Cardiovascular (CV) trials of antidiabetic drugs and drugs of other indications for chronic conditions are usually large-scale/long-term trials with a composite outcome of CV events as the endpoint and are typically designed for a superiority hypothesis or non-inferiority hypothesis using a fixed sample size design. To increase the chance of trial success or to stop the trial earlier if there is surprisingly strong efficacy or no hope of demonstrating the non-inferiority, the trial can use an adaptive non-inferiority/superiority design rather than the fixed sample size design. In this paper, we first derive closed-form formulas for the number of events and total exposure as functions of many trial parameters incorporating delayed treatment effect after taking treatment and diluted treatment effect after treatment discontinuation. We then outline some considerations for the design of an adaptive noninferiority/superiority CV trial based on ideas of other authors. We also use an example to illustrate the application of the methods.