Progressive rehabilitation of the sprained ankle: A novel treatment method

ObjectivesThis randomised, single blinded cohort study was designed to assess the immediate effect of manual fascial manipulation on walking pain and the range of ankle dorsiflexion within the first 4 days after ankle trauma.MethodsMeasurements were taken from 19 subjects, 5 female and 14 male, who presented with grade I–III ankle sprains. Ankle dorsiflexion was photographed in a standardised position and calculated by means of the Dartfish® Advanced Video Analysis Software and SPSS® (version 17) was used to compare the pre- and post-treatment data.ResultsAfter one treatment session 13 of the 19 subjects were walking pain free and 3 of the 19 where walking with only little pain. The highly significant (p < 0.001) mean improvement of ankle dorsiflexion was 7.9° (±5.8°). All, apart from one subject, whom were walking pain free after treatment showed a minimum of 4° increased dorsiflexion.ConclusionEarly fascia work around the injured ankle improves ankle dorsiflexion and reduces walking pain. It may reduce the delay of tissue healing and, thus, optimise further rehabilitation of the sprained ankle which may also reduce socio-economic costs.     

镫骨骨质缺损对听力传导影响的有限元分析

目的建立完善的鼓膜-听骨链模型,利用有限元初步探讨镫骨前、后脚骨质缺损对听力传导的影响。方法实验数据源于对一名无中耳病史的成年男性左侧颞骨进行Micro-CT扫描,在医学影像处理软件Mimics上进行三维重建,利用Geomagic形成需要的曲面,最后在SolidWorks上将成型的鼓膜-听骨链模型进行切割组装,建立正常听骨链模型以及镫骨前、后脚骨质缺损模型,利用模型分析骨质缺损对听力传导的影响。结果建立的鼓膜-听骨链模型镫骨足板频振曲线符合相关文献报道,在镫骨前、后脚骨质缺损病理模型下,曲线与正常中耳模型曲线接近。结论利用多软件综合处理,可建立可信度较高的中耳听骨链模型;有限元模拟分析结果显示,镫骨前、后脚缺损部分骨质,未对听力传导产生明显影响。     

Analysis of ordered composite endpoints

Composite endpoints are frequently used in clinical trials, but simple approaches, such as the time to first event, do not reflect any ordering among the endpoints. However, some endpoints, such as mortality, are worse than others. A variety of procedures have been proposed to reflect the severity of the individual endpoints such as pairwise ranking approaches, the win ratio, and the desirability of outcome ranking. When patients have different lengths of follow-up, however, ranking can be difficult and proposed methods do not naturally lead to regression approaches and require specialized software. This paper defines an ordering score O to operationalize the patient ranking implied by hierarchical endpoints. We show how differential right censoring of follow-up corresponds to multiple interval censoring of the ordering score allowing standard software for survival models to be used to calculate the nonparametric maximum likelihood estimators (NPMLEs) of different measures. Additionally, if one assumes that the ordering score is transformable to an exponential random variable, a semiparametric regression is obtained, which is equivalent to the proportional hazards model subject to multiple interval censoring. Standard software can be used for estimation. We show that the NPMLE can be poorly behaved compared to the simple estimators in staggered entry trials. We also show that the semiparametric estimator can be more efficient than simple estimators and explore how standard Cox regression maneuvers can be used to assess model fit, allow for flexible generalizations, and assess interactions of covariates with treatment. We analyze a trial of short versus long-term antiplatelet therapy using our methods.     

Validation of PATHFx 2.0: An open-source tool for estimating survival in patients undergoing pathologic fracture fixation

Treatment decisions in patients with metastatic bone disease rely on accurate survival estimation. We developed the original PATHFx models using expensive, proprietary software and now seek to provide a more cost-effective solution. Using open-source machine learning software to create PATHFx version 2.0, we asked whether PATHFx 2.0 could be created using open-source methods and externally validated in two unique patient populations. The training set of a well-characterized, database records of 189 patients and the bnlearn package within R Version 3.5.1 (R Foundation for Statistical Computing), was used to establish a series of Bayesian belief network models designed to predict survival at 1, 3, 6, 12, 18, and 24 months. Each was externally validated in both a Scandinavian (n = 815 patients) and a Japanese (n = 261 patients) data set. Brier scores and receiver operating characteristic curves to assessed discriminatory ability. Decision curve analysis (DCA) evaluated whether models should be used clinically. DCA showed that the model should be used clinically at all time points in the Scandinavian data set. For the 1-month time point, DCA of the Japanese data set suggested to expect better outcomes assuming all patients will survive greater than 1 month. Brier scores for each curve demonstrate that the models are accurate at each time point. Statement of Clinical Significance: we successfully transitioned to PATHFx 2.0 using open-source software and externally validated it in two unique patient populations, which can be used as a cost-effective option to guide surgical decisions in patients with metastatic bone disease.     

Seeking the optimal schedule for chickenpox vaccination in Canada: Using an agent-based model to explore the impact of dose timing,coverage and waning of immunity on disease outcomes

Many countries continue to consider implementing a universal chickenpox vaccine program; however, there is no consensus on the most appropriate and effective timing between vaccine doses. The chickenpox vaccine schedule debate is highlighted in Canada, where there are currently eight different vaccine schedules across the country. The objective of this study was to test the overall effectiveness of chickenpox vaccination, as well as the specific impact of two different vaccine schedules, on chickenpox disease outcomes in Alberta over 75 years. Using an agent-based model of chickenpox disease, we tested the impact of three vaccination scenarios including: baseline (no vaccination), a long dosing interval-Schedule LDI (1^st dose – 12 months; 2^nd dose –  4-6 years) and a short dosing interval-Schedule SDI (1^st dose – 12 months; 2^nd dose – 18 months) on chickenpox and shingles disease outcomes. Chickenpox vaccination led to a substantial decrease in chickenpox incidence over 75 years post-vaccine implementation. Compared to Schedule LDI, Schedule SDI resulted in a significantly lower chickenpox incidence, a higher age of chickenpox infection, a lower chickenpox breakthrough rate and a higher shingles incidence rate. Our model findings suggest that the chickenpox vaccine is effective over a long period of time and the dose timing of the vaccine may impact disease outcomes and vaccine effectiveness. However, the effectiveness of the vaccine dose timing is only one consideration for policy-makers who are implementing a chickenpox vaccine program, with others including risk of adverse events, the impact of the schedule on other antigens in a combination vaccine, parental acceptance and the cost associated with different schedules.     

Bayesian leveraging of historical control data for a clinical trial with time-to-event endpoint

The recent 21st Century Cures Act propagates innovations to accelerate the discovery, development, and delivery of 21st century cures. It includes the broader application of Bayesian statistics and the use of evidence from clinical expertise. An example of the latter is the use of trial-external (or historical) data, which promises more efficient or ethical trial designs. We propose a Bayesian meta-analytic approach to leverage historical data for time-to-event endpoints, which are common in oncology and cardiovascular diseases. The approach is based on a robust hierarchical model for piecewise exponential data. It allows for various degrees of between trial-heterogeneity and for leveraging individual as well as aggregate data. An ovarian carcinoma trial and a non-small cell cancer trial illustrate methodological and practical aspects of leveraging historical data for the analysis and design of time-to-event trials.     

A conceptual model and detailed framework for stress-related,strain-related,and overuse athletic injury

A multitude of athletic injuries occur when the various tissues that make up the human body experience stresses and strains that exceed their material strength. The precise amount of stress and strain that any given tissue can withstand is determined by the mechanical properties and resultant strength of that particular tissue. These mechanical properties are directly determined by an individual’s physiology and acute regulation of these properties. A number of theoretical frameworks for athletic injury occurrence have been proposed, however, a detailed conceptual framework for injury aetiology that considers the interplay between the physiological and mechanical factors and outlines the causal pathways to tissue damage and injury is needed. This will guide injury research towards a more thorough investigation of causal mechanisms and understanding of risk factors. Further, it is important to take into account the considerable differences in loading patterns which can result in varying injury outcomes such as acute stress-related, strain-related, or overuse injury. Within this article a simplified conceptual model of athletic injury is proposed along with a detailed, evidence-informed, conceptual framework for athletic injury aetiology that focuses on stress-related, strain-related, and overuse injury.