Academic literature on the topic 'Robert Jones and Agnes Hunt Orthopaedic Hospital'

Aims Our rural orthopaedic service has undergone service restructure during the COVID-19 pandemic in order to sustain hip fracture care. All adult trauma care has been centralised to the Royal Shrewsbury Hospital for assessment and medical input, before transferring those requiring operative intervention to the Robert Jones and Agnes Hunt Orthopaedic Hospital. We aim to review the impact of COVID-19 on hip fracture workload and service changes upon management of hip fractures. Methods We reviewed our prospectively maintained trust database and National Hip Fracture Database records for the months of March and April between the years 2016 and 2020. Our assessment included fracture pattern (intrascapular vs extracapsular hip fracture), treatment intervention, length of stay and mortality. Results We treated 288 patients during March and April between 2016 and 2020, with a breakdown of 55, 58, 53, 68, and 54 from 2016 to 2020 respectively. Fracture pattern distribution in the pre-COVID-19 years of 2016 to 2019 was 58% intracapsular and 42% extracapsular. In 2020 (COVID-19 period) the fracture patterns were 65% intracapsular and 35% extracapsular. Our mean length of stay was 13.1 days (SD 8.2) between 2016 to 2019, and 5.0 days (6.3) days in 2020 (p < 0.001). Between 2016 and 2019 we had three deaths in hip fracture patients, and one death in 2020. Hemiarthroplasty and dynamic hip screw fixation have been the mainstay of operative intervention across the five years and this has continued in the COVID-19 period. We have experienced a rise in conservatively managed patients; ten in 2020 compared to 14 over the previous four years. Conclusion There has not been a reduction in the number of hip fractures during COVID-19 period compared to the same time period over previous years. In our experience, there has been an increase in conservative treatment and decreased length of stay during the COVID -19 period. Cite this article: Bone Joint Open 2020;1-8:500–507.

Background:Biological therapy plays a major role in the management of patients with rheumatic disorders. Evidences generated at experimental settings have shown biosimilars as clinically effective, safe and cost effective. Nevertheless, real world data are lacking about cost effectiveness and causes of switching back to originator product among patientsObjectives:To describe the associated factors and cost evaluation of switching back to the originator etanercept from the biosimilar among patients with rheumatic disorders at The Robert Jones and Agnes Hunt Orthopaedic Hospital of United KingdomMethods:A descriptive cross-sectional study was undertaken with secondary data in a tertiary care hospital. All the patients who were switched from original etanercept (originator) to biosimilar Etanercept from October 2018 to June 2019 were included in the study. A pre-tested data extraction sheet was used in the data collection. Annual expenditure estimates for the treatment modalities were collected by consulting the experts. Descriptive analysis was done for the characteristics of the study sample and for the estimated annual costs. Associations of age and sex in the switching of treatment modalities were explored with chi-square test and Mann Whitney U test with 5% significance level.Results:Records of 100 participants were extracted with a male to female ratio of 1: 1.4. The median [interquartile range (IQR)] of the participants was 54 (44 to 66) years. The leading three diagnoses were: rheumatoid arthritis (65%), Ankylosing Spondylitis (18%) and Psoriatic arthritis (14%). Out of the participants, 32 (32%) switched back to originator with a median (IQR) duration of 16.0 (10.5 to 19.5) weeks of commencing the biosimilar. The proportions of switching back were 28.1%, 34.4% and 37.5% among those who did, in the chronological 3- monthly intervals of the study. The main reasons for switching back included; side effects (21.9%), lack of efficacy (65.6%), both of these (9.4%) and other reasons (3.1%). Older age was observed among those who switched back (p<0.05) but gender did not show a statistically significant association (p=0.532). The annual estimated cost for biosimilar was 37.3% less than that for originator per patient.Conclusion:In our cohort nearly one third switched back to the originator following the commencement of biosimilar incurring a financial and resource burden to the rheumatology department which in turn will have wider ramifications on the health care system. Exploring the reasons and factors associated with switching back to the originator in larger scale studies would help in planning cost-effective interventions and understanding the reasons why the patients revert back to the originator from the biosimilar therapy, especially among the older patients.References:[1]Villamañan BE, Jiménez NI, Moreno RF, et al. AB1475-HPR Cost evolution of biological agents for the treatment of spondyloarthritis in a spanish tertiary hospital: influential factors in price development. Annals of the Rheumatic Diseases 2018, 77: p1867-1868. doi: 10.1136/annrheumdis-2018-eular.2681[2]Brites L, Costa F, Freitas J, Luis M, Coutinho M, Santiago M, Duarte C, Salvador MJ, da Silva JAP. Impact of Block Switch to Biosimilar Etanercept in Practice, Accross Different Rheumatic Diseases [abstract]. Arthritis Rheumatol. 2018; 70 (suppl 10). Available at <https://acrabstracts.org/abstract/impact-of-block-switch-to-biosimilar-etanercept-in-practice-accross-different-rheumatic-diseases>. Accessed [January 30, 2020].Disclosure of Interests:None declared

Background:Trabecular bone score (TBS) is an index of skeletal quality that has been validated as an independent risk factor for fracture and incorporated into fracture risk assessment (FRAX). TBS provides information on bone microarchitecture not captured from standard bone mineral density (BMD) measured by dual energy X-ray absorptiometry (DXA). Nonetheless, the clinical implications of using TBS in routine practice are not yet fully understood and warrant further evaluation.Objectives:To determine whether lumbar TBS can have an impact on clinician’s treatment threshold derived from DXA and clinical risk factors: does the addition of TBS to DXA measurements make the clinician more or less likely to recommend bone sparing therapy?Methods:A cross-sectional study at a tertiary metabolic bone centre in the West Midlands region of England. Three expert metabolic bone physicians, two rheumatologists and one elderly care, assessed consecutive patients referred for a DXA scan ± clinic review and provided treatment recommendations with and without TBS. Patients ≥ 18 years old with BMI of 15-37 who were not on bone sparing therapy were considered eligible. TBS was defined according to T-score as normal (T-score ≥ -1), moderate (-1 > T-score ≥ -2.5) or degraded (T-score ≤ -2.5). TBS groups were stratified by BMD T-scores (normal, osteopenia, or osteoporosis) using minimum T-score of total hip, femoral neck, and spine to identify categories in which TBS may be of more clinical use. The main outcome measure was the proportion of change in clinician’s treatment threshold between BMD alone and BMD plus TBS. The difference was assessed for significance using Chi-square test. Additionally, the change in UK National Osteoporosis Guideline Group (NOGG) threshold was also assessed using TBS-adjusted FRAX scores. Correlations between BMD-TBS strata and the change in intervention threshold (yes/no) were carried out using Spearman test.Results:540 patients were analysed. The inclusion of TBS resulted in 8.2% change in clinician’s treatment threshold (p <0.001) shifting the outcome 6.5 % for and 1.7 % against treatment. More than half of the cases in which the clinical decision was changed were for patients with osteopenia and degraded TBS (significant correlation; P <0.001). NOGG intervention threshold was changed in 7.4% of the cases (P<0.001); 6.1% for and 1.3% against treatment. 37.5% of NOGG changed outcome was related to osteopenia with degraded TBS (p<0.001). Kappa agreement between the clinician and NOGG was fair at 0.42 (p<0.001).Conclusion:These results demonstrate that using TBS in routine clinical practice is most likely to impact treatment decision in patients with osteopenia who have compromised bone microarchitecture. Incorporating TBS in routine DXA scans may lead to a net increase in bone protective therapy of approximately 5%. It is unknown whether adopting such an approach universally can reduce future fracture risk, and prospective studies are needed to address this question.References:[1]Hans D et al. J Bone Miner Res. 2011;26(11):2762-9.[2]McCloskey EV et al. Calcif Tissue Int. 2015;96(6):500-9.Table 1.Demographic and baseline characteristics (n = 540)Female470 (87%)Age (years)68.1 ± 11.6Body mass index (BMI)26.2 ± 4.6Femoral neck T-score-1.80 ± 1.04Total hip T-score-1.32 ± 1.07Lumbar spine T-score-1.37 ± 1.42Lumbar spine TBS1.32 ± 0.13Major osteoporotic fractures238 (44%)Spinal fractures81 (15%)FRAX major osteoporotic fracture14.43 ± 9.03FRAX hip fracture4.60 ± 6.20TBS-adjusted FRAX major osteoporotic fracture13.82 ± 8.80TBS-adjusted FRAX hip fracture4.45 ± 5.73Figure 1.Distribution of changed clinical treatment threshold in normal, moderate, and degraded TBS according to BMD T-scoreAcknowledgments:Bone density unit &Rheumatology team, Robert Jones and Agnes Hunt Orthopaedic HospitalDisclosure of Interests:None declared

Background:Trabecular bone score (TBS) is a textural index of bone microarchitecture and has been found to be related to 3D bone structure. A number of cohort studies have demonstrated the value of TBS as an independent fracture risk in clinical trials. Yet, very little is known about the performance and clinical value of TBS in real life practice.Objectives:To investigate the sensitivity and specificity of TBS in identifying prevalent fractures when compared with bone mineral density (BMD) measured by DXA. To evaluate the added value of TBS in fracture risk prediction above that obtained from DXA.Methods:Consecutive patients aged ≥ 18 with BMI 15-37 attnding a DXA plus TBS assessment were considered eligible. Sensitivity, specificity, and area under the curve (AUC) for prevalent major osteoporotic fracture (MOF) and clinical vertebral fractures (VF) were assessed for the following parameters: BMD lowest T-score ≤-2.5 (neck of femur, total hip, or spine), TBS T-score ≤-2.5, and either TBS or BMD T-score ≤-2.5. BMD categories (normal, osteopenia, and osteoporosis) were stratified by TBS T-score: normal (T-score ≥-1), moderate (-1≥T-score≥-2.5), and degraded TBS (T-score ≤-2.5) resulting in 9 risk groups. Odds ratios were calculated for all risk categories and fracture prevalence was compared between the best and worst TBS strata at each BMD level using chi-square test.Results:540 patients (87% females, 68.1 ± 11.6 years) were included. 238 (44%) had MOF including 81 (15%) clinical VF. For MOF, BMD had higher sensitivity (49.6% vs 30.7%), lower specificity (68.2% vs 82.1%), and similar AUC (0.59 vs 0.56) versus TBS. For VF, the sensitivity, specificity and AUC for BMD were 60%, 64%, and 0.62 respectively versus 42%, 79.7%, and 0.61 for TBS. Combining TBS and BMD (either T-score ≤ -2.5) increased the sensitivity to 63% for MOF and 75.3% for VF without affecting AUC (0.6 and 0.64 respectively). Patients with osteoporosis and degraded TBS had the highest OR of 2.65 for MOF and 3.8 for VF. The fracture risk increased at the same level of BMD when TBS was degraded. Numerically, the risk of MOF increased steadily from strata 1 to 9 and was statistically significant for osteoporosis with degraded TBS and osteoporosis with moderate TBS. When both TBS and BMD were normal, the risk of fracture was significantly reduced. In the osteopenia and osteoporosis BMD categories, patients with degraded TBS had significantly higher prevalence of fracture compared to those with normal TBS in the same BMD category.Conclusion:Fracture risk stratification can be improved when TBS is added to BMD. The sensitivity of predicting fracture may also improve when TBS and BMD are combined. Patients with both normal TBS and BMD have the lowest fracture risk, whereas those with degraded TBS and osteoporosis have the highest risk of fracture and should be targeted for early or more aggressive treatment.References:[1]Hans D et al. J Bone Miner Res. 2011;26(11).[2]McCloskey EV et al. Calcif Tissue Int. 2015;96(6).Table 1.Prevalence and risk of MOF and VF according to BMD stratified by TBS T-scorePatients within categoryNumber of MOFOR for MOFNumber of VFOR for VFNormal BMD & TBS497 (14.3%)0.19(0.08-0.43)*00.83(0.80-.87)*Normal BMD moderate TBS195 (26.3%)0.44(0.16-1.24)2 (10.5%)0.66(0.15-2.9)Normal BMD degraded TBS72 (28.6%)0.50(0.1-2.6)1 (14.3%)0.94(0.11-7.9)Osteopenia normal TBS9633 (34.4%)0.61(0.39-0.97)7 (7.3%)0.39(0.18-0.88)*Osteopenia moderate TBS9843 (43.9%)0.99(0.64-1.54)11 (11.2%)0.67(0.34-1.32)Osteopenia degraded TBS5730 (52.6%)1.47(.085-2.55)11 (19.3%)1.41(0.7-2.86)Osteoporosis normal TBS3918 (46.2%)1.1(0.57-2.1)6 (15.4%)1(0.42-2.6)Osteoporosis moderate TBS11259 (52.7%)1.55(1.02-2.35)*21 (18.8%)1.42(0.82-2.45)Osteoporosis degraded TBS6341 (65.1%)2.65(1.53-4.59)*22 (34.9%)3.8(2.12-6.83)*Total54023881Acknowledgments:Bone density team, Robert Jones and Agnes Hunt Orthopaedic HospitalDisclosure of Interests:None declared

Abstract Background/Aims Secukinumab is an interleukin-17 inhibitor has been found to be effective in the treatment of ankylosing spondylitis (AS) in studies, including phase 3 clinical trials, however these are conducted in highly selected patients and it is important to confirm the efficacy and safety in a real world data. Response to secukinumab should be assessed after 16-weeks and continued if there has been sufficient response to treatment according to the BASDAI and spinal VAS scores. Methods This was a multicentre cross-sectional observational study in collaboration with Midland Ankylosing Spondylitis Collaboration. Consecutive baseline and 16th week data of all AS patients on Secukinumab from 2017 to 2019 were collected and analysed to assess treatment response. All data were compiled in excel sheets and analysed using Medcalc calculator. Data were collected from collaborative efforts of the Royal Wolverhampton NHS trust, Queen’s Hospital (Burton on Trent), Leicester Royal Infirmary and Robert Jones and Agnes Hunt hospital. Results Total 92 patients with radiographic AS on standard dose of secukinumab were included at baseline and 88 were followed up till week 16. Mean age was 45.9(SD ± 15) (Median=44years) and 67% were male. Baseline Mean BASDAI was 7 (SD ± 1.7); Mean CRP was 16.6 (SD ± 11.2), Mean VAS was 7.6(SD ± 1.6). There was statistical significant change in BASDAI, VAS and CRP levels at week 16th. ΔBASDAI=2.2 (SD ± 2) (p = 0.002), ΔVAS=3.2 (SD ± 2.1) (p = 0.001), ΔCRP=6.9 (SD ± 17) (p = 0.03). At 16th week, 68% had clinical improvement while 4 patients discontinued therapy (2-colitis, 1-uveitis and 1-patient choice). 10% overall had some adverse effects with most common being upper respiratory tract infection. We also compared patients with previous anti-TNF exposure (TE) to Anti-TNF naïve (TN). 63% were in TE group vs 37% in TN. 69% of TE and 76% of TN showed clinical improvement at week 16.Mean ΔBASDAI was more in TN group vs TE (p = 0.01), however there was no difference in ΔVAS and ΔCRP levels. (p = 0.0 & p = 0.2 respectively). Conclusion This multi-centre retrospective analysis found secukinumab to be clinically effective in 68% of patients with AS. There was significant improvement in BASDAI, VAS and CRP levels at week16. Compared to anti-TNF resistant patients, TNF-Naïve responded better to secukinumab, although both showed good clinical improvement. These findings support the use of secukinumab in the treatment of AS, as a first line therapy or for those who have failed anti-TNF therapy. Safety signals observed in the real-word data set were consistent with those seen in the clinical trials and the Summary of Product Characteristics. Disclosure N. Jain: None. R. Laxminarayan: Honoraria; Honorarium from Novartis, Lilly, Pfizer and Abvie. A. Moorthy: Honoraria; Speaker and conference fee MSD, Novartis, Abbvie. R. Amarasena: None. N. Cleaton: None. G. Kakade: None. A. Gunawardane: None. T. Khan: None. H. Sapkota: None. N. Barkham: Grants/research support; research funding from Novartis, Eli Lilly, UCB.