Like in most disciplines in Medicine, the value of predicting the occurrence of a disease or event is an important realm in the field of Cardiology that repeatedly invites numerous clinical investigations. This has given rise to numerous scoring schemes, probability indices and prediction tools that enable the clinician to expect a complication or outcome with reasonable scientific certainty. Developing new insights to determine the probability of occurrence of a clinical event accompanying various disease entities ensures that clinicians have scientific guidance and logical basis in the diagnosis and management of cardiovascular diseases. This becomes even more imperative in economies where the resources are not limitless, yet ironically, where the scourge of the affliction is somehow endless. Thus, every pathway of investigative work that leads to elucidative outputs on chronic disease remains vital. In this issue, our Japanese colleagues explored the usefulness of OptivolTM, an algorithmic analysis based on continuous intrathoracic impedance monitoring, in conventional bradyarrhythmia pacing patients. On the other hand, our local counterparts looked into speckle-tracking echocardiography (STE)-derived mitral annular displacement after TAVI. Both investigations look into parameters dealing with cardiovascular entities which are addressed by new technologies. Quite expectedly, the necessity for new data is paramount when innovations and advancements are made in the management of cardiovascular diseases. As technology and science change the manner by which we diagnose and manage cardiovascular diseases, so will these realms bring about the need to keep abreast with changes in physiology, metabolism and biochemistry brought about by devices and interventions. Be it pacing, or a transcatheter-implanted valve stent, or a left ventricular assist device, the concomitant alterations in hemodynamics and structural relationships will naturally bring about new domains that will require insightful evaluations and analysis. Understandably, we look to big data that will be able to impact healthcare analytics – as they provide us with the statistical capacity and robustness of information in applying them to clinical practice. We likewise eagerly await mega clinical trials – as they will solidly impact the clinician’s capability and decision making as he confronts common medical emergencies and routine clinical situations. Nonetheless, there is always room for well-conducted, pivotal reports and prospective investigations to lead us to valid conclusions – notwithstanding the challenges and limitations imposed by small sample sizes, limited funding, short study durations, among others.