Contralateral slip prediction in slipped capital femoral epiphysis: is bone age the answer?

Prophylactic pinning of an asymptomatic hip in Slipped Capital Femoral Epiphysis (SCFE) is controversial. Bone age has been used as a predictor of future contralateral slip risk and also in the decision making for prophylactic intervention. The efficacy of bone age at predicting a contralateral slip was tested in this study. Eighteen Caucasian children prospectively had bone age assessment using wrist and hand radiographs when presenting with a unilateral SCFE. After in situ fixation of the affected side prospective monitoring was performed at regular intervals in the outpatient department. Surgical intervention was undertaken if the contralateral hip was symptomatic. Three children (2 boys and 1 girl) went on to develop a contralateral slip at a mean of 20 months from initial presentation. Six children were deemed at risk of contralateral slip due to a bone age of > or = 12.5 years for boys and > or = 10.5 years for girls. Only one from this group developed a contralateral slip. The relative risk of proceeding to a contralateral slip when the bone age is below the designated values was 1 (95% confidence interval of 0.1118 to 8.95). The sensitivity and specificity were 33% and 66% respectively. The positive predictive value was 15% and the diagnostic efficiency was 61%. Although this is a small study, it would appear that delayed bone age by itself is not a good predictor of future contralateral slip. Routine prophylactic pinning is not justified based on bone age alone, with the risks of surgical fixation it carries. A prospective long term longitudinal study is required.     

An Unusual Case of Bipartite Patella Fracture with Quadriceps Rupture

Abstract Bipartite patella fracture with quadriceps rupture is an unusual injury. It is quite often mistaken as an avulsion fracture of patella, and the X-ray of contra-lateral knee is useful for diagnosis, and appropriate treatment should be decided at the time of surgery. We report a single case of this entity in which bipartite patella fracture was misdiagnosed initially as a patellar fracture.     

Physical therapy management of entrapment of the superficial peroneal nerve in the lower leg: A case report

This case report describes a 40-year-old male who presented with complaints of pain in the left lower lateral one-third of the leg. Tenderness was elicited 9.7?cm above the lateral malleoli with a positive Tinel's sign at the same site causing radiating pain into the foot (visual analog scale (VAS) score of 6.3?cm). Physical diagnosis for entrapment of the superficial peroneal nerve at the site of the peroneal tunnel was entertained based on clinical examination and three positive provocation tests. Conventionally, treatment for this type of entrapment has been surgical decompression by splitting the crural fascia, with successful outcomes. This is potentially a first-time report describing physical therapy management of entrapment mechanical interface with pain modalities, soft tissue mobilization, and neural mobilization. Reduction of pain was noted in this patient (VAS score of 0?cm by the sixth session) with complete pain resolution maintained at a six-month follow-up.     

Aesthetic Finger Prosthesis

Complete or partial fingers are the most commonly encountered forms of partial hand losses. Though finger amputations are commonly due to traumatic injuries, digit loss may also be attributed to congenital malformations and disease. Irrespective of the etiology, the loss of a finger has a considerable functional and psychological impact on an individual. In order to alleviate these problems, partial or complete finger prosthesis may be fabricated. This clinical report portrays a method to fabricate silicone rubber prosthesis for a patient who has a partial finger loss caused due to trauma.     

Plug and play: combining materials and technologies to improve bone regenerative strategies

Despite recent advances in the development of biomaterials intended to replace natural bone grafts for the regeneration of large, clinically relevant defects, most synthetic solutions that are currently applied in the clinic are still inferior to natural bone grafts with regard to regenerative potential and are limited to non‐weight‐bearing applications. From a materials science perspective, we always face the conundrum of the preservation of bioactivity of calcium phosphate ceramics in spite of better mechanical and handling properties and processability of polymers. Composites have long been investigated as a method to marry these critical properties for the successful regeneration of bone and, indeed, have shown a significant improvement when used in combination with cells or growth factors. However, when looking at this approach from a clinical and regulatory perspective, the use of cells or biologicals prolongs the path of new treatments from the bench to the bedside. Applying 'smart' synthetic materials alone poses the fascinating challenge of instructing tissue regeneration in situ, thereby tremendously facilitating clinical translation. In the journey to make this possible, and with the aim of adding up the advantages of different biomaterials, combinations of fabrication technologies arise as a new strategy for generating instructive three‐dimensional (3D) constructs for bone regeneration. Here we provide a review of recent technologies and approaches to create such constructs and give our perspective on how combinations of technologies and materials can help in obtaining more functional bone regeneration. Copyright © 2013 John Wiley & Sons, Ltd.     

Left-Hand Side Exploration of Novel Bacterial Topoisomerase Inhibitors to Improve Selectivity against hERG Binding

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Deep learning-based computer vision to recognize and classify suturing gestures in robot-assisted surgery

BackgroundOur previous work classified a taxonomy of suturing gestures during a vesicourethral anastomosis of robotic radical prostatectomy in association with tissue tears and patient outcomes. Herein, we train deep learning-based computer vision to automate the identification and classification of suturing gestures for needle driving attempts.MethodsUsing two independent raters, we manually annotated live suturing video clips to label timepoints and gestures. Identification (2,395 videos) and classification (511 videos) datasets were compiled to train computer vision models to produce 2- and 5-class label predictions, respectively. Networks were trained on inputs of raw red/blue/green pixels as well as optical flow for each frame. Each model was trained on 80/20 train/test splits.ResultsIn this study, all models were able to reliably predict either the presence of a gesture (identification, area under the curve: 0.88) as well as the type of gesture (classification, area under the curve: 0.87) at significantly above chance levels. For both gesture identification and classification datasets, we observed no effect of recurrent classification model choice (long short-term memory unit versus convolutional long short-term memory unit) on performance.ConclusionOur results demonstrate computer vision’s ability to recognize features that not only can identify the action of suturing but also distinguish between different classifications of suturing gestures. This demonstrates the potential to utilize deep learning computer vision toward future automation of surgical skill assessment.