Data Science and Geriatric Anesthesia Research: Opportunity and Challenges

Mani Ratnesh S Sandhu; Mayanka Tickoo; Amit Bardia

doi:10.1016/j.cger.2024.03.009

Data Science and Geriatric Anesthesia Research: Opportunity and Challenges

Clin Geriatr Med. 2025 Feb;41(1):101-116. doi: 10.1016/j.cger.2024.03.009.

Authors

Mani Ratnesh S Sandhu¹, Mayanka Tickoo², Amit Bardia³

Affiliations

¹ Department of Neurosurgery, University of Iowa Hospitals and Clinics, Iowa City, IA, USA.
² Division of Pulmonary, Department of Medicine, Critical Care and Sleep Medicine, Tufts Medical Center, Biewend Building, 3Road Floor, 260 Tremont Street, Boston, MA 02118, USA.
³ Department of Anesthesiology, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 06520, USA. Electronic address: [email protected].

PMID: 39551536
DOI: 10.1016/j.cger.2024.03.009

Abstract

With an increase in geriatric population undergoing surgical procedures, research focused on enhancing their perioperative outcomes is of paramount importance. Currently, most of the evidence-based medicine protocols are driven by studies concentrating on adults encompassing all adult age groups. Given the alterations in physiology with aging, geriatric patients respond differently to anesthetics and, therefore, require specific research initiatives to further expound on the same. Large databases and the development of sophisticated analytic tools can provide meaningful insights into this. Here, we discuss a few research opportunities and challenges that data scientists face when focusing on geriatric perioperative research.

Keywords: Clinical outcome; Data; Deep learning; Geriatric anesthesia; Geriatric perioperative; Machine learning.

Publication types

Review

MeSH terms

Aged
Anesthesia* / methods
Anesthesiology / methods
Biomedical Research
Data Science* / methods
Geriatric Anesthesia
Geriatrics* / methods
Humans