Familial Hypercholesterolaemia Case-Finding Through Cascade Screening in Cardiology Outpatients: Eighteen Months of Index-and-Cascade Identification, Treatment Response and Two-Year Outcomes

Dr. Gaurav Aggarwal, Dr Mr. Ketan Sharma, Dr. Shiv Kumar Gupta

Familial Hypercholesterolaemia; Cascade Screening; LDL Cholesterol; PCSK9 Inhibitor; Ezetimibe; Cardiovascular Prevention; Clinical Genetics

Familial hypercholesterolaemia (FH) carries a substantially elevated lifetime risk of premature coronary disease, yet remains under-diagnosed in many cardiology services. Cascade screening of first-degree relatives of probands is widely recommended but unevenly implemented. We prospectively enrolled 45 newly identified probands meeting Dutch Lipid Clinic Network criteria for probable or definite FH at a tertiary cardiology lipid clinic and screened 153 first-degree and second-degree relatives, yielding 71 newly diagnosed cases of FH a cascade yield of 46.4%. Treatment intensification followed a stepwise protocol: 38 patients (53.5%) were managed on high-intensity statin alone, 22 (31.0%) on statin plus ezetimibe, and 11 (15.5%) required addition of a PCSK9 inhibitor. LDL-cholesterol fell by 39%, 52%, and 70% respectively at 12 weeks, and attainment of the LDL target below 70 mg/dL at 12 months was 26.3%, 45.5%, and 81.8% across the three treatment strata. Over 24 months of follow-up, eight major adverse cardiovascular events occurred, concentrated among patients with statin intolerance, late diagnosis, and incomplete adherence. The findings support structured cascade screening combined with stepwise treatment intensification as a practical, high-yield strategy for FH case-finding and risk reduction.

[1] Agarwal, A., Kumar, D., & S, P. M. (2026). Optimizing clinical effectiveness of enhanced recovery after surgery (ERAS): Multidisciplinary pathways, patient-centered outcomes, and data-driven performance analytics. International Innovations & Scholarly Trends Journal, 2(2).
[2] Bhatnagar, M., Kumar, N., & Shivam. (2026). Quality improvement frameworks in modern surgical practice: Evidence-based models, implementation science, and outcome-oriented performance evaluation. International Journal of Scientific Research and Engineering Development, 9(2).
[3] Catherine, S., Gupta, N., Gopi, E., & Swadhi, R. (2025). Enhancing patient engagement and outcomes through digital transformation: Machine learning in medical marketing. In Impact of digital transformation on business growth and performance (pp. 285–312). IGI Global.
[4] Deepa, R., Swadhi, R., Udayavani, V., Lakshmi, R., & Rafiq, S. (2026). Motion-controlled wearables for physiological monitoring and predictive diagnostics. In R. Vettriselvan & N. Suresh (Eds.), Intelligent motion control for human-centered systems (pp. 1–28). IGI Global.
[5] Devi, M., Manokaran, D., Sehgal, R. K., Shariff, S. A., & Vettriselvan, R. (2025). Precision medicine, personalized treatment, and network-driven innovations: Transforming healthcare with AI. In AI for large scale communication networks (pp. 303–322). IGI Global.
[6] Durgia, B., Kumar, P., & Neha. (2026). Comparative clinical effectiveness and long-term functional outcomes of conservative versus surgical management in degenerative and compressive spinal disorders. International Journal of Scientific Research in Engineering and Management, 10(03).
[7] Gautam, M., Samyal, M., & Chaudhary, S. (2026). Preoperative risk stratification and surgical outcome prediction: Integrating clinical scoring systems, data-driven models, and patient-centered optimization. International Innovations & Scholarly Trends Journal, 2(3).
[8] Gupta, O. P., Gautam, S., & Maitiy, S. (2026). Management strategies for degenerative musculoskeletal disorders: An integrated clinical and technological framework. International Journal of Recent Development in Engineering and Technology, 15(3).
[9] Jha, S. C., Kumar, P., & Neha. (2026). Artificial intelligence-assisted decision support in internal medicine: Enhancing clinical judgment, precision care, and health system performance. International Journal of Scientific Development and Research, 11(2).
[10] Kumar, P., Gautam, S., & Maitiy, S. (2026). Diagnostic utility of biomarkers in early disease stratification: Clinical applications, predictive value, and emerging innovations. Journal of Emerging Technologies and Innovative Research, 13(2).
[11] Kumar, R., Sharma, K., & Gupta, S. K. (2026). Multimorbidity patterns and therapeutic complexity in adult medical practice: Implications for polypharmacy and patient-centred care. International Journal of Creative Research Thoughts, 14(2).
[12] Rasi, R. A., & Ashifa, K. M. (2019). Role of community-based programmes for active ageing: Elders self-help group in Kerala. Indian Journal of Public Health Research & Development, 10(12).
[13] Sahu, R. L., Sharma, K., & Gupta, S. K. (2026). Biological and mechanical determinants of fracture healing: An integrated mechano-biological, systemic, and translational framework. International Journal of Recent Development in Engineering and Technology, 15(3).
[14] Selvi, K., Anbarasan, P., Madhumita, G., Janaki, L., & Devi, K. K. (2026). Governance, security, and ethical considerations in AI-driven motion control systems. In Methodologies and applications of intelligent motion control systems (pp. 217–242). IGI Global.
[15] Subramani, M., Chillagattu, V., Gayathri, K., Rastogi, V., & Ranganathan, S. (2026). Digital twin integration for predictive and real-time motion control in infrastructure engineering. In Methodologies and applications of intelligent motion control systems (pp. 189–216). IGI Global.
[16] Swadhi, R., Gayathri, K., Suresh, N. V., Catherine, S., & Velmurugan, P. R. (2025). Leveraging machine learning for enhanced patient engagement and outcomes: Revolutionizing healthcare marketing. In Impact of digital transformation on business growth and performance (pp. 313–340). IGI Global.
[17] Vettriselvan, R., Ramya, R., Selvalakshmi, V., Jyothi, P., & Velmurugan, P. R. (2026). Empowering patients through knowledge: Educational strategies in rehabilitation. In Holistic approaches to health recovery (pp. 263–290). IGI Global.
[18] Vettriselvan, R., Velmurugan, P. R., Varshney, K. R., EP, J., & Deepika, R. (2025). Health impacts of smartphone and internet addictions across age groups: Physical and mental health across generations. In Impacts of digital technologies across generations (pp. 187–210). IGI Global.
[19] Vijayalakshmi, M., Subramani, A. K., Vettriselvan, R., Velmurugan, P. R., & Hasine, J. (2025). Strategic collaborations in medical innovation and AI-driven globalization: Advancing healthcare startups. In Navigating strategic partnerships for sustainable startup growth (pp. 85–110). IGI Global.
[20] Vinodh, N., Subramani, A. K., & Vettriselvan, R. (2026). Transforming the future of management and medical education: AI-driven innovations in curriculum design. In AI education strategies for future-proofing curriculum design (pp. 459–476). IGI Global.
[21] Yatish, Khatoon, N., & Kumar, A. (2026). Advancing preventive strategies for chronic disease management: Clinical, behavioral, and population-level perspectives. International Journal of Novel Trends and Innovation, 4(2).