 13 years old. MethodsAt an academic pediatric resident continuity clinic, an interdisciplinary team designed and conducted multiple Plan-Do-Study-Act (PDSA) cycles over one year. The primary aim, and process measure, was to increase the percentage of encounters with screening for GC/CT in the 12 months prior to the encounter to 80%. The secondary outcome measure was rate of detection of GC or CT infection. Further, pulse checks of provider/staff knowledge and adherence were conducted. The balancing measure was denied insurance claims. ResultsThe mean screening rate of 29.2% increased during the project implementation to 65.1% with several bundles of PDSA cycles. There were no cases of gonorrhea detected in the baseline period or implementation period. The case rate of chlamydia was similar during both periods (from 9.7 per 1,000 adolescent encounters to 10.8 per 1,000 adolescent encounters, p = 0.74). There was similarly high provider/staff knowledge about (p = 0.35) and adherence to (p = 0.06) the screening protocol at 6 and 12 months of implementation. There was no increase in percentage of denied insurance claims. ConclusionThis QI initiative doubled rates of GC/CT screening with no statistically significant increase in number of cases.

Test, Trace, and Put on the Blockchain?: A Viewpoint Evaluating the Use of Decentralized Systems for Algorithmic Contact Tracing to Combat a Global Pandemic.

The enormous pressure of the increasing case numbers experienced during the COVID-19 pandemic has given rise to a variety of novel digital systems designed to provide solutions to unprecedented challenges in public health. The field of algorithmic contact tracing, in particular, an area of research that had previously received limited attention, has moved into the spotlight as a crucial factor in containing the pandemic. The use of digital tools to enable more robust and expedited contact tracing and notification, while maintaining privacy and trust in the data generated, is viewed as key to identifying chains of transmission and close contacts, and, consequently, to enabling effective case investigations. Scaling these tools has never been more critical, as global case numbers have exceeded 100 million, as many asymptomatic patients remain undetected, and as COVID-19 variants begin to emerge around the world. In this context, there is increasing attention on blockchain technology as a part of systems for enhanced digital algorithmic contact tracing and reporting. By analyzing the literature that has emerged from this trend, the common characteristics of the designs proposed become apparent. An archetypal system architecture can be derived, taking these characteristics into consideration. However, assessing the utility of this architecture using a recognized evaluation framework shows that the added benefits and features of blockchain technology do not provide significant advantages over conventional centralized systems for algorithmic contact tracing and reporting. From our study, it, therefore, seems that blockchain technology may provide a more significant benefit in other areas of public health beyond contact tracing.

Depression during the COVID-19 pandemic. A retrospective study on depressive disorders among psychiatric patients admitted at “elisabeta doamna” hospital galati, romania

IntroductionIsolation, life changes and increased stress lead to widespread concerns about the effects of the Covid-19 pandemic on psychiatric patients. The rise in depressive disorders is one of the negative effects associated directly and indirectly to the pandemic.ObjectivesThe purpose of this study was to investigate the impact of the COVID-19 pandemic on the prevalence of depressive disorders among the patients admitted to our hospital. The state of pandemia was declared on the 11th of March but it had already become a main stream media subject in our country at the beginning of the month with real life changes for our citizens.MethodsA retrospective study was performed at the Psychiatric Hospital ‘Elisabeta Doamna’ Galati, using the exact same period, between 01.03 and 30.09, in 2019 and 2020. ICD-10 criteria were used and pacients with either F32.x,F33.x or F38.x as discharge diagnosis were included.ResultsIn total, 7638 cases were admitted during the period in 2019, of which 751 (9,83%) had depressive disorders. In comparison with 2020 where out of 4050 admitted patients, the number had risen to 1034 (25,53%) a net increase in total number of cases by 37.6%.ConclusionsAnalysis of the data shows a 2.5 times increase in the percentage of depressive disorders among our patients. Even taking in account the lower admition rates, we have seen a clear shift in the psychiatric profile of the average pacient and this has to be taken into consideration in the long and short term treatment of any psychiatric patient.

Graph modelling for tracking the COVID-19 pandemic spread

The modelling is widely used in determining the best strategies for the mitigation of the impact of infectious diseases. Currently, the modelling of a complex system such as the spread of COVID-19 infection is among the topical issues. The aim of this article is graph-based modelling of the COVID-19 infection spread. The article investigates the studies related to the modelling of COVID-19 pandemic and analyses the factors affecting the spread of the disease and its main characteristics. We propose a conceptual model of COVID-19 epidemic by considering the social distance, the duration of contact with an infected person and their location-based demographic characteristics. Based on the hypothetical scenario of the spread of the virus, a graph model of the process are developed starting from the first confirmed infection case to human-to-human transmission of the virus and visualized by considering the epidemiological characteristics of COVID-19. The application of graph for the pandemic modelling allows for considering multiple factors affecting the epidemiological process and conducting numerical experiments. The advantage of this approach is justified with the fact that it enables the reverse analysis the spread as a result of the dynamic record of detected cases of the infection in the model. This approach allows for to determining undetected cases of infection based on the social distance and duration of contact and eliminating the uncertainty significantly. Note that social, economic, demographic factors, the population density, mental values and etc. affect the increase in number of cases of infection and hence, the research was not able to consider all factors. In future research will analyze multiple factors impacting the number of infections and their use in the models will be considered.

Modelling COVID-19 transmission in Africa: countrywise projections of total and severe infections under different lockdown scenarios

ObjectivesAs of 13 January 2021, there have been 3 113 963 confirmed cases of SARS-CoV-2 and 74 619 deaths across the African continent. Despite relatively lower numbers of cases initially,...

Graph modelling for tracking the COVID-19 pandemic spread

The modelling is widely used in determining the best strategies for the mitigation of the impact of infectious diseases. Currently, the modelling of a complex system such as the spread of COVID-19 infection is among the topical issues. The aim of this article is graph-based modelling of the COVID-19 infection spread. The article investigates the studies related to the modelling of COVID-19 pandemic and analyses the factors affecting the spread of the disease and its main characteristics. We propose a conceptual model of COVID-19 epidemic by considering the social distance, the duration of contact with an infected person and their location-based demographic characteristics. Based on the hypothetical scenario of the spread of the virus, a graph model of the process are developed starting from the first confirmed infection case to human-to-human transmission of the virus and visualized by considering the epidemiological characteristics of COVID-19. The application of graph for the pandemic modelling allows for considering multiple factors affecting the epidemiological process and conducting numerical experiments. The advantage of this approach is justified with the fact that it enables the reverse analysis the spread as a result of the dynamic record of detected cases of the infection in the model. This approach allows for to determining undetected cases of infection based on the social distance and duration of contact and eliminating the uncertainty significantly. Note that social, economic, demographic factors, the population density, mental values and etc. affect the increase in number of cases of infection and hence, the research was not able to consider all factors. In future research will analyze multiple factors impacting the number of infections and their use in the models will be considered.

Learning Curve for Robotic-Assisted Laparoscopic Retroperitoneal Lymph Node Dissection.

Introduction: Robotic retroperitoneal lymph node dissection (R-RPLND) is a challenging procedure. We hypothesized that surgical times and operative complications would decrease as surgeons became more facile with R-RPLND. Materials and Methods: We retrospectively reviewed 121 consecutive R-RPLNDs performed at Naval Medical Center San Diego and Mayo Clinic Arizona by 4 fellowship trained robotic surgeons between 2008 and 2018. Linear regression was used to analyze independent predictors of setup time, operative time, and lymph node counts. Logistic regression was used to analyze open conversions, overall complications, and high-grade complications. Variables included as independent predictors were: sequential case number, surgeon, clinical stage, chemotherapy status, RPLND template, and body mass index. Univariate and multivariate analyses were conducted. Statistical significance was established at α = 0.05. Results: There was no change in setup time with case number (p = 0.317), but differences were noted between surgeons. Operative times decreased with increasing case number (p < 0.001) but were negatively affected by clinical stage III testis cancer (p = 0.029) and history of chemotherapy exposure (p = 0.050). Surgical times are predicted to decrease by 1 hour after 44 cases. Lymph node counts were dependent only on the surgeon. No factors were predictive of open conversions. Fewer overall complications occurred as experience was gained (p = 0.001), but high-grade complications could not be predicted. Conclusions: Consistent with the learning curves shown for other technologically advanced surgical techniques, experience appears to improve surgical times and lower complication rates for R-RPLND.

Infection pattern, case fatality rate and spread of Lassa virus in Nigeria

BackgroundLassa fever (LF) is a zoonotic infectious disease of public concern in Nigeria. The infection dynamics of the disease is not well elucidated in Nigeria. This study was carried out to describe the pattern of infection, case fatality rate and spread of lassa virus (LASV) from 2017 to 2020.MethodsWeekly epidemiological data on LF from December, 2016 to September, 2020 were obtained from Nigeria Centre for Disease Control. The number of confirmed cases and deaths were computed according to months and states. Descriptive statistics was performed and case fatality rate was calculated. Distribution and spread maps of LF over the four years period was performed on ArcMap 10.7.ResultsA total of 2787 confirmed cases and 516 deaths were reported in Nigeria from December, 2016 to September, 2020. Increase in number of cases and deaths were observed with 298, 528, 796 and 1165 confirmed cases and 79, 125, 158 and 158 deaths in 2017, 2018, 2019 and 2020 respectively. Over 60% of the cases were reported in two states, Edo and Ondo states. The LF cases spread from 19 states in 2017 to 32 states and Federal Capital Territory (FCT) in 2020. Ondo state (25.39%) had the highest of deaths rate from LF over the four years. Case fatality rate (CFR) of LF was highest in 2017 (26.5%) with CFR of 23.7, 19.6 and 13.4% in 2018, 2019 and 2020 respectively. The peak of infection was in the month of February for the four years. Infections increases at the onset of dry season in November and decline till April when the wet season sets-in.ConclusionThere is an annual increase in the number of LASV infection across the states in Nigeria. There is need to heighten control strategies through the use of integrated approach, ranging from vector control, health education and early diagnosis.

Adapted Physical Activity to Ensure the Physical and Psychological Well-Being of COVID-19 Patients

The novel coronavirus disease 2019 (COVID-19) has been responsible for a global pandemic involving massive increases in the daily numbers of cases and deaths. Due to the emergency caused by the pandemic, huge efforts have been made to develop COVID-19 vaccines, the first of which were released in December 2020. Effective vaccines for COVID-19 are needed to protect the population, especially healthcare professionals and fragile individuals, such as older people or chronic-disease-affected patients. Physical exercise training generally has health benefits and assists in the prevention of several chronic diseases. Moreover, physical activity improves mental health by reducing anxiety, depression, and negative mood and improving self-esteem. Therefore, the present review aims to provide a detailed view of the literature, presenting updated evidence on the beneficial effects of adapted physical activity, based on personalized and tailor-made exercise, in preventing, treating, and counteracting the consequences of COVID-19.

An evaluation of lipid profile and pro-inflammatory cytokines as determinants of cardiovascular disease in those with diabetes: a study on a Mexican American cohort

Sedentary life styles coupled with high-calorie diets and unhealthy social habits such as smoking, have put an ever-increasing number of people at risk of cardiovascular disorders (CVD), worldwide. A concomitant increase in the prevalence of type 2-diabetes (hyperglycemia), a risk factor for CVD, has further contributed towards escalating CVD-related mortalities. The increase in number of cases of type 2-diabetes underscores the importance of early diagnosis of cardiovascular disease in those with diabetes. In this work, we have evaluated the sensitivity and specificity of dyslipidemia and proinflammatory cytokines to be used as biomarkers for predicting the risk of CVD in those with diabetes. We hypothesize that interplay between dyslipidemia and diabetes-induced low-grade inflammation in those with type 2-diabetes increases the risk of CVD. A total of 215 participants were randomly recruited from the Cameron County Hispanic Cohort (CCHC). Of these, 99% were Mexican Americans living on Texas-Mexico border. Levels of cytokines, adipokines and lipid profile were measured. Cardiovascular disease (CVD) for this study was defined as prior diagnosis of heart attack, angina and stroke, while diabetes was defined by fasting blood glucose (FBG) of > 100 mg/dL and HbA1c of > 6.5, in accordance with American Diabetes Association (ADA) guidelines. Depending on type and distribution of data, various statistical tests were performed. Our results demonstrated higher rates of heart attack (14% vs 11.8%) and stroke (19.8% vs 10%) in those with diabetes as compared to non-diabetes. The odds of having a heart attack were eight times higher in the presence of elevated triglycerides and pro-inflammatory markers (TNFα and IL6) as compared to presence of pro-inflammatory markers only. The odds for heart attack among those with diabetes, increased by 20 fold in presence of high levels of triglycerides, TNFα, and IL6 when coupled with low levels of high-density lipid cholesterol (HDL-C). Lastly, our analysis showed that poorly controlled diabetes, characterized by HbA1c values of > 6.5 increases the odds of stroke by more than three fold. The study quantifies the role of lipid profile and pro-inflammatory markers in combination with standard risk factors towards predicting the risk of CVD in those with type 2-diabetes. The findings from the study can be directly translated for use in early diagnosis of heart disease and guiding interventions leading to a reduction in CVD-associated mortality in those with type 2-diabetes.