Artificial intelligence for objectively measuring years regained after facial rejuvenation surgery.

BACKGROUND: Few objective measures are available for assessing the success of facial rejuvenation after face lift surgery. Convolutional neural networks (CNNs) may be used for this type of measurement. The purpose of this investigation is to use artificial intelligence (AI) via CNNs to objectively classify patient photos by age before and after aesthetic surgery. Uniquely, men and patients undergoing deep plane face lifts were included. METHODS: A CNN (FaceX) was used for facial age recognition and age estimation. Patient photos were analyzed preoperatively, and at three (PO1) and 12 months (PO2) postoperatively. The study population included male and female patients who underwent facial rejuvenation at our institution from 2017 to 2021. Patient photos were collected with the same camera, distance, and lighting. RESULTS: 226 patients were analyzed with a mean true age of 62.2 (SD 6.7) years. The AI estimated the mean preoperative age to be 64.7 (SD 10.4) years. The AI was 96.0 % accurate. Across all subjects, a 3.5-year, 5 % reduction in age (p ≤ 0.001) was attributed at PO1, and a 1.7 year, 3 % age reduction (p = 0.034) at PO2. No single ancillary procedure or technique conferred more benefit than others. The 15 males had a 2.0 year, 4 % age reduction (p = 0.06) at PO1. CONCLUSION: AI can be used to objectively measure the success of facelift surgery and compare outcomes among rhytidectomy techniques. Additionally, multiple, different approaches were effective with no single approach being superior. As AI continues to rapidly advance, more accurate models may be developed for multiple applications in facial plastic surgery.

Predictors of opioid requirement among patients receiving free flap reconstruction to the head and neck.

BACKGROUND: Opioids are a part of standard of care treatment of acute, severe postoperative pain. However, increased opioid requirements have been shown to be associated with increased postoperative complications, morbidity, and mortality. The aim of this study was to identify potential predictive factors associated with increased or decreased opioid requirements after free tissue transfer (FTT) to the head and neck. MATERIALS/METHODS: A retrospective review was conducted on subjects who underwent head and neck reconstruction (HNR) from 2015 to 2021 at a single tertiary care center. Patients with inpatient stay over 10 days and those receiving fentanyl for sedation purposes were excluded due to EMR limitations and confounding, respectively. The total dose of opioid medication each patient received was calculated and summed using morphine milligram equivalents (MME). Statistical analysis was conducted using poisson regression and multivariable regression models. RESULTS: Two hundred and ninety-one patients were included. The mean opioid requirement for all subjects was 228.6 (SD 250.0) MMEs during their entire postoperative stay and the mean length of stay was 6.0 (SD 1.7) days. An established opioid prescription prior to surgical resection was the greatest predictor of increased risk for opioid requirement according univariate and multivariate analysis 2.356 (2.321-2.392), p ≤ 0.0001 and 1.833 (1.802-1.863), p ≤ 0.0001, respectively. Fibula transfers were associated with higher opioid requirements while scapula transfers were associated with decreased opioid requirements compared to other free tissue transfer types. CONCLUSION: Preoperative opioid use was associated with higher postoperative opioid requirements. Multimodal pain management (MMPM) was not associated with a decreased opioid requirement; however, further studies are needed to investigate the hierarchy, dosing, and timing of MMPM in relation to opioid requirements and pain control.

Rate of Fat Graft Volume Loss After Parotidectomy.

BACKGROUND: Reconstruction after parotidectomy can include fat grafting, which allows for symmetry, but grafts have demonstrated volume loss over time. OBJECTIVES: To provide quantitative evidence for the rate of volume loss of fat grafts. METHODS: Patients who received parotidectomy with fat graft reconstruction at a single institution from August 2016 to October 2020 were identified. Relationships between clinical factors and the logarithmic rate of fat graft volume loss were analyzed. RESULTS: Twelve patients received parotidectomy, fat graft reconstruction, and underwent a postoperative magnetic resonance imaging (MRI) scan. Rate of fat graft volume loss was a mean of 1.8% per month (standard deviation [SD]: 2.1% per month). Total parotid fat graft volume loss was a mean of 57.4% (SD: 67.5%). The mean follow-up time was 35.5 months (range: 9-89.8 months). Correlations between body mass index (BMI), history of smoking, and history of alcohol consumption and logarithmic rates of fat graft volume loss were increased but not significantly. CONCLUSIONS: Fat grafts have the potential of 60% volume loss at approximately 1 year. If there is clinical suspicion that patients will require adjuvant radiation or have clinical factors such as a smoking or alcohol-use history, volume requirements may be even greater to maintain adequate parotid volume for aesthetic purposes.

Evaluating YouTube Videos on Facelift Surgery for Facial Rejuvenation as a Resource for Patients.

OBJECTIVES: This study evaluated the content and patient educational quality of YouTube videos on facelift surgery for facial rejuvenation. This study investigated the relationship between education quality compared to video content, video metrics, and popularity. METHODS: Two hundred videos were identified across 4 search terms: "facelift surgery," "facelift surgery what to expect," "facelift surgery patient education," and "what is facelift surgery." Unrelated videos, operating room recordings, medical professional lectures, non-English, non-audio, and testimonials were excluded from review. Video quality was assessed using the Global Quality Score (GQS) (range: 1-5), modified DISCERN score (range: 5-25), and JAMA Benchmark Criteria (range: 0-4). Secondary outcomes included upload source, video metrics (views, likes, dislikes, duration, days since upload, comments), and Video Power Indexto measure popularity. The first 10 comments on videos were characterized as positive, neutral, or negative. RESULTS: One hundred forty-three videos were excluded (43 did not meet criteria, 100 duplicates), and 57 videos were included. Fifty-five videos (96.5%) were uploaded by private medical practices. Overall video quality was poor across all 3 scoring systems: GQS (2.92 ± 1.14), modified DISCERN (13.03 ± 3.64), and JAMA Benchmark Criteria (1.78 ± 0.52). Popularity positively correlated with JAMA Benchmark Criteria (R = .49, P < .05) but did not correlate with other quality criteria. CONCLUSIONS: For patients undergoing facelift surgery, there are limited educational videos on YouTube with few videos detailing indications, alternatives, complications, and the postoperative course. YouTube is a growing resource for patient education and opportunities exist for medical institutions to produce higher-quality videos for prospective patients.

Tap-Tap: Learning Endonasal and Percutaneous Nasal Osteotomy Techniques on 3D-Printed Midface Models.

Nasal osteotomy is one of the most challenging steps of rhinoplasty. Lack of hands-on training and confidence with this procedure adds to the complexity for learners and trainees. As three-dimensional (3D) printing becomes increasingly accessible, simulation on 3D printed models has the potential to address this educational need in a safe, reproducible, and clinically realistic manner. The simulation session described in this communication, which utilized our low-cost, 3D-printed nasal osteotomy ($12.37) task trainer, produced both educational and confidence benefits for trainees. Here we describe the design, organization, curriculum, and pilot data for a 3D-printed nasal osteotomy task trainer for the simulation of endonasal and percutaneous nasal osteotomy.

Comparing Upper Airway Stimulation to Transoral Robotic Base of Tongue Resection for Treatment of Obstructive Sleep Apnea.

OBJECTIVES: Transoral robotic surgery (TORS) and upper airway stimulation (UAS) are modalities for treating tongue base obstruction contributing to obstructive sleep apnea (OSA). We aim to compare patients with OSA undergoing TORS to those undergoing UAS. METHODS: We retrospectively reviewed patients treated with TORS and UAS using the senior authors' surgical database. We evaluated demographic, preoperative polysomnography (PSG), postoperative PSG, complication, hospital length of stay, and hospital readmission data to compare the two cohorts. RESULTS: Seventy-six patients underwent UAS. This included 50 men and 26 women. The mean age and body mass index were 61.92 and 29.38. The mean pre- versus postoperative apnea hypopnea index (AHI) and O2 nadir were 36.64 versus 7.20 and 80.27% versus 88.77%, respectfully. The rate of surgical success and postoperative AHI less than 15 and 5 were 86.84%, 89.47%, and 59.21. All patients underwent ambulatory surgery, and no one was readmitted. Twenty-four patients underwent TORS. This included 20 men and four women with a mean age and body mass index BMI of 46.42 and 29.63. The mean pre- versus postoperative AHI and O2 nadir were 35.70 versus 20.05 and 80.50% versus 84.10%, respectfully. The rate of surgical success and postoperative AHI less than 15 and 5 were 54.17%, 50.00%, and 20.83%. The mean length of stay was 1.33 days, and four patients were readmitted. We found significant differences in age, postoperative AHI and O2 nadir, surgical success and postoperative AHI less than 15 and 5, length of stay, and rate of readmission. CONCLUSIONS: UAS is successful in treating OSA showing improved outcomes, length of stay, and readmission compared to TORS. LEVEL OF EVIDENCE: 3 Laryngoscope, 129:1010-1013, 2019.

Telemedicine in otolaryngology outpatient setting-single Center Head and Neck Surgery experience.

OBJECTIVES/HYPOTHESIS: We present our experience with telemedicine visits in an otolaryngology outpatient setting within our institution's Center for Head and Neck Surgery. STUDY DESIGN: Retrospective chart review. METHODS: A review of telemedicine outpatient encounters examining patient demographics, visit type, and wait times was conducted. Internet-based navigation applications were used to calculate travel distance and estimate commute time to our clinic. Patient survey responses were reviewed. RESULTS: Two hundred fifty telemedicine encounters were reviewed between December 2015 and June 2017. The average age of patients was 50 years (range, 4-87 years). Patients waited an average of 10 minutes for their telemedicine appointments and avoided an average estimated commute time of 78 minutes (64 miles). The majority of visits were postoperative encounters (70%). Clinical follow-up of recent results or nonpostoperative complaints accounted for the remaining 30% of visits. All patients were offered a post-telemedicine survey, and 78 (31%) completed the survey. Of the respondents, 95% of patients reported that they were satisfied with their visit. Among patients who were dissatisfied, wait time and technical issues were cited as reasons. CONCLUSIONS: With appropriate patient selection, telemedicine is an effective way to safely conduct outpatient clinic visits while maintaining high patient satisfaction. It can be particularly useful for institutions with large catchment areas to minimize travel times and increase ease of communication. LEVEL OF EVIDENCE: 4. Laryngoscope, 128:2072-2075, 2018.