Correlation of CT perfusion with MRI brain in symptomatic carotid artery stenosis.

Background: Cerebral white matter disease and large vessel cerebral steno-occlusive are both associated with high incidence of strokes and mortality. There is a lack of literature correlating the cerebral perfusion downstream of a stenotic lesion with white matter changes in the cerebral hemispheres. The aim of this study was to correlate the white matter changes in magnetic resonance imaging (MRI) with computed tomography (CT) perfusion parameters in patients with symptomatic carotid stenosis. Methods: A total of 50 patients with symptomatic carotid stenosis underwent MRI brain and CT Perfusion. Percentage differences in cerebral blood flow (CBF) and mean transit time (MTT) were correlated with symmetric and asymmetric small vessel ischemic disease (SVID) on MRI. Receiver operating characteristic (ROC) curve analysis was performed to determine sensitivity and specificity for different values of percentage CBF and MTT difference. Results: A total of 17 patients with symmetrical SVID had a mean CBF difference of 6.58 (SD of 3.17) and mean MTT difference of 11.61 (SD of 4.32). 33 patients with asymmetrical SVID had a mean CBF difference of 34.73 (SD of 6.87) and mean MTT difference of 44.63 (SD of 9.12). ROC curve analysis showed percentage CBF and MTT differences of 12.5% and 26.5% respectively to be associated with 100% specificity and sensitivity. Conclusion: In patients with symptomatic carotid stenosis, CT perfusion parameters correlate with MRI features of SVID.

Exploratory analysis of the suitability of data from the civil registration system for estimating excess mortality due to COVID-19 in Faridabad district of India.

Background & objectives: Due to shortcomings in death registration and medical certification, the excess death approach is recommended for COVID-19 mortality burden estimation. In this study the data from the civil registration system (CRS) from one district in India was explored for its suitability in the estimation of excess deaths, both directly and indirectly attributable to COVID-19. Methods: All deaths registered on the CRS portal at the selected registrar's office of Faridabad district in Haryana between January 2016 and September 2021 were included. The deaths registered in 2020 and 2021 were compared to previous years (2016-2019), and excess mortality in both years was estimated by gender and age groups as the difference between the registered deaths and historical average month wise during 2016-2019 using three approaches - mean and 95 per cent confidence interval, FORECAST.ETS function in Microsoft Excel and linear regression. To assess the completeness of registration in the district, 150 deaths were sampled from crematoria and graveyards during 2020 and checked for registration in the CRS portal. Agreement in the cause of death (CoD) in CRS with the International Classification of Diseases-10 codes assigned for a subset of 585 deaths after verbal autopsy was calculated. Results: A total of 7017 deaths were registered in 2020, whereas 6792 deaths were registered till 30 September 2021 which represent a 9 and 44 per cent increase, respectively, from the historical average for that period. The highest increase was seen in the age group >60 yr (19% in 2020 and 56% in 2021). All deaths identified in crematoria and graveyards in 2020 had been registered. Observed peaks of all-cause excess deaths corresponded temporally and in magnitude to infection surges in the district. All three approaches gave overlapping estimates of the ratio of excess mortality to reported COVID-19 deaths of 1.8-4 in 2020 and 10.9-13.9 in 2021. There was poor agreement (κ<0.4) between CoD in CRS and that assigned after physician review for most causes, except tuberculosis and injuries. Interpretation & conclusions: CRS data, despite the limitations, appeared to be appropriate for all-cause excess mortality estimation by age and sex but not by cause. There was an increase in death registration in 2020 and 2021 in the district.

Mortality in India established through verbal autopsies (MINErVA): Strengthening national mortality surveillance system in India.

BACKGROUND: Following data access and storage concerns, Government of India transferred the management of its Sample Registration System (SRS) based mortality surveillance (formerly known as the Million Death Study) to an Indian agency. This paper introduces the new system, challenges it faced and its vision for future. METHODS: The All India Institute of Medical Sciences (AIIMS), New Delhi, the new nodal agency, established the "Mortality in India Established through Verbal Autopsy" (MINErVA) platform with state level partners across India in November 2017. The network in its first three years has undertaken capacity building of supervisors conducting verbal autopsy under the SRS, established a panel of trained physician reviewers and developed three IT-based platforms for training, quality control and coding. Coding of VA forms started from January 2015 onwards, and the cause specific mortality fractions (CSMF) of the first 14 185 adult verbal autopsy (VA) records for 2015 were compared with earlier published data for 2010-2013 to check for continuity of system performance. RESULTS: The network consists of 25 institutions and a panel of 676 trained physician reviewers. 916 supervisors have been trained in conducting verbal autopsies. More than 75 000 VA forms have been coded to date. The median time taken for finalizing cause of death on the coding platform is 37 days. The level of physician agreement (67%) and proportion of VA forms requiring adjudication (12%) are consistent with published literature. Preliminary CSMF estimates for 2015 were comparable with those for 2010-2013 and identified same top ten causes of death. In addition to the delay, two major challenges identified for coding were language proficiency of physician reviewers vis-à-vis language of narratives and quality of verbal autopsies. While an initial strategic decision was made to consolidate the system to ensure continuity, future vision of the network is to move towards technology-based solutions including electronic data capture of VAs and its analysis and improving the use of mortality data in decision making. CONCLUSION: MINErVA network is now fully functional and is moving towards achieving global standards. It provides valuable lessons for other developing countries to establish their own mortality surveillance systems.