Predicting 10-year stroke mortality: development and validation of a nomogram.

Predicting long-term stroke mortality is a clinically important and unmet need. We aimed to develop and internally validate a 10-year ischaemic stroke mortality prediction score. In this UK cohort study, 10,366 patients with first-ever ischaemic stroke between January 2003 and December 2016 were followed up for a median (interquartile range) of 5.47 (2.96-9.15) years. A Cox proportional-hazards model was used to predict 10-year post-admission mortality. The predictors associated with 10-year mortality included age, sex, Oxfordshire Community Stroke Project classification, estimated glomerular filtration rate (eGFR), pre-stroke modified Rankin Score, admission haemoglobin, sodium, white blood cell count and comorbidities (atrial fibrillation, coronary heart disease, heart failure, cancer, hypertension, chronic obstructive pulmonary disease, liver disease and peripheral vascular disease). The model was internally validated using bootstrap resampling to assess optimism in discrimination and calibration. A nomogram was created to facilitate application of the score at the point of care. Mean age (SD) was 78.5 ± 10.9 years, 52% female. Most strokes were partial anterior circulation syndromes (38%). 10-year mortality predictors were: total anterior circulation stroke (hazard ratio, 95% confidence intervals) (2.87, 2.62-3.14), eGFR < 15 (1.97, 1.55-2.52), 1-year increment in age (1.04, 1.04-1.05), liver disease (1.50, 1.20-1.87), peripheral vascular disease (1.39, 1.23-1.57), cancers (1.37, 1.27-1.47), heart failure (1.24, 1.15-1.34), 1-point increment in pre-stroke mRS (1.20, 1.17-1.22), atrial fibrillation (1.17, 1.10-1.24), coronary heart disease (1.09, 1.02-1.16), chronic obstructive pulmonary disease (1.13, 1.03-1.25) and hypertension (0.77, 0.72-0.82). Upon internal validation, the optimism-adjusted c-statistic was 0.76 and calibration slope was 0.98. Our 10-year mortality model uses routinely collected point-of-care information. It is the first 10-year mortality score in stroke. While the model was internally validated, further external validation is also warranted.

Shock index predicts up to 90-day mortality risk after intracerebral haemorrhage.

BACKGROUND: Shock index (SI - heart rate/systolic blood pressure) has been studied as a measure of haemodynamic status. We aimed to determine whether SI measures within 72 h of admission were associated with adverse outcomes in intracerebral haemorrhage (ICH). METHODS: Patients were drawn from the Virtual International Stroke Trials Archive-Intracerebral Haemorrhage (VISTA-ICH). Multivariable Cox regressions modelled the relationship between SI (on admission, 24, 48, 72 h) and mortality (at 3-, 7-, and 90-days), 90-day incident pneumonia and cardiovascular events (MACE). Ordinal logistic regressions modelled the relationship between SI and 90-day modified Rankin Scale (mRS). RESULTS: 979 patients were included. Baseline SI was not associated with mortality. 24 h SI > 0.7 was associated with 7-day mortality (hazard ratio (95% confidence interval) = 3.14 (1.37-7.19)). 48 h and 72 h SI > 0.7 were associated with 7-day (4.23 (2.07-8.66) and 3.24 (1.41-7.42) respectively) and 90-day mortality (2.97 (1.82-4.85) and 2.05 (1.26-3.61) respectively). SI < 0.5 at baseline, 48 h and 72 h was associated with decreased pneumonia risk. 24 h and 48 h SI > 0.7was associated with increased MACE risk. 48 h and 72 h SI > 0.7 was associated with increased odds of higher 90-day mRS. CONCLUSION: Higher-than-normal SI subsequent to initial encounter was associated with higher post-ICH mortality at 3, 7, and 90 days. Lower-than-normal SI was associated with a decreased risk of incident pneumonia.

An Ecological Study Assessing the Relationship between Public Health Policies and Severity of the COVID-19 Pandemic.

Reliance on government-led policies have heightened during the COVID-19 pandemic. Further research on the policies associated with outcomes other than mortality rates remains warranted. We aimed to determine associations between government public health policies on the severity of the COVID-19 pandemic. This ecological study including countries reporting ≥25 daily COVID-related deaths until end May 2020, utilised public data on policy indicators described by the Blavatnik school of Government. Associations between policy indicators and severity of the pandemic (mean mortality rate, time to peak, peak deaths per 100,000, cumulative deaths after peak per 100,000 and ratio of mean slope of the descending curve to mean slope of the ascending curve) were measured using Spearman rank-order tests. Analyses were stratified for age, income and region. Among 22 countries, containment policies such as school closures appeared effective in younger populations (rs = -0.620, p = 0.042) and debt/contract relief in older populations (rs = -0.743, p = 0.009) when assessing peak deaths per 100,000. In European countries, containment policies were generally associated with good outcomes. In non-European countries, school closures were associated with mostly good outcomes (rs = -0.757, p = 0.049 for mean mortality rate). In high-income countries, health system policies were generally effective, contrasting to low-income countries. Containment policies may be effective in younger populations or in high-income or European countries. Health system policies have been most effective in high-income countries.

Country-level determinants of the severity of the first global wave of the COVID-19 pandemic: an ecological study.

OBJECTIVE: We aimed to identify the country-level determinants of the severity of the first wave of the COVID-19 pandemic. DESIGN: Ecological study of publicly available data. Countries reporting >25 COVID-19 related deaths until 8 June 2020 were included. The outcome was log mean mortality rate from COVID-19, an estimate of the country-level daily increase in reported deaths during the ascending phase of the epidemic curve. Potential determinants assessed were most recently published demographic parameters (population and population density, percentage population living in urban areas, population >65 years, average body mass index and smoking prevalence); economic parameters (gross domestic product per capita); environmental parameters (pollution levels and mean temperature (January-May); comorbidities (prevalence of diabetes, hypertension and cancer); health system parameters (WHO Health Index and hospital beds per 10 000 population); international arrivals; the stringency index, as a measure of country-level response to COVID-19; BCG vaccination coverage; UV radiation exposure; and testing capacity. Multivariable linear regression was used to analyse the data. PRIMARY OUTCOME: Country-level mean mortality rate: the mean slope of the COVID-19 mortality curve during its ascending phase. PARTICIPANTS: Thirty-seven countries were included: Algeria, Argentina, Austria, Belgium, Brazil, Canada, Chile, Colombia, the Dominican Republic, Ecuador, Egypt, Finland, France, Germany, Hungary, India, Indonesia, Ireland, Italy, Japan, Mexico, the Netherlands, Peru, the Philippines, Poland, Portugal, Romania, the Russian Federation, Saudi Arabia, South Africa, Spain, Sweden, Switzerland, Turkey, Ukraine, the UK and the USA. RESULTS: Of all country-level determinants included in the multivariable model, total number of international arrivals (beta 0.033 (95% CI 0.012 to 0.054)) and BCG vaccination coverage (-0.018 (95% CI -0.034 to -0.002)), were significantly associated with the natural logarithm of the mean death rate. CONCLUSIONS: International travel was directly associated with the mortality slope and thus potentially the spread of COVID-19. Very early restrictions on international travel should be considered to control COVID-19 outbreaks and prevent related deaths.

Impact of Diabetes on Complications, Long Term Mortality and Recurrence in 608,890 Hospitalised Patients with Stroke.

Background: Patients with diabetes mellitus (DM) have been found to be at an increased risk of suffering a stroke. However, research on the impact of DM on stroke outcomes is limited. Objectives: We aimed to examine the influence of DM on outcomes in ischaemic (IS) and haemorrhagic stroke (HS) patients. Methods: We included 608,890 consecutive stroke patients from the Thailand national insurance registry. In-hospital mortality, sepsis, pneumonia, acute kidney injury (AKI), urinary tract infection (UTI) and cardiovascular events were evaluated using logistic regressions. Long-term analysis was performed on first-stroke patients with a determined pathology (n = 398,663) using Royston-Parmar models. Median follow-ups were 4.21 and 4.78 years for IS and HS, respectively. All analyses were stratified by stroke sub-type. Results: Mean age (SD) was 64.3 (13.7) years, 44.9% were female with 61% IS, 28% HS and 11% undetermined strokes. DM was associated with in-hospital death, pneumonia, sepsis, AKI and cardiovascular events (odds ratios ranging from 1.13-1.78, p < 0.01) in both stroke types. In IS, DM was associated with long-term mortality and recurrence throughout the follow-up: HRmax (99% CI) at t = 4108 days: 1.54 (1.27, 1.86) and HR (99% CI) = 1.27(1.23,1.32), respectively. In HS, HRmax (t = 4108 days) for long-term mortality was 2.10 (1.87, 2.37), significant after day 14 post-discharge. HRmax (t = 455) for long-term recurrence of HS was 1.29 (1.09, 1.53), significant after day 116 post-discharge. Conclusions: Regardless of stroke type, DM was associated with in-hospital death and complications, long-term mortality and stroke recurrence.