{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,3]],"date-time":"2026-11-03T13:47:27Z","timestamp":1793713647823,"version":"4.6.1"},"reference-count":22,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T00:00:00Z","timestamp":1772668800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Arthroplasty"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>While frailty assessment has become integral to preoperative risk stratification, the optimal measurement tool remains unclear for elderly women undergoing total shoulder arthroplasty (TSA). This study compared the predictive performance of the Risk Analysis Index (RAI) against traditional metrics, including the modified frailty index-5 (mFI-5) and Geriatric Nutritional Risk Index (GNRI) in this specific population.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We conducted a retrospective analysis of ACS NSQIP data from 2015\u20132021, including female patients aged 65\u201389 undergoing inpatient TSA. RAI incorporates age, functional status, recent weight loss, and physiological markers, including renal failure, congestive heart failure, and dyspnea. The mFI-5 assesses five comorbidities (diabetes, hypertension, COPD, heart failure, functional dependence), while the GNRI evaluates nutritional status using albumin and body weight. The discriminative ability of RAI, mFI-5, and GNRI was assessed using area under the curve (AUC) analysis for multiple 30-day outcomes. Primary outcomes were non-home discharge and extended length of stay (\u2265\u20094\u00a0days), selected based on their clinical importance for discharge planning and quality metrics. Secondary outcomes included 30-day mortality, major and minor complications, readmission, and reoperation. Discriminative ability was assessed using area under the curve (AUC) analysis. Internal validation was performed using bootstrap resampling.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Among 11,965 patients analyzed, RAI demonstrated superior predictive performance for primary outcomes with AUCs of 0.784 for non-home discharge and 0.670 for extended length of stay, significantly outperforming mFI-5 (AUCs 0.601 and 0.590, respectively) and GNRI (AUCs 0.544 and 0.543). For secondary outcomes, RAI maintained competitive performance across mortality, complications, readmissions, and reoperations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The Risk Analysis Index provides superior discrimination for non-home discharge and extended length of stay compared to traditional frailty measures in elderly female TSA patients, with particularly strong predictive performance for discharge disposition, supporting its adoption as the preferred risk stratification tool for discharge planning in this population.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s42836-025-00366-3","type":"journal-article","created":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T03:28:49Z","timestamp":1772681329000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Risk analysis index demonstrates superior predictive performance compared to traditional frailty metrics in elderly female patients undergoing inpatient total shoulder arthroplasty"],"prefix":"10.1186","volume":"8","author":[{"given":"Cameron J.","family":"Sabet","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bhav","family":"Jain","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bara M.","family":"Hammadeh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulhalim","family":"Kikhia","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammad D.","family":"Alfawareh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,3,5]]},"reference":[{"key":"366_CR1","doi-asserted-by":"publisher","first-page":"2601","DOI":"10.1016\/j.jse.2020.03.049","volume":"29","author":"ER Wagner","year":"2020","unstructured":"Wagner ER, Farley KX, Higgins I, Wilson JM, Daly CA, Gottschalk MB. The incidence of shoulder arthroplasty: rise and future projections compared with hip and knee arthroplasty. J Shoulder Elbow Surg. 2020;29:2601\u20139. https:\/\/doi.org\/10.1016\/j.jse.2020.03.049.","journal-title":"J Shoulder Elbow Surg"},{"key":"366_CR2","doi-asserted-by":"publisher","first-page":"1232","DOI":"10.1016\/j.jse.2018.12.004","volume":"28","author":"RE Holzgrefe","year":"2019","unstructured":"Holzgrefe RE, Wilson JM, Staley CA, Anderson TL, Wagner ER, Gottschalk MB. Modified frailty index is an effective risk-stratification tool for patients undergoing total shoulder arthroplasty. J Shoulder Elbow Surg. 2019;28:1232\u201340. https:\/\/doi.org\/10.1016\/j.jse.2018.12.004.","journal-title":"J Shoulder Elbow Surg"},{"key":"366_CR3","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1016\/j.jseint.2023.08.010","volume":"8","author":"K Ling","year":"2024","unstructured":"Ling K, Achonu JU, Martino R, Liu SH, Komatsu DE, Wang ED. Six-item modified frailty index independently predicts complications following total shoulder arthroplasty. JSES Int. 2024;8:99\u2013103. https:\/\/doi.org\/10.1016\/j.jseint.2023.08.010.","journal-title":"JSES Int"},{"key":"366_CR4","doi-asserted-by":"publisher","first-page":"319","DOI":"10.1097\/BOT.0000000000001455","volume":"33","author":"SA Traven","year":"2019","unstructured":"Traven SA, Reeves RA, Althoff AD, Slone HS, Walton ZJ. New five-factor modified frailty index predicts morbidity and mortality in geriatric hip fractures. J Orthop Trauma. 2019;33:319\u201323. https:\/\/doi.org\/10.1097\/BOT.0000000000001455.","journal-title":"J Orthop Trauma"},{"key":"366_CR5","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1177\/2192568217700099","volume":"7","author":"DM Leven","year":"2017","unstructured":"Leven DM, Lee NJ, Kim JS, Kothari P, Steinberger J, Guzman J, et al. Frailty is predictive of adverse postoperative events in patients undergoing lumbar fusion. 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J Orthop Surg Res. 2025;20:247. https:\/\/doi.org\/10.1186\/s13018-025-05609-2.","journal-title":"J Orthop Surg Res"}],"container-title":["Arthroplasty"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42836-025-00366-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s42836-025-00366-3","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s42836-025-00366-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T03:28:53Z","timestamp":1772681333000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1186\/s42836-025-00366-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3,5]]},"references-count":22,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["366"],"URL":"https:\/\/doi.org\/10.1186\/s42836-025-00366-3","relation":{},"ISSN":["2524-7948"],"issn-type":[{"value":"2524-7948","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,3,5]]},"assertion":[{"value":"5 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 March 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"Ethics approval was not required for this study because it used de-identified data from the American College of Surgeons National Surgical Quality Improvement Program. The requirement for informed consent was waived due to the retrospective study design and the absence of identifiable patient information.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"18"}}