Partial ceratohyoidectomy as surgical treatment for horses with temporohyoid osteoarthropathy: 10 cases (2010-2021).

OBJECTIVE: To describe outcomes of horses with temporohyoid osteoarthropathy (THO) treated with partial ceratohyoidectomy. ANIMALS: 10 client-owned horses. PROCEDURES: Medical records from 2 institutions were examined for records of horses with THO treated with partial ceratohyoidectomy between 2010 and 2021. History, signalment, clinical signs, diagnostics, medications, and surgery-related details were recorded. Horses with a minimum of 6 months follow-up were recruited for neurologic and imaging examinations in the hospital or field where radiography of the basihyoid-ceratohyoid articulation were performed along with CT, when available. RESULTS: 10 horses with THO were included (9 unilateral; 1 bilateral). Nine planned partial ceratohyoidectomies were performed in 8 horses, whereas 2 horses had preoperatively planned complete ceratohyoidectomies transitioned to partial ceratohyoidectomies during surgery due to intraoperative complications. Postoperative complications occurred mostly in transitioned surgeries (obstructed airway, tongue mobility issues, and incisional hemorrhage), whereas only 1 horse with a planned ceratohyoidectomy had postoperative complication of rhabdomyolysis. All complications resolved before hospital discharge. Neurologic signs improved in all 10 horses, with 2 showing complete resolution. Nine horses were available for radiographic follow-up, 6 of which also had head CT scans. A space between the ceratohyoid and basihyoid bones was measurable on radiography in all 9 horses, and was confirmed on CT. Three horses demonstrated proliferation of either ceratohyoid or basihyoid bones. The 9 horses with unilateral disease returned to previous work, and the horse with bilateral disease was retired. CLINICAL RELEVANCE: Partial ceratohyoidectomy is a surgical option for treatment of THO that provides similar clinical outcomes to published reports on ceratohyoidectomy.

The standard sagittal starting point and entry angle for tibia intramedullary nails results in malreduction of proximal tibial fractures.

INTRODUCTION: The aim of this study was to determine the sagittal starting point and entry angle necessary for anatomic reduction in proximal tibial fractures and to compare reductions obtained using a standard versus modified sagittal entry angle. METHODS: Extra-articular proximal tibial fracture sawbone models were divided into three groups. The first group was used to determine the sagittal starting point and entry angle necessary for an anatomic reduction by inserting nails into the distal fragment and then reducing the proximal fragment over the nail. The second and third groups had nails inserted through the standard coronal and sagittal starting point using the standard sagittal entry angle (parallel to the anterior cortex) versus a more posteriorly directed modified sagittal entry angle (directed at the center of the tibia at the level of the tibia tubercle prominence). Fracture gapping and translation in the sagittal plane were measured for each group. RESULTS: Anatomic reduction was only possible with a sagittal starting point that was too posterior for actual use. The standard sagittal entry angle resulted in greater posterior fracture translation and less anterior fracture gapping then the modified sagittal entry angle, 10.6 ± 1.1 versus 1.6 ± 2.8 mm (p < 0.01) and 1.3 ± 0.5 versus 5.3 ± 2.5 mm (p = 0.01), respectively. CONCLUSION: Anatomic reduction was not achieved with the standard sagittal starting point and entry angle. Considering these finding, surgeons should have a low threshold to utilize adjunct reduction methods for these injuries.

Methodology for fitting and updating predictive accident models with trend.

Reliable predictive accident models (PAMs) (also referred to as Safety Performance Functions (SPFs)) have a variety of important uses in traffic safety research and practice. They are used to help identify sites in need of remedial treatment, in the design of transport schemes to assess safety implications, and to estimate the effectiveness of remedial treatments. The PAMs currently in use in the UK are now quite old; the data used in their development was gathered up to 30 years ago. Many changes have occurred over that period in road and vehicle design, in road safety campaigns and legislation, and the national accident rate has fallen substantially. It seems unlikely that these ageing models can be relied upon to provide accurate and reliable predictions of accident frequencies on the roads today. This paper addresses a number of methodological issues that arise in seeking practical and efficient ways to update PAMs, whether by re-calibration or by re-fitting. Models for accidents on rural single carriageway roads have been chosen to illustrate these issues, including the choice of distributional assumption for overdispersion, the choice of goodness of fit measures, questions of independence between observations in different years, and between links on the same scheme, the estimation of trends in the models, the uncertainty of predictions, as well as considerations about the most efficient and convenient ways to fit the required models.

Vehicle mass and injury risk in two-car crashes: A novel methodology.

This paper introduces a novel methodology based on disaggregate analysis of two-car crash data to estimate the partial effects of mass, through the velocity change, on absolute driver injury risk in each of the vehicles involved in the crash when absolute injury risk is defined as the probability of injury when the vehicle is involved in a two-car crash. The novel aspect of the introduced methodology is in providing a solution to the issue of lack of data on the speed of vehicles prior to the crash, which is required to calculate the velocity change, as well as a solution to the issue of lack of information on non-injury two-car crashes in national accident data. These issues have often led to focussing on relative measures of injury risk that are not independent of risk in the colliding cars. Furthermore, the introduced methodology is used to investigate whether there is any effect of vehicle size above and beyond that of mass ratio, and whether there are any effects associated with the gender and age of the drivers. The methodology was used to analyse two-car crashes to investigate the partial effects of vehicle mass and size on absolute driver injury risk. The results confirmed that in a two-car collision, vehicle mass has a protective effect on its own driver injury risk and an aggressive effect on the driver injury risk of the colliding vehicle. The results also confirmed that there is a protective effect of vehicle size above and beyond that of vehicle mass for frontal and front to side collisions.

Child pedestrian casualties and deprivation.

The existence of an association between child pedestrian accidents and socio-economic deprivation in Great Britain is well established. The factors driving this association are complex and difficult to isolate. This study uses accident prediction models to investigate the links between child pedestrian casualties and a range of environmental and socio-economic factors commonly linked to deprived areas and people. Separate models are constructed relating to the areas in which the children become casualties, and the areas in which the children reside. Significant socio-economic factors include: single-parenthood, reliance on income support, and crime; and environmental factors include domestic garden area, junction density and pedestrian and vehicular flow density. The study found that factors pertaining to the local environment were more prevalent in the models considering accident locations, whilst socio-economic factors were of greater influence in the residency model.

The sensitivity of estimates of regression to the mean.

Estimations of the effectiveness of remedial treatments in road safety analysis are frequently bedevilled by the problem of regression to the mean (RTM). The number of accidents x observed at a site in the "before" period is a "noisy" quantity: x is Poisson distributed about an (unknown) true mean m for that site, so that x = m + e. Sites selected for treatment tend to have a positive random error component e, which will on average be zero in the "after" period, even if no treatment is applied. Methods for estimating RTM usually require some assumption about the underlying (prior) between-site distribution of the true means f0(m): for example, in the empirical Bayes method, a gamma distribution is assumed. The paper considers the impact of different assumptions for this distribution and, indeed, whether any distributional form needs to be assumed. Using Markov Chain Monte Carlo methods, a variety of distributional forms are assumed for f0(m) and applied to each of a number of real data sets, including that from a major study on the effectiveness of speed cameras. It is shown that, in some cases, the size of the estimated RTM effect can be quite sensitive to the choice of distribution.