Steroids in rhinoplasty: a survey of current UK otolaryngologists' practice

2005 ◽  
Vol 120 (2) ◽  
pp. 108-112 ◽  
Author(s):  
E Ofo ◽  
A Singh ◽  
J Marais

The use of steroids during rhinoplasty to reduce post-operative periorbital oedema and ecchymosis has been advocated. A number of randomized controlled trials have demonstrated the benefit of steroids in rhinoplasty. The aim of this study was to determine current UK practice in the use of steroids during rhinoplasty performed by otolaryngologists.A postal survey of consultant otolaryngologists in the UK was conducted. We received 203 responses, with 115 consultants performing 12 or more rhinoplasties per year. Only 28 consultants (24 per cent) used steroids routinely in patients undergoing rhinoplasty and of these 11 used a protocol, although this was unpublished. Dexamethasone was the most common steroid used (82 per cent), being administered as a single intravenous dose of 8 mg in the majority of cases (54 per cent). There was no correlation between the use of steroids and the number of rhinoplasties performed by individual consultants.Despite the evidence supporting the use of steroids to reduce post-operative sequelae following rhinoplasty, only a minority of consultants in the UK appear to use them as part of their practice.

Methodology ◽  
2017 ◽  
Vol 13 (2) ◽  
pp. 41-60
Author(s):  
Shahab Jolani ◽  
Maryam Safarkhani

Abstract. In randomized controlled trials (RCTs), a common strategy to increase power to detect a treatment effect is adjustment for baseline covariates. However, adjustment with partly missing covariates, where complete cases are only used, is inefficient. We consider different alternatives in trials with discrete-time survival data, where subjects are measured in discrete-time intervals while they may experience an event at any point in time. The results of a Monte Carlo simulation study, as well as a case study of randomized trials in smokers with attention deficit hyperactivity disorder (ADHD), indicated that single and multiple imputation methods outperform the other methods and increase precision in estimating the treatment effect. Missing indicator method, which uses a dummy variable in the statistical model to indicate whether the value for that variable is missing and sets the same value to all missing values, is comparable to imputation methods. Nevertheless, the power level to detect the treatment effect based on missing indicator method is marginally lower than the imputation methods, particularly when the missingness depends on the outcome. In conclusion, it appears that imputation of partly missing (baseline) covariates should be preferred in the analysis of discrete-time survival data.


2020 ◽  
Vol 146 (12) ◽  
pp. 1117-1145
Author(s):  
Kathryn R. Fox ◽  
Xieyining Huang ◽  
Eleonora M. Guzmán ◽  
Kensie M. Funsch ◽  
Christine B. Cha ◽  
...  

2009 ◽  
Author(s):  
Jennifer L. Steel ◽  
Leigh A. Gemmell ◽  
David A. Geller ◽  
Michael Spring ◽  
Jonathan Grady ◽  
...  

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