ASSESSING RISK INTRODUCED THROUGH A CODE CHANGE

Techniques are presented herein that shift the risk assessment focus during a software development process, away from the traditional end-of-process review (when a new feature is delivered, or an application is deployed) to earlier in the process when developers are actively at work. Such an approach allows a developer to assess the risk that a candidate software change is about to introduce prior to the developer committing that change, providing the developer with time (during the early portion of the process) to revisit the software and eliminate the identified risk. Aspects of the presented techniques leverage elements of a continuous integration (CI) and continuous deployment (CD) facility, the results that are available from existing unit and end-to-end tests, and the collection and analysis of OpenTelemetry (OTEL)-based metrics, events, logs, and traces (MELT) data to deliver security insights

IDENTIFYING ENTERPRISE RISK BASED ON BUSINESS CONTEXT WITH THREAT INTELLIGENCE

Presented herein are techniques that facilitate prioritizing risk mitigation efforts for business-critical services and transactions through the incorporation of a business context into threat intelligence scoring. Under aspects of the presented techniques, traditional threat intelligence tools may be employed to evaluate the risk that is associated with an enterprise asset; the results of such an evaluation may then be augmented with an enterprise-assigned business value for the asset to derive the asset’s business risk; and such a business risk may be leveraged to prioritize risk mitigation efforts, may be combined with other business risks, etc. The above-described process may be referred to herein as Business Risk Management (BRM)

Impact of the 2017 ACC/AHA guidelines on the prevalence of hypertension among Indian adults: Results from a cross-sectional survey

BackgroundThe impact of the 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guidelines for diagnosis and management of hypertension on the prevalence of hypertension in India is unknown.MethodsWe analyzed data from the Cardiac Prevent 2015 survey to estimate the change in the prevalence of hypertension. The JNC8 guidelines defined hypertension as a systolic blood pressure of ≥140 ​mmHg or diastolic blood pressure of ≥90 ​mmHg. The 2017 ACC/AHA guidelines define hypertension as a systolic blood pressure of ≥130 ​mmHg or diastolic blood pressure of ≥80 ​mmHg. We standardized the prevalence as per the 2011 census population of India. We also calculated the prevalence as per the World Health Organization (WHO) World Standard Population (2000-2025).ResultsAmong 180,335 participants (33.2% women), the mean age was 40.6 ​± ​14.9 years (41.1 ​± ​15.0 and 39.7 ​± ​14.7 years in men and women, respectively). Among them, 8,898 (4.9%), 99,791 (55.3%), 35,694 (11.9%), 23,084 (12.8%), 9,989 (5.5%) and 2,878 (1.6%) participants belonged to age group 18-19, 20-44, 45-54, 55-64, 65-74 and ​≥ ​75 years respectively. The prevalence of hypertension according to the JNC8 and 2017 ACC/AHA guidelines was 29.7% and 63.8%, respectively- an increase of 115%. With the 2011 census population of India, this suggests that currently, 486 million Indian adults have hypertension according to the 2017 ACC/AHA guidelines, an addition of 260 million as compared to the JNC8 guidelines.ConclusionAccording to the 2017 ACC/AHA guidelines, 3 in every 5 Indian adults have hypertension

COVID-19 infected ST-Elevation myocardial infarction in India (COSTA INDIA)

Objective: To find out differences in the presentation, management and outcomes of COVID-19 infected STEMI patients compared to age and sex-matched non-infected STEMI patients treated during the same period. Methods: This was a retrospective multicentre observational registry in which we collected data of COVID-19 positive STEMI patients from selected tertiary care hospitals across India. For every COVID-19 positive STEMI patient, two age and sex-matched COVID-19 negative STEMI patients were enrolled as control. The primary endpoint was a composite of in-hospital mortality, re-infarction, heart failure, and stroke. Results: 410 COVID-19 positive STEMI cases were compared with 799 COVID-19 negative STEMI cases. The composite of death/reinfarction/stroke/heart failure was significantly higher among the COVID-19 positive STEMI patients compared with COVID-19 negative STEMI cases (27.1% vs 20.7% p value = 0.01); though mortality rate did not differ significantly (8.0% vs 5.8% p value = 0.13). Significantly lower proportion of COVID-19 positive STEMI patients received reperfusion treatment and primary PCI (60.7% vs 71.1% p value=< 0.001 and 15.4% vs 23.4% p value = 0.001 respectively). Rate of systematic early PCI (pharmaco-invasive treatment) was significantly lower in the COVID-19 positive group compared with COVID-19 negative group. There was no difference in the prevalence of high thrombus burden (14.5% and 12.0% p value = 0.55 among COVID-19 positive and negative patients respectively) Conclusions: In this large registry of STEMI patients, we did not find significant excess in in-hospital mortality among COVID-19 co-infected patients compared with non-infected patients despite lower rate of primary PCI and reperfusion treatment, though composite of in-hospital mortality, re-infarction, stroke and heart failure was higher