The phenomena of treatment-confounder exist as mediating factors that predict the subsequent treatment in time-to-recurrent analysis. Conventional models produce misleading statistical inference of causal effects in the presence of time-dependent covariates due to conditioning on the causal pathways. Marginal structural models can be applied to quantify the causal treatment effect, estimated using longitudinal weights which mimic the randomization procedure by balancing the covariate distributions across the treatment groups. We formulated a continuous-time marginal structural model to access the effect of cumulative exposure of Sodium-Glucose co-Transporters 2 Inhibitor (SGLT-2i) medications on time-to-recurrent outcome of urinary tract infection (UTI). Our results supported the earlier findings in which the recurrent episodes of UTI did not increase when patients were prescribed low dose or high dose of SGLT-2i medications.