• Alan D Kaye, Jaeyeon Kweon, Ahmed Hashim, Mohamed Maher Elwaraky, Islam Mohammad Shehata, Patrick M Luther, and Sahar Shekoohi.
• Department of Anesthesiology, Louisiana State University Health Sciences Center at Shreveport, Shreveport, LA, 71103, USA.
• Curr Pain Headache Rep. 2024 Oct 1; 28 (10): 9991005999-1005.

Purpose Of ReviewThe elderly population typically suffer from a variety of diseases that mostly reflect the degenerative changes linked with the aging process. These diseases may be exacerbated by acute pain or by an abrupt aggravation of previously stable chronic pain.Recent FindingsPhysical and psychological changes associated with aging may influence one's experience of pain and, as a result, the severity of pain. Pain treatment in the elderly can be complex and is often a budgetary burden on the nation's health care system. These difficulties arise, in part, because of unanticipated pharmacodynamics, changed pharmacokinetics, and polypharmacy interactions. Therefore, it is critical to integrate a multidisciplinary team to develop a management strategy that incorporates medical, psychological, and surgical methods to control persistent pain conditions. It is in this critical process that pain prediction models can be of great use. The purpose of pain prediction models for the elderly is the use of mathematical models to predict the occurrence and intensity of pain and pain-related conditions. These mathematical models employ a vast quantity of data to ascertain the many risk factors for the development of pain problems in the elderly, whether said risks are adjustable or not. These models will pave the way for more informed medical decision making that are based on the findings of thousands of patients who have previously experienced the same illness and related pain conditions. However, future additional research needs to be undertaken to build prediction models that are not constrained by substantial legal or methodological limitations.© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

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