Resilience plays a significant role in reaching optimal functional recovery in hip-fractured elderly people. Results suggest the introduction of early routine assessment of resilience in future outcome studies in rehabilitation.

Introduction Haemophilia is a recessive X‐linked inherited bleeding disorder, whose typical symptom is spontaneous intra‐articular haemorrhage leading to joint damage, which can be quantified by the Haemophilia Joint Health Score (HJHS). Arthropathy and other characteristics of haemophilic patients may reduce bone mineral density (BMD), increasing the risk for fragility fractures, which also may occur due to bone quality impairment. Aim To evaluate bone quantity by BMD and bone quality by Trabecular Bone Score (TBS), bone strain (BS) and hip structural analysis (HSA) in a haemophilic population, and to relate these parameters to general and specific risk factors for osteoporosis and to HJHS. Methods Seventy haemophilic patients ≥18 years were enrolled. Densitometric derived lumbar spine and femoral BMD with TBS, BS and HSA were performed. Data regarding risk factors for osteoporosis, presence of arthroprosthesis or arthrodesis were collected, and HJHS was calculated. A Z‐score ≤−2.0 defined a low bone mass. Results Overall, a reduced bone mass was present in 52 patients at the femur and in 38 at the lumbar spine. Lumbar spine BMD, TBS and BS did not correlate with HJHS. HSA bone geometric parameters correlated negatively with HJHS. BMD and HSA correlated with some risk factors for osteoporosis, namely HIV and its therapy, hepatitis C and smoking. Conclusions Haemophilic patients showed a reduced BMD at lumbar spine and/or femur. Femoral bone density and geometry correlated with HJHS. The microarchitecture of the trabecular vertebral bone seemed to be not influenced by the haemophilic joint damage.

Purpose In-brace radiograph of adolescents with idiopathic scoliosis (AIS) has been shown to reflect brace efficacy and the possibility of achieving curve correction. Conversely, the first out-of-brace radiograph could demonstrate the patient’s ability to maintain the correction. We aimed to determine which of the two radiographs is the best predictor of the Cobb angle at the end of treatment (final radiograph). Design Retrospective cohort study of a prospective dataset. Methods The population was selected based on the following inclusion criteria: AIS, age 10–18 years; Risser score 0–2; Cobb angle 25–40°; brace treatment; availability of all radiographs. Statistics: Pearson correlations provide a first exploration of data. The univariate and multivariate logistic regression model tested the predictors. Finally ROC curve provided a check of model accuracy. Results A total of 131 patients were included (mean age 13.0 ± 1.3, Cobb angle 33.2 ± 5.5°; 78% females). At the end of treatment, 56% had stabilised, 9% had progressed, and 44% had improved. The difference between the in-brace and final radiographs was 8.0 ± 6.0°, while the difference between the first out-of-brace and final radiographs was 1.8 ± 5.2°. The best predictor of final outcome was the first out-of-brace radiograph (0.80), compared to in-brace (0.68) and baseline (0.59) radiographs. The best cut-offs to predict avoidance of progression were 30% and 10% of the correction rates for the in-brace and first out-of-brace radiographs, respectively. Conclusion The first out-of-brace radiograph predicts end results better than the in-brace radiograph. It offers an excellent clinical reference for clinicians and patients. The first out-of-brace radiograph should be considered an essential element of future predictive models. Level of Evidence 1 Diagnostic: individual cross-sectional studies with consistently applied reference standard and blinding.

Purpose Treatment selection for idiopathic scoliosis is informed by the risk of curve progression. Previous models predicting curve progression lacked validation, did not include the full growth/severity spectrum or included treated patients. The objective was to develop and validate models to predict future curve angles using clinical data collected only at, or both at and prior to, an initial specialist consultation in idiopathic scoliosis. Methods This is an analysis of 2317 patients with idiopathic scoliosis between 6 and 25 years old. Patients were previously untreated and provided at least one prior radiograph prospectively collected at first consult. Radiographs were re-measured blinded to the predicted outcome: the maximum Cobb angle on the last radiograph while untreated. Linear mixed-effect models were used to examine the effect of data from the first available visit (age, sex, maximum Cobb angle, Risser, and curve type) and from other visits while untreated (maximum Cobb angle) and time (from the first available radiograph to prediction) on the Cobb angle outcome. Interactions of the first available angle with time, of time with sex, and time with Risser were also tested. Results We included 2317 patients (83% of females) with 3255 prior X-rays where 71% had 1, 21.1% had 2, and 7.5% had 3 or more. Mean age was 13.9 ± 2.2yrs and 81% had AIS. Curve types were: 50% double, 26% lumbar/thoracolumbar-lumbar, 16% thoracic, and 8% other. Cobb angle at the first available X-ray was 20 ± 10° (0–80) vs 29 ± 13° (6–122) at the outcome visit separated by 28 ± 22mths. In the model using data at and prior to the specialist consult, larger values of the following variables predicted larger future curves: first available Cobb angle, Cobb angle on other previous X-ray, and time (with Time2 and Time3) to the target prediction. Larger values on the following variables predicted a smaller future Cobb angle: Risser and age at the first available X-ray, time*Risser and time*female sex interactions. Cross-validation found a median error of 4.5o with 84% predicted within 10°. Similarly, the model using only data from the first specialist consult had a median error of 5.5o with 80% of cases within 10° and included: maximum Cobb angle at first specialist consult, Time, Time2, age, curve type, and both interactions. Conclusions The models can help clinicians predict how much curves would progress without treatment at future timepoints of their choice using simple variables. Predictions can inform treatment prescription or show families why no treatment is recommended. The nonlinear effects of time account for the rapid increase in curve angle at the beginning of growth and the slowed progression after maturity. These validated models predicted future Cobb angle with good accuracy in untreated idiopathic scoliosis over the full growth spectrum.

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