{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,31]],"date-time":"2026-10-31T00:44:45Z","timestamp":1793407485175,"version":"4.5.0"},"reference-count":30,"publisher":"MJS Publishing, Medical Journals Sweden AB","license":[{"start":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T00:00:00Z","timestamp":1751846400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ActaO"],"abstract":"<jats:p>Background and purpose:\u00a0Treatment-related shared decision-making (SDM) in older adults with hip fractures is complex due to the need to balance patient-specific factors such as life goals, frailty, and surgical risks. It includes considerations such as prognosis and decisions concerning whether to operate or not on frail, life-limited patients. We aimed to develop machine learning (ML)-driven prediction models for short- and long-term mortality in a large cohort of patients with hip fractures.Methods:\u00a0In this national registry-based retrospective cohort study, patients aged \u2265 70 years registered in the nationwide Dutch Hip Fracture Audit from 2018\u20132023 were included. Predictive variables were selected based on the literature and\/or clinical relevance. 6 ML algorithms, including logistic regression, were trained with internal cross-validation and evaluated on discrimination (c-statistic), sensitivity, specificity, calibration, and interpretability.Results:\u00a074,396 patients (median age 84, IQR 78\u201389; 68% female) were analyzed. Most patients lived at home (69%) and high malnutrition risk was seen in 10%. 18% had dementia. Mortality rates were 9.1% (30-day), 15% (90-day), and 26% (1-year). Logistic regression performed comparably to other algorithms, but was chosen as the preferred algorithm due to its superior interpretability (c-statistic: 30-day 0.82, 90-day 0.81, 1-year 0.80).Conclusion:\u00a0We developed and validated ML algorithms, including logistic regression, for mortality prediction in older hip fracture patients with adequate performance. This information may inform SDM.<\/jats:p>","DOI":"10.2340\/17453674.2025.44248","type":"journal-article","created":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T13:05:21Z","timestamp":1751893521000},"page":"521-528","source":"Crossref","is-referenced-by-count":11,"title":["Machine learning-based prediction of short- and long-term mortality for shared decision-making in older hip fracture patients: the Dutch Hip Fracture Audit algorithms in 74,396 cases"],"prefix":"10.2340","volume":"96","author":[{"given":"Hidde","family":"Dijkstra","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cathleen S","family":"Parsons","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanne-Eva VAN","family":"Bremen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hanna C","family":"Willems","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne A H","family":"De Hond","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Barbara C","family":"Van Munster","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Job N","family":"Doornberg","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacobien H F","family":"Oosterhoff","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1183","published-online":{"date-parts":[[2025,7,7]]},"reference":[{"key":"117203","doi-asserted-by":"crossref","unstructured":"van Bremen H-E, Seppala L J, Hegeman J H, van der Velde N, Willems H C. Characteristics and outcomes of nonoperatively managed patients with hip fracture using the Dutch Hip Fracture Audit. J Orthop Trauma 2024; 38: 265-72. doi: 10.1097\/BOT.0000000000002778.","DOI":"10.1097\/BOT.0000000000002778"},{"key":"117204","doi-asserted-by":"crossref","unstructured":"Peeters C M M, Visser E, Van de Ree C L P, Gosens T, Den Oudsten B L, De Vries J. Quality of life after hip fracture in the elderly: s systematic literature review. Injury 2016; 47: 1369-82. doi: 10.1016\/j.injury.2016.04.018.","DOI":"10.1016\/j.injury.2016.04.018"},{"key":"117205","doi-asserted-by":"crossref","unstructured":"Haleem S, Choudri M J, Kainth G S, Parker M J. Mortality following hip fracture: trends and geographical variations over the last SIXTY years. Injury 2023; 54: 620-9. doi: 10.1016\/j.injury.2022.12.008.","DOI":"10.1016\/j.injury.2022.12.008"},{"key":"117206","doi-asserted-by":"crossref","unstructured":"Loggers S A I, Willems H C, Van Balen R, Gosens T, Polinder S, Ponsen K J, et al. Evaluation of quality of life after nonoperative or operative management of proximal femoral fractures in frail institutionalized patients: the FRAIL-HIP study. JAMA Surg 2022; 157: 424-34. doi: 10.1001\/jamasurg.2022.0089.","DOI":"10.1001\/jamasurg.2022.0089"},{"key":"117207","doi-asserted-by":"crossref","unstructured":"Loggers S A I, Geraerds A J L M, Joosse P, Willems H C, Gosens T, Van Balen R, et al. Nonoperative versus operative management of frail institutionalized older patients with a proximal femoral fracture: a cost-utility analysis alongside a multicenter prospective cohort study. Osteoporos Int 2023; 34: 515-25. doi: 10.1007\/s00198-023-06673-2.","DOI":"10.1007\/s00198-022-06638-x"},{"key":"117208","doi-asserted-by":"crossref","unstructured":"Laane D, Kroes T, van den Berg A, de Jongh M, The R, Van der Velde D, et al. Patient and proxy perspectives in decision-making for geriatric hip fracture management in the Netherlands: a qualitative study. BMJ Open 2024; 14. doi: 10.1136\/bmjopen-2023-082093.","DOI":"10.1136\/bmjopen-2023-082093"},{"key":"117209","doi-asserted-by":"crossref","unstructured":"van de Ree C L P, De Jongh M A C, Peeters C M M, de Munter L, Roukema J A, Gosens T. Hip fractures in elderly people: surgery or no surgery? A systematic review and meta-analysis. Geriatr Orthop Surg Rehabil 2017; 8: 173-80. doi: 10.1177\/2151458517713821.","DOI":"10.1177\/2151458517713821"},{"key":"117210","doi-asserted-by":"crossref","unstructured":"Dijkstra H, Oosterhoff J H F, van de kuit A, IJpma F F A, Schwab J H, et al. Development of machine-learning algorithms for 90-day and one-year mortality prediction in the elderly with femoral neck fractures based on the HEALTH and FAITH trials. Bone Jt Open 2023; 4: 168-81. doi: 10.1302\/2633-1462.43.BJO-2022-0162.R1.","DOI":"10.1302\/2633-1462.43.BJO-2022-0162.R1"},{"key":"117211","doi-asserted-by":"crossref","unstructured":"W\u00fcrdemann F S, van Zwet E W, Krijnen P, Hegeman J H, Schipper I B, Calf A H, et al. Is hospital volume related to quality of hip fracture care? Analysis of 43,538 patients and 68 hospitals from the Dutch Hip Fracture Audit. Eur J Trauma Emerg Surg 2023; 49: 1525-34. doi: 10.1007\/s00068-022-02205-5.","DOI":"10.1007\/s00068-022-02205-5"},{"key":"117212","doi-asserted-by":"crossref","unstructured":"W\u00fcrdemann F S, Krijnen P, van Zwet E W, Arends A J, Heetveld M J, Trappenburg M C, et al. Trends in data quality and quality indicators 5 years after implementation of the Dutch Hip Fracture Audit. Eur J Trauma Emerg Surg 2022; 48: 4783-96. doi: 10.1007\/s00068-022-02012-y.","DOI":"10.1007\/s00068-022-02012-y"},{"key":"117213","doi-asserted-by":"crossref","unstructured":"van der Werf L R, Voeten S C, van Loe C M M, Karthaus E G, Wouters M W J M, Prins H A. Data verification of nationwide clinical quality registries. BJS Open 2019; 3: 857-64. doi: 10.1007\/s00068-022-02012-y.","DOI":"10.1002\/bjs5.50209"},{"key":"117214","doi-asserted-by":"crossref","unstructured":"Bui M, Nijmeijer W S, Hegeman J H, Witteveen A, Groothuis-Oudshoorn C G M. Systematic review and meta-analysis of preoperative predictors for early mortality following hip fracture surgery. Osteoporos Int 2024; 35: 561-74. doi: 10.1007\/s00198-023-06942-0.","DOI":"10.1007\/s00198-023-06942-0"},{"key":"117215","doi-asserted-by":"crossref","unstructured":"Nijmeijer W S, Voorthuis B J, Groothuis-Oudshoorn C G M, W\u00fcrdemann F S, van der Velde D, Vollenbroek-Hutten M M R, et al. . The prediction of early mortality following hip fracture surgery in patients aged 90 years and older: the Almelo Hip Fracture Score 90 (AHFS90). Osteoporos Int 2023; 34: 867-77. doi: 10.1007\/s00198-023-06696-9.","DOI":"10.1007\/s00198-023-06696-9"},{"key":"117216","doi-asserted-by":"crossref","unstructured":"Liu F, Liu C, Tang X, Gong D, Zhu J, Zhang X. Predictive value of machine learning models in postoperative mortality of older adults patients with hip fracture: a systematic review and meta-analysis. Arch Gerontol Geriatr 2023; 115: 105120. doi: 10.1016\/j.archger.2023.105120.","DOI":"10.1016\/j.archger.2023.105120"},{"key":"117217","doi-asserted-by":"crossref","unstructured":"Oosterhoff J H F, Dijkstra H, Karhade A V, Poolman R W, Schipper I B, Nelissen R G H H, et al. . Clockwise torque results in higher reoperation rates in left-sided femur fractures. 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Development and validation of a hospital screening tool for malnutrition: the short nutritional assessment questionnaire (SNAQ\u00a9). Clin Nutr 2005; 24: 75-82. doi: 10.1016\/j.clnu.2004.07.015.","DOI":"10.1016\/j.clnu.2004.07.015"},{"key":"117221","doi-asserted-by":"crossref","unstructured":"Stratton R J, King C L, Stroud M A, Jackson A A, Elia M. \u2018Malnutrition Universal Screening Tool\u2019 predicts mortality and length of hospital stay in acutely ill elderly. Br J Nutr 2006; 95: 325-30. doi: 10.1079\/bjn20051622.","DOI":"10.1079\/BJN20051622"},{"key":"117222","doi-asserted-by":"crossref","unstructured":"Voeten S C, Nijmeijer W S, Vermeer M, Schipper I B, Hegeman J H. Validation of the Fracture Mobility Score against the Parker Mobility Score in hip fracture patients. Injury 2020; 51: 395-9. doi: 10.1016\/j.injury.2019.10.035.","DOI":"10.1016\/j.injury.2019.10.035"},{"key":"117223","doi-asserted-by":"crossref","unstructured":"Steyerberg E W, Vergouwe Y. 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