Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study
Background: Clinical manifestations of polycystic ovary syndrome (PCOS) are heterogeneous, with hallmarks including anovulation, androgen excess, and insulin resistance. Case Report: A 38-year-old female with typical PCOS features presented with hypertension, obesity, and elevated fasting and postpr...
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Elsevier
2025-01-01
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| Series: | AACE Clinical Case Reports |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2376060524001317 |
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| author | Paramesh Shamanna, MD Anuj Maheshwari, MD Ashok Keshavamurthy, MD Sanjay Bhat, DM Abhijit Kulkarni, DM Shivakumar R, MD Kumar K, MD Mukulesh Gupta, MD Mohamed Thajudeen, MD Ranjita Kulkarni, MD Shashikiran Patil, MD Shashank Joshi, DM |
| author_facet | Paramesh Shamanna, MD Anuj Maheshwari, MD Ashok Keshavamurthy, MD Sanjay Bhat, DM Abhijit Kulkarni, DM Shivakumar R, MD Kumar K, MD Mukulesh Gupta, MD Mohamed Thajudeen, MD Ranjita Kulkarni, MD Shashikiran Patil, MD Shashank Joshi, DM |
| author_sort | Paramesh Shamanna, MD |
| collection | DOAJ |
| description | Background: Clinical manifestations of polycystic ovary syndrome (PCOS) are heterogeneous, with hallmarks including anovulation, androgen excess, and insulin resistance. Case Report: A 38-year-old female with typical PCOS features presented with hypertension, obesity, and elevated fasting and postprandial insulin levels. She was enrolled in the Digital Twin (DT) platform, which uses artificial intelligence and Internet of Things to deliver personalized nutrition by predicting postprandial glucose responses and suggesting alternative foods with lower postprandial glucose response through a mobile app. After 360 days, significant improvements were observed. Weight decreased from 65.4 kg to 57.3 kg (−12.4%); body mass index lowered from 26.2 to 22.96 (−12.4%); Waist circumference reduced from 104 cm to 86.3 cm (−17.0%); clinic systolic blood pressure/diastolic blood pressure reduced from 144/93 to 102/80 mmHg (−29.17%/-13.98%); fasting insulin dropped from 27.6 to 15.5 μIU/mL (−43.8%); postprandial insulin decreased from 182.4 to 23.8 μIU/mL (−87.0%); Homeostatic Model Assessment of Insulin Resistance reduced from 6.47 to 3.48 (−46.2%); estimated glomerular filteration rate improved from 116 to 128 mL/min/1.73m2 (+10.3%); urine microalbumin creatinine ratio decreased from 596 to 73 mg/g (−87.8%). Ultrasound showed reduced ovarian volume and improved fatty liver infiltration, while computed tomography scan revealed significant reductions in epicardial (21.8%), pericardial (69.9%), and visceral fat (44.4%). Discussion: This case shows the effective use of DT technology for managing PCOS, significantly improving weight, body mass index, insulin, blood pressure, and lipid profile. It supports the potential of artificial intelligence-driven, personalized interventions in chronic disease management. Conclusion: This case highlights the potential of DT technology in managing PCOS, showing significant metabolic and reproductive improvements, suggesting promising future research directions. |
| format | Article |
| id | doaj-art-4b110d9e97164f56b2a990be31f3e0f9 |
| institution | Kabale University |
| issn | 2376-0605 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
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| series | AACE Clinical Case Reports |
| spelling | doaj-art-4b110d9e97164f56b2a990be31f3e0f92025-01-15T04:11:46ZengElsevierAACE Clinical Case Reports2376-06052025-01-011117074Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case StudyParamesh Shamanna, MD0Anuj Maheshwari, MD1Ashok Keshavamurthy, MD2Sanjay Bhat, DM3Abhijit Kulkarni, DM4Shivakumar R, MD5Kumar K, MD6Mukulesh Gupta, MD7Mohamed Thajudeen, MD8Ranjita Kulkarni, MD9Shashikiran Patil, MD10Shashank Joshi, DM11Bangalore Diabetes Centre, Bangalore, Karnataka, India; Address correspondence to Dr Paramesh Shamanna, Bangalore Diabetes Centre, Bangalore, Karnataka 560043, India.Shri Hari Kamal Diabetes and Heart Clinic, Lucknow, Uttar Pradesh, IndiaChandana Clinic, Bangalore, Karnataka, IndiaDepartment of Cardiology, Mukambika Heart Care, Bangalore, Karnataka, IndiaDepartment of Cardiology, South End Speciality Clinics, Bangalore, Karnataka, IndiaBangalore Diabetes Centre, Bangalore, Karnataka, IndiaBangalore Diabetes Centre, Bangalore, Karnataka, IndiaUdyaan Health Care, Lucknow, Uttar Pradesh, IndiaTwin Health, Mountain View, CaliforniaTwin Health, Mountain View, CaliforniaTwin Health, Mountain View, CaliforniaDepartment of Diabetology and Endocrinology, Lilavati Hospital and Research center, Mumbai, IndiaBackground: Clinical manifestations of polycystic ovary syndrome (PCOS) are heterogeneous, with hallmarks including anovulation, androgen excess, and insulin resistance. Case Report: A 38-year-old female with typical PCOS features presented with hypertension, obesity, and elevated fasting and postprandial insulin levels. She was enrolled in the Digital Twin (DT) platform, which uses artificial intelligence and Internet of Things to deliver personalized nutrition by predicting postprandial glucose responses and suggesting alternative foods with lower postprandial glucose response through a mobile app. After 360 days, significant improvements were observed. Weight decreased from 65.4 kg to 57.3 kg (−12.4%); body mass index lowered from 26.2 to 22.96 (−12.4%); Waist circumference reduced from 104 cm to 86.3 cm (−17.0%); clinic systolic blood pressure/diastolic blood pressure reduced from 144/93 to 102/80 mmHg (−29.17%/-13.98%); fasting insulin dropped from 27.6 to 15.5 μIU/mL (−43.8%); postprandial insulin decreased from 182.4 to 23.8 μIU/mL (−87.0%); Homeostatic Model Assessment of Insulin Resistance reduced from 6.47 to 3.48 (−46.2%); estimated glomerular filteration rate improved from 116 to 128 mL/min/1.73m2 (+10.3%); urine microalbumin creatinine ratio decreased from 596 to 73 mg/g (−87.8%). Ultrasound showed reduced ovarian volume and improved fatty liver infiltration, while computed tomography scan revealed significant reductions in epicardial (21.8%), pericardial (69.9%), and visceral fat (44.4%). Discussion: This case shows the effective use of DT technology for managing PCOS, significantly improving weight, body mass index, insulin, blood pressure, and lipid profile. It supports the potential of artificial intelligence-driven, personalized interventions in chronic disease management. Conclusion: This case highlights the potential of DT technology in managing PCOS, showing significant metabolic and reproductive improvements, suggesting promising future research directions.http://www.sciencedirect.com/science/article/pii/S2376060524001317polycystic ovary syndrome (PCOS)Digital Twin technologyinsulin resistancemetabolic healthpersonalized medicine |
| spellingShingle | Paramesh Shamanna, MD Anuj Maheshwari, MD Ashok Keshavamurthy, MD Sanjay Bhat, DM Abhijit Kulkarni, DM Shivakumar R, MD Kumar K, MD Mukulesh Gupta, MD Mohamed Thajudeen, MD Ranjita Kulkarni, MD Shashikiran Patil, MD Shashank Joshi, DM Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study AACE Clinical Case Reports polycystic ovary syndrome (PCOS) Digital Twin technology insulin resistance metabolic health personalized medicine |
| title | Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study |
| title_full | Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study |
| title_fullStr | Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study |
| title_full_unstemmed | Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study |
| title_short | Digital Twin Technology in Resolving Polycystic Ovary Syndrome and Improving Metabolic Health: A Comprehensive Case Study |
| title_sort | digital twin technology in resolving polycystic ovary syndrome and improving metabolic health a comprehensive case study |
| topic | polycystic ovary syndrome (PCOS) Digital Twin technology insulin resistance metabolic health personalized medicine |
| url | http://www.sciencedirect.com/science/article/pii/S2376060524001317 |
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