The detection of low-frequency radio transients can help pinpoint high-energy events in our sky such as supernovae or gamma-ray bursts. We use data from the VLA Low Band Ionospheric and Transient Experiment (VLITE) to search for such transients. By running VLITE images through the LOFAR Transients Pipeline, an algorithm that finds and associates sources, generates their light curves, and builds up variability parameters, we can identify these transients. Here we present the results of an investigation of systematic uncertainties in the VLITE images on the variability and effectiveness of finding transients. We also apply an anomaly detection algorithm, initially developed for LOFAR data, on simulated transients in VLITE images to determine the ranges of variability parameters that indicate a high confidence in identified transient candidates.