Plastic and Reconstructive Surgery • December 2021 private equity has been explored in other specialties, the extent of private equity engagement in plastic surgery is unknown. 2,3 This study characterizes trends in private equity deals from 2011 to 2019. We hypothesized that there would be greater private equity investment toward companies with scalable business models, which include cosmetic products and retail clinics, as opposed to companies with a focus in regenerative medicine or devices that require extensive research and development efforts.A retrospective review of private equity deals was performed using Pitchbook (PitchBook, Seattle, Wash.), a market database comprising public information on companies and investors. Data were analyzed from deals posted in January 1, 2011, through December 31, 2019. 4 The total amount (U.S. dollars) of private equity investment made to plastic surgeryrelated companies was identified. Six therapeutic areas were identified: cosmetic products (over-the-counter skincare products), dermatology (nonsurgical) physician practices, plastic surgeon physician practices, devices/lasers, retail clinics (including medical spas and franchise clinics), and regenerative medicine/ biotechnology companies (composed of companies that offer tissue engineering and wound-healing solutions).
DISCLAIMER This paper was submitted to the Bulletin of the World Health Organization and was posted to the COVID-19 open site, according to the protocol for public health emergencies for international concern as described in Vasee Moorthy et al. (http://dx.doi.org/10.2471/BLT.20.251561).The information herein is available for unrestricted use, distribution and reproduction in any medium, provided that the original work is properly cited as indicated by the Creative Commons Attribution 3.0 Intergovernmental Organizations licence (CC BY IGO 3.0).
: Artificial intelligence (Al)-based analyses may serve as a more objective tool for measuring cosmetic improvements following aesthetic plastic surgery. This preliminary proof-of-concept study utilized a novel commercial facial recognition software to assess perceived changes in age and attractiveness among patients receiving rhinoplasty.
This study was a retrospective evaluation of three-dimensional photographs of patients who underwent rhinoplasty by the senior author (DS). Both pre- and post-operative (> 12-month follow-up) Vectra three-dimensional images (Canfield Scientific, Parsippany, NJ) were assessed using Haystack AI Software (Haystack AI, New York, NY). Facial attractiveness (score 1–10) and apparent age were predicted. A retrospective chart review of demographic variables was additionally performed. Paired t tests were used to compare age and attractiveness scores before and after surgery. Multivariate linear regression was performed to identify factors associated with age and attractiveness scores.
One hundred twenty-four patients receiving rhinoplasty met the study criteria (average age: 35.58). Overall, rhinoplasty was associated with increases in Al-rated attractiveness (+0.28, P = 0.03) and decreases in perceived age relative to the patient’s true age (−1.03 years, P = 0.03). Greater decreases in postoperative perceived age were achieved in patients who appeared older than their actual age preoperatively (P < 0.001).
Facial recognition software was successfully used to evaluate improvements in perceived age and attractiveness in patients undergoing aesthetic rhinoplasty. Patients were perceived by the software as younger and more attractive following rhinoplasty. Age reversal was greatest among patients who appeared much older than their actual age at the time of surgery.
Level of Evidence: IV
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