I am trying to do a quick and dirty meta-analysis based on published values

The paper I'm reading has a table showing two independent population, with means ($m_1$ and $m_2$), stdev ($std_1$ and $std_2$) and N ($N_1$ and $N_2$) for each population. I do not have the exact p-values for the t-test (only a range 0.05>p>0.01 for example).

To compare to my data, I would like to calculate the effect size (Hedges' $g$) ± 95%CI.

From my research, I think I found how to calculate Cohen's $d$, and from there Hedges' $g$ (formulas [from here][1])

$$ d = \frac{m_1-m_2}{\sqrt{\frac{((N_1-1)*std_1+(N_2-1)*std_2)}{(N_1+N_2-2)}}} $$

and $$ g = d * (1-\frac{3}{4*(N_1+N_2-2)-1)} $$

However, I'm not sure how to calculate the CI of the effect size. The document explains how to calculate the variance $V_d$ and $V_g$ but I don't know how to go from variance to CI. [1]: https://www.meta-analysis.com/downloads/Meta-analysis%20Effect%20sizes%20based%20on%20means.pdf

I am trying to do a quick and dirty meta-analysis based on published values

The paper I'm reading has a table showing two independent population, with means ($m_1$ and $m_2$), stdev ($std_1$ and $std_2$) and N ($N_1$ and $N_2$) for each population. I do not have the exact p-values for the t-test (only a range 0.05>p>0.01 for example).

To compare to my data, I would like to calculate the effect size (Hedges' $g$) ± 95%CI.

From my research, I think I found how to calculate Cohen's $d$, and from there Hedges' $g$ (formulas from here)

$$ d = \frac{m_1-m_2}{\sqrt{\frac{((N_1-1)*std_1+(N_2-1)*std_2)}{(N_1+N_2-2)}}} $$

and $$ g = d * (1-\frac{3}{4*(N_1+N_2-2)-1)} $$

However, I'm not sure how to calculate the CI of the effect size. The document explains how to calculate the variance $V_d$ and $V_g$ but I don't know how to go from variance to CI.