Relationship between the cumulative exposure to atherogenic index of plasma and ischemic stroke: A retrospective cohort study

Background: Atherogenic index of plasma (AIP) has been demonstrated as a surrogate marker for ischemic stroke, but there is limited evidence for the effect of long-term elevation of AIP on ischemic stroke. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of ischemic stroke. Methods: A total of 54,123 participants in the Kailuan Study who attended consecutive health examinations in 2006, 2008, and 2010 and had no history of ischemic stroke or cancer were included. The time-weighted cumulative AIP (cumAIP) was calculated as a weighted sum of the mean AIP values for each time interval and then normalized to the total duration of exposure (2006–2010). Participants were divided into four groups according to quartile of cumAIP: the Q1 group, ≤ −0.50; Q2 group, − 0.50 to − 0.12; Q3 group, − 0.12 to 0.28; and Q4 group, ≥ 0.28. Cox proportional hazard models were used to evaluate the relationship between cumAIP and ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: After a median follow-up of 11.03 years, a total of 2,742 new ischemic stroke events occurred. The risk of ischemic stroke increased with increasing quartile of cumAIP. After adjustment for potential confounders, Cox regression models showed that participants in the Q2, Q3, and Q4 groups had significantly higher risks of ischemic stroke than those in the Q1 group. The HRs (95% CIs) for ischemic stroke in the Q2, Q3, and Q4 groups were 1.17 (1.03, 1.32), 1.33 (1.18, 1.50), and 1.45 (1.28, 1.64), respectively. The longer duration of high AIP exposure was significantly associated with increased ischemic stroke risk. Conclusions: High cumulative AIP is associated with a higher risk of ischemic stroke, which implies that the long-term monitoring and maintenance of an appropriate AIP may help prevent such events

Visit-to-visit variability in triglyceride-glucose index and diabetes:A 9-year prospective study in the Kailuan Study

Instruction/Aims: It is unknown whether variability in the triglyceride-glucose index (TyG-index) is associated with the risk of diabetes. Here, we sought to characterize the relationship between TyG-index variability and incident diabetes. Methods: We performed a prospective study of 48,013 participants in the Kailuan Study who did not have diabetes. The TyG-index was calculated as ln [triglyceride (TG, mg/dL) concentration × fasting blood glucose concentration (FBG, mg/dL)/2]. The TyG-index variability was assessed using the standard deviation (SD) of three TyG-index values that were calculated during 2006/07, 2008/09, and 2010/11. We used the Cox proportional hazard models to analyze the effect of TyG-index variability on incident diabetes. Results: A total of 4,055 participants were newly diagnosed with diabetes during the study period of 8.95 years (95% confidence interval (CI) 8.48–9.29 years). After adjustment for confounding factors, participants in the highest and second-highest quartiles had significantly higher risks of new-onset diabetes versus the lowest quartile, with hazard ratios (95% CIs) of 1.18 (1.08–1.29) and 1.13 (1.03–1.24), respectively (P trend< 0.05). These higher risks remained after further adjustment for the baseline TyG-index. Conclusions: A substantial fluctuation in TyG-index is associated with a higher risk of diabetes in the Chinese population, implying that it is important to maintain a normal and consistent TyG-index

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Relationship between the cumulative exposure to atherogenic index of plasma and ischemic stroke:a retrospective cohort study

Background: Atherogenic index of plasma (AIP) has been demonstrated as a surrogate marker for ischemic stroke, but there is limited evidence for the effect of long-term elevation of AIP on ischemic stroke. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of ischemic stroke. Methods: A total of 54,123 participants in the Kailuan Study who attended consecutive health examinations in 2006, 2008, and 2010 and had no history of ischemic stroke or cancer were included. The time-weighted cumulative AIP (cumAIP) was calculated as a weighted sum of the mean AIP values for each time interval and then normalized to the total duration of exposure (2006–2010). Participants were divided into four groups according to quartile of cumAIP: the Q1 group, ≤−0.50; Q2 group, − 0.50 to − 0.12; Q3 group, − 0.12 to 0.28; and Q4 group, ≥ 0.28. Cox proportional hazard models were used to evaluate the relationship between cumAIP and ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs). Results: After a median follow-up of 11.03 years, a total of 2,742 new ischemic stroke events occurred. The risk of ischemic stroke increased with increasing quartile of cumAIP. After adjustment for potential confounders, Cox regression models showed that participants in the Q2, Q3, and Q4 groups had significantly higher risks of ischemic stroke than those in the Q1 group. The HRs (95% CIs) for ischemic stroke in the Q2, Q3, and Q4 groups were 1.17 (1.03, 1.32), 1.33 (1.18, 1.50), and 1.45 (1.28, 1.64), respectively. The longer duration of high AIP exposure was significantly associated with increased ischemic stroke risk. Conclusions: High cumulative AIP is associated with a higher risk of ischemic stroke, which implies that the long-term monitoring and maintenance of an appropriate AIP may help prevent such events.</p

Temporal relationship between triglyceride-glucose index and blood pressure and their joint cumulative effect on cardiovascular disease risk: a longitudinal cohort study

Abstract Background Concurrent insulin resistance and elevated blood pressure are commonly observed in cardiovascular disease (CVD) and have long been proposed to contribute to CVD. However, the temporal relationship between them and the effect of their cumulative co-exposure on future incident CVD remains unclear. Methods Longitudinal analysis of data on 57,192 participants from a real-world, prospective cohort study (Kailuan Study) was performed to address the temporal relationship between Triglyceride-Glucose Index (TyG, calculated as ln [TG (mg/dL) × FBG (mg/dL)/2]) and blood pressure (BP) assessed by cross-lagged analyses in an approximately 4-year exposure period (2006/2007 to 2010/2011). After excluding 879 participants with known diabetes, 56,313 nonCVD participants were included for further analysis of the CVD outcome. Cox regression models were used to examine the hazard ratios (HRs) upon the cumulative TyG (CumTyG) and BP(CumBP) in the exposure period. Results The standard regression coefficient from baseline TyG to follow-up systolic BP was 0.0142 (95% CI 0.0059–0.0226), which was greater than the standard regression coefficient from baseline systolic BP to follow-up TyG (− 0.0390; 95% CI − 0.0469 to − 0.0311). The same results were observed in the cross-lag between TyG and diastolic blood pressure [0.0271 (0.0185 to 0.0356) vs. − 0.0372 (− 0.0451 to − 0.0293)]. During a median follow-up of 9.98 years, 3981 CVD cases occurred. Significant interactions were observed between the median CumTyG (8.61) and CumSBP thresholds (130, 140 mmHg) (P = 0.0149), the median CumTyG (8.61) and CumDBP thresholds (80, 90 mmHg) (P = 0.0441). Compared to CumTyG < 8.61 and CumSBP < 130 mmHg, after adjusting for potential confounding factors, the HR gradually increased in the high co-exposure groups. The hazard ratios (HRs) and 95% confidence intervals (CIs) for Q2–Q6 were 1.39 (1.24, 1.57), 1.94 (1.69, 2.22), 2.40 (2.12, 2.71), 2.74 (2.43, 3.10), and 3.07 (2.74, 3.45). Additionally, the CVD risks in the co-exposure were more prominent in younger participants. Conclusions These findings suggest that elevated TyG has a greater impact on future blood pressure changes than vice versa. Dual assessment and management of insulin resistance and blood pressure contribute to the prevention of CVD, especially in younger individuals

Relationship between cumulative exposure to triglyceride-glucose index and heart failure: a prospective cohort study

Abstract Background High triglyceride-glucose index (TyG) is a major risk factor for heart failure, but the long-term effect of high TyG index on the risk of developing heart failure remains unclear. Therefore, we aimed to determine the relationship between the cumulative exposure to TyG index and the risk of heart failure. Methods A total of 56,149 participants from the Kailuan Study, who participated in three consecutive health examinations in 2006, 2008, and 2010 and had no history of heart failure or cancer were recruited for this study. The cumulative TyG index was calculated as the weighted sum (value × time) of the mean TyG index for each time interval. The participants were placed into quartiles based on their cumulative TyG index. The study ended on December 31, 2020, and the primary outcome was new-onset heart failure during the follow-up period. In addition, a Cox proportional hazards regression model and a restricted cubic spline analysis were used to further evaluate the relationship between cumulative TyG index and the risk of heart failure. Results During a median follow-up period of 10.04 years, a total of 1,312 new heart failure events occurred. After adjustment for potential confounding factors, the Cox regression analysis showed that the hazard ratios (95% confidence intervals) for the risk of heart failure in the Q2, Q3, and Q4 groups were 1.02 (0.83,1.25), 1.29 (1.07,1.56) and 1.40 (1.15,1.71), respectively, vs. the Q1 group. The subgroup analysis showed a significant interaction between cumulative TyG index and BMI or waist circumference, but there was no interaction between age, sex and cumulative TyG index. The restricted cubic spline analysis showed a dose-response relationship between cumulative TyG index and the risk of heart failure. In addition, the sensitivity analysis generated results that were consistent with the primary results. Conclusions High cumulative TyG index is associated with a higher risk of heart failure. Thus, the TyG index may be useful for the identification of individuals at high risk of heart failure. The present findings emphasize the importance of the long-term monitoring of the TyG index in clinical practice

The effect of acute aerobic exercise on arterial stiffness in individuals with different body fat percentages: A cross-sectional study

BACKGROUND: Body fat percentage were positively correlated with arterial stiffness, but the acute change in arterial stiffness after aerobic exercise in individuals with different body fat percentages remains unclear. This study was aimed to determine the effect of acute aerobic exercise on arterial stiffness in individuals with different body fat percentages. METHODS: Individuals who both participated in the seventh survey of the Kailuan study and the fifth iteration of National Physical Fitness Monitoring were enrolled in our study. All participants underwent measurement of brachial-ankle pulse wave velocity, blood pressure, and heart rate before and after a two-stage load test on cycle ergometry. Additionally, the generalized linear model was established to analyse between-group differences of the change in brachial-ankle pulse wave velocity before and after exercise for individuals with different body fat percentages. RESULTS: The participants (N = 940, 36.8 ± 7.7years old, all male) were divided into: Q1 10.0-19.3%, Q2 19.3-23.3%, Q3 23.3-27.1% and Q4 27.1-37.7% by body fat percentage quartile. Overall, after exercise, brachial-ankle pulse wave velocity decreased significantly (before, 1,375.1 ± 209.1; after, 1,341.5 ± 208.0cm/s; p < 0.01). After adjusting for confounding factors, the generalized linear model showed that the β values and 95% confidence interval (CI) of Q1, Q2 and Q3 groups were -38.1 (95% CI: -57.3, -19.0), -8.5 (95% CI: -25.8, 3.7),-3.7 (95% CI: -20.5, 13.0), respectively, when compared with Q4. For an increase in body fat percentage by one standard deviation (5.8%), β = 14.5 (95% CI: 7.3, 21.6). Similar results were obtained in sensitivity analyses. CONCLUSIONS: Acute aerobic exercise had a positive effect on the arterial stiffness of adults with different body fat percentages. Compared with individuals with high body fat percentages, the arterial stiffness of people with low body fat percentages had significant reduction after exercise

Cumulative exposure to high remnant-cholesterol concentrations increases the risk of cardiovascular disease in patients with hypertension: a prospective cohort study

Abstract Background The relationship of cumulative remnant-cholesterol (Cum-RC) concentration with the risk of cardiovascular disease (CVD) in patients with hypertension remains unclear. Methods We studied data for 28,698 individuals for whom three consecutive total cholesterol, high-density lipoprotein-cholesterol (HDL-C), and triglyceride concentrations were available, and who did not have CVD (14,349 with hypertension and 14,349 without), that was collected between 2006 and 2010. Participants with hypertension were placed into four groups based on Cum-RC quartile: a Q1 group (< 26.40 mg/dl), a Q2 group (26.40–39.56 mg/dl), a Q3 group (39.57–54.65 mg/dl), and a Q4 group (≥ 54.66 mg/dl). Cox proportional hazards models were used to evaluate the relationship between Cum-RC and the risk of CVD. Results Over a median 10.9 (interquartile range, 10.5–11.3) years, 1,444 participants with hypertension developed CVD. After adjustment for multiple potential confounding factors, and compared with the Q1 Cum-RC group of the participants with hypertension, the adjusted hazard ratios for CVD for the Q2–Q4 groups were 1.07(0.92,1.26), 1.08(0.91,1.28), and 1.26(1.03,1.54) (P = 0.0405); those for myocardial infarction were 1.51(1.00,2.31), 2.02(1.22,3.27), and 2.08(1.41,3.28) (P < 0.0001); and those for ischemic stroke were 1.02(0.84,1.24), 1.04(0.86,1.25), and 1.29(1.02,1.62), respectively (P = 0.0336). However, no significant relationship was found between Cum-RC and the risk of hemorrhage stroke. At the same Cum-RC, the risk of CVD was significantly higher in participants with hypertension than in those without. Conclusions A consistently high remnant-cholesterol concentration increases the risk of CVD in individuals with hypertension. Therefore, the achievement of blood pressure and RC concentration targets should help reduce the risk of CVD in individuals with hypertension

Individual and combined contributions of non-high-density lipoprotein cholesterol and brachial-ankle pulse wave velocity to cardiovascular disease risk: Results of a prospective study using the Kailuan cohort

Objective: We aimed to characterize the relationship of a combination of circulating non-high-density lipoprotein-cholesterol (non-HDL-C) concentration and brachial-ankle pulse wave velocity (baPWV) with cardiovascular disease (CVD). Methods: We performed a prospective cohort study of the residents of the Kailuan community, with data from a total of 45,051 participants being included in the final analysis. The participants were allocated to four groups according to their non-HDL-C and baPWV status, each of which was categorized as high or normal. Cox proportional hazards models were used to explore the relationships of non-HDL-C and baPWV, individually and in combination, with the incidence of CVD. Results: During the 5.04-year follow-up period, 830 participants developed CVD. Compared with the Normal non-HDL-C group independently, the multivariable adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD in the High non-HDL-C was 1.25 (1.08–1.46). Compared with the Normal baPWV group independently, the HRs and 95% CIs for CVD in the High baPWV was 1.51 (1.29–1.76). In addition, compared with the Normal both non-HDL-C and baPWV group, the HRs and 95% CIs for CVD in the High non-HDL-C and normal baPWV, Normal non-HDL-C and high baPWV, and High both non-HDL-C and baPWV groups were 1.40 (1.07–1.82), 1.56 (1.30–1.88), and 1.89 (1.53–2.35), respectively. Conclusion: High non-HDL-C concentration and high baPWV are independently associated with a higher risk of CVD, and individuals with high both non-HDL-C and baPWV are at a still higher risk of CVD