Abstract 034: A Healthy Lifestyle Score Including Sleep Duration And Risk Of Cardiovascular Disease

Objectives: The aim of this study was to evaluate the relationship between a lifestyle score including sleep duration and CVD risk, and to estimate whether adding sleep duration into a traditional lifestyle score improved CVD risk prediction. Methods: A prospective analysis was conducted among 67250 women in the Nurses’ Health Study and 29279 men in the Health Professionals Follow-up Study who were followed from 1986 to 2016. The traditional lifestyle score was defined as not smoking, normal BMI(18.5-24.9 kg/m 2 ), ≥30 min/d of moderate physical activity, higher diet quality (top 40% of AHEI), moderate alcohol intake (women:5-15g/day; men:5-30g/day). Low-risk sleep duration, defined as sleeping ≥6 to <8 hours/day, was included as an additional component. Cox proportion hazards regression models were used to estimate hazard ratios (HRs) and 95% confidence intervals (CIs) of CVD, CHD, and stroke. We used the likelihood ratio test and C-statistics to compare the predictive value of the two scores. Results: A total of 11826 incident CVD cases were documented. In multivariable-adjusted models, each low-risk factor was independently and significantly associated with lower risk of CVD, CHD, and stroke. The multivariable-adjusted HRs (95% CIs) comparing six with zero low-risk factors in the healthy lifestyle score were 0.17(0.12, 0.23) for CVD, 0.15(0.10, 0.22) for CHD, and 0.19(0.12, 0.33) for stroke. Approximately 67% of CVD and CHD cases, and 62% stroke cases were attributable to poor adherence to a healthy lifestyle. P- value for likelihood ratio test comparing nested models including the traditional lifestyle score vs traditional lifestyle score plus sleep duration was <0.001. Adding sleep duration to the traditional score prediction model increased the C-statistics from 0.63 (95% CI: 0.62, 0.63) to 0.64 (95% CI: 0.63, 0.65)( P <0.001). Conclusions: Incorporating sleep duration into traditional lifestyle scores improves prediction of CVD risk and warrants consideration for inclusion in lifestyle recommendations.

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Admission lactate level and the GRACE 2.0 score are independent and additive predictors of 30-day mortality of STEMI patients treated with primary PCI - preliminary results of a real-world registry

European Heart Journal Acute Cardiovascular Care ◽

10.1093/ehjacc/zuab020.163 ◽

2021 ◽

Vol 10 (Supplement_1) ◽

Author(s):

D Szabo ◽

A Szabo ◽

S Kugler ◽

A Pinter ◽

V Juhasz ◽

...

Keyword(s):

Likelihood Ratio ◽

Likelihood Ratio Test ◽

Real World ◽

Lactate Level ◽

Discriminatory Power ◽

Circulatory Support ◽

Ratio Test ◽

Primary Pci ◽

Nested Models ◽

C Statistic

Abstract Funding Acknowledgements Type of funding sources: None. Background In many of the current risk estimation algorithms for patients with ST-elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI), heart rate and systolic blood pressure are key predictors. Yet, these parameters may also be influenced by the actual medical treatment / circulatory support, thereby decreasing the discriminatory power of the models. Purpose We aimed to investigate whether venous lactate level, a marker of microcirculatory failure, may have an added prognostic value beyond conventional predictors. Methods In a pilot real-world registry, 174 cases were studied. Venous blood gas analysis was performed in all patients at hospital admission. Nested logistic regression models were built using the extensively validated "Global Registry of Acute Coronary Events" (GRACE) 2.0 score alone (base model) or with the addition of venous lactate level (expanded model) using 30-day all-cause mortality as outcome measure. Independence of predictors (lack of collinearity) was evaluated by the variance inflation factor (VIF). Instead of the insensitive c-statistic, difference in performance of the nested models was analyzed by the likelihood ratio test and the integrated discrimination improvement (IDI). Results The VIF was 1.0684, indicating independence of the measured lactate values from the calculated GRACE 2.0 scores. Both base and expanded models showed high discriminatory power: c-statistic = 0.88 and 0.89, respectively, p = 0.68). Nevertheless, addition of venous lactate level to the GRACE 2.0 score improved predictions of 30-day mortality significantly as assessed by both likelihood ratio test (chi-square = 8.97, p = 0.0027) and IDI (IDI = 0.1029, 95% CI: 0.0002-0.2055, p = 0.0494). Conclusions Venous lactate level may be an independent predictor of 30-day mortality of STEMI patients treated with primary PCI. The addition of this marker to the GRACE 2.0 model may improve mortality prediction of these patients. Abstract Figure.

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