Mortality Risk Factors in Patients who are in Heart Transplantation Waiting List

Abstract Introduction While there is emerging evidence for acute sleep disruption in the aftermath of coronavirus disease 2019 (COVID-19), it is unknown whether sleep traits contribute to mortality risk. In this study, we tested whether earlier-life sleep duration, chronotype, insomnia, napping or sleep apnea were associated with increased 30-day COVID-19 mortality. Methods We included 34,711 participants from the UK Biobank, who presented for COVID-19 testing between March and October 2020 (mean age at diagnosis: 69.4±8.3; range 50.2–84.6). Self-reported sleep duration (less than 6h/6-9h/more than 9h), chronotype (“morning”/”intermediate”/”evening”), daytime dozing (often/rarely), insomnia (often/rarely), napping (often/rarely) and presence of sleep apnea (ICD-10 or self-report) were obtained between 2006 and 2010. Multivariate logistic regression models were used to adjust for age, sex, education, socioeconomic status, and relevant risk factors (BMI, hypertension, diabetes, respiratory diseases, smoking, and alcohol). Results The mean time between sleep measures and COVID-19 testing was 11.6±0.9 years. Overall, 5,066 (14.6%) were positive. In those who were positive, 355 (7.0%) died within 30 days (median = 8) after diagnosis. Long sleepers (>9h vs. 6-9h) [20/103 (19.4%) vs. 300/4,573 (6.6%); OR 2.09, 95% 1.19–3.64, p=0.009), often daytime dozers (OR 1.68, 95% 1.04–2.72, p=0.03), and nappers (OR 1.52, 95% 1.04–2.23, p=0.03) were at greater odds of mortality. Prior diagnosis of sleep apnea also saw a two-fold increased odds (OR 2.07, 95% CI: 1.25–3.44 p=0.005). No associations were seen for short sleepers, chronotype or insomnia with COVID-19 mortality. Conclusion Data across all current waves of infection show that prior sleep traits/disturbances, in particular long sleep duration, daytime dozing, napping and sleep apnea, are associated with increased 30-day mortality after COVID-19, independent of health-related risk factors. While sleep health traits may reflect unmeasured poor health, further work is warranted to examine the exact underlying mechanisms, and to test whether sleep health optimization offers resilience to severe illness from COVID-19. Support (if any) NIH [T32GM007592 and R03AG067985 to L.G. RF1AG059867, RF1AG064312, to K.H.], the BrightFocus Foundation A2020886S to P.L. and the Foundation of Anesthesia Education and Research MRTG-02-15-2020 to L.G.

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Mortality and associated risk factors in diabetics

Acta Endocrinologica ◽

10.1530/acta.0.110s021 ◽

1985 ◽

Vol 110 (4_Suppl) ◽

pp. S21-S26 ◽

Cited By ~ 33

Author(s):

R. J. Jarrett ◽

M. J. Shipley

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Coronary Heart Disease ◽

Heart Disease ◽

Mortality Risk ◽

Mortality Rates ◽

Potential Risk Factors ◽

Diabetic Population ◽

Associated Risk Factors ◽

The Relationship

Summary. In 168 male diabetics aged 40-64 years participating in the Whitehall Study, ten-year age adjusted mortality rates were significantly higher than in non-diabetics for all causes, coronary heart disease, all cardiovascular disease and, in addition, causes other than cardiovascular. Mortality rates were not significantly related to known duration of the diabetes. The predictive effects of several major mortality risk factors were similar in diabetics and non-diabetics. Excess mortality rates in the diabetics could not be attributed to differences in levels of blood pressure or any other of the major risk factors measured. Key words: diabetics; mortality rates; risk factors; coronary heart disease. There are many studies documenting higher mortality rates - particularly from cardiovascular disease -in diabetics compared with age and sex matched diabetics from the same population (see Jarrett et al. (1982) for review). However, there is sparse information relating potential risk factors to subsequent mortality within a diabetic population, information which might help to explain the increased mortality risk and also suggest preventive therapeutic approaches. In the Whitehall Study, a number of established diabetics participated in the screening programme and data on mortality rates up to ten years after screening are available. We present here a comparison of diabetics and non-diabetics in terms of relative mortality rates and the influence of conventional risk factors as well as an analysis of the relationship between duration of diabetes and mortality risk.

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