A thromboembolic model for the efficacy and safety evaluation of combined mechanical and pharmacologic revascularization strategies

BACKGROUND AND PURPOSE: Recanalization strategies mediated by intra-arterial fibrinolytic therapy in combination with mechanical clot disruption may be a more effective treatment approach than either therapy used alone. There are few preclinical animal models to evaluate these strategies. Here we report on a model to simultaneously evaluate both of these treatment approaches. METHODS: Allogeneic clot was injected through the 6 F guide catheter after creating \u3e50% luminal stenosis of the common carotid arteries of New Zealand White rabbits. The stenosis was released after 1 h, allowing sufficient time for clot-vessel wall interaction. Occlusion was confirmed and each vessel was assigned to receive either balloon angioplasty alone, intra-arterial tissue plasminogen activator (tPA, Alteplase, Genentech, San Francisco, California, USA), tPA delivery through prototype balloon infusion wire (NIT Therapeutics, Pittsburgh, Pennsylvania, USA), partial stent deployment or partial stent deployment with locally delivered tPA. The negative control received no treatment. RESULTS: In vivo revascularization Thrombolysis in Cerebral Infarction (TICI) score revealed that the balloon infusion wire achieved a stable and higher revascularization score of TICI 2B, with a lower dose of tPA in comparison with other treatment strategies. All treatment strategies resulted in endothelial denudation and exposure of the internal elastic lamina. CONCLUSIONS: The proposed animal model permits reliable and consistent thromboembolic occlusion of the target vasculature and allows for an assessment of both pharmacologic and mechanical revascularization strategies for acute ischemic stroke

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Preclinical acute ischemic stroke modeling

Preclinical ischemic stroke is at the crossroads in search of reliable and robust simulation models as past experiences with their translation from the laboratory to the standard of clinical care have often been disappointing. The efficacy of neuroprotective agents is still elusive, and the use of thrombolytics alone is limited to the narrow time window of presentation from the onset of the deficit. Hence, the focus has shifted to interventional revascularization to salvage the parenchyma at the risk of infarction. As the burden of disease morbidity and mortality is so enormous, neurointerventionalists have adopted a more aggressive approach to mechanical revascularization with the limited approved tools available-the Penumbra and the MERCI retrieval system, and the recently incorporated stent retrievers. In fact, the interventional space is among the fastest growing fields in stroke research today. Assessing treatment efficacy in these scenarios is infinitely complex as the heterogeneity of the cerebrovasculature, physical and mechanical nature of the occlusive embolus and the time of presentation are all confounders in assessing treatment outcomes. As no single thromboembolic model is apt to address all of these questions, an integrated methodology with a combination of both in vitro and in vivo assessment needs to be adopted. This involves clinically relevant thromboembolic analogs in device evaluation in vascular replicas, thromboembolic stroke induction in large animal gyrencephalic ischemic stroke models for thrombolytic, imaging and neuroprotection research and a native cerebrovascular target for evaluation of the safety and efficacy of mechanical thrombectomy devices

Quantitative evaluation of C-arm CT cerebral blood volume in a canine model of ischemic stroke

BACKGROUND AND PURPOSE: Previous studies have shown the feasibility of assessing qualitative CBV measurements in the angiography suite by using FPD-CBCT systems. We have investigated the correlation of FPD-CBCT CBV lesion volumes to the infarct volume. MATERIALS AND METHODS: Unilateral strokes were created in 7 adult dogs. MR imaging and FPD-CBCT data were obtained after MCA occlusion. FPD-CBCT CBV and ADC maps were generated for all subjects. The animals were sacrificed immediately following the last imaging study to measure infarct volume on histology. The reliability of FPD-CBCT-based lesion volume measurements was compared with those measured histologically by using regression and Bland-Altman analysis. RESULTS: The best correlation (R(2) = 0.72) between lesion volumes assessed with FPD-CBCT and histology was established with a threshold of mean healthy CBV - 2.5 x SD. These results were inferior to the correlation of lesion volumes measured with ADC and histology (R(2) = 0.99). Bland-Altman analysis showed that the agreement of ADC-derived lesion volumes with histology was superior to the agreement of FPD-CBCT-derived lesion volumes with histology. CONCLUSIONS: We correlated FPD-CBCT measurements of CBV and MR ADC lesion volumes with histologically assessed infarct volume. As expected, ADC is a very accurate and precise method for determining the extent of infarction. FPD-CBCT CBV lesion volumes are correlated to the size of the infarct. Improvement of FPD-CBCT image quality provides an opportunity to establish quantitative CBV measurement in the angiography suite

Temporal evolution of susceptibility artifacts from coiled aneurysms on MR angiography: an in vivo canine study

BACKGROUND AND PURPOSE: Intracranial aneurysms treated by coiling have a risk for recurrence, requiring surveillance imaging. MRA has emerged as an attractive technique for postcoiling aneurysm imaging. Previous research has evaluated MR imaging artifacts of the coil mass in vitro. Our aim in this study was to evaluate MR imaging artifacts of coiled aneurysms in vivo with time. MATERIALS AND METHODS: Four sidewall aneurysms were created in each of 4 dogs. Aneurysms were embolized receiving only 1 type of coils. After embolization, the animals were transferred to MR imaging, which included axial 3D TOF MRA (TEs, 3.5, 5, and 6.9 ms), phase-contrast MRA, and coronal CE-MRA. MR imaging studies were repeated at 1, 4, 6, 8, 14, and 28 weeks. We calculated an OEF: OEF = V(A)/V(CM), where the numerator represents the volume of the MR imaging artifacts and the denominator is the true volume of the coil mass measured by 3D RA. RESULTS: OEFs were largest immediately after embolization and showed a gradual decay until approximately 4 weeks, when there was stabilization of the size of the artifacts. By 4 weeks, there was mild coil compaction (average coil mass volume decrease of 7.8%); however, the OEFs decreased by 25% after 4 weeks (P \u3c .001). CONCLUSIONS: MR imaging susceptibility artifacts change with time, being maximal in the postembolization setting and decaying until 4 weeks. The clinical implications of this study are that baseline MRA for comparison with future imaging should be acquired at a minimum of 1 week after the procedure

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundRegular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations.MethodsThe Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds.FindingsThe leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles.InterpretationLong-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere