Postponing AMI to 100 Years: An Emerging Concept

Acute myocardial infarction is a deadly disease, and in the Indian context, it occurs at a younger age, even below the age of 40 years, and sometimes even below 30 years. These young MI patients have high mortality rates, and many of them are not able to reach the hospital. The pathophysiology of AMI is very well understood. AMI is a multifactorial disease and has several risk factors, like dyslipidemia, diabetes, hypertension, smoking, diet, etc. However, low-density lipoprotein cholesterol (LDL-C) has a very strong causal relationship with atherosclerosis. Reducing LDL-C to <70 results in the arrest of the progression of atherosclerosis, and slashing its level to below 50 produces the regression of atherosclerosis. The cumulative exposure of LDL-C to the arterial wall is a very strong determinant of atherosclerosis and the development of AMI. The coronary heart disease (CHD) threshold target of LDL-C for the development of AMI is roughly 7000 mg/year. If LDL-C is 100 mg/dL from an early age, the CHD threshold target for the development of AMI will reach 70 years of age. However, if LDL-C target is <70 mg/dL from an early age, the patients will reach the CHD threshold of LDL-C at the age of 100 years. Based on the current science, this is an emerging concept to postpone AMI by several years, even up to 100 years. The goal of LDL-C <70 mg/dL can be achieved by available oral or injectable drugs. Gene editing with CRISPR technology is emerging as a very exciting modality for lowering LDL-C to a very low level for the rest of life.

Retinal nerve fiber layer thickness and retinal vascular caliber alterations in coal miners in northern China:a community-based observational study

AIM:To evaluate retinal nerve fiber layer thickness and retinal vascular caliber alterations in coal mine workers.METHODS:The community-based observational crosssectional study included 4004 participants of a subpopulation of the Kailuan Study.All the study participants underwent structured interviews with a standardized questionnaire,fundus photography and spectral-domain optical coherence tomography(OCT)examinations performed by trained doctors.RESULTS:The retinal nerve fiber layer thickness was significantly higher(P=0.006)and the central macular thickness was lower in coal miners(n=659,51.0±7.8 y)as compared to the control(working above the ground;n=477,51.8±7.5 y;P=0.032).Additionally,the downhole workers showed a significantly thicker retinal artery(P=0.012)and vein diameters(P<0.001).In multivariable regression,a thicker retinal nerve fiber layer was associated with a higher cumulative silica dust exposure(P=0.005)after adjusting for younger age and larger spherical equivalent.In a reverse pattern,a higher cumulative silica dust exposure(P=0.004)was significantly associated with a thicker retinal nerve fiber layer after adjusting for age,high-density lipoproteins and uric acid.Wider retinal vein diameters were associated with higher cumulative silica dust exposure(P=0.036)after adjusting for younger age and larger spherical equivalent.CONCLUSION:The retinal vessels diameters and retinal nerve fiber layer thickness are significantly thicker in long term of coal mining.The results of our study indicate that underground working environment may lead to retinal vessel dilation and inflammation.Thus,ocular examination might be needed within coal miners in order to monitor the occupational eye health as well as the incidence and progression of eye diseases.

Statistical Inference for a Simple Step Stress Model with Competing Risks Based on Generalized Type-ⅠHybrid Censoring

This paper investigates a simple step-stress accelerated lifetime test(SSALT)model for the inferential analysis of exponential competing risks data.A generalized type-I hybrid censoring scheme is employed to improve the efficiency and controllability of the test.Firstly,the MLEs for parameters are established based on the cumulative exposure model(CEM).Then the conditional moment generating function(MGF)for unknown parameters is set up using conditional expectation and multiple integral techniques.Thirdly,confidence intervals(CIs)are constructed by the exact MGF-based method,the approximate normality-based method,and the bias-corrected and accelerated(BCa)percentile bootstrap method.Finally,we present simulation studies and an illustrative example to compare the performances of different methods.