Laser photocoagulation is one of the important methods for treating retinal diseases, and retinal laser technology continues to advance. For decades, researchers have been striving to find a laser treatment that can minimize tissue damage while achieving optimal results. With low toxicity, low scattering light, strong penetrating power, small compared with the traditional laser damage, light reaction and no pain, the 577 nm subthreshold micropulse laser(SML)turns this goal into reality and ushers in a new era of laser treatment for fundus diseases. This article reviews the concept, mechanism, related parameters and clinical application progress of 577 nm SML in a variety of retinal diseases, aiming to provide references for clinical treatments.

ObjectiveTo investigate the association between estimated glucose disposal rate （eGDR） and the severity of coronary heart disease. MethodsWe conducted a hospital-based cross-sectional study that included 1258 patients （mean age： 62（53-68） years） who underwent coronary angiography for suspected coronary artery disease （53.9% were male）. Insulin resistance level （IR） was calculated according to eGDR formula： eGDR = 21.158 - （0.09 × WC） - （3.407 × hypertension） - （0.551 × HbA1c） ［hypertension （yes = 1 / no = 0）， HbA1c = HbA1c （%）］. Subjects were grouped according to the eGDR quantile. CAD severity was determined by the number of narrowed vessels： no-obstructive CAD group （all coronary stenosis were<50%， n=704）， Single-vessel CAD group （only one involved major coronary artery stenosis≥50%， n=205）， Multi-vessel CAD group （two or more involved major coronary arteries stenosis≥50%， n=349）； Multivariate logistic regression model was used to analyze the association between eGDR and CAD severity. The linear relationship between eGDR and CAD in the whole range of eGDR was analyzed using restricted cubic spline. Subgroup analyses were used to assess the association between eGDR and CAD severity in different diabetic states. Receiver operating characteristic （ROC） curve analysis were used to evaluate the value of eGDR in improving CAD recognition. ResultsA decrease in the eGDR index was significantly associated with an increased risk of CAD severity （OR： 2.79； 95%CI： 1.72~4.55； P<0.001）. In multivariate logistic regression models， individuals with the lowest quantile of eGDR （T1） were 2.79 times more likely to develop multi-vessel CAD than those with the highest quantile of eGDR （T3） （OR： 2.79； 95%CI： 1.72~4.55； P<0.001）. Multivariate restricted cubic spline analysis showed that eGDR was negatively associated with CAD and multi-vessel CAD （P-nonlinear>0.05）. In non-diabetic patients， compared with the reference group （T3）， the T1 group had a significantly increased risk of CAD （OR： 1.42； 95% CI： 1.00~2.01； P<0.05） and multi-vessel CAD （OR： 1.86； 95%CI： 1.21~2.86； P<0.05）. No statistical association was found between eGDR and CAD in diabetic patients. In ROC curve analysis， when eGDR was added to traditional model for CAD， significant improvements were observed in the model's recognition of CAD and multi-vessel CAD. ConclusionOur study shows eGDR levels are inversely associated with CAD and CAD severity. eGDR， as a non-insulin measure to assess IR， could be a valuable indicator of CAD severity for population.