Ultrasound of oral and masticatory muscles: Why every neuromuscular swallow team should have an ultrasound machine

Patients with neuromuscular disorders often present with swallowing difficulties due to oral phase problems and pharyngeal residue after swallow. It is important to assess the underlying pathology and cause of the swallowing disturbance in this patient group, such as dystrophic changes in oral and masticatory muscles. This allows for more patient‐tailored recommendations, for example optimal compensation strategies to maintain function for longer. Ultrasound can show structural changes caused by dystrophy or denervation of muscles, detect involuntary movements such as fasciculations, and provide dynamic video images of tongue motion during swallowing attempts. This article, based on the authors' extensive experience with ultrasound in neuromuscular disease, explains the concepts of oral muscle ultrasound and its proven value in assessing neuromuscular mastication and swallowing problems. As a patient‐friendly and portable technique, we advocate its use as a standard tool for analyzing neuromuscular dysphagia. Clin. Anat. 30:183–193, 2017. © 2017 Wiley Periodicals, Inc.     

An Experimental Model of Heat Storage in Working Firefighters

Objective. Develop experimental models to study uncompensable heat stress (UCHS) in working firefighters (FFs). Methods. FFs ingested core temperature (Tc) capsules prior to performing sequential tasks in 40°C andpersonal protective ensemble (PPE), or 18°C andno PPE. Both trials were conducted in an environmental chamber with FFs using self-contained breathing apparatus (SCBA). Results. FFs exercising in heat andPPE reproduced UCHS conditions. For every FF in both trials for whom the capsules worked, Tc was elevated, andTc_max occurred after completion of study protocol. Trials with PPE resulted in a mean maximum temperature of 38.94°C (± 0.37°C); Tc_max reached 40.4°C. Without PPE, maximum Tc averaged 37.79°C (± 0.07°C). Heat storage values ranged from 131 to 1205 kJ, averaging 578 kJ (± 151.47kJ) with PPE and210.83 kJ (± 21.77kJ) without PPE. Conclusions. An experimental model has been developed that simulates the initial phases of an interior fire attack to study the physiology of UCHS in FF. The hot environment andPPE increase maximum Tc andheat storage over that due to the exertion required to perform the tasks andmay decrease time to volitional fatigue. This model will permit controlled studies to optimize work-rest cycles, rehab conditions, andphysical conditioning of FFs.     

Brief report: Risk factors for pneumococcal vaccine refusal in adults

Background: Invasive pneumococcal disease is a significant cause of morbidity and mortality in the United States. Despite availability of an effective vaccine, many patients refuse vaccination.
Objective: To investigate patient characteristics and features of the patient–provider relationship associated with pneumococcal vaccine refusal.
Design: Case–control study using chart review.
Patients: Five hundred adults from the medical clinics of a 1,000-bed inner-city teaching hospital.
Measurements and Main Results: Independent risk factors for pneumococcal vaccine refusal included patient–provider gender discordance (odds ratio (OR)=2.09, 95% confidence interval (CI) 1.07 to 4.09); a visit to a not-usual provider at the time of vaccine offering (OR=2.26, 95% CI 1.13 to 4.49); never having received influenza vaccination (OR=7.44, 95% CI 3.76 to 14.76); prior pneumococcal vaccine refusals (OR=3.45, 95% CI 1.60 to 7.43); and a history of ever having refused health maintenance tests (OR=2.86, 95% CI 1.40 to 5.84).
Conclusions: We have identified both patient factors and factors related to the patient–provider relationship that are risk factors for pneumococcal vaccine refusal. By identifying patients at risk for pneumococcal vaccine refusal, efforts to increase vaccination rates can be better targeted.     

AR in VR: assessing surgical augmented reality visualizations in a steerable virtual reality environment

Purpose 

Augmented reality (AR) has emerged as a promising approach to support surgeries; however, its application in real world scenarios is still very limited. Besides sophisticated registration tasks that need to be solved, surgical AR visualizations have not been studied in a standardized and comparative manner. To foster the development of future AR applications, a steerable framework is urgently needed to rapidly evaluate new visualization techniques, explore their individual parameter spaces and define relevant application scenarios.

Methods 

Inspired by its beneficial usage in the automotive industry, the underlying concept of virtual reality (VR) is capable of transforming complex real environments into controllable virtual ones. We present an interactive VR framework, called Augmented Visualization Box (AVB), in which visualizations for AR can be systematically investigated without explicitly performing an error-prone registration. As use case, a virtual laparoscopic scenario with anatomical surface models was created in a computer game engine. In a study with eleven surgeons, we analyzed this VR setting under different environmental factors and its applicability for a quantitative assessment of different AR overlay concepts.

Results 

According to the surgeons, the visual impression of the VR scene is mostly influenced by 2D surface details and lighting conditions. The AR evaluation shows that, depending on the visualization used and its capability to encode depth, 37% to 91% of the experts made wrong decisions, but were convinced of their correctness. These results show that surgeons have more confidence in their decisions, although they are wrong, when supported by AR visualizations.

Conclusion 

With AVB, intraoperative situations are realistically simulated to quantitatively benchmark current AR overlay methods. Successful surgical task execution in an AR system can only be facilitated if visualizations are customized toward the surgical task.

     

Dealing with the complex drug–drug interactions: Towards mechanistic models

Unmanageable severe adverse events caused by drug‐drug interactions (DDIs), leading to market withdrawals or restrictions in the clinical usage, are increasingly avoided with the improvement in our ability to predict such DDIs quantitatively early in drug development. However, significant challenges arise in the evaluation and/or prediction of complex DDIs caused by inhibitor drugs and/or metabolites that affect not one but multiple pathways of drug clearance. This review summarizes the discussion topics at the 2013 AAPS symposium on “Dealing with the complex drug‐drug interactions: towards mechanistic models”. Physiologically based pharmacokinetic (PBPK) models, in combination with the established in vitro‐to‐in vivo extrapolations of intestinal and hepatic disposition, have been successfully applied to predict clinical pharmacokinetics and DDIs, especially for drugs with CYP‐mediated metabolism, and to explain transporter‐mediated and complex DDIs. Although continuous developments are being made towards improved mechanistic prediction of the transporter‐enzyme interplay in the hepatic and intestinal disposition and characterizing the metabolites contribution to DDIs, the prediction of DDIs involving them remains difficult. Regulatory guidelines also recommended use of PBPK modeling for the quantitative prediction and evaluation of DDIs involving multiple perpetrators and metabolites. Such mechanistic modeling approaches culminate to the consensus that modeling is helpful in predicting DDIs or quantitatively rationalizing the clinical findings in complex situations. Furthermore, they provide basis for the prediction and/or understanding the pharmacokinetics in populations like patients with renal impairment, pediatrics, or various ethnic groups where the conduct of clinical studies might not be feasible in early drug development stages and yet some guidance on management of dosage is necessary. Copyright © 2014 John Wiley & Sons, Ltd.