{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T15:47:32Z","timestamp":1792597652706,"version":"4.5.0"},"reference-count":109,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"20","content-domain":{"domain":["lww.com","ovid.com"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,10,21]]},"abstract":"<jats:sec>\n                    <jats:title\/>\n                    <jats:p>\n                      <jats:list list-type=\"plain\">\n                        <jats:list-item>\n                          <jats:p>\u27a2 Adult spinal deformity (ASD) outcomes are poorly predicted by chronological age alone; biological age markers, including frailty indices, sarcopenia measurements, and bone quality metrics, provide better risk assessment.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Systemic frailty tools (modified Frailty Index, ASD-Frailty Index [ASD-FI], Risk Analysis Index) predict perioperative morbidity and discharge disposition more accurately than age-based models do.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Musculoskeletal assessments, psoas and paraspinal muscle cross-sectional areas, fatty infiltration grading, and computed tomography-derived Hounsfield unit thresholds identify patients with sarcopenia and osteoporosis at elevated risk for proximal junctional failure, implant fracture, and pseudarthrosis.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Artificial intelligence and machine learning can automate osteosarcopenia quantification and define pelvic incidence-dependent alignment phenotypes, which may personalize correction targets.<\/jats:p>\n                        <\/jats:list-item>\n                        <jats:list-item>\n                          <jats:p>\u27a2 Integrating multidimensional biological age profiles into preoperative planning facilitates tailored surgical aggressiveness, age-appropriate and morphology-appropriate alignment goals, and targeted prophylactic strategies, paving the way toward a physiology-driven model in ASD surgery.<\/jats:p>\n                        <\/jats:list-item>\n                      <\/jats:list>\n                    <\/jats:p>\n                  <\/jats:sec>","DOI":"10.2106\/jbjs.25.01324","type":"journal-article","created":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T15:00:08Z","timestamp":1792594808000},"page":"1596-1607","update-policy":"https:\/\/doi.org\/10.1097\/lww.0000000000001000","source":"Crossref","is-referenced-by-count":0,"title":["The Role of Biological Age in Adult Spinal Deformity Surgery"],"prefix":"10.2106","volume":"108","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5354-6213","authenticated-orcid":false,"given":"Luis M.","family":"Salazar","sequence":"first","affiliation":[{"name":"Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4982-3708","authenticated-orcid":false,"given":"Swapna","family":"Vaja","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7473-1311","authenticated-orcid":false,"given":"Dino","family":"Samartzis","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nathan J.","family":"Lee","sequence":"additional","affiliation":[{"name":"Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, Illinois"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"276","published-online":{"date-parts":[[2026,9,3]]},"reference":[{"issue":"10193","key":"bib1-20261021","doi-asserted-by":"crossref","first-page":"160","DOI":"10.1016\/S0140-6736(19)31125-0","article-title":"Adult spinal deformity","volume":"394","author":"Diebo","year":"2019","journal-title":"Lancet."},{"issue":"1","key":"bib2-20261021","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1093\/neuros\/nyz454","article-title":"Epidemiology and socioeconomic trends in adult spinal deformity care","volume":"87","author":"Safaee","year":"2020","journal-title":"Neurosurgery."},{"issue":"11","key":"bib3-20261021","doi-asserted-by":"crossref","first-page":"3060","DOI":"10.1007\/s00586-022-07379-5","article-title":"Importance of physiological age in determining indications 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