# Bridging the Gap: A narrative review of osteoporosis disability, adipokines, and the role of AI in postmenopausal women

## TL;DR

This paper reviews osteoporosis in postmenopausal women, focusing on adipokines and AI's potential to improve diagnosis and prevention.

## Contribution

It explores the emerging role of adipokines in bone metabolism and the potential of AI for early osteoporosis detection.

## Key findings

- Adipokines like chemerin, vaspin, and omentin-1 may influence bone health and metabolism.
- Machine learning could revolutionize osteoporosis diagnosis and fracture risk prediction.
- BMD measurement remains a key diagnostic tool, accounting for 70% of overall bone strength.

## Abstract

Osteoporosis is a global health concern characterized by reduced bone density and compromised bone quality, resulting in an increased risk of fractures, particularly in postmenopausal women. The assessment of bone mineral density (BMD) plays a pivotal role in diagnosing osteoporosis, as it accounts for approximately 70% of overall bone strength. The World Health Organization (WHO) has endorsed BMD measurement as a reliable method for diagnosing this condition. In Pakistan, the incidence of bone fractures is on the rise, largely attributable to an aging population and a range of contributing factors. Understanding the global and local prevalence of osteoporosis, its impact on morbidity and mortality, and the contributing factors is vital for developing effective preventive and therapeutic strategies.

The role of adipokines, including chemerin, vaspin, and omentin-1, in bone metabolism is an emerging area of investigation. These adipokines play diverse roles in physiology, ranging from inflammation and metabolic regulation to cardiovascular health. Understanding their potential impact on bone health is a topic of ongoing research. The intricate relationship between bone density, bone quality, and overall bone strength is central to understanding the diagnosis and management of osteoporosis. Current innovation in machine learning and predictive model can bring revolution in the field of bone health and osteoporosis. Early identification of people with osteoporosis or risk of fracture through machine learning can prevent disability and improve the quality of life.