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1.
Aesthet Surg J ; 2024 Sep 03.
Artículo en Inglés | MEDLINE | ID: mdl-39224090

RESUMEN

Dissecting deep to the superficial musculoaponeurotic system, SMAS, a popular option for facelifts, has the potential for injury to the parotid gland leading to post operative sialoceles and fistulas. Similarly, deep plane procedures in the neck which include partial submandibular gland resection may lead to salivary gland leaks. We previously described the management of sialocele following rhytidectomy.1 Since then, administration of Botulinum toxin A has emerged as the primary treatment and prevention of this rare complication. The technique of administration and dosage of botulinum toxin in the treatment algorithm is not well-defined. We present a literature review and our current protocol of the most efficacious injection technique and dosing to prevent and treat injury to the parotid and submandibular glands.

2.
Aesthet Surg J Open Forum ; 6: ojae062, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39257998

RESUMEN

Background: At a time when Internet and social media use is omnipresent among patients in their self-directed research about their medical or surgical needs, artificial intelligence (AI) large language models (LLMs) are on track to represent hallmark resources in this context. Objectives: The authors aim to explore and assess the performance of a novel AI LLM in answering questions posed by simulated patients interested in aesthetic breast plastic surgery procedures. Methods: A publicly available AI LLM was queried using simulated interactions from the perspective of patients interested in breast augmentation, mastopexy, and breast reduction. Questions posed were standardized and categorized under aesthetic needs inquiries and awareness of appropriate procedures; patient candidacy and indications; procedure safety and risks; procedure information, steps, and techniques; patient assessment; preparation for surgery; postprocedure instructions and recovery; and procedure cost and surgeon recommendations. Using standardized Likert scales ranging from 1 to 10, 4 expert breast plastic surgeons evaluated responses provided by AI. A postparticipation survey assessed expert evaluators' experience with LLM technology, perceived utility, and limitations. Results: The overall performance across all question categories, assessment criteria, and procedures examined was 7.3/10 ± 0.5. Overall accuracy of information shared was scored at 7.1/10 ± 0.5; comprehensiveness at 7.0/10 ± 0.6; objectivity at 7.5/10 ± 0.4; safety at 7.5/10 ± 0.4; communication clarity at 7.3/10 ± 0.2; and acknowledgment of limitations at 7.7/10 ± 0.2. With regards to performance on procedures examined, the model's overall score was 7.0/10 ± 0.8 for breast augmentation; 7.6/10 ± 0.5 for mastopexy; and 7.4/10 ± 0.5 for breast reduction. The score on breast implant-specific knowledge was 6.7/10 ± 0.6. Conclusions: Albeit not without limitations, AI LLMs represent promising resources for patient guidance and patient education. The technology's machine learning capabilities may explain its improved performance efficiency.

3.
Aesthet Surg J Open Forum ; 6: ojae058, 2024.
Artículo en Inglés | MEDLINE | ID: mdl-39228821

RESUMEN

Background: Artificial intelligence large language models (LLMs) represent promising resources for patient guidance and education in aesthetic surgery. Objectives: The present study directly compares the performance of OpenAI's ChatGPT (San Francisco, CA) with Google's Bard (Mountain View, CA) in this patient-related clinical application. Methods: Standardized questions were generated and posed to ChatGPT and Bard from the perspective of simulated patients interested in facelift, rhinoplasty, and brow lift. Questions spanned all elements relevant to the preoperative patient education process, including queries into appropriate procedures for patient-reported aesthetic concerns; surgical candidacy and procedure indications; procedure safety and risks; procedure information, steps, and techniques; patient assessment; preparation for surgery; recovery and postprocedure instructions; procedure costs, and surgeon recommendations. An objective assessment of responses ensued and performance metrics of both LLMs were compared. Results: ChatGPT scored 8.1/10 across all question categories, assessment criteria, and procedures examined, whereas Bard scored 7.4/10. Overall accuracy of information was scored at 6.7/10 ± 3.5 for ChatGPT and 6.5/10 ± 2.3 for Bard; comprehensiveness was scored as 6.6/10 ± 3.5 vs 6.3/10 ± 2.6; objectivity as 8.2/10 ± 1.0 vs 7.2/10 ± 0.8, safety as 8.8/10 ± 0.4 vs 7.8/10 ± 0.7, communication clarity as 9.3/10 ± 0.6 vs 8.5/10 ± 0.3, and acknowledgment of limitations as 8.9/10 ± 0.2 vs 8.1/10 ± 0.5, respectively. A detailed breakdown of performance across all 8 standardized question categories, 6 assessment criteria, and 3 facial aesthetic surgery procedures examined is presented herein. Conclusions: ChatGPT outperformed Bard in all assessment categories examined, with more accurate, comprehensive, objective, safe, and clear responses provided. Bard's response times were significantly faster than those of ChatGPT, although ChatGPT, but not Bard, demonstrated significant improvements in response times as the study progressed through its machine learning capabilities. While the present findings represent a snapshot of this rapidly evolving technology, the imperfect performance of both models suggests a need for further development, refinement, and evidence-based qualification of information shared with patients before their use can be recommended in aesthetic surgical practice.

4.
Aesthet Surg J ; 2024 Aug 20.
Artículo en Inglés | MEDLINE | ID: mdl-39163270

RESUMEN

BACKGROUND: While there exists ample evidence on the impact of perioperative blood pressure on hematoma incidence following facelift; the association of elevated or labile intraoperative blood pressure with postoperative hematoma remains to be explored. OBJECTIVES: The authors evaluate the association of elevated or labile intraoperative systolic blood pressure (SBP) with postoperative hematoma, using the senior author's single surgeon experience of 118 consecutive facelifts. METHODS: A multivariate logistic regression was conducted using complete demographic, procedure-related, blood pressure-related, and outcomes-related data, with the outcome of interest representing postoperative hematoma. One-way ANOVA and linear regression analyses were used to assess for significant associations between a preoperative history of hypertension and a tendency to demonstrate elevated or labile intraoperative SBP. A Fisher's Exact test was subsequently used to assess for specific intraoperative SBP measurement cut-offs significantly associated with postoperative hematoma, including maximum recorded intraoperative SBP, and specific degree of intraoperative SBP fluctuations. RESULTS: Multivariate logistic regression demonstrated no statistically significant patient- or procedure-related demographic predictors of postoperative hematoma. With aggressive treatment of preoperative hypertension, high preoperative SBP was not found to be a significant predictor of postoperative hematoma following facelift, although this approached statistical significance (p=0.05). In contrast, labile intraoperative SBP (maximum recorded intraoperative SBP - minimum recorded intraoperative SBP; p=0.026), as well as high immediate postoperative SBP (p=0.002), were both independent and statistically significant predictors of postoperative hematoma. Patients with a preoperative history of hypertension, and more specifically those with elevated SBP measurements in the preoperative clinic, were more likely to demonstrate labile (p=0.007) or elevated (p=0.005) intraoperative SBP during facelift surgery. Specifically, maximum recorded intraoperative SBP ≥155mmHg (p=0.045), as well as maximum intraoperative SBP fluctuations ≥80mmHg (p=0.036) were found to be significantly associated with hematoma. CONCLUSIONS: A multimodal approach is necessary to control perioperative systolic blood pressure within the strict <120mmHg target demonstrated to significantly decrease hematoma incidence. The senior author's preference is for intraoperative SBP to remain within a strict 90-100mmHg range. In contrast to hypertension that is aggressively treated and successfully controlled, hypertension that is difficult to control intraoperatively, may be a predictor of systolic blood pressure that is difficult to control postoperatively, and thus a significant risk factor for postoperative hematoma following facelift.

5.
Aesthet Surg J ; 44(10): 1127-1129, 2024 Sep 16.
Artículo en Inglés | MEDLINE | ID: mdl-39024417
7.
Aesthetic Plast Surg ; 48(13): 2399-2403, 2024 Jul.
Artículo en Inglés | MEDLINE | ID: mdl-38714536

RESUMEN

INTRODUCTION: Hematoma formation after blepharoplasty is serious and potentially vision-threatening, with hypertension being the primary risk factor. The aim of this paper is to assess perioperative blood pressure trends and rates of complication in patients undergoing a strict blood pressure protocol designed to keep perioperative systolic blood pressure below 120 mmHg. METHODS: A retrospective chart review was performed of 32 patients undergoing face lift with conomitant blepharoplasty from January 2015 to July 2018. For each patient blood pressure readings obtained before, during, and after surgery were reviewed. Two-sample one-tail T-tests were performed, and p values less than 0.05 were considered statistically significant. RESULTS: The mean systolic blood pressure (SBP) for all patients was highest intraoperatively. Patients with known hypertension had higher mean SBPs than patients without hypertension across all phases of care, with a statistically significant difference in immediate preoperative SBP (p=0.05). Males had a higher average blood pressure immediately postoperatively (p=0.05). A previous diagnosis of hypertension in females was associated with a higher immediate preoperative SBP (p=0.07) as well as age over 65 (p=0.07). The overall rate of complications was 37.5%. No patients experienced hematoma. CONCLUSION: This study demonstrated that keeping blood pressure below 120 mmHg after surgery was an effective method of preventing hematoma after blepharoplasty, even in patients concurrently on anti-coagulative medications. Special attention to blood pressure control should be shown to patients with known risk factors such as a previous diagnosis of hypertension, male sex, or age greater than 65. LEVEL OF EVIDENCE III: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .


Asunto(s)
Blefaroplastia , Hematoma , Hipertensión , Humanos , Blefaroplastia/métodos , Blefaroplastia/efectos adversos , Hematoma/prevención & control , Hematoma/etiología , Estudios Retrospectivos , Femenino , Masculino , Persona de Mediana Edad , Hipertensión/prevención & control , Anciano , Complicaciones Posoperatorias/prevención & control , Complicaciones Posoperatorias/etiología , Presión Sanguínea/fisiología , Adulto , Antihipertensivos/uso terapéutico , Resultado del Tratamiento , Medición de Riesgo , Estudios de Cohortes
9.
Aesthet Surg J ; 44(8): 889-896, 2024 Jul 15.
Artículo en Inglés | MEDLINE | ID: mdl-38318684

RESUMEN

BACKGROUND: Large language models (LLMs) have revolutionized the way plastic surgeons and their patients can access and leverage artificial intelligence (AI). OBJECTIVES: The present study aims to compare the performance of 2 current publicly available and patient-accessible LLMs in the potential application of AI as postoperative medical support chatbots in an aesthetic surgeon's practice. METHODS: Twenty-two simulated postoperative patient presentations following aesthetic breast plastic surgery were devised and expert-validated. Complications varied in their latency within the postoperative period, as well as urgency of required medical attention. In response to each patient-reported presentation, Open AI's ChatGPT and Google's Bard, in their unmodified and freely available versions, were objectively assessed for their comparative accuracy in generating an appropriate differential diagnosis, most-likely diagnosis, suggested medical disposition, treatments or interventions to begin from home, and/or red flag signs/symptoms indicating deterioration. RESULTS: ChatGPT cumulatively and significantly outperformed Bard across all objective assessment metrics examined (66% vs 55%, respectively; P < .05). Accuracy in generating an appropriate differential diagnosis was 61% for ChatGPT vs 57% for Bard (P = .45). ChatGPT asked an average of 9.2 questions on history vs Bard's 6.8 questions (P < .001), with accuracies of 91% vs 68% reporting the most-likely diagnosis, respectively (P < .01). Appropriate medical dispositions were suggested with accuracies of 50% by ChatGPT vs 41% by Bard (P = .40); appropriate home interventions/treatments with accuracies of 59% vs 55% (P = .94), and red flag signs/symptoms with accuracies of 79% vs 54% (P < .01), respectively. Detailed and comparative performance breakdowns according to complication latency and urgency are presented. CONCLUSIONS: ChatGPT represents the superior LLM for the potential application of AI technology in postoperative medical support chatbots. Imperfect performance and limitations discussed may guide the necessary refinement to facilitate adoption.


Asunto(s)
Inteligencia Artificial , Complicaciones Posoperatorias , Humanos , Femenino , Complicaciones Posoperatorias/etiología , Complicaciones Posoperatorias/diagnóstico , Complicaciones Posoperatorias/terapia , Mamoplastia/métodos , Mamoplastia/efectos adversos , Adulto , Diagnóstico Diferencial
10.
Aesthet Surg J ; 44(7): 769-778, 2024 Jun 14.
Artículo en Inglés | MEDLINE | ID: mdl-38366026

RESUMEN

BACKGROUND: Social media platforms have come to represent integral components of the professional marketing and advertising strategy for plastic surgeons. Effective and consistent content development, however, remains technically demanding and time consuming, prompting most to employ, at non-negligible costs, social media marketing specialists for content planning and development. OBJECTIVES: In the present study, we aimed to investigate the ability of presently available artificial intelligence (AI) models to assist plastic surgeons in their social media content development and sharing plans. METHODS: An AI large language model was prompted on the study's objectives through a series of standardized user interactions. Social media platforms of interest, on which the AI model was prompted, included Instagram, TikTok, and X (formerly Twitter). RESULTS: A 1-year, entirely AI-generated social media plan, comprising a total of 1091 posts for the 3 aforementioned social media platforms, is presented. Themes of the AI-generated content proposed for each platform were classified in 6 categories, including patient-related, practice-related, educational, "uplifting," interactive, and promotional posts. Overall, 91 publicly recognized holidays and observant and awareness days were incorporated into the content calendars. The AI model demonstrated an ability to differentiate between the distinct formats of each of the 3 social media platforms investigated, generating unique ideas for each, and providing detailed content development and posting instructions, scripts, and post captions, leveraging features specific to each platform. CONCLUSIONS: By providing detailed and actionable social media content creation and posting plans to plastic surgeons, presently available AI models can be readily leveraged to assist in and significantly alleviate the burden associated with social media account management, content generation, and potentially patient conversion.


Asunto(s)
Inteligencia Artificial , Medios de Comunicación Sociales , Cirujanos , Cirugía Plástica , Humanos , Comercialización de los Servicios de Salud/métodos
11.
Aesthetic Plast Surg ; 48(5): 953-976, 2024 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-38273152

RESUMEN

INTRODUCTION: Large language models (LLM) have revolutionized the way humans interact with artificial intelligence (AI) technology, with marked potential for applications in esthetic surgery. The present study evaluates the performance of Bard, a novel LLM, in identifying and managing postoperative patient concerns for complications following body contouring surgery. METHODS: The American Society of Plastic Surgeons' website was queried to identify and simulate all potential postoperative complications following body contouring across different acuities and severity. Bard's accuracy was assessed in providing a differential diagnosis, soliciting a history, suggesting a most-likely diagnosis, appropriate disposition, treatments/interventions to begin from home, and red-flag signs/symptoms indicating deterioration, or requiring urgent emergency department (ED) presentation. RESULTS: Twenty-two simulated body contouring complications were examined. Overall, Bard demonstrated a 59% accuracy in listing relevant diagnoses on its differentials, with a 52% incidence of incorrect or misleading diagnoses. Following history-taking, Bard demonstrated an overall accuracy of 44% in identifying the most-likely diagnosis, and a 55% accuracy in suggesting the indicated medical dispositions. Helpful treatments/interventions to begin from home were suggested with a 40% accuracy, whereas red-flag signs/symptoms, indicating deterioration, were shared with a 48% accuracy. A detailed analysis of performance, stratified according to latency of postoperative presentation (<48hours, 48hours-1month, or >1month postoperatively), and according to acuity and indicated medical disposition, is presented herein. CONCLUSIONS: Despite promising potential of LLMs and AI in healthcare-related applications, Bard's performance in the present study significantly falls short of accepted clinical standards, thus indicating a need for further research and development prior to adoption. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .


Asunto(s)
Contorneado Corporal , Cirugía Plástica , Humanos , Inteligencia Artificial , Complicaciones Posoperatorias/diagnóstico , Lenguaje
12.
Aesthet Surg J ; 44(2): 134-143, 2024 Jan 16.
Artículo en Inglés | MEDLINE | ID: mdl-37540899

RESUMEN

Hematoma is a common complication after facelift procedures. Multiple factors have been shown to increase the risk of hematoma formation, such as male gender, anticoagulant medication use, perioperative hypertension, increased intrathoracic pressure, and operative technique. The purpose of this manuscript is to provide an overview of existing literature to provide surgeons with evidence-based recommendations on how to minimize hematoma risk during facelift surgery. A literature search for hematoma and facelift surgery was performed that identified 478 unique manuscripts. Abstracts were reviewed, excluding articles not describing facelift surgery, those written before 1970, studies with a sample size of fewer than 5 patients, non-English studies, and those that did not provide postoperative hematoma rates. Forty-five articles were included in this text, with their recommendations. Measures such as the prophylactic management of pain, nausea, and hypertension, the use of fibrin glue tissue sealants, the use of local anesthesia rather than general anesthesia, and strict blood pressure control of at least <140 mmHg were found to significantly reduce hematoma formation. Quilting sutures has shown benefit in some high-risk patients. Measures such as drains, compression dressings, perioperative use of selective serotonin reuptake inhibitors, and perioperative steroids had no significant effect on hematoma formation. In addition to appropriate patient selection and careful intraoperative hemostasis, many adjunct measures have been shown to reduce postoperative hematoma formation in facelift procedures.


Asunto(s)
Hipertensión , Ritidoplastia , Humanos , Masculino , Ritidoplastia/efectos adversos , Ritidoplastia/métodos , Anestesia Local , Hipertensión/prevención & control , Hipertensión/complicaciones , Adhesivo de Tejido de Fibrina/uso terapéutico , Hematoma/etiología , Hematoma/prevención & control , Complicaciones Posoperatorias/etiología , Complicaciones Posoperatorias/prevención & control
14.
Aesthet Surg J ; 44(3): 344-345, 2024 Feb 15.
Artículo en Inglés | MEDLINE | ID: mdl-38085921

Asunto(s)
Sedestación , Humanos
16.
Aesthet Surg J Open Forum ; 5: ojad099, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-38075298

RESUMEN

In this bibliometric analysis, we investigated the top 100 most cited articles on rhytidectomy, a prevalent cosmetic surgical procedure in the United States of America. Using data from Web of Science spanning from 1900 to 2021, we found these papers collectively cited 7737 times, with individual citation counts ranging from 277 to 37 (mean 77). Notably, the majority of these papers (58 out of 100) were categorized as Level of Evidence 5, indicating a prevalence of expert opinions, anatomical studies, and narrative reviews. Interestingly, none of the papers achieved Level 1 status, underscoring a lack of high-quality research in the field. The primary focus of these papers was on operative techniques (48 papers) and surgical anatomy of the face (20 papers). Only 10 articles incorporated patient-reported outcome measures (PROMs), but none utilized validated scales. This analysis highlights the urgent need for improved research methodologies in rhytidectomy studies, emphasizing the necessity for rigorous, high-quality research, and the implementation of validated rhytidectomy-specific PROMs.

18.
Aesthet Surg J ; 43(12): 1530-1531, 2023 11 16.
Artículo en Inglés | MEDLINE | ID: mdl-37972079
19.
Aesthet Surg J Open Forum ; 5: ojad059, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37899910
20.
Aesthet Surg J Open Forum ; 5: ojad076, 2023.
Artículo en Inglés | MEDLINE | ID: mdl-37694226

RESUMEN

Clinical case reporting plays a vital role in sharing detailed patient narratives, providing insights into rare conditions, innovative treatments, and unexpected outcomes. However, existing reporting guidelines in aesthetic medicine fail to capture the specific nuances of procedures and outcomes in this field. The authors' objectives were to develop comprehensive guidelines for Case REporting in Aesthetic Medicine (CREAM). The study employed a 3-phase consensus process, including a literature review, expert interviews, and a consensus meeting. A diverse group of 10 expert participants (plastic surgeons, dermatologists, noncore specialists, evidence-based medicine expert, and research scientist) in Phase I and 30 experienced aesthetic practitioners in Phase II contributed to the research. Statistical analysis was conducted to assess agreement levels among participants and explore associations and variations within the data. The participants represented various specialties, genders, LGBTQ+ identities, and ethnic backgrounds. The research resulted in the development of the CREAM guidelines, consisting of a 16-item checklist. The guidelines covered essential aspects of case reporting, such as patient and practice information, procedure details, clinical assessment and outcomes, adverse events, and ethical considerations. Statistical analysis indicated a high level of consensus among participants, as well as significant associations between checklist items. CREAM guidelines represent a step toward enhancing transparency and standardization in case reporting in aesthetic medicine. Adhering to these guidelines will allow authors to contribute to a robust evidence base, prioritize patient safety, and drive advancements aesthetic medicine.

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