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Background:. To address patient health literacy, the American Medical Association recommends that readability of patient education materials should not exceed a sixth grade reading level; the National Institutes of Health recommend no greater than an eigth-grade reading level. However, patient-facing materials in plastic surgery often remain at an above-recommended average reading level. The purpose of this study was to evaluate ChatGPT 3.5 as a tool for optimizing patient-facing craniofacial education materials. Methods:. Eighteen patient-facing craniofacial education materials were evaluated for readability by a traditional calculator and ChatGPT 3.5. The resulting scores were compared. The original excerpts were then inputted to ChatGPT 3.5 and simplified by the artificial intelligence tool. The simplified excerpts were scored by the calculators. Results:. The difference in scores for the original excerpts between the online calculator and ChatGPT 3.5 were not significant (P = 0.441). Additionally, the simplified excerpts’ scores were significantly lower than the originals (P

Summary:. Vascularized fibular epiphyseal transfer (VFET) offers a functional advantage in pediatric limb salvage due to the preservation of growth potential and an articular surface for remodeling. This review summarizes the available evidence on the clinical characteristics and outcomes of pediatric reconstruction applying VFET at different recipient sites and with varying techniques. VFET was used to reconstruct the proximal humerus, distal radius or ulna, proximal femur, distal fibula, calcaneus, and mandible. Although most often harvested on the anterior tibial artery, VFET has also been performed using the peroneal artery, the inferior lateral genicular artery, and a dual pedicle. Recipient site flap inset most often involved fixation with plates and/or screws as well as soft tissue reconstruction using a retained slip of biceps femoris tendon. Outcomes included limb growth, range of motion, and strength. The most common reported complications were bone flap fracture and peroneal nerve palsy. The anterior tibial artery was the most applied pedicle with reliable limb growth, but with the added risk of postoperative peroneal palsy. Bone flap fracture most often occurred at the proximal humerus and femur recipient sites. Plate fixation and the combined use of allograft had lower instances of bone flap fracture. This review highlights how the anticipated dynamic growth and remodeling this free flap offers in the long term must be weighed against its complexity and potential complications.

Background:. Artificial intelligence (AI) leverages today’s exceptional computational powers and algorithmic abilities to learn from large data sets and solve complex problems. The aim of this study was to construct an AI model that can intelligently and reliably recognize the anatomy of cleft lip and nasal deformity and automate placement of nasolabial markings that can guide surgical design. Methods:. We adopted the high-resolution net architecture, a recent family of convolutional neural networks–based deep learning architecture specialized in computer-vision tasks to train an AI model, which can detect and place the 21 cleft anthropometric points on cleft lip photographs and videos. The model was tested by calculating the Euclidean distance between hand-marked anthropometric points placed by an expert cleft surgeon to ones generated by our cleft AI model. A normalized mean error (NME) was calculated for each point. Results:. All NME values were between 0.029 and 0.055. The largest NME was for cleft-side cphi. The smallest NME value was for cleft-side alare. These errors were well within standard AI benchmarks. Conclusions:. We successfully developed an AI algorithm that can identify the 21 surgically important anatomic landmarks of the unilateral cleft lip. This model can be used alone or integrated with surface projection to guide various cleft lip/nose repairs. Having demonstrated the feasibility of creating such a model on the complex three-dimensional surface of the lip and nose, it is easy to envision expanding the use of AI models to understand all of human surface anatomy—the full territory and playground of plastic surgeons.

Background:. Although polysomnography is paramount when evaluating neonatal airway obstruction, “normal” published references do not exist. We present normative polysomnography data for newborns age 0–1 month. We compare this reference to pre and postoperative sleep data from infants undergoing mandibular distraction osteogenesis (MDO) at this same age. Methods:. Following IRB approval, normative subjects were recruited from our neonatal intensive care unit to undergo nap polysomnography. One blinded sleep physician read all studies. From 2016 to 2019, we prospectively collected sleep data for newborns undergoing MDO. Results:. In total, 22 neonates without airway obstruction provided normative sleep data. Median total apnea-hypopnea index (AHI), obstructive apnea-hypopnea index (OAHI), and central apnea index (CAI) were 7.3, 4.9, and 0.7 events/hour. Median O2 nadir was 91%. Polysomnography for 13 neonates before MDO and during consolidation showed median preoperative AHI was 38.3, OAHI was 37.0, CAI was 1.9, and median O2 nadir was 83%. Following MDO, median AHI was 6.1, OAHI was 4.0, CAI was 1.3, and median O2 nadir was 92.5%. Paired t-tests confirmed significant improvements in all indices; when comparing the postoperative group with the normative group, there was no difference in oxygenation nor any respiratory index. Conclusions:. “Normal” neonates have more obstructive events and lower oxygenation nadirs than previously appreciated. We provide normative nap polysomnography values for this age group and encourage centers with multidisciplinary MDO teams to utilize this data to calibrate patient selection algorithms, inform treatment discussions, and better understand surgical outcomes. Limitations include a small sample size and single institution study.

SUMMARY. The purpose of this study was to assess the frequency by which plastic surgery-related terms have been included in the lyrics of Western music hits from the 1970s to the present day as a proxy for estimating the cultural impact of plastic surgery. A list of the Billboard Year-End Hot 100 songs from 1968 to 2019 and the Billboard Year-End Hot R&B/Hip-Hop songs from 1970 to 2019 was obtained for a combined total of 8550 songs. Lyrics for each song were extracted via a web-scraping system, and a database of plastic surgery-related terms was developed by our team. Each term was then queried amongst the compiled lyrics data sets, and the total frequency of plastic surgery-related terms per year and per decade was determined. Each term was also examined in its context of usage to validate its relevance to plastic surgery and determine its connotation through sentiment analysis. The frequency of plastic surgery-related terms referenced in the Billboard Year-End Hot 100 and Billboard Year-End Hot R&B/Hip-Hop charts has increased 15-fold from the 1970s (n = 1 song) to 2010s (n = 15 songs). The terms most often mentioned included “doctor,” “silicone,” “plastic,” “surgery,” “nip-tuck,” and “lipo.” Artists who most frequently used plastic surgery-related terms were Kanye West, 2 Chainz, and Nicki Minaj. The current study is the first to evaluate trends in plastic surgery references in music formally. In turn, this study helps further our understanding of the interplay between plastic surgery and popular culture.