How I Do It: Cost-effective 3D printed models for renal masses.

3D printing has been growing in many surgical fields including Urology. The primary use has been to print kidneys with tumors to better understand anatomy and to assist with surgical planning and education. Previous studies that utilized 3D printing of kidneys for partial nephrectomies have been limited by the cost and complexity of model creation, rendering them highly impractical to be used on a routine basis. Using a simpler and more cost-effective design and materials allow the 3D kidney models to be used in a wider range and number of patients. We describe our streamlined process to create 3D kidney models costing $30 on average and we believe this process can be repeated by others.

The use of individualized 3D-printed models on trainee and patient education, and surgical planning for robotic partial nephrectomies.

3D printing is a growing tool in surgical education to visualize and teach complex procedures. Previous studies demonstrating the usefulness of 3D models as teaching tools for partial nephrectomy used highly detailed models costing between $250 and 1000. We aimed to create thorough, inexpensive 3D models to accelerate learning for trainees and increase health literacy in patients. Patient-specific, cost-effective ($30-50) 3D models of the affected urologic structures were created using pre-operative imaging of 40 patients undergoing partial nephrectomy at Thomas Jefferson University Hospital (TJUH) between July 2020 and May 2021. Patients undergoing surgery filled out a survey before and after seeing the model to assess patient understanding of their kidney, pathophysiology, surgical procedure, and risks of surgery. Three urological residents, one fellow, and six attendings filled out separate surveys to assess their surgical plan and confidence before and after seeing the model. In a third survey, they ranked how much the model helped their comprehension and confidence during surgery. Patient understanding of all four subjects significantly improved after seeing the 3D model (P < 0.001). The urology residents (P < 0.001) and fellow (P < 0.001) reported significantly increased self-confidence after interacting with the model. Attending surgeon confidence increased significantly after seeing the 3D model (P < 0.01) as well. Cost-effective 3D models are effective learning tools and assist with the evaluation of patients presenting with renal masses, and increase patient, resident, and fellow understanding in partial nephrectomies. Further research should continue to explore the utility of inexpensive models in other urologic procedures.

Incidence and predictors of comorbid insomnia in a sleep surgery clinic.

STUDY OBJECTIVES: The objective was to determine the prevalence and predictors of comorbid insomnia in patients presenting for sleep surgery evaluation. The insomnia severity index (ISI) was utilized to evaluate patients' insomnia severity. METHODS: A retrospective chart review was performed in patients presenting to an otolaryngology sleep surgery clinic; patients also completed a sleep history questionnaire. Patients were divided between those with and without clinically significant insomnia defined as ISI ≥ 15. RESULTS: A total of 119 patients were included in the study: 50 (42%) with an ISI ≥ 15 and 69 (58%) with an ISI < 15. Clinically significant insomnia was associated with respiratory disturbance index (P = .028) but not apnea-hypopnea index or SaO2 nadir (P > .05). Clinically significant insomnia was associated with frequency of wake ups (P = .008), time to fall back asleep (P = .049), history of continuous positive airway pressure device use (P = .012), Epworth Sleepiness Scale (P = .008), and Sino-nasal Outcome Test (SNOT-22) (P < .001). CONCLUSIONS: Patients reporting to a sleep surgery clinic are at an elevated risk for comorbid insomnia. The relationship between increased respiratory event-related arousals and nonsleep SNOT-22 scores to related sleep-maintenance insomnia supports the connection between insomnia, nasal obstruction, and continuous positive airway pressure intolerance. CITATION: Sagheer SH, Scott ER, Ananth A, Boon M, Huntley C. Incidence and predictors of comorbid insomnia in a sleep surgery clinic. J Clin Sleep Med. 2021;17(11):2165-2169.

Modeling drug exposure in rodents using e-cigarettes and other electronic nicotine delivery systems.

Smoking tobacco products is the leading cause of preventable death worldwide. Coordinated efforts have successfully reduced tobacco cigarette smoking in the United States; however, electronic cigarettes (e-cigarette) and other electronic nicotine delivery systems (ENDS) recently have replaced traditional cigarettes for many users. While the clinical risks associated with long-term ENDS use remain unclear, advancements in preclinical rodent models will enhance our understanding of their overall health effects. This review examines the peripheral and central effects of ENDS-mediated exposure to nicotine and other drugs of abuse in rodents and evaluates current techniques for implementing ENDS in preclinical research.