Key performance and training parameters in primary total hip arthroplasty – an expert consensus using the Delphi technique

Aims: Primary total hip arthroplasty (THA) is a commonly performed and successful operation which orthopaedic trainees must demonstrate competence in prior to completion of surgical training. An assessment of agreement between surgical trainers regarding the critical steps of a primary THA has never been undertaken. The aim of this study was to define and rank the key steps of a primary THA regards ease of teaching and their importance in achieving the best patient outcome. Materials and methods: The Delphi technique with 3 iterative rounds was used to establish expert group consensus. The benchmark for consensus was set at an 80% agreement in any category for each step of a THR. The intra-class correlation coefficient (ICC) was used to report on the inter- and intra-rater reliabilities between and within participants responses respectively in rounds 2 and 3. Results: 50 consultant orthopaedic hip surgeons completed round 2, and 28 completed round 3. Overall, 27 steps (54 parameters) were identified, with 16 parameters achieving consensus agreement for their impact on patient outcome, and 17 for ease of teaching. The inter-rater ICC for patient outcome parameters was 0.89 and 0.92 in rounds 2 and 3 respectively while for teaching parameters it was 0.82 and 0.73. 50% of surgeons agreed that acetabular reaming, assessing and accurately restoring leg length, and acetabular cup anteversion were the 3 most difficult steps to teach trainees, while 90% agreed these 3 steps were substantially important to patient outcome. Another 5 steps achieved consensus for their substantial impact on patient outcome but failed to achieve consensus for ease of teaching. Conclusions: The results of this expert consensus have produced a rank-order list of the key steps in primary THA, which may be used for orthopaedic curriculum development and guiding focused improvements for surgical training in primary THR including simulation

Vitamin K Status in Nutritionally Compromised Circumstances

Vitamin K deficiency is very rare except in neonatal populations. This is due to dietary sources, particularly plant-derived phylloquinones (vitamin K1) being abundantly distributed in nature and ubiquitously available in common foods. However, there is very little information on the bioavailability of vitamin K from foods. Furthermore, despite the increased understanding of vitamin K's biological roles, there are difficulties in establishing a causal link between plausible biomarkers of vitamin K deficiency and reproducible health outcome measures. Additionally, with vitamin K there is the added complication that this vitamin is also synthesized in the gastrointestinal tract by gut microflora. As a result, the exact dietary requirements for vitamin K in numerical terms have not been fully established. Clinically significant vitamin K deficiency is almost nonexistence in healthy populations. However, there are states in which it is compromised in some population cohorts other than neonatal populations. This review illustrates some examples of vitamin K insufficiency states, which include eating disorders, undernourished children, inflammatory bowel disease, and chronic kidney disease. It also describes some biomarkers of vitamin K status used in recent studies.</p

Applicability of a Single Time Point Strategy for the Prediction of Area Under the Concentration Curve of Linezolid in Patients: Superiority of C trough- over C max-Derived Linear Regression Models

BACKGROUND AND OBJECTIVES: Linezolid, a oxazolidinone, was the first in class to be approved for the treatment of bacterial infections arising from both susceptible and resistant strains of Gram-positive bacteria. Since overt exposure of linezolid may precipitate serious toxicity issues, therapeutic drug monitoring (TDM) may be required in certain situations, especially in patients who are prescribed other co-medications. METHODS: Using appropriate oral pharmacokinetic data (single dose and steady state) for linezolid, both maximum plasma drug concentration (C(max)) versus area under the plasma concentration–time curve (AUC) and minimum plasma drug concentration (C(min)) versus AUC relationship was established by linear regression models. The predictions of the AUC values were performed using published mean/median C(max) or C(min) data and appropriate regression lines. The quotient of observed and predicted values rendered fold difference calculation. The mean absolute error (MAE), root mean square error (RMSE), correlation coefficient (r), and the goodness of the AUC fold prediction were used to evaluate the two models. RESULTS: The C(max) versus AUC and trough plasma concentration (C(trough)) versus AUC models displayed excellent correlation, with r values of >0.9760. However, linezolid AUC values were predicted to be within the narrower boundary of 0.76 to 1.5-fold by a higher percentage by the C(trough) (78.3 %) versus C(max) model (48.2 %). The C(trough) model showed superior correlation of predicted versus observed values and RMSE (r = 0.9031; 28.54 %, respectively) compared with the C(max) model (r = 0.5824; 61.34 %, respectively). CONCLUSIONS: A single time point strategy of using C(trough) level is possible as a prospective tool to measure the AUC of linezolid in the patient population