Age-stratified Mortality Research Articles

Age, sex, and multi-morbidity stratified mortality risk estimates for adults with cerebral palsy to inform clinical decision making

BackgroundWhile research has provided key insights into mortality rates and risks for individuals with cerebral palsy (CP), clinically useable mortality risk estimates remain unreported for adults with CP, especially by key patient-level factors. ObjectiveThe objective of this study was to generate clinically useable mortality risk estimates among adults with CP to inform clinical decision making. MethodsThis retrospective cohort study, using a fee-for-service Medicare database, identified adults ≥18-years-old with CP from 01/01/2008-12/31/2010 and followed through 12/31/2019 for death. Mortality risk at 1-, 3-, 5-, and 9-year intervals were selected based on common clinical length of time to reasonably benefit from preventive care. Sex-stratified analyses assessed risk estimates by narrow age group (18–25/26-34/35–44/45-54/55–64/65-74/≥75 years old) and multi-morbidity group (Whitney Comorbidity Index score 0–2/3/4–6/≥7). ResultsOf 24,767 adults with CP, n = 12,962 were men (mean [SD] age = 48.3 [15.0] years) and n = 11,805 were women (age = 49.7 [15.8] years). Loss to follow-up was rare. 1-year risk was similar between men and women (3.4 % vs. 3.3 %), but increased slightly more for men than women through 9-years (30.1 % vs. 28.0 %). As expected, the mortality risk increased with older age and higher WCI scores. The probability of death (and survival) is presented per age and multi-morbidity group for men and women with CP. ConclusionsMortality risk estimates were reported at clinically relevant intervals by age, sex, and multi-morbidity status. This information can be used to weigh harm-to-benefit ratios of screening and treatment strategies based on mortality expectancy estimates.

Tobacco smoking, smoking cessation and life expectancy among people with HIV on antiretroviral therapy in South Africa: a simulation modelling study.

As access to effective antiretroviral therapy (ART) has improved globally, tobacco-related illnesses, including cardiovascular disease, cancer and chronic respiratory conditions, account for a growing proportion of deaths among people with HIV (PWH). We estimated the impact of tobacco smoking and smoking cessation on life expectancy among PWH in South Africa. In a microsimulation model, we simulated 18 cohorts of PWH with virologic suppression, each homogenous by sex, initial age (35y/45y/55y) and smoking status (current/former/never). Input parameters were from data sources published between 2008 and 2022. We used South African data to estimate age-stratified mortality hazard ratios: 1.2-2.3 (females)/1.1-1.9 (males) for people with current versus never smoking status; and 1.0-1.3 (females)/1.0-1.5 (males) for people with former versus never smoking status, depending on age at cessation. We assumed smoking status remains unchanged during the simulation; people who formerly smoked quit at model start. Simulated PWH face a monthly probability of disengagement from care and virologic non-suppression. In sensitivity analysis, we varied smoking-associated and HIV-associated mortality risks. Additionally, we estimated the total life-years gained if a proportion of all virologically suppressed PWH stopped smoking. Forty-five-year-old females/males with HIV with virologic suppression who smoke lose 5.3/3.7 life-years compared to PWH who never smoke. Smoking cessation at age 45y adds 3.4/2.4 life-years. Simulated PWH who continue smoking lose more life-years from smoking than from HIV (females, 5.3 vs. 3.0 life-years; males, 3.7 vs. 2.6 life-years). The impact of smoking and smoking cessation increase as smoking-associated mortality risks increase and HIV-associated mortality risks, including disengagement from care, decrease. Model results are most sensitive to the smoking-associated mortality hazard ratio; varying this parameter results in 1.0-5.1 life-years gained from cessation at age 45y. If 10-25% of virologically suppressed PWH aged 30-59y in South Africa stopped smoking now, 190,000-460,000 life-years would be gained. Among virologically suppressed PWH in South Africa, tobacco smoking decreases life expectancy more than HIV. Integrating tobacco cessation interventions into HIV care, as endorsed by the World Health Organization, could substantially improve life expectancy.

Editor's Choice -- Age Stratified Midterm Survival Following Endovascular Versus Open Repair of Juxtarenal Abdominal Aortic Aneurysms

Age stratified mortality was examined following fenestrated endovascular aneurysm repair (F-EVAR) vs. open repair of juxtarenal abdominal aortic aneurysms (AAAs) METHODS: All patients undergoing first time elective F-EVAR and complex open aneurysm repair (c-OAR) for juxtarenal AAA in the Vascular Quality Initiative between 2014 and 2021 were identified. Open repairs were compared with commercially available fenestrated endovascular aneurysm repair and physician modified endografts (PMEGs). Patients were stratified into three age groups (< 65, 65 - 75, > 75 years). Primary outcomes were peri-operative and five year mortality, and inverse probability weighted risk adjustment was performed to account for baseline differences. Overall, 1 961 patients underwent F-EVAR (82% commercial F-EVAR, 18% PMEG) and 3 385 patients underwent c-OAR. Across age groups, the distribution of F-EVAR (vs. c-OAR) was: < 65 years: 23%, 65 - 75 years: 33%, > 75 years: 52%. After adjustment, among patients < 65 years, compared with c-OAR, F-EVAR was associated with similar peri-operative mortality (0.9% vs. 2.1%; hazard ratio [HR] 0.40, 95% confidence interval [CI] 0.07 - 1.44], p= .22), and five year mortality (13% vs. 9.5%; HR 1.44, 95% CI 0.71 - 2.90, p= .31). Among patients aged 65 - 75 years, between juxtarenal AAA repair modalities, compared with c-OAR, F-EVAR was associated with a significantly lower risk of peri-operative mortality (2.2% vs. 5.0%; HR 0.50, 95% CI 0.30 - 0.79, p= .004), and five year mortality (13% vs. 13%; HR 0.94, 95% CI 0.65 - 1.36, p= .74). Similarly, among patients > 75 years, compared with c-OAR, F-EVAR was associated with lower peri-operative mortality (2.2% vs. 6.5%; HR 0.26, 95% CI 0.13 - 0.47, p < .001), but with similar five year mortality (18% vs. 21%; HR 0.83, 95% CI 0.57 - 1.20, p= .31). Among patients with a juxtarenal AAA, F-EVAR was associated with a lower peri-operative mortality compared with c-OAR in patients ≥ 65 years, but was similar in those < 65 years. At five years, F-EVAR was associated with similar mortality in all age groups, though there was a non-significant trend for a higher mortality rate in younger patients.

Age-stratified comparison of prognosis in cardiac resynchronization therapy with or without prophylactic defibrillator for non-ischemic cardiomyopathy - a nationwide cohort study.

Prior studies have suggested that the benefit from primary preventive defibrillator treatment for patients with non-ischemic cardiomyopathy primarily, treated with cardiac resynchronization therapy, may be age-dependent. We aimed to compare age-stratified mortality rates and mode of death in patients with non-ischemic cardiomyopathy who are treated with either primary preventive Cardiac Resynchronization Therapy-defibrillator (CRT-D) or CRT-pacemaker (CRT-P). All patients with non-ischemic cardiomyopathy and CRT-P or primary preventive CRT-D who were implanted in Sweden during the period 2005-2020 were included. Propensity scoring was used to create a matched cohort. Primary outcome was all-cause mortality within five years. 4027 patients were included, 2334 with CRT-P and 1693 with CRT-D. Crude 5-year mortality was 635 (27%) vs. 246 (15%), p < 0.001. In Cox regression analysis, adjusted for clinically relevant covariables, CRT-D was independently associated with higher five-year survival (0.72 [0.61-0.85], p < 0.001). Cardiovascular mortality was similar between groups (62% vs. 64%, p = 0.64), but death from heart failure was more common in the CRT-D group (46% vs. 36%, p = 0.007). In the matched cohort (n = 2414), five-year mortality was 21% (24% versus 16%, p < 0.001). In age-stratified analyses, CRT-P was associated with higher mortality in age-groups <60 years and 70-79 years, but there was no difference in age groups 60-69 years or 80-89 years. In this nationwide registry-based study, patients with CRT-D have better five-year survival compared to patients with CRT-P. The interaction between age and mortality reduction not consistent, but patients with CRT-D aged <60 years had the largest absolute mortality reduction.

Mortality Burden and Life-Years Lost Across the Age Spectrum for Adults Living with CKD.

Younger individuals living with CKD face a lifetime at risk for complications and mortality. Limited data exists to inform individual patients with CKD across the lifespan how their risk for mortality compares with equivalently aged individuals without CKD, particularly at younger ages. The objective of this study is to provide age specific contexts to the risk of mortality associated with a diagnosis of CKD. We created a pooled study cohort using participants with CKD enrolled in the Chronic Renal Insufficiency Cohort along with participants aged 21-75 years included in the 1999-2008 NHANES surveys. Age-stratified mortality rates, along with unadjusted and adjusted hazard ratios (HR) for mortality were generated to compare differences between those with and without CKD. Mean life-years-lost (LYL) relating to CKD were calculated using CDC life tables. A total of 16,725 participants were included. Mortality rates were higher in those with CKD at all ages. The adjusted age stratified hazard ratio (HR) for mortality in those with CKD versus without was highest in the 21-35yr strata (HR [95% CI]: 4.9 [2.8, 8.]) )and lowest in the 65-75yr strata (HR [95% CI]: 2.0 [1.7, 2.3]). Mean LYL secondary to CKD was inversely related with increasing age. Compared to age-matched peers without CKD, the age-stratified risk for mortality and LYL associated with a diagnosis of CKD is highest in younger individuals. Further research is needed to elucidate the societal and personal costs of premature mortality associated with CKD in young adults.

Is austerity a cause of slower improvements in mortality in high-income countries? A panel analysis

BackgroundThe rate of improvement in mortality slowed across many high-income countries after 2010. Following the 2007–08 financial crisis, macroeconomic policy was dominated by austerity as countries attempted to address perceived problems of growing state debt and government budget deficits. This study estimates the impact of austerity on mortality trends for 37 high-income countries between 2000 and 2019. MethodsWe fitted a suite of fixed-effects panel regression models to mortality data (period life expectancy, age-standardised mortality rates (ASMRs), age-stratified mortality rates and lifespan variation). Austerity was measured using the Alesina-Ardagna Fiscal Index (AAFI), Cyclically-Adjusted Primary Balance (CAPB), real indexed Government Expenditure, and Public Social Spending as a % of GDP. Sensitivity analyses varied the lag times, and confined the panel to economic downturns and to non-oil-dominated economies. ResultsSlower improvements, or deteriorations, in life expectancy and mortality trends were seen in the majority of countries, with the worst trends in England & Wales, Estonia, Iceland, Scotland, Slovenia, and the USA, with generally worse trends for females than males. Austerity was implemented across all countries for at least some time when measured by AAFI and CAPB, and for many countries across all four measures (and particularly after 2010). Austerity adversely impacted life expectancy, ASMR, age-specific mortality and lifespan variation trends when measured with Government Expenditure, Public Social Spending and CAPB, but not with AAFI. However, when the dataset was restricted to periods of economic downturn and in economies not dominated hydrocarbon production, all measures of austerity were found to reduce the rate of mortality improvement. InterpretationStalled mortality trends and austerity are widespread phenomena across high-income countries. Austerity is likely to be a cause of stalled mortality trends. Governments should consider alternative economic policy approaches if these harmful population health impacts are to be avoided.

The Impact of SARS-CoV-2 Infection in Patients with Inborn Errors of Immunity: the Experience of the Italian Primary Immunodeficiencies Network (IPINet)

COVID-19 manifestations range from asymptomatic to life-threatening infections. The outcome in different inborn errors of immunity (IEI) is still a matter of debate. In this retrospective study, we describe the experience of the of the Italian Primary Immunodeficiencies Network (IPINet). Sixteen reference centers for adult or pediatric IEI were involved. One hundred fourteen patients were enrolled including 35 pediatric and 79 adult patients. Median age was 32 years, and male-to-female ratio was 1.5:1. The most common IEI were 22q11.2 deletion syndrome in children (26%) and common variable immunodeficiency (CVID) in adults (65%). Ninety-one patients did not require hospital admission, and among these, 33 were asymptomatic. Hospitalization rate was 20.17%. Older age (p 0.004) and chronic lung disease (p 0.0008) represented risk factors for hospitalization. Hospitalized patients mainly included adults suffering from humoral immunodeficiencies requiring immunoglobulin replacement therapy and as expected had lower B cell counts compared to non-hospitalized patients. Infection fatality rate in the whole cohort was 3.5%. Seroconversion was observed is 86.6% of the patients evaluated and in 83.3% of CVID patients. 16.85% of the patients reported long-lasting COVID symptoms. All but one patient with prolonged symptoms were under IgRT. The fatality rate observed in IEI was slightly similar to the general population. The age of the patients who did not survive was lower compared to the general population, and the age stratified mortality in the 50–60 age range considerable exceeded the mortality from 50 to 60 age group of the Italian population (14.3 vs 0.6%; p < 0.0001). We hypothesize that this is due to the fact that comorbidities in IEI patients are very common and usually appear early in life.

Does Cardiovascular Mortality Overtake Cancer Mortality During Cancer Survivorship?: An English Retrospective Cohort Study

BackgroundCancer survivors have a higher risk for developing cardiovascular diseases than the general population. ObjectivesThe aim of this study was to investigate whether cardiovascular mortality overtakes cancer-specific mortality during cancer survivorship and, if so, at what point cardiovascular disease becomes the dominant cause of death. MethodsThis cohort study used linked English electronic health records, including death registration data. The study population included 104,028 adults ≥40 years of age whose first cancer diagnosis was for 1 of 9 common cancers and who were alive and followed up at least 1 year after diagnosis. Age-stratified mortality rates were estimated from cardiovascular disease or cancer by predicting from Poisson models incorporating categorical age at diagnosis and time since diagnosis. Where cardiovascular disease mortality overtook cancer mortality, the crossover point was estimated using interpolation. ResultsMortality from cardiovascular causes overtook mortality due to the primary cancer at 2 to 11 years after cancer diagnosis in survivors of all 9 cancer types ≥80 years of age at diagnosis and after 5 to 17 years in survivors of 7 cancer types 60 to 79 years of age at diagnosis. Cardiovascular mortality overtook all cancer mortality for 6 and 2 cancer sites in the ≥80-year and 60- to 79-year age groups, respectively, over a longer time period. Cardiovascular mortality did not overtake cancer mortality during the observation period in patients aged 40 to 59 years, except among survivors of uterine cancer. ConclusionsIn older survivors of 9 common cancers, cardiovascular mortality becomes dominant over mortality from the primary cancer, though not always over total cancer mortality, as time passes since cancer diagnosis.

On assessing excess mortality in Germany during the COVID-19 pandemic

Coronavirus disease 2019 (COVID-19) is associated with a very high number of casualties in the general population. Assessing the exact magnitude of this number is a non-trivial problem, as relying only on officially reported COVID-19 associated fatalities runs the risk of incurring in several kinds of biases. One of the ways to approach the issue is to compare overall mortality during the pandemic with expected mortality computed using the observed mortality figures of previous years. In this paper, we build on existing methodology and propose two ways to compute expected as well as excess mortality, namely at the weekly and at the yearly level. Particular focus is put on the role of age, which plays a central part in both COVID-19-associated and overall mortality. We illustrate our methods by making use of age-stratified mortality data from the years 2016 to 2020 in Germany to compute age group-specific excess mortality during the COVID-19 pandemic in 2020.

Sixteen years analysis of PM2.5 and mortality in Kuwait

BACKGROUND AND AIM: Middle Eastern desert countries like Kuwait are notoriously known for dramatic dust storms and enormous petrochemical industries affecting ambient air pollution. However, local health authorities have not been able to assess health impacts of air pollution due to limited monitoring networks and lack of historical exposure data. We aimed to estimate the relationship between estimated historical fine particulate matter (PM2.5) and mortality in Kuwait stratified by cause, gender and age. METHODS: We developed a novel approach using machine learning and remote sensing to estimate spatially and temporally resolved daily urban PM2.5 exposures from 2001 to 2016 in the country. We then used over-dispersed generalized additive models to investigate the association with cause-specific, gender- and age-stratified mortality timeseries. RESULTS:There was a total of 70,321 deaths during the study period of 16 years. The average urban PM2.5 was estimated to be 46.2±19.8 µg/m3. A 10 µg/m3 increase in a 5-day moving average of urban PM2.5 was associated with 1.31% (95% CI: 0.56 to 2.07%) increase in all-cause mortality and a 1.15% (0.13 to 2.18%) increase in daily cardiovascular deaths. The corresponding associations among males and females were 1.23% (0.29 to 2.17%) and 1.44% (0.33 to 2.56%), respectively. For the elderly (above 65 years) there was a 1.23% (0.15 to 2.31%) increase in all-cause mortality. The associations were unchanged after adjusting for dust storm days. CONCLUSIONS:We leveraged available pollution, weather and remote sensing data to predict historical PM2.5 with high temporal and spatial resolution. Urban PM2.5 concentrations were above the international regulatory limits. Our findings suggest that, PM2.5 is associated with increased mortality across different strata of the Kuwaiti population. The approach we used can be implemented in other countries that lack historical pollution data or those with insufficient monitoring networks. KEYWORDS: Desert, Dust storm, Kuwait, Middle East, Air Pollution, Machine Learning

Estimating age-specific COVID-19 fatality risk and time to death by comparing population diagnosis and death patterns: Australian data

BackgroundMortality is a key component of the natural history of COVID-19 infection. Surveillance data on COVID-19 deaths and case diagnoses are widely available in the public domain, but they are not used to model time to death because they typically do not link diagnosis and death at an individual level. This paper demonstrates that by comparing the unlinked patterns of new diagnoses and deaths over age and time, age-specific mortality and time to death may be estimated using a statistical method called deconvolution.MethodsAge-specific data were analysed on 816 deaths among 6235 cases over age 50 years in Victoria, Australia, from the period January through December 2020. Deconvolution was applied assuming logistic dependence of case fatality risk (CFR) on age and a gamma time to death distribution. Non-parametric deconvolution analyses stratified into separate age groups were used to assess the model assumptions.ResultsIt was found that age-specific CFR rose from 2.9% at age 65 years (95% CI:2.2 – 3.5) to 40.0% at age 95 years (CI: 36.6 – 43.6). The estimated mean time between diagnosis and death was 18.1 days (CI: 16.9 – 19.3) and showed no evidence of varying by age (heterogeneity P = 0.97). The estimated 90% percentile of time to death was 33.3 days (CI: 30.4 – 36.3; heterogeneity P = 0.85). The final age-specific model provided a good fit to the observed age-stratified mortality patterns.ConclusionsDeconvolution was demonstrated to be a powerful analysis method that could be applied to extensive data sources worldwide. Such analyses can inform transmission dynamics models and CFR assessment in emerging outbreaks. Based on these Australian data it is concluded that death from COVID-19 occurs within three weeks of diagnosis on average but takes five weeks in 10% of fatal cases. Fatality risk is negligible in the young but rises above 40% in the elderly, while time to death does not seem to vary by age.

Estimated impact of maternal vaccination on global paediatric influenza-related in-hospital mortality: A retrospective case series.

BackgroundInfluenza virus infection is an important cause of under-five mortality. Maternal vaccination protects children younger than 3 months of age from influenza infection. However, it is unknown to what extent paediatric influenza-related mortality may be prevented by a maternal vaccine since global age-stratified mortality data are lacking.MethodsWe invited clinicians and researchers to share clinical and demographic characteristics from children younger than 5 years who died with laboratory-confirmed influenza infection between January 1, 1995 and March 31, 2020. We evaluated the potential impact of maternal vaccination by estimating the number of children younger than 3 months with in-hospital influenza-related death using published global mortality estimates.FindingsWe included 314 children from 31 countries. Comorbidities were present in 166 (53%) children and 41 (13%) children were born prematurely. Median age at death was 8·6 (IQR 4·5–16·6), 11·5 (IQR 4·3–24·0), and 15·5 (IQR 7·4–27·0) months for children from low- and lower-middle-income countries (LMICs), upper-middle-income countries (UMICs), and high-income countries (HICs), respectively. The proportion of children younger than 3 months at time of death was 17% in LMICs, 12% in UMICs, and 7% in HICs. We estimated that 3339 annual influenza-related in-hospital deaths occur in the first 3 months of life globally.InterpretationIn our study, less than 20% of children is younger than 3 months at time of influenza-related death. Although maternal influenza vaccination may impact maternal and infant influenza disease burden, additional immunisation strategies are needed to prevent global influenza-related childhood mortality. The missing data, global coverage, and data quality in this study should be taken into consideration for further interpretation of the results.FundingBill & Melinda Gates Foundation.

P054 Risk of death during the 2020 UK COVID-19 epidemic among people with rare diseases compared to the general population

Background/Aims To quantify the risk of death among people with rare autoimmune rheumatic diseases (RAIRD) during the UK 2020 COVID-19 epidemic compared with baseline risk and the risk of death in the general population during COVID-19. Methods A cohort study was performed using data from the National Congenital Anomaly and Rare Disease Registration Service (NCARDRS). Coded diagnoses for RAIRD were identified from Hospital Episode Statistics from 2003 onwards. Previous coding validation work demonstrated our case ascertainment methods had a positive predictive value >85%. ONS published data were used for general population mortality rates. The main outcome measure was age-standardised mortality rates (ASMRs) for all-cause death. Secondary outcome measures were age-sex standardised mortality rates, and age-stratified mortality rates. Results 168,691 people with RAIRD were alive on 1 March 2020. Their median age was 61.7 (IQR 41.5-75.4) years, and 118,379 (70.2%) were female. 1,815 (1.1%) people with RAIRD died during March and April 2020. The ASMR among people with RAIRD was 3669.3 (95% CI 3500.4-3838.1) per 100,000 person-years, which was 1.44 (95% CI 1.42-1.45) times higher than the average ASMR during the same months of the previous 5 years. In the whole population of England, the ASMR during March and April 2020 was 1361.1 (1353.6- 1368.7) per 100,000 people, which was 1.38 times higher than the average ASMR during the same months of the previous 5 years (see related abstract about influenza seasons). Unlike in the general population, sex-specific rates in RAIRD were similar in males and females. When comparing risk of death during COVID-19 to pre-COVID-19, people with RAIRD had an increased risk of death from age 35 upwards, compared to around age 55 upwards in the general population. As the protective effect of being female was not seen in RAIRD, the group at the largest increased risk compared to their pre-COVID-19 risk were women aged 35 upwards. The absolute risk of all-cause death for someone aged 20-29 with RAIRD was similar to someone in the general population aged >20 years older, someone aged 40-49 years with RAIRD similar to someone in the general population 20 years older, and someone aged 60-69 with RAIRD similar to someone in the general population aged >10 years older. Conclusion The excess risk of all-cause death during COVID-19 occurs at a younger age among people with RAIRD than among the general population, and particularly affects females. . We urgently need to quantify how much risk is due to COVID-19 infection and how much due to disruption to healthcare services to inform better guidance about shielding, access to healthcare and vaccine priorities for people with rare diseases. Disclosure M. Rutter: None. P.C. Lanyon: None. E. Peach: None. M.J. Grainge: None. R.B. Hubbard: None. J. Aston: None. M. Bythell: None. S. Stevens: None. F.A. Pearce: None.

Correlation between premorbid IL-6 levels and COVID-19 mortality: Potential role for Vitamin D

There is recent evidence that interleukin-6 (IL-6) levels are elevated in cases of complicated COVID-19, but it is also possible that this cytokine may have a far more important role in the pathogenesis of viral infection. IL-6 is known to be modulated by Vitamin D, and there is preliminary evidence that deficiency of this vitamin is linked to poorer outcomes. To identify whether IL-6 levels prior to infection might predict outcome, early data on COVID-19 mortality from Italy and the UK were compared with previously published results of mean IL-6 levels from these countries as well as from the USA. There was a highly significant correlation (r = 0.9883; p = 0.00025) between age-stratified mortality rates and IL-6 levels from previously published data on healthy individuals. To determine whether Vitamin D may be beneficial at lowering IL-6 levels in patients, a limited analysis of trials examining the relationship between these entities published since 2015 was undertaken. Eight out of 11 studies described a significant lowering effect of Vitamin D on IL-6. Given that IL-6 likely facilitates viral cell entry and replication, levels prior to infection may predict mortality. This provides a rationale for prophylactic and therapeutic measures directed at lowering IL-6, including Vitamin D prescription.

An Empirical Estimate of the Infection Fatality Rate of COVID-19 from the First Italian Outbreak

Background: The coronavirus 2019 (COVID-19) pandemic has been spreading globally for months, yet the infection fatality ratio of the disease is still uncertain. This is partly because of inconsistencies in testing and death reporting standards across countries. Our purpose is to provide accurate estimates which do not rely on testing and death count data directly but only use population level statistics. Methods: We collected demographic and death records data from the Italian Institute of Statistics. We focus on the area in Italy that experienced the initial outbreak of COVID-19 and estimated a Bayesian model fitting age-stratified mortality data from 2020 and previous years. We also assessed the sensitivity of our estimates to alternative assumptions on the proportion of population infected. Findings: We estimate an overall infection fatality rate of 1·29% (95% credible interval [CrI] 0·89-2·01), as well as large differences by age, with a low infection fatality rate of 0·05% for under 60 year old (CrI 0-0·19) and a substantially higher 4·25% (CrI 3·01-6·39) for people above 60 years of age. In our sensitivity analysis, we found that even under extreme assumptions, our method delivered useful information. For instance, even if only 10% of the population were infected, the infection fatality rate would not rise above 0·2% for people under 60. Interpretation: Our empirical estimates based on population level data show a sharp difference in fatality rates between young and old people and firmly rule out overall fatality ratios below 0·5% in populations with more than 30% over 60 years old. Funding Statement: Harvard Business School and Economics Department, NBER, Einaudi Institute for Economics and Finance. Declaration of Interests: GR and MP declare no competing interests.

Coronary Artery Calcium and the Age-Specific Competing Risk of Cardiovascular Versus Cancer Mortality: The Coronary Artery Calcium Consortium

BackgroundCoronary artery calcium (CAC) is a guideline recommended cardiovascular disease (CVD) risk stratification tool that increases with age and is associated with non-cardiovascular disease outcomes including cancer. We sought to define the age-specific change in the association between CAC and cause-specific mortality. MethodsThe Coronary Artery Calcium Consortium includes 59,502 asymptomatic patients age 40-75 without known CVD. Age-stratified mortality rates and parametric survival regression modeling was performed to estimate the age-specific CAC score at which CVD and cancer mortality risk were equal. ResultsThe mean age was 54±8 years (67% men) and there were 2,423 deaths over a mean 12±3 years follow-up. Among individuals with CAC = 0, cancer was the leading cause of death, with low CVD mortality rates for both younger (40-54 years) 0.2/1,000 person-years and older participants (65-75 years) 1.3/1,000 person-years. When CAC ≥400, CVD was consistently the leading cause of death among younger (71% of deaths) and older participants (56% of deaths). The CAC score at which CVD overtook cancer as the leading cause of death increased exponentially with age and was approximately 115 at age 50 and 380 at age 65. ConclusionsRegardless of age, when CAC = 0 cancer was the leading cause of death and the cardiovascular disease mortality rate was low. Our age-specific estimate for the CAC score at which CVD overtakes cancer mortality allows for a more precise approach to synergistic prediction and prevention strategies for CVD and cancer.

Characteristics and outcomes of clusters of multimorbid patients in UK general practice

Abstract Background Current clinical specialities, guidelines and quality of care metrics are organised around single diseases and treatments of multiple conditions are rarely coordinated, resulting in insufficient or even conflicting care. This study uses large scale English general practice (GP) records to identify and characterise clusters of patients based on their multimorbidity to allow better design of health services and highlight groups that require additional interventions. Methods This is a retrospective cohort study that includes multimorbid adult patients (N = 113,211), from a random sample of 391,669 English patients with valid GP records in 2012 where 38 long-term conditions were defined. Latent class analysis, stratified by age groups, was used to identify multimorbidity clusters. Class solutions are validated and associations between multimorbidity clusters, patient characteristics, public health service utilisation and mortality are assessed. Results Poor socioeconomic status is associated with clusters with higher service use and mortality risk. Physical-mental health co-morbidity is a major component of multimorbidity across all age strata. The clusters with highest age-stratified mortality risk in under 65 year olds were linked to alcohol and substance misuse, whereas in over 65 year olds they were linked to cardiovascular disease. The largest cluster in the 85+ years strata (58%) has the lowest number of morbidities, a low degree of service use and mortality. Consistency was seen across identification and validation data. Conclusions We find a clear distinction between morbidity clusters, both in the prevalence of long term conditions within them, and in their associations with outcomes (service use and mortality). Specific health services and interventions might be more effective when targeted on the distinct types of multimorbidity we have identified, with a particular focus on the morbidity clusters associated with the worst patient outcomes. Key messages The first study to derive age stratified multimorbidity clusters from a large GP record system, whose patients are representative of the English population. Knowledge about particularly dangerous clusters of multimorbidity, such as those involving alcohol and drug use in 18–64 years old, and cardiovascular disease in those 65 years or older.

Correction to: Disparities in early mortality among chronic kidney disease patients who transition to peritoneal dialysis and hemodialysis with and without catheters.

In the original publication, age stratified mortality rates were incorrectly added in Fig. 2. The correct Fig. 2 is given below.

Loose Ends in the Epidemiology of the 1918 Pandemic: Explaining the Extreme Mortality Risk in Young Adults.

In the century since the 1918 influenza pandemic, insights have been sought to explain the pandemic’s signature pattern of high death rates in young adults and low death rates in the elderly and infants. Our understanding of the origin and evolution of the pandemic has shifted considerably. We review evidence of the characteristic age-related pattern of death during the 1918 pandemic relative to the “original antigenic sin” hypothesis. We analyze age-stratified mortality data from Copenhagen around 1918 to identify break points associated with unusual death risk. Whereas infants had no meaningful risk elevation, death risk gradually increased, peaking for young adults 20–34 years of age before dropping sharply for adults ages 35–44 years, suggesting break points for birth cohorts around 1908 and 1878. Taken together with data from previous studies, there is strong evidence that those born before 1878 or after 1908 were not at increased risk of dying of 1918 pandemic influenza. Although the peak death risk coincided with the 1889–1892 pandemic, the 1908 and 1878 break points do not correspond with known pandemics. An increasing number of interdisciplinary studies covering fields such as virology, phylogenetics, death, and serology offer exciting insights into patterns and reasons for the unusual extreme 1918 pandemic mortality risk in young adults.

Contemporary Burn Survival

The standard of burn treatment today reflects major advances. We sought to quantitate the impact of these advances on burn survival via age-stratified mortality ratios compared with other reported mortality analyses in burns. Age, percent of the total body surface area (TBSA) burned, presence of inhalation injury, length of stay, and survival status were recorded at admission and at discharge for all new burn admissions between 1989 and 2017. The expected mortality probability was calculated using historical multiple regression techniques and compared with observed data. We developed a prediction model for our observed data. Between 1989 and 2017, there were 10,384 consecutive new burn admissions, with 355 mortalities (median age, 13 years; median percent TBSA burn, 11%). We saw a significant decrease in our observed mortality data compared to historical predictions (p < 0.0001), and a 2% reduction per year in mortality during the 3 decades. The prediction model of mortality for the data is as follows: Pr(dying)= ex/(1+ ex) where x= -6.44 - 0.12 age+ 0.0042 age2 - 0.0000283 age3+ 0.0499 TBSA+ 1.21 Inhalation Injury+ 0.015 third degree TBSA. The reduction in mortality over time may be attributed to successful changes in standard of care protocols in the burn center that improved the outlook for burned individuals, including protocols for management of inhalation injury, nutrition, resuscitation, and early excision and grafting.