https://doi.org/10.1177/1120700019836962 HIP International 1–9 © The Author(s) 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/1120700019836962 journals.sagepub.com/home/hpi HIP HIP International Introduction Hip fractures are a socio-economic burden to both indi- vidual and the community, and result in loss of independ- ence, reduced quality of life and substantial mortality. 1,2 Outcomes are worse in extremely elderly and nursing home residents, with a 120-day mortality of 38.1%. 3,4 Specifically, in this frail and medically unfit patients with advanced comorbidities, the decision to pursue life-pro- longing surgery needs to be carefully considered in the context of patient’s life expectancy. 5,6 Clinical prediction models provide insight into the rela- tive effects of predictors for prognosis of mortality. These models provide absolute risk estimates for individual patients in order to optimise quality of care. Development and validation of the Brabant Hip Fracture Score for 30-day and 1-year mortality Cornelis LP van de Ree 1 , Taco Gosens 1,2 , Alexander H van der Veen 3 , Cees JM Oosterbos 4 , Martijn W Heymans 5 and Mariska AC de Jongh 1,6 Abstract Background: Hip fractures in the elderly are associated with advanced comorbidities and high mortality rates. Mortality prediction models can support clinicians in tailoring treatment for medical decision making in frail elderly patients. The aim of this study was to develop and internally validate the Brabant Hip Fracture Score, for 30-day (BHFS-30) and 1-year mortality (BHFS-365) after hip fracture. Material and methods: A cohort study was conducted in 2 hospitals on operatively treated patients of 65 years and older with a hip fracture. Manual backward multivariable logistic regression was used to select independent predictors of 30-day and 1-year mortality. Internal validation was performed using bootstrapping techniques. Model performance was assessed with: (1) discrimination via the area under the receiver operating characteristic curve (AUC); (2) explained variance via Nagelkerke’s R 2 ; (3) calibration via Hosmer-Lemeshow (H&L) test and calibration plots. Results: Independent predictors of 30-day mortality were: age, gender, living in an institution, Hb, respiratory disease, diabetes and malignancy. In addition, cognitive frailty and renal insufficiency, were selected in the BHFS-365. Both models showed acceptable discrimination after internal validation (AUC = 0.71 and 0.75). The Hosmer-Lemeshow test indicated no lack of fit (p > 0.05). Discussion: We demonstrated that the internally validated and easy to use BHFS in surgically treated elderly patients after a hip fracture showed acceptable discrimination and adequate calibration. In clinical practice a cutoff of BHFS-30 ⩾ 24 could identify frail elderly patients at high risk for early mortality and could support clinicians, patients and families in tailoring treatment for medical decision making. Keywords Clinical prediction model, elderly, hip fracture, mortality Date received: 19 October 2018; accepted: 31 December 2018 1 Department Trauma TopCare, Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands 2 Department of Orthopaedic Surgery, Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands 3 Department of Surgery, Catharina Hospital, Eindhoven, the Netherlands 4 Department of Orthopaedic Surgery, Catharina Hospital, Eindhoven, the Netherlands 5 Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands 6 Brabant Trauma Registry, Network Emergency Care Brabant, Elisabeth-TweeSteden Hospital, Tilburg, the Netherlands Corresponding author: Cornelis LP van de Ree, Department Trauma TopCare, Elisabeth- TweeSteden Hospital, Hilvarenbeekseweg 60, 5022 GC Tilburg, The Netherlands. Email: m.vanderee@etz.nl 836962HPI 0 0 10.1177/1120700019836962HIP InternationalRee et al. research-article 2019 Original Research Article