Using Negative Control Outcomes to Detect Selection Bias in Mendelian Randomization Studies.

Frailty is a multidimensional syndrome characterised by reduced physiological reserve and increased vulnerability to stressors, predisposing individuals to adverse clinical outcomes []. In patients with cardiovascular disease, frailty has been consistently associated with higher rates of mortality, rehospitalisation, functional decline, and prolonged recovery []. Patients undergoing percutaneous coronary intervention (PCI) often present with multiple comorbidities and significant cardiovascular burden, making frailty assessment particularly relevant in this population. Survivors of cardiovascular interventions may experience persistent physical limitations, psychological distress, and reduced quality of life, which may be influenced by frailty status at hospital discharge []. Although frailty has consistently been associated with short-term adverse outcomes following cardiac intensive care unit (CICU) discharge [], uncertainty remains regarding its long-term impact on survival, persistent frailty, and health-related quality of life after PCI []. Existing studies have largely focused on elderly populations, short follow-up durations, or mortality alone, with limited data evaluating the combined trajectory of frailty, survival, and quality of life after PCI. Furthermore, evidence from low- and middle-income countries remains scarce.