18 results found
Ridzwan MIZ, Sukjamsri C, Pal B, et al., 2018, Femoral fracture type can be predicted from femoral structure: A finite element study validated by digital volume correlation experiments., J Orthop Res, Vol: 36, Pages: 993-1001
Proximal femoral fractures can be categorized into two main types: Neck and intertrochanteric fractures accounting for 53% and 43% of all proximal femoral fractures, respectively. The possibility to predict the type of fracture a specific patient is predisposed to would allow drug and exercise therapies, hip protector design, and prophylactic surgery to be better targeted for this patient rendering fracture preventing strategies more effective. This study hypothesized that the type of fracture is closely related to the patient-specific femoral structure and predictable by finite element (FE) methods. Fourteen femora were DXA scanned, CT scanned, and mechanically tested to fracture. FE-predicted fracture patterns were compared to experimentally observed fracture patterns. Measurements of strain patterns to explain neck and intertrochanteric fracture patterns were performed using a digital volume correlation (DVC) technique and compared to FE-predicted strains and experimentally observed fracture patterns. Although loaded identically, the femora exhibited different fracture types (six neck and eight intertrochanteric fractures). CT-based FE models matched the experimental observations well (86%) demonstrating that the fracture type can be predicted. DVC-measured and FE-predicted strains showed obvious consistency. Neither DXA-based BMD nor any morphologic characteristics such as neck diameter, femoral neck length, or neck shaft angle were associated with fracture type. In conclusion, patient-specific femoral structure correlates with fracture type and FE analyses were able to predict these fracture types. Also, the demonstration of FE and DVC as metrics of the strains in bones may be of substantial clinical value, informing treatment strategies and device selection and design. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:993-1001, 2018.
Riviere C, Lazic S, Boughton OR, et al., 2018, Current concepts for aligning knee implants: patient-specific or systematic?, EFORT Open Reviews, Vol: 3, Pages: 1-6, ISSN: 2058-5241
Arnold M, Zhao S, Ma S, et al., 2017, Microindentation - a tool for measuring cortical bone stiffness? A systematic review., Bone Joint Res, Vol: 6, Pages: 542-549, ISSN: 2046-3758
OBJECTIVES: Microindentation has the potential to measure the stiffness of an individual patient's bone. Bone stiffness plays a crucial role in the press-fit stability of orthopaedic implants. Arming surgeons with accurate bone stiffness information may reduce surgical complications including periprosthetic fractures. The question addressed with this systematic review is whether microindentation can accurately measure cortical bone stiffness. METHODS: A systematic review of all English language articles using a keyword search was undertaken using Medline, Embase, PubMed, Scopus and Cochrane databases. Studies that only used nanoindentation, cancellous bone or animal tissue were excluded. RESULTS: A total of 1094 abstracts were retrieved and 32 papers were included in the analysis, 20 of which used reference point indentation, and 12 of which used traditional depth-sensing indentation. There are several factors that must be considered when using microindentation, such as tip size, depth and method of analysis. Only two studies validated microindentation against traditional mechanical testing techniques. Both studies used reference point indentation (RPI), with one showing that RPI parameters correlate well with mechanical testing, but the other suggested that they do not. CONCLUSION: Microindentation has been used in various studies to assess bone stiffness, but only two studies with conflicting results compared microindentation with traditional mechanical testing techniques. Further research, including more studies comparing microindentation with other mechanical testing methods, is needed before microindentation can be used reliably to calculate cortical bone stiffness.Cite this article: M. Arnold, S. Zhao, S. Ma, F. Giuliani, U. Hansen, J. P. Cobb, R. L. Abel, O. Boughton. Microindentation - a tool for measuring cortical bone stiffness? A systematic review.Bone Joint Res2017;6:542-549. DOI: 10.1302/2046-3758.69.BJR-2016-0317.R2.
Boughton OR, Zhao S, Arnold M, et al., 2017, Measuring bone stiffness using microindentation, British Orthopaedic Research Society (BORS) 2016 Conference, Publisher: British Editorial Society of Bone and Joint Surgery, Pages: 31-31, ISSN: 2049-4416
Ma S, Goh EL, Jin A, et al., 2017, Long-term effects of bisphosphonate therapy: perforations, microcracks and mechanical properties, SCIENTIFIC REPORTS, Vol: 7, ISSN: 2045-2322
Ma S, Goh EL, Patel B, et al., 2016, Are the cracks starting to appear in bisphosphonate therapy?, British Orthopaedic Research Society (BORS) 2016 Conference, Publisher: British Editorial Society of Bone and Joint Surgery, Pages: 53-53, ISSN: 2049-4416
Boughton O, Jones GG, Lavy CB, et al., 2015, Young, male, road traffic victims: a systematic review of the published trauma registry literature from low and middle income countries, SICOT-J, Vol: 1, Pages: 10-10
Boughton OR, Bernard J, Szarko M, 2015, Odontoid process fractures: the role of the ligaments in maintaining stability. A biomechanical, cadaveric study, SICOT-J, Vol: 1, Pages: 11-11
Crossley KM, Callaghan MJ, van Linschoten R, 2015, Patellofemoral pain, BMJ, Pages: h3939-h3939
Lazic S, Boughton O, Hing C, et al., 2014, Arthroscopic washout of the knee: A procedure in decline, The Knee, Vol: 21, Pages: 631-634, ISSN: 0968-0160
Boughton O, Borgulya G, Cecconi M, et al., 2013, A published pharmacogenetic algorithm was poorly predictive of tacrolimus clearance in an independent cohort of renal transplant recipients., Br J Clin Pharmacol, Vol: 76, Pages: 425-431
AIMS: An algorithm based on the CYP3A5 genotype to predict tacrolimus clearance to inform the optimal initial dose was derived using data from the DeKAF study (Passey et al. Br J Clin Pharmacol 2011; 72: 948-57) but was not tested in an independent cohort of patients. Our aim was to test whether the DeKAF dosing algorithm could predict estimated tacrolimus clearance in renal transplant recipients at our centre. METHODS: Predicted tacrolimus clearance based on the DeKAF algorithm was compared with dose-normalized trough whole-blood concentrations (estimated clearance) on day 7 after transplantation in a single-centre cohort of 255 renal transplant recipients. RESULTS: There was a weak correlation (r = 0.431) between clearance based on dose-normalized trough whole-blood concentrations and DeKAF algorithm-predicted clearance. The means of the tacrolimus clearance predicted by the DeKAF algorithm and the estimated tacrolimus clearance based on the dose-normalized trough blood concentrations were plotted against the differences in the clearance as a Bland-Altman plot. Logarithmic transformation was performed owing to the increased difference in tacrolimus clearance as the mean clearance increased. There was a highly significant systematic error (P < 0.0005) characterized by a sloped regression line [gradient, 0.88 (95% confidence interval, 0.75-1.01)] on the Bland-Altman plot. CONCLUSIONS: The DeKAF algorithm was unable to predict the estimated tacrolimus clearance accurately based on real tacrolimus doses and blood concentrations in our cohort of patients. Other genes are known to influence the clearance of tacrolimus, and a polygenic algorithm may be more predictive than those based on a single genotype.
Boughton OR, Mackenzie H, 2012, Osteoarthritis of the Trapeziometacarpal Joint (TMJ): A Review of the Literature, Osteoarthritis- Diagnosis, Treatment and Surgery
Boughton O, Adds PJ, Jayasinghe JAP, 2010, The potential complications of open carpal tunnel release surgery to the ulnar neurovascular bundle and its branches: A cadaveric study, Clinical Anatomy, Vol: 23, Pages: 545-551, ISSN: 0897-3806
Lazic S, Boughton OR, Kellett C, et al., Day-Case Surgery For Total Hip And Knee Replacement: How Safe And Effective Is It?, EFORT open reviews, ISSN: 2058-5241
Soukup B, Bishomun S, Boughton OR, et al., Improving Undergraduate Orthopedic Surgery Skills and Knowledge in a One Day Course, Medical Science Educator
Wiik AV, Logishetty K, Brevadt MJ, et al., The loading patterns of a short femoral stem in total hip arthroplasty, Journal of Orthopaedics and Traumatology, ISSN: 1590-9921
Aims:The purpose of this study was to examine the gait pattern of total hip arthroplasty(THA) patients with a new short femoral stem at different speeds and inclinations.Methods:A total of 40 unilateral THA patients were tested on an instrumented treadmill. Theycomprised two groups (shorter stemmed THA n=20, longer stemmed THA n=20), bothwhich had the same surgical posterior approach. The shorter femoral stemmedpatients were taken from an ongoing hip trial with minimum 12 months postop. Thecomparative longer THR group with similar disease and severity were taken from a gaitdatabase along with a demographically similar group of healthy controls (n=35).All subjects were tested through their entire range of gait speeds and inclines withground reaction forces collected. Body weight scaling was applied and a symmetryindex to compare the implanted hip to the contralateral normal hip. An analysis ofvariance with significance set at α=0.05 was used.Results:The experimental groups were matched demographically and implant groups forpatient reported outcome measures and radiological disease. Both THA groups walkedslower than controls, but symmetry at all intervals for all groups were not significantlydifferent. Push-off loading was less favourable for both the shorter and longer stemmedTHR groups (p<0.05) depending on speed.Discussion:Irrespective of femoral stem length, symmetry for ground reaction forces for both THAgroups were returned to a normal range when compared to controls. Howeverindividual implant performance showed inferior (p<0.05) push-off forces andnormalised step length in both THR groups when compared to control
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