Full
Outline
To investigates the association between the variability of remnant cholesterol (RC) during long-term follow-up and cardiac conduction block (CCB) based on the Kailuan cohort.
A retrospective study was conducted on the research cohort in the Kailuan study population who consecutively participated in the physical examinations of 2006, 2008, and 2010. Based on the inclusion and exclusion criteria, 39 299 subjects were ultimately enrolled in the study. The variability of RC during the follow-up period was calculated, with the variability assessed through standard deviation (SD), average real variability (ARV), coefficient of variation (CV), and variability independent of the mean (VIM). The participants were divided into 4 groups based on the interquartile range of RC variability, and followed up every 2 years. The endpoints were defined as the occurrence of CCB, death, or the termination of follow-up (December 31, 2019). Kaplan-Meier test and Log-Rank test were carried out respectively calculate and compare the cumulative incidence rate of endpoint events across groups. Cox proportional hazards model and restricted cubic spline (RCS) analysis were performed to analyze the association between the variability of RC and CCB and its subtypes.
After an average follow-up of 7.43 years in 39 299 participants, 916 patients developed CCB. After adjusting for confounding factors, using CCB as the outcome event, and were dividing the participants into groups based on the RC-SD quartiles, the hazard ratios (HR) for CCB occurrence were 1.344 in the Q1 group (95% CI: 1.110~1.626, P=0.002), 1.068 (95% CI: 0.878 to 1.299, P=0.509) in the Q3 group and 1.311 (95% CI: 1.089~1.579, P=0.004) in the Q4 group, when compared to the group of lowest incidence density (the Q2 group). Similar results were obtained for the quartiles of RC-ARV, RC-CV, and RC-VIN grouping. RCS analysis revealed a U-shaped association between RC-SD and CCB (Poverall<0.05, Pnonlinearity<0.05). Sensitivity and stratified analyses further validated this finding.
There exists a U-shaped association between the variability of RC and the risk of CCB. This finding provides a new direction for preventing the occurrence of CCB. Countermeasures China’s blood lipid management strategy should undergo a paradigm shift from pursuing “low-level stability” toward integrating “long-term stability of biomarker levels” This entails systematically incorporating the new concept of “maintaining physiological fluctuations of blood lipids within an optimal range” into the national prevention and treatment plans for cardiovascular and cerebrovascular diseases, primary public health service programs, and the public health education system. Such a transition will propel chronic disease management into a more precise and scientific new stage.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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