Shasha Yu

Purpose: To explore the predictive value of ACEF scores for identifying the risk of cardiovascular disease (CVD) in the general population. Methods: A total of 8613 participants without a history of CVD were enrolled in the follow-up. The endpoint was CVD incidence, defined as stroke or coronary heart disease (CHD) diagnosed during the follow-up period. Cox regression analyses were used to calculate hazard ratios (HRs) with respect to the age, creatinine, and ejection fraction (ACEF) scores and CVD. A Kaplan–Meier curve was used to analyze the probability of CVD in different quartiles of ACEF. Restricted cubic spline was used to further explore whether the relationship between ACEF and CVD was linear. Finally, we assessed the discriminatory ability of ACEF for CVD using C-statistics, net reclassification index, and integrated discrimination improvement (IDI). Results: During a median follow-up period of 4.66 years, 388 participants were diagnosed with CVD. The Kaplan–Meier curve showed that ACEF was associated with CVD, and participants with high ACEF scores were significantly more likely to be diagnosed with CVD compared to participants with low ACEF scores in the general population. In the multivariate Cox regression analysis, the adjusted HRs for four quartiles of ACEF were as follows: the first quartile was used as a reference; the second quartile: HR = 2.33; the third quartile: HR = 4.81; the fourth quartile: HR = 8.00. Moreover, after adding ACEF to the original risk prediction model, we observed that new models had higher C-statistic values of CVD than the traditional model. Furthermore, the results of both NRI and IDI were positive, indicating that ACEF enhanced the prediction of CVD. Conclusions: Our study showed that the ACEF score was associated with CVD in the general population in northeastern China. Furthermore, ACEF could be a new tool for identifying patients at high risk of primary CVD in the general population.

Summary Based on the use of Osteoporosis Self-Assessment Tool for Asians (OSTA) to assess osteoporosis risk, we found that short sleep duration and taking a daytime nap had an increased risk of osteoporosis. Purpose To explore the associations between different sleep patterns with osteoporosis. Methods 3659 postmenopausal women (average age of 60 years) were divided into low, middle, and high osteoporosis risk categories based on the Osteoporosis Self-Assessment Tool for Asians (OSTA). After having collected by a standard questionnaire, total and nocturnal sleep duration was collapsed to form categories of ≤ 6 h, > 6 h and ≤ 7 h, > 7 h and ≤ 8 h, > 8 h and ≤ 9 h, > 9 h, and daytime nap duration of 0 h and > 0 h. Results As a categorical variable, the total sleep duration of ≤ 6 h per day (OR = 1.34, 95% CI 1.04–1.72), nocturnal sleep duration of ≤ 6 h per night (OR = 1.65, 95% CI 1.24–2.18), and taking a daytime nap (OR = 1.33, 95% CI 1.09–1.64) had higher osteoporosis risk after adjustment for covariates. As a continuous variable, after the adjustment for covariates, both longer total (OR = 0.86, 95% CI 0.78–0.94) and nocturnal sleep duration (OR = 0.83, 95% CI 0.76–0.91) had lower risk of osteoporosis risk while taking longer daytime nap (OR = 1.10, 95% CI 1.02–1.19) had higher osteoporosis risk. Conclusions Postmenopausal women with both short total and nocturnal sleep duration (6 h or less) and taking a daytime nap had increased osteoporosis risk as assessed by OSTA.