confidence interval around standardised regression coefficient?

I have computed a simple linear regression model as below, but am confused as to whether the confint() function is sufficient to provide 95% confidence intervals around the standardised regression coefficient in the linear model (beta)?

Has anyone else run into this issue or is confint() sufficient to extract the 95% confidence interval (i.e., +/-1.96 standard errors of the standardised regression coefficient)?

h1a - lm(formula = var1~ var2, data = df) # estimate value of intercept (b0) and slope (b1) and store model in variable

summary(h1a) # extract p-value for year and adjusted R^2 for model

standardCoefs(h1a) # extract standardized beta coefficient

ci_h1a - confint(h1a, conf.level = 0.95, digits = 4)[2,] # extract confidence interval