Reconsidering the developmental origins of adult disease paradigm: The 'metabolic coordination of childbirth' hypothesis.

In uncomplicated pregnancies, birthweight is inversely associated with adult non-communicable disease (NCD) risk. One proposed mechanism is maternal malnutrition during pregnancy. Another explanation is that shared genes link birthweight with NCDs. Both hypotheses are supported, but evolutionary perspectives address only the environmental pathway. We propose that genetic and environmental associations of birthweight with NCD risk reflect coordinated regulatory systems between mother and foetus, that evolved to reduce risks of obstructed labour. First, the foetus must tailor its growth to maternal metabolic signals, as it cannot predict the size of the birth canal from its own genome. Second, we predict that maternal alleles that promote placental nutrient supply have been selected to constrain foetal growth and gestation length when fetally expressed. Conversely, maternal alleles that increase birth canal size have been selected to promote foetal growth and gestation when fetally expressed. Evidence supports these hypotheses. These regulatory mechanisms may have undergone powerful selection as hominin neonates evolved larger size and encephalisation, since every mother is at risk of gestating a baby excessively for her pelvis. Our perspective can explain the inverse association of birthweight with NCD risk across most of the birthweight range: any constraint of birthweight, through plastic or genetic mechanisms, may reduce the capacity for homeostasis and increase NCD susceptibility. However, maternal obesity and diabetes can overwhelm this coordination system, challenging vaginal delivery while increasing offspring NCD risk. We argue that selection on viable vaginal delivery played an over-arching role in shaping the association of birthweight with NCD risk.

Machine-learning-derived heart and brain age are independently associated with cognition.

BACKGROUND AND PURPOSE: A heart age biomarker has been developed using deep neural networks applied to electrocardiograms. Whether this biomarker is associated with cognitive function was investigated. METHODS: Using 12-lead electrocardiograms, heart age was estimated for a population-based sample (N = 7779, age 40-85 years, 45.3% men). Associations between heart delta age (HDA) and cognitive test scores were studied adjusted for cardiovascular risk factors. In addition, the relationship between HDA, brain delta age (BDA) and cognitive test scores was investigated in mediation analysis. RESULTS: Significant associations between HDA and the Word test, Digit Symbol Coding Test and tapping test scores were found. HDA was correlated with BDA (Pearson's r = 0.12, p = 0.0001). Moreover, 13% (95% confidence interval 3-36) of the HDA effect on the tapping test score was mediated through BDA. DISCUSSION: Heart delta age, representing the cumulative effects of life-long exposures, was associated with brain age. HDA was associated with cognitive function that was minimally explained through BDA.

Associations between serum high-density lipoprotein cholesterol levels and cause-specific mortality in a general population of 345 000 men and women aged 20-79 years.

BACKGROUND: Benefits of elevated high-density lipoprotein cholesterol (HDL-C) levels are challenged by reports demonstrating U-shaped relations between HDL-C levels and all-cause mortality; the association with cause-specific mortality is less studied. METHODS: A total of 344 556 individuals (20-79 years, 52 % women) recruited from population-based health screening during 1985-2003 were followed until the end of 2018 for all-cause and cause-specific mortality by serum HDL-C level at inclusion of <30, 30-39, 40-49, 50-59, 60-69, 70-79, 80-89, 90-99 and >99 mg/dl (< 0.78, 0.78-1.01, 1.04-1.27, 1.30-1.53, 1.55-1.79, 1.81-2.04, 2.07-2.31, 2.33-2.56, >2.56 mmol/L). Hazard ratios (HRs) were adjusted for sex, age, calendar period, smoking, total cholesterol, triglycerides, systolic blood pressure, physical activity, educational length, body mass index and ill health. RESULTS: During a mean follow-up of 22 years, 69 505 individuals died. There were U-shaped associations between HDL-C levels and all-cause, cancer and non-cardiovascular disease/non-cancer mortality (non-CVD/non-cancer), whereas for CVD there was increased risk of death only at lower levels. With HDL-C stratum 50-59 mg/dl (1.30-1.53 mmol/L) as reference, HRs [95% confidence intervals (CIs)] for levels >99 mg/dl (>2.56 mmol/L) were 1.32 (1.21-1.43), 1.05 (0.89-1.24), 1.26 (1.09-1.46) and 1.68 (1.48-1.90) for all-cause, CVD, cancer and non-CVD/non-cancer mortality, respectively. For HDL-C levels <30 mg/dl (0.78 mmol/L), the corresponding HRs (95% CIs) were 1.30 (1.24-1.36), 1.55 (1.44-1.67), 1.14 (1.05-1.23) and 1.19 (1.10-1.29). The mortality from alcoholic liver disease, cancers of mouth-oesophagus-liver, chronic liver diseases, chronic obstructive pulmonary disease, accidents and diabetes increased distinctly with increasing HDL-C above the reference level. HDL-C levels lower than the reference level were mainly associated with increased mortality of ischaemic heart disease (IHD), other CVDs, stomach cancer and diabetes. CONCLUSIONS: Higher HDL-C levels were associated with increased mortality risk of several diseases which also have been associated with heavy drinking, and lower HDL-C levels were associated with increased mortality from IHD, other CVDs, gastric cancer and diabetes.

Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.

Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age ([Formula: see text]), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.

Life history trade-offs associated with exposure to low maternal capital are different in sons compared to daughters: Evidence from a prospective Brazilian birth cohort.

Background: Environmental exposures in early life explain variability in many physiological and behavioural traits in adulthood. Recently, we showed that exposure to a composite marker of low maternal capital explained the clustering of adverse behavioural and physical traits in adult daughters in a Brazilian birth cohort. These associations were strongly mediated by whether or not the daughter had reproduced by the age of 18 years. Using evolutionary life history theory, we attributed these associations to trade-offs between competing outcomes, whereby daughters exposed to low maternal capital prioritised investment in reproduction and defence over maintenance and growth. However, little is known about such trade-offs in sons. Methods: We investigated 2,024 mother-son dyads from the same birth cohort. We combined data on maternal height, body mass index, income, and education into a composite "maternal capital" index. Son outcomes included reproductive status at the age of 18 years, growth trajectory, adult anthropometry, body composition, cardio-metabolic risk, educational attainment, work status, and risky behaviour (smoking, violent crime). We tested whether sons' early reproduction and exposure to low maternal capital were associated with adverse outcomes and whether this accounted for the clustering of adverse outcomes within individuals. Results: Sons reproducing early were shorter, less educated, and more likely to be earning a salary and showing risky behaviour compared to those not reproducing, but did not differ in foetal growth. Low maternal capital was associated with a greater likelihood of sons' reproducing early, leaving school, and smoking. High maternal capital was positively associated with sons' birth weight, adult size, and staying in school. However, the greater adiposity of high-capital sons was associated with an unhealthier cardio-metabolic profile. Conclusion: Exposure to low maternal investment is associated with trade-offs between life history functions, helping to explain the clustering of adverse outcomes in sons. The patterns indicated future discounting, with reduced maternal investment associated with early reproduction but less investment in growth, education, or healthy behaviour. However, we also found differences compared to our analyses of daughters, with fewer physical costs associated with early reproduction. Exposure to intergenerational "cycles of disadvantage" has different effects on sons vs. daughters, hence interventions may have sex-specific consequences.

Obesity Prevalence and Associated Socio-Demographic Characteristics and Health Behaviors in Russia and Norway.

Associations between obesity and socio-demographic and behavioral characteristics vary between populations. Exploring such differences should throw light on factors related to obesity. We examined associations between general obesity (GO, defined by body mass index) and abdominal obesity (AO, defined by waist-to-hip ratio) and sex, age, socio-economic characteristics (education, financial situation, marital status), smoking and alcohol consumption in women and men aged 40-69 years from the Know Your Heart study (KYH, Russia, N = 4121, 2015-2018) and the seventh Tromsø Study (Tromsø7, Norway, N = 17,646, 2015-2016). Age-standardized prevalence of GO and AO was higher in KYH compared to Tromsø7 women (36.7 vs. 22.0% and 44.2 vs. 18.4%, respectively) and similar among men (26.0 vs. 25.7% and 74.8 vs. 72.2%, respectively). The positive association of age with GO and AO was stronger in KYH vs. Tromsø7 women and for AO it was stronger in men in Tromsø7 vs. KYH. Associations between GO and socio-economic characteristics were similar in KYH and Tromsø7, except for a stronger association with living with spouse/partner in KYH men. Smoking had a positive association with AO in men in Tromsø7 and in women in both studies. Frequent drinking was negatively associated with GO and AO in Tromsø7 participants and positively associated with GO in KYH men. We found similar obesity prevalence in Russian and Norwegian men but higher obesity prevalence in Russian compared to Norwegian women. Other results suggest that the stronger association of obesity with age in Russian women is the major driver of the higher obesity prevalence among them compared to women in Norway.

What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks.

Excess mortality has been used to measure the impact of COVID-19 over time and across countries. But what baseline should be chosen? We propose two novel approaches: an alternative retrospective baseline derived from the lowest weekly death rates achieved in previous years and a within-year baseline based on the average of the 13 lowest weekly death rates within the same year. These baselines express normative levels of the lowest feasible target death rates. The excess death rates calculated from these baselines are not distorted by past mortality peaks and do not treat non-pandemic winter mortality excesses as inevitable. We obtained weekly series for 35 industrialized countries from the Human Mortality Database for 2000-2020. Observed, baseline and excess mortalities were measured by age-standardized death rates. We assessed weekly and annual excess death rates driven by the COVID-19 pandemic in 2020 and those related to seasonal respiratory infections in earlier years. There was a distinct geographic pattern with high excess death rates in Eastern Europe followed by parts of the UK, and countries of Southern and Western Europe. Some Asia-Pacific and Scandinavian countries experienced lower excess mortality. In 2020 and earlier years, the alternative retrospective and the within-year excess mortality figures were higher than estimates based on conventional metrics. While the latter were typically negative or close to zero in years without extraordinary epidemics, the alternative estimates were substantial. Cumulation of this "usual" excess over 2-3 years results in human losses comparable to those caused by COVID-19. Challenging the view that non-pandemic seasonal winter mortality is inevitable would focus attention on reducing premature mortality in many countries. As SARS-CoV-2 is unlikely to be the last respiratory pathogen with the potential to cause a pandemic, such measures would also strengthen global resilience in the face of similar threats in the future.

Seroprevalence of antibodies against SARS-CoV-2 in the adult population during the pre-vaccination period, Norway, winter 2020/21.

BackgroundSince March 2020, 440 million people worldwide have been diagnosed with COVID-19, but the true number of infections with SARS-CoV-2 is higher. SARS-CoV-2 antibody seroprevalence can add crucial epidemiological information about population infection dynamics.AimTo provide a large population-based SARS-CoV-2 seroprevalence survey from Norway; we estimated SARS-CoV-2 seroprevalence before introduction of vaccines and described its distribution across demographic groups.MethodsIn this population-based cross-sectional study, a total of 110,000 people aged 16 years or older were randomly selected during November-December 2020 and invited to complete a questionnaire and provide a dried blood spot (DBS) sample.ResultsThe response rate was 30% (31,458/104,637); compliance rate for return of DBS samples was 88% (27,700/31,458). National weighted and adjusted seroprevalence was 0.9% (95% CI (confidence interval): 0.7-1.0). Seroprevalence was highest among those aged 16-19 years (1.9%; 95% CI: 0.9-2.9), those born outside the Nordic countries 1.4% (95% CI: 1.0-1.9), and in the counties of Oslo 1.7% (95% CI: 1.2-2.2) and Vestland 1.4% (95% CI: 0.9-1.8). The ratio of SARS-CoV-2 seroprevalence (0.9%) to cumulative incidence of virologically detected cases by mid-December 2020 (0.8%) was slightly above one. SARS-CoV-2 seroprevalence was low before introduction of vaccines in Norway and was comparable to virologically detected cases, indicating that most cases in the first 10 months of the pandemic were detected.ConclusionFindings suggest that preventive measures including contact tracing have been effective, people complied with physical distancing recommendations, and local efforts to contain outbreaks have been essential.

Socioeconomic inequalities in physiological risk biomarkers and the role of lifestyles among Russians aged 35-69 years.

BACKGROUND: Socioeconomic inequalities in cardiovascular (CVD) health outcomes are well documented. While Russia has one of the highest levels of CVD mortality in the world, the literature on contemporary socio-economic inequalities in biomarker CVD risk factors is sparse. This paper aims to assess the extent and the direction of SEP inequalities in established physiological CVD risk biomarkers, and to explore the role of lifestyle factors in explaining SEP inequalities in physiological CVD risk biomarkers. METHODS: We used cross-sectional data from a general population-based survey of Russians aged 35-69 years living in two cities (n = 4540, Know Your Heart study 2015-18). Logistic models were used to assess the associations between raised physiological risk biomarkers levels (blood pressure levels, cholesterol levels, triglycerides, HbA1C, and C-reactive protein) and socioeconomic position (SEP) (education and household financial constraints) adjusting for age, obesity, smoking, alcohol and health-care seeking behavior. RESULTS: High education was negatively associated with a raised risk of blood pressure (systolic and diastolic) and C-reactive protein for both men and women. High education was positively associated with total cholesterol, with higher HDL levels among women, and with low triglycerides and HbA1c levels among men. For the remaining risk biomarkers, we found little statistical support for SEP inequalities. Adjustment for lifestyle factors, and particularly BMI and waist-hip ratio, led to a reduction in the observed SEP inequalities in raised biomarkers risk levels, especially among women. High financial constraints were weakly associated with high risk biomarkers levels, except for strong evidence for an association with C-reactive protein (men). CONCLUSIONS: Notable differences in risk biomarkers inequalities were observed according to the SEP measure employed. Clear educational inequalities in raised physiological risk biomarkers levels, particularly in blood pressure and C-reactive protein were seen in Russia and are partly explained by lifestyle factors, particularly obesity among women. These findings provide evidence-based information on the need for tackling health inequalities in the Russian population, which may help to further contribute to CVD mortality decline.

Comparing prevalence of chronic kidney disease and its risk factors between population-based surveys in Russia and Norway.

BACKGROUND: Little data exists on the prevalence of chronic kidney disease (CKD) in the Russian population. We aimed to estimate the prevalence of CKD in a population-based study in Russia, compare with a similar study in Norway, and investigate whether differences in risk factors explained between-study differences in CKD. METHODS: We compared age- and sex-standardised prevalence of reduced eGFR (< 60 ml/min/1.73m2 CKD-EPI creatinine equation), albuminuria and or a composite indicator of CKD (one measure of either reduced eGFR or albuminuria) between participants aged 40-69 in the population-based Know Your Heart (KYH) study, Russia (2015-2018 N = 4607) and the seventh Tromsø Study (Tromsø7), Norway (2015-2016 N = 17,646). We assessed the contribution of established CKD risk factors (low education, diabetes, hypertension, antihypertensive use, smoking, obesity) to between-study differences using logistic regression. RESULTS: Prevalence of reduced eGFR or albuminuria was 6.5% (95% Confidence Interval (CI) 5.4, 7.7) in KYH and 4.6% (95% CI 4.0, 5.2) in Tromsø7 standardised for sex and age. Odds of both clinical outcomes were higher in KYH than Tromsø7 (reduced eGFR OR 2.06 95% CI 1.67, 2.54; albuminuria OR 1.54 95% CI 1.16, 2.03) adjusted for sex and age. Risk factor adjustment explained the observed between-study difference in albuminuria (OR 0.92 95% CI 0.68, 1.25) but only partially reduced eGFR (OR 1.42 95% CI 1.11, 1.82). The strongest explanatory factors for the between-study difference was higher use of antihypertensives (Russian sample) for reduced eGFR and mean diastolic blood pressure for albuminuria. CONCLUSIONS: We found evidence of a higher burden of CKD within the sample from the population in Arkhangelsk and Novosibirsk compared to Tromsø, partly explained by between-study population differences in established risk factors. In particular hypertension defined by medication use was an important factor associated with the higher CKD prevalence in the Russian sample.

Comparison of methods for predicting COVID-19-related death in the general population using the OpenSAFELY platform.

BACKGROUND: Obtaining accurate estimates of the risk of COVID-19-related death in the general population is challenging in the context of changing levels of circulating infection. METHODS: We propose a modelling approach to predict 28-day COVID-19-related death which explicitly accounts for COVID-19 infection prevalence using a series of sub-studies from new landmark times incorporating time-updating proxy measures of COVID-19 infection prevalence. This was compared with an approach ignoring infection prevalence. The target population was adults registered at a general practice in England in March 2020. The outcome was 28-day COVID-19-related death. Predictors included demographic characteristics and comorbidities. Three proxies of local infection prevalence were used: model-based estimates, rate of COVID-19-related attendances in emergency care, and rate of suspected COVID-19 cases in primary care. We used data within the TPP SystmOne electronic health record system linked to Office for National Statistics mortality data, using the OpenSAFELY platform, working on behalf of NHS England. Prediction models were developed in case-cohort samples with a 100-day follow-up. Validation was undertaken in 28-day cohorts from the target population. We considered predictive performance (discrimination and calibration) in geographical and temporal subsets of data not used in developing the risk prediction models. Simple models were contrasted to models including a full range of predictors. RESULTS: Prediction models were developed on 11,972,947 individuals, of whom 7999 experienced COVID-19-related death. All models discriminated well between individuals who did and did not experience the outcome, including simple models adjusting only for basic demographics and number of comorbidities: C-statistics 0.92-0.94. However, absolute risk estimates were substantially miscalibrated when infection prevalence was not explicitly modelled. CONCLUSIONS: Our proposed models allow absolute risk estimation in the context of changing infection prevalence but predictive performance is sensitive to the proxy for infection prevalence. Simple models can provide excellent discrimination and may simplify implementation of risk prediction tools.

Nitrate and nitrite contamination in drinking water and cancer risk: A systematic review with meta-analysis.

BACKGROUND: Pollution of water sources, largely from wide-scale agricultural fertilizer use has resulted in nitrate and nitrite contamination of drinking water. The effects on human health of raised nitrate and nitrite levels in drinking water are currently unclear. OBJECTIVES: We conducted a systematic review of peer-reviewed literature on the association of nitrate and nitrite in drinking water with human health with a specific focus on cancer. METHODS: We searched eight databases from 1 January 1990 until 28 February 2021. Meta-analyses were conducted when studies had the same exposure metric and outcome. RESULTS: Of 9835 studies identified in the literature search, we found 111 studies reporting health outcomes, 60 of which reported cancer outcomes (38 case-control studies; 12 cohort studies; 10 other study designs). Most studies were set in the USA (24), Europe (20) and Taiwan (14), with only 3 studies from low and middle-income countries. Nitrate exposure in water (59 studies) was more commonly investigated than nitrite exposure (4 studies). Colorectal (15 studies) and gastric (13 studies) cancers were the most reported. In meta-analyses (4 studies) we identified a positive association of nitrate exposure with gastric cancer, OR = 1.91 (95%CI = 1.09-3.33) per 10 mg/L increment in nitrate ion. We found no association of nitrate exposure with colorectal cancer (10 studies; OR = 1.02 [95%CI = 0.96-1.08]) or cancers at any other site. CONCLUSIONS: We identified an association of nitrate in drinking water with gastric cancer but with no other cancer site. There is currently a paucity of robust studies from settings with high levels nitrate pollution in drinking water. Research into this area will be valuable to ascertain the true health burden of nitrate contamination of water and the need for public policies to protect human health.

Seroprevalence of SARS-Cov-2 Antibodies in Adults, Arkhangelsk, Russia.

Population-based data on coronavirus disease in Russia and on the immunogenicity of the Sputnik V vaccine are sparse. In a survey of 1,080 residents of Arkhangelsk 40-75 years of age, 65% were seropositive for IgG. Fifteen percent of participants had been vaccinated; of those, 97% were seropositive.

Evidence of large systematic differences between countries in assigning ischaemic heart disease deaths to myocardial infarction: the contrasting examples of Russia and Norway.

BACKGROUND: There is considerable variation in mortality rates from myocardial infarction (MI) across high-income countries, some of which may be artefactual. METHODS: Time trends in mortality rates from ischaemic heart disease (IHD) and MI were analysed for a set of high-income countries from the end of the 1970s. Using individual-level mortality data from Russia (2005-2017) and Norway (2005-2016), we investigated factors associated with the proportion of total IHD deaths certified as due to MI. RESULTS: In most countries, MI mortality rates have dramatically declined from the 1970s. However, the share of MI in total IHD deaths varies substantially across countries. In Russia, only 12% of IHD deaths had MI assigned as the underlying cause vs 63% in Norway. IHD deaths occurring outside of hospital without autopsy were far less likely to be assigned as MI in Russia (2%) than in Norway (59%). CONCLUSIONS: Although established international criteria for MI require specific clinical or post-mortem evidence, it appears that certifying specialists in different countries may interpret these criteria differently. At one extreme, Russian doctors may only assign MI as a cause of death when there is specific pathophysiological evidence. At the other extreme, their counterparts in Norway may be willing to specify MI as the cause even when this evidence is not available. Internationally established criteria for MI diagnosis are challenging to apply for out-of-hospital deaths. Differences between countries in how certifiers interpret these criteria may account for at least some of the international variation in MI mortality rates.

Factors associated with excess all-cause mortality in the first wave of the COVID-19 pandemic in the UK: A time series analysis using the Clinical Practice Research Datalink.

BACKGROUND: Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic. METHODS AND FINDINGS: We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception. CONCLUSIONS: The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.

Excess mortality in Russia and its regions compared to high income countries: An analysis of monthly series of 2020.

BACKGROUND: Russia has been portrayed in media as having one of the highest death tolls due to the COVID-19 pandemic in the world. However, the precise scale of excess mortality is still unclear. We provide the first estimates of excess mortality in Russia as a whole and its regions in 2020, placing this in an international context. METHODS: We used monthly death rates for Russia and 83 regions plus the equivalent for 36 comparator countries. Expected mortality was derived in two ways using averages in the same months in preceding years and the same averages adjusted for secular trends. Excess death rates were estimated for the whole year and the last 3 quarters. We also estimated the relationships between excess mortality and reported COVID-19 cases and deaths across countries and Russian regions. RESULTS: Estimating excess deaths rates based on the trend-adjusted average, Russia had the highest excess mortality of any of the 37 countries considered. Using the simple average, Russia had the third highest. Most of the excess deaths were recorded in the 4th quarter of 2020 and the level and trajectory of excess mortality in Russia and most of Eastern European countries differed from that in Western countries. While both the cumulative number of COVID-19 cases and deaths showed positive correlations with excess mortality across countries (r=0.65 and r=0.75, p<0.001), the association across the Russian regions was, surprisingly, negative for cases (r=-0.34, p<0.01) and deaths (r=-0.09, p=0.42). When we replaced reported deaths with final data from death certificates the correlation was positive (r=0.38, p<0.001). CONCLUSION: Russia has one of the largest absolute burden of excess mortality in 2020 but there is a counter-intuitive negative association between excess mortality and cumulative incidence at the regional level. Under-recording of COVID-19 cases seems to be a problem in some regions.

Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an observational study of 4.3 million adults over the age of 65.

BACKGROUND: Residents in care homes have been severely impacted by COVID-19. We describe trends in the mortality risk among residents of care homes compared to private homes. METHODS: On behalf of NHS England we used OpenSAFELY-TPP to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to Care and Quality Commission data. FINDINGS: We included 4,340,648 people aged 65 years or older on the 1st of February 2019, 2.2% of whom were classified as residing in a care or nursing home. Age-standardised mortality risks were approximately 10 times higher among care home residents compared to those in private housing in February 2019: comparative mortality figure (CMF) = 10.59 (95%CI = 9.51, 11.81) among women, and 10.87 (9.93, 11.90) among men. By April 2020 these relative differences had increased to more than 17 times with CMFs of 17.57 (16.43, 18.79) among women and 18.17 (17.22, 19.17) among men. CMFs did not increase during the second wave, despite a rise in the absolute age-standardised COVID-19 mortality risks. INTERPRETATION: COVID-19 has had a disproportionate impact on the mortality of care home residents in England compared to older residents of private homes, but only in the first wave. This may be explained by a degree of acquired immunity, improved protective measures or changes in the underlying frailty of the populations. The care home population should be prioritised for measures aimed at controlling COVID-19. FUNDING: Medical Research Council MR/V015737/1.

Deep neural networks reveal novel sex-specific electrocardiographic features relevant for mortality risk.

Aims: Incorporation of sex in study design can lead to discoveries in medical research. Deep neural networks (DNNs) accurately predict sex based on the electrocardiogram (ECG) and we hypothesized that misclassification of sex is an important predictor for mortality. Therefore, we first developed and validated a DNN that classified sex based on the ECG and investigated the outcome. Second, we studied ECG drivers of DNN-classified sex and mortality. Methods and results: A DNN was trained to classify sex based on 131 673 normal ECGs. The algorithm was validated on internal (68 500 ECGs) and external data sets (3303 and 4457 ECGs). The survival of sex (mis)classified groups was investigated using time-to-event analysis and sex-stratified mediation analysis of ECG features. The DNN successfully distinguished female from male ECGs {internal validation: area under the curve (AUC) 0.96 [95% confidence interval (CI): 0.96, 0.97]; external validations: AUC 0.89 (95% CI: 0.88, 0.90), 0.94 (95% CI: 0.93, 0.94)}. Sex-misclassified individuals (11%) had a 1.4 times higher mortality risk compared with correctly classified peers. The ventricular rate was the strongest mediating ECG variable (41%, 95% CI: 31%, 56%) in males, while the maximum amplitude of the ST segment was strongest in females (18%, 95% CI: 11%, 39%). Short QRS duration was associated with higher mortality risk. Conclusion: Deep neural networks accurately classify sex based on ECGs. While the proportion of ECG-based sex misclassifications is low, it is an interesting biomarker. Investigation of the causal pathway between misclassification and mortality uncovered new ECG features that might be associated with mortality. Increased emphasis on sex as a biological variable in artificial intelligence is warranted.