The aims were to assess whether preoperative joint-specific function (JSF) and health-related quality of life (HRQoL) were associated with level of clinical frailty in patients waiting for a primary total hip arthroplasty (THA) or knee arthroplasty (KA).

Patients waiting for a THA (n=100) or KA (n=100) for more than six months were prospectively recruited from the study centre. Overall, 162 patients responded to the questionnaire (81 THA; 81 KA). Patient demographics, Oxford score, EuroQol five dimension (EQ-5D) score, EuroQol visual analogue score (EQ-VAS), Rockwood Clinical Frailty Score (CFS), and time spent on the waiting list were collected.

There was a significant correlation between CFS and the Oxford score (THA r=ˆ’0.838; p<0.001, KA r=ˆ’0.867; p<0.001), EQ-5D index (THA r=ˆ’0.663, p<0.001; KA r=ˆ’0.681; p< 0.001), and EQ-VAS (THA r=ˆ’0.414; p<0.001, KA r=ˆ’0.386; p<0.001). Confounding variables (demographics and waiting time) where adjusted for using multiple regression analysis. For each 8.5 (THA, 95% CI 7.1 to 10.0; p<0.001) and 9.9 (KA, 95% CI 8.4 to 11.4; p<0.001) point change in the Oxford score, there was an associated change in level of the CFS. For each 0.16 (THA, 95% CI 0.10 to 0.22; p<0.001) and 0.20 (KA, 95% CI 0.12 to 0.27; p<0.001) utility change in EQ-5D, there was an associated change in level of the CFS. EQ-VAS (THA, B=ˆ’11.5; p<0.001, KA B=ˆ’7.9; p=0.005) was also associated with CFS.

JSF and HRQoL in patients awaiting THA or KA for more than six months, were independently associated with level of clinical frailty. With further prospective studies, clinical frailty may prove to be a useful metric to assist in the prioritization of arthroplasty waiting lists.

At-home softcast removal with no routine clinical follow-up has shown to be safe and effective following paediatric orthopaedic trauma. It minimises clinician contact time and reduces cost. However, there is limited data on the caregiver experience.

Retrospective analysis of paediatric fractures requiring application of circumferential softcast that was later removed at home. Two time points were included: (1)July–September 2022, (2)February–April 2023. Demographics data included age, fracture classification, angulation, manipulation requirement, complications or unplanned re-attendance. Caregivers were given an information leaflet on cast removal. Caregivers completed a telephone Likert questionnaire reviewing time taken to remove cast, qualitative descriptors of cast removal and overall satisfaction.

77 families were contacted at mean 93 days post injury. Mean age was 7.5 years. 41(53%) were distal radius and 20(26%) both-bone forearm fractures. The remaining were hand, elbow or tibia injuries. 40(52%) injuries required manipulation under procedural sedation with mean sagittal angulation 24 degrees. 13(17%) patients re-attended with cast problems. Caregivers estimated a mean 13 minutes to remove cast. 83% found it ‘extremely’ or ‘somewhat’ easy. 75% were ‘extremely’ or ‘somewhat’ satisfied. 71% were ‘extremely’ or ‘somewhat’ likely to recommend at-home cast removal. Qualitative descriptors ranged from from ‘traumatising’ to ‘fun’ and ‘straightforward’.

The experience at our tertiary centre confirms at-home softcast removal with no further orthopaedic follow-up is safe and feasible, even in those requiring manipulation under sedation. The majority of families reported a positive experience; this however is not universal. Adequate patient information resources are integral to a positive caregiver's experiences.

The primary aim was to assess whether patients waiting 6-months or more for a total hip (THA) or knee (KA) arthroplasty had a deterioration in their health-related quality of life (HRQoL). Secondary aims were to assess change in level of frailty and the number living in a state worse than death (WTD).

Eight-six patients waiting for a primary TKA or KA for more than 6-months were selected at random from waiting lists in three centres. Patient demographics, waiting time, EuroQol 5-dimension (EQ-5D) and visual analogue scores (EQ-VAS), Rockwood clinical frailty score (CFS) and SF-36 subjective change in HRQoL were recorded at the time of and for a timepoint 6-months prior to assessment. The study was powered to the EQ-5D (primary measure of HRQoL).

There were 40 male and 46 female patients with a mean age of 68 (33 to 91) years; 65 patients were awaiting a THA and 21 a TKA. The mean waiting time was 372 (226 to 749) days. The EQ-5D index deteriorated by 0.222 (95%CI 0.164 to 0.280, p<0.001). The EQ-VAS also deteriorated by 10.8 (95%CI 7.5 to 14.0, p<0.001). CFS progressed from a median of 3 to 4 (p<0.001). The number of patients WTD increased from seven to 22 (p<0.001). Thirty-one(36%) patients felt their HRQoL was much worse and 28 (33%) felt it was somewhat worse.

Patients waiting more than 6-months had a clinically significant deterioration in their HRQoL and demonstrated increasing level of frailty with more than a quarter living in a health state WTD.

The evidence for treatment of acute complex radial head fractures with radial head replacement (RHR) predominantly comprises short to mid-term follow-up. This study describes the complications and long-term patient reported outcomes following RHR.

From a single-centre trauma database we retrospectively identified 119 patients over a 16-year period who underwent primary RHR for an acute complex radial head fracture. We reviewed electronic records to document post-operative complications, including prosthesis revision and removal. Patients were contacted to confirm complications and long-term patient reported outcomes. The primary outcome measure was the QuickDash (QD).

The mean age at injury was 50 years (16–94) and 63 (53%) were female. Most implants were uncemented ‘loose-fit’ monopolar prostheses; 86% (n=102) were metallic and 14% (n=17) silastic. Thirty patients (25%) required revision surgery (n=3) or prosthesis removal (n=27). Five patients underwent arthrolysis and there were four cases of infection. In the long-term, 80% (80/100; 19 deceased) were contacted at a mean of 12 years (7.5–23.5). The median QD was 6.8 (IQR, 16.8), the median EQ-5D was 0.8 (IQR, 0.6) and the median Oxford Elbow Score was 46 (IQR, 7). Overall satisfaction was high with a mean of 9.4/10 (2–10). There was no significant difference in any outcome measure for those patients requiring revision or removal surgery (all p>0.05).

This is the largest series in the literature documenting the long-term patient reported outcome after RHR. Despite a quarter of patients requiring further surgery, RHR is supported by positive long-term results for the treatment of complex radial head fractures.

Limited long term data exists comparing operatively and non-operatively treated Achilles tendon ruptures. A previous randomised controlled trial comparing early outcomes showed a short term advantage for surgery, but there are no long term prospective randomised comparisons. Our aim was to determine whether surgery conferred long term benefits in terms of patient reported outcomes or re-rupture.

64 patients (80%) were followed up with postal questionnaires. Patients were asked to complete the Short Musculoskeletal Function Assessment (SMFA), Achilles Tendon Total Rupture Score (ATRS) and EQ-5D questionnaires, and to report re-ruptures.

32 patients were treated non-operatively and 32 operatively; 59 completed the SMFA and 64 the ATRS and EQ-5D assessments. There was no significant difference in SMFA score (median 1.09, IQR 4.89 in the cast group versus 2.17 and 7.07 in the operative group; p=0.347), ATRS (median 96, IQR 18 versus 93 and 15; p=0.509), EQ-5D Index (median 1.0, IQR 0.163 versus 1.0 and 0.257; p=0.327) and EQ-5D Visual Analogue Score (median score 85, IQR 15 versus 85 and 24; p=0.650). There were 2 re-ruptures in the operative group and 4 in the non-operative group (p=0.067).

This is the first prospective, randomised, long term report comparing operative and non-operative management. At follow up between 13–17 years after injury, patients reported good function and health related quality of life. There was no significant difference in re-rupture rate between the treatment groups.

A key challenge for healthcare delivery in OECD countries is the projected significant increases in populations over the age of 65 years. Australia for example will experience an increase of 16.4% by 2015 while Canada will experience an increase of 16%, UK an increase of 17.9% and US an increase of 14.3% during the same time period (Australian Bureau of Statistics, 2010). Increases of such magnitude will have significant and far reaching implications for healthcare delivery, labour force participation, housing and demand for skilled labour (Australian Bureau of Statistics, 2010). Given the impending economic impact of providing healthcare services to this projected increase of seniors, examination of technology solutions that serve to provide effective and efficient healthcare delivery during the peri and postoperative care process are highly desired and help those desiring to age in place.

Recent studies have demonstrated rapid growth in the number of seniors using computers in the US and other developed countries and is projected to increase further (Jimison et al., 2006). This technology adoption leads to further growth in the potential for health monitoring technologies (Clifford and Clifton, 2012) with the key aim being the maintenance of a seniors' autonomy through understanding how he or she can manage his or her individual health problem and what necessary actions should be taken and when (Ludwig et al., 2012).

Projections by the Congressional Budget Office for Social Security, Medicare, and Medicaid transfers as a percentage of GDP show the share of output spent on seniors' care programs in US rising from 7.6% in 2000 to 13.9% in 2030 to 21.1% in 2075 (Zhang et al., 2009, Falls, 2008). Despite the increased number of home monitoring technologies in age care contexts, there are several challenges that have to be met before integrating such services into the practice, as a real-life application (Ludwig et al., 2012). As the incidence of arthroplasty surgery is projected to increase over six fold between 2010 and 2030 in the US (Kurtz, Ong, Lau, Mowat, & Halpern, 2007), the post arthroplasty period represents a challenging environment for the adoption of new monitoring technologies to optimize the rehabilitative and recovery process.

This study develops a framework for post-arthroplasty monitoring through the application of the intelligence continuum (Wickramasinghe and Schaffer, 2006) to the post-arthroplasty care process including an analysis of the risks and complications. The benefits, barriers and critical elements of designing the theory based framework for home-monitoring technologies provides the structural framework for clinical application of the monitoring modalities. The entire arthroplasty process is included in order to provide appropriate management governance (figure 1) with the following metrics:

Improving post-operative quality by continuous monitoring of risk factors at home