Author
Dr. Alpana Bansal, Shilki Sharma, Anupama Choudhary
Keywords
High-risk Pregnancy; Antenatal Surveillance; Doppler Velocimetry; Cardiotocography; Thrombophilia; Advanced Maternal Age; Obstetric Critical Care; Precision Medicine; Multidisciplinary Obstetrics; Digital Health Monitoring.
Abstract
High-risk pregnancies contribute disproportionately to maternal and perinatal morbidity and mortality despite advancements in obstetric surveillance and tertiary care infrastructure. Effective management requires integration of clinical expertise, structured antenatal monitoring, multidisciplinary coordination, and emerging digital health innovations. This analytical study evaluates determinants, management strategies, and clinical outcomes among 480 high-risk pregnancies managed in a tertiary care institution over four years. Multivariate logistic regression demonstrated that hypertensive disorders (β=0.52, p<0.001), thrombophilia (β=0.41, p<0.001), advanced maternal age (β=0.36, p<0.01), and inadequate antenatal compliance (β=0.44, p<0.001) significantly predicted adverse maternal outcomes. Structured Doppler monitoring reduced fetal compromise risk by 38% (p<0.01). The final predictive model explained 79% of variance in adverse maternal-fetal outcomes (R²=0.79). Findings support a systems-based management framework combining classical obstetric evidence, personalised thromboprophylaxis, psychosocial assessment, and AI-assisted risk stratification. High-risk pregnancy care must transition from reactive intervention to proactive, digitally enhanced, multidisciplinary management to optimise maternal and neonatal survival.
References
[1] Brown, V. A., Sawers, R. S., Parsons, R. J., Duncan, S. L., & Cooke, I. D. (1982). The value of antenatal cardiotocography in the management of high-risk pregnancy: a randomized controlled trial. BJOG: An International Journal of Obstetrics & Gynaecology, 89(9), 716–722.
[2] 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.
[3] Correa-de-Araujo, R., & Yoon, S. S. (2021). Clinical outcomes in high-risk pregnancies due to advanced maternal age. Journal of Women’s Health, 30(2), 160–167.
[4] Dangal, G. (2007). High-risk pregnancy. The Internet Journal of Gynecology and Obstetrics, 7(1), 1–7.
[5] Dargaud, Y., Rugeri, L., Fleury, C., Battie, C., Gaucherand, P., Huissoud, C., & Trzeciak, M. C. (2017). Personalized thromboprophylaxis using a risk score for the management of pregnancies with high risk of thrombosis: a prospective clinical study. Journal of Thrombosis and Haemostasis, 15(5), 897–906.
[6] Datta, S. (Ed.). (2006). Anesthetic and obstetric management of high-risk pregnancy. Springer Science & Business Media.
[7] 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.
[8] Effer, S. B. (1969). Management of high-risk pregnancy: report of a combined obstetrical and neonatal intensive care unit. Canadian Medical Association Journal, 101(7), 55.
[9] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[10] Hoxha, A., Tormene, D., Campello, E., & Simioni, P. (2022). Treatment of refractory/high-risk pregnancies with antiphospholipid syndrome: a systematic review of the literature. Frontiers in Pharmacology, 13, 849692.
[11] James, D. K., Steer, P. J., Weiner, C. P., & Gonik, B. (2010). High risk pregnancy e-book: Management options—expert consult. Elsevier Health Sciences.
[12] Pattinson, R. C., Norman, K., & Odendaal, H. J. (1994). The role of Doppler velocimetry in the management of high risk pregnancies. BJOG: An International Journal of Obstetrics & Gynaecology, 101(2), 114–120.
[13] Queenan, J. T., Spong, C. Y., & Lockwood, C. J. (Eds.). (2012). Queenan’s management of high-risk pregnancy: an evidence-based approach. John Wiley & Sons.
[14] Ranganathan, M., Jacob, A., Ashifa, K. M., Kumar, G. J., Anthony, M., Vijay, M., & Kumari, R. B. (2024). An investigation of the effects of chronic stress on attention in parents of children with neurodevelopmental disorders. Universal Journal of Public Health, 12(1), 37–50.
[15] Sarig, G., Vidergor, G., & Brenner, B. (2009). Assessment and management of high-risk pregnancies in women with thrombophilia. Blood Reviews, 23(4), 143–147.
[16] Shanthi, H. J., Gokulakrishnan, A., Sharma, S., Deepika, R., & Swadhi, R. (2025). Leveraging Artificial Intelligence for Enhancing Urban Health: Applications, Challenges, and Innovations. In Nexus of AI, Climatology, and Urbanism for Smart Cities (pp. 275–306). IGI Global.
[17] Spong, C. Y., & Lockwood, C. J. (Eds.). (2023). Queenan’s Management of High-risk Pregnancy: An Evidence-based Approach. John Wiley & Sons.
[18] Trivedi, S. S. (2015). Management of High-Risk Pregnancy—a practical approach. JP Medical Ltd.
[19] 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.
[20] Zhu, J., Said, F. M., & Tan, C. H. (2024). Progress in Research on the Management of High-Risk Pregnancies in China. International Journal of Biotechnology and Biomedicine (IJBB), 1(2), 44–56.
[2] 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.
[3] Correa-de-Araujo, R., & Yoon, S. S. (2021). Clinical outcomes in high-risk pregnancies due to advanced maternal age. Journal of Women’s Health, 30(2), 160–167.
[4] Dangal, G. (2007). High-risk pregnancy. The Internet Journal of Gynecology and Obstetrics, 7(1), 1–7.
[5] Dargaud, Y., Rugeri, L., Fleury, C., Battie, C., Gaucherand, P., Huissoud, C., & Trzeciak, M. C. (2017). Personalized thromboprophylaxis using a risk score for the management of pregnancies with high risk of thrombosis: a prospective clinical study. Journal of Thrombosis and Haemostasis, 15(5), 897–906.
[6] Datta, S. (Ed.). (2006). Anesthetic and obstetric management of high-risk pregnancy. Springer Science & Business Media.
[7] 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.
[8] Effer, S. B. (1969). Management of high-risk pregnancy: report of a combined obstetrical and neonatal intensive care unit. Canadian Medical Association Journal, 101(7), 55.
[9] Elkin, N., Mohammed, A. K., Kılınçel, Ş., Soydan, A. M., Tanrıver, S. Ç., Çelik, Ş., & Ranganathan, M. (2025). Mental health literacy and happiness among university students: A social work perspective to promoting well-being. Frontiers in Psychiatry, 16, 1541316.
[10] Hoxha, A., Tormene, D., Campello, E., & Simioni, P. (2022). Treatment of refractory/high-risk pregnancies with antiphospholipid syndrome: a systematic review of the literature. Frontiers in Pharmacology, 13, 849692.
[11] James, D. K., Steer, P. J., Weiner, C. P., & Gonik, B. (2010). High risk pregnancy e-book: Management options—expert consult. Elsevier Health Sciences.
[12] Pattinson, R. C., Norman, K., & Odendaal, H. J. (1994). The role of Doppler velocimetry in the management of high risk pregnancies. BJOG: An International Journal of Obstetrics & Gynaecology, 101(2), 114–120.
[13] Queenan, J. T., Spong, C. Y., & Lockwood, C. J. (Eds.). (2012). Queenan’s management of high-risk pregnancy: an evidence-based approach. John Wiley & Sons.
[14] Ranganathan, M., Jacob, A., Ashifa, K. M., Kumar, G. J., Anthony, M., Vijay, M., & Kumari, R. B. (2024). An investigation of the effects of chronic stress on attention in parents of children with neurodevelopmental disorders. Universal Journal of Public Health, 12(1), 37–50.
[15] Sarig, G., Vidergor, G., & Brenner, B. (2009). Assessment and management of high-risk pregnancies in women with thrombophilia. Blood Reviews, 23(4), 143–147.
[16] Shanthi, H. J., Gokulakrishnan, A., Sharma, S., Deepika, R., & Swadhi, R. (2025). Leveraging Artificial Intelligence for Enhancing Urban Health: Applications, Challenges, and Innovations. In Nexus of AI, Climatology, and Urbanism for Smart Cities (pp. 275–306). IGI Global.
[17] Spong, C. Y., & Lockwood, C. J. (Eds.). (2023). Queenan’s Management of High-risk Pregnancy: An Evidence-based Approach. John Wiley & Sons.
[18] Trivedi, S. S. (2015). Management of High-Risk Pregnancy—a practical approach. JP Medical Ltd.
[19] 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.
[20] Zhu, J., Said, F. M., & Tan, C. H. (2024). Progress in Research on the Management of High-Risk Pregnancies in China. International Journal of Biotechnology and Biomedicine (IJBB), 1(2), 44–56.
Received : 29 January 2026
Accepted : 21 March 2026
Published : 29 March 2026
DOI: 10.30726/ijmrss/v13.i1.2026.13105