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Background: Breastand reductions mastopexies continue to rank among the most frequently performed plastic surgical procedures worldwide. While there exists a consensus on several aspects of the procedure, a plethora of controversies remain. This study aims to compare the most relevant peri- and intra-operative factors on an international level to standardize this common procedure according to evidence-based guidelines. Methods: A questionnaire was sent to over five thousand surgeons in 77 countries. The survey was divided into three categories according to the volume of removed breast tissue (50–500 g, 500–1000 g, and > 1000 g) and inquired about standard practices, secondary procedures, use of new technologies, current controversies, and surgeon demographics. The results were evaluated and correlated with evidence-based literature. Results: A total of 1431 surveys were gathered, corresponding to a response rate of 29%. It was found that specific surgical approaches and standard practices prevail on an international basis. Still, there exist controversies that seem to be linked to geographic locations. For instance, irrespective of resection weight, in the majority of countries, a superior or superomedial pedicle is used most frequently, while in North America and South East Asia, the inferior-based pedicle is preferred. Conclusions: We identified common traits in several aspects of breast reduction surgery. However, in this study, it became apparent that international practice patterns remain incoherent. Seen from a global perspective, plastic surgeons would thus still benefit from high-quality studies to further establish evidence-based, standardized, and universally applicable practice guidelines. Level of Evidence: Not gradable [ABSTRACT FROM AUTHOR]

Bladder acontractility affects several thousand patients in the United States, but the available therapies are limited. Latissimus dorsi detrusor myoplasty (LDDM) is a therapeutic option that allows patients with bladder acontractility to void voluntarily. Our goal was to conduct a systematic review of the literature to determine whether LDDM is a better option than clean intermittent catheterization (CIC) (standard treatment) in patients with bladder acontractility. On January 17, 2020, we conducted a systematic review of the PubMed/MEDLINE, Cochrane Clinical Answers, Cochrane Central Register of Controlled Trials, Embase, and ClinicalTrials.gov databases, without time frame limitations, to identify articles on the use of LDDM for bladder acontractility. Of 75 potential articles, 4 fulfilled the eligibility criteria. The use of LDDM to treat patients with bladder acontractility was reported in four case series by the same group in Europe. Fifty-eight patients were included, and no comparison groups were included. The most common cause of bladder acontractility was spinal cord injury (n=36). The mean (±standard deviation) operative time was 536 (±22) minutes, postoperative length of hospital stay ranged from 10 to 13 days, and follow-up ranged from 9 to 68 months. Most patients had complete response, were able to void voluntarily, and had post-void residual volume less than 100 mL. Although promising outcomes have been obtained, evidence is still weak regarding whether LDDM is better than CIC to avoid impairment of the urinary tract among patients with bladder acontractility. Further prospective studies with control groups are necessary. [ABSTRACT FROM AUTHOR]

The potential to differentiate into different cell lines, added to the easy and cost-effective method of extraction, makes adipose-derived stem cells (ADSCs) an object of interest in lymphedema treatment. Our study’s goal was to conduct a comprehensive systematic review of the use of ADSCs in lymphatic tissue engineering and regeneration. On July 23, 2019, using PubMed/MEDLINE, Cochrane Clinical Answers, Cochrane Central Register of Controlled Trials, and Embase databases, we conducted a systematic review of published literature on the use of ADSCs in lymphatic tissue engineering and regeneration. There were no language or time frame limitations, and the following search strategy was applied: ((Adipose stem cell) OR Adipose-derived stem cell)) AND ((Lymphedema) OR Breast Cancer Lymphedema). Only original research manuscripts were included. Fourteen studies fulfilled the inclusion criteria. Eleven studies were experimental (in vitro or in vivo in animals), and only three were clinical. Publications on the topic demonstrated that ADSCs promote lymphangiogenesis, and its effect could be enhanced by modulation of vascular endothelial growth factor-C, interleukin-7, prospero homeobox protein 1, and transforming growth factor-β1. Pilot clinical studies included 11 patients with breast cancer-related lymphedema, and no significant side effects were present at 12-month follow-up. Literature on the use of ADSCs in lymphatic tissue engineering and regeneration demonstrated promising data. Clinical evidence is still in its infancy, but the scientific community agrees that ADSCs can be useful in regenerative lymphangiogenesis. Data collected in this review indicate that unprecedented advances in lymphedema treatment can be anticipated in the upcoming years. [ABSTRACT FROM AUTHOR]

Breast cancer treatment-related lymphedema (BCRL) is a common comorbidity in breast cancer survivors. Although magnetic resonance imaging (MRI) is widely used to evaluate therapeutic response of patients with various medical conditions, it is not routinely used to evaluate lymphedema patients. We conducted a systematic review of the literature to identify studies on the use of MRI to evaluate therapy for BCRL. We hypothesized that MRI could provide information otherwise not possible through other examinations. On October 21, 2019, we conducted a systematic review on the PubMed/MEDLINE and Scopus databases, without time frame or language limitations, to identify studies on the use of MRI to evaluate therapy for BCRL. We excluded studies that investigated other applications of MRI, such as lymphedema diagnosis and surgical planning. Of 63 potential articles identified with the search, three case series fulfilled the eligibility criteria. In total, 53 patients with BCRL were included and quantitatively evaluated with MRI before and after manual lymphatic drainage. Authors used MRI or MR lymphagiography to investigate factors such as lymphatic vessel cross-sectional area, tissue water relaxation time (T2), and chemical exchange saturation transfer. The only study that compared MRI measurement with standard examinations reported that MRI added information to the therapy evaluation. MRI seems to be a promising tool for quantitative measurement of therapeutic response in patients with BCRL. However, the identified studies focused on only manual lymphatic drainage and were limited by the small numbers of patients. More studies are necessary to shed light on the topic. [ABSTRACT FROM AUTHOR]

The dysplastic maxilla and retracted zygoma characterize Apert's syndrome. The relationship between the cranial base and facial development is believed to be influential and substantial. The purpose of this study is to explore the temporal relationships of maldevelopment of these structures to identify potential influence patterns. Fifty-four CT scans (unoperated Apert's, n = 18; control, n = 36) were included and divided into three age subgroups (0–6 months, 6 months–2 years, and 2–6 years). All measurements were analyzed by Materialize software. Cephalometrics relating to midface and cranial base were collected. In anteroposterior direction, prior to 6 months, the zygoma was markedly retruded by 12% in Apert's, followed by persistent retrusive shape into adulthood, averaging 17% shorter compared to controls. The maxillary anteroposterior dimension was 22% shorter than normal before 6 months of age, thereafter, it maintained at least an 18% deficiency into adulthood. In the horizontal direction, the transverse width of the zygoma increased 39% between 6 months and 2 years of age, and it was 14% wider on average overall into adulthood. The maxilla had normal growth in transverse and vertical directions. The zygoma is the most severely deformed anatomic facial structure in early infancy, in both positional relation and geometric shape in Apert's syndrome. This may develop as a 'bridge', influencing the structure, transmitting malformation stresses, caused by premature fused coronal and peri-zygomatic sutures, into facial structures and the maxilla. [ABSTRACT FROM AUTHOR]

Several authors have proposed classifications to analyze the quality over time of secondary alveolar bone grafting. However, little discussion has been held to quantitatively measure the secondary bone grafting for correction of nasal deformity associated to cleft palate and lip. Twenty patients with unilateral alveolar cleft, who underwent secondary alveolar bone grafting, were studied with 3D computer tomography. The height between the inferior portion of the pyriform aperture and the incisal border of the unaffected side (height A) and the affected side (height B) was measured using a software Mirror. A percentage was then obtained dividing the height B by the height A and classified into grades I, II, and III if the value was greater than 67%, between 34% and 66%, or less than 33%. Age, time of followup, initial operation, and age of canine eruption were also recorded. All patients presented appropriate occlusion and function. Mean time of followup was 7 years, and mean initial age for operation was 10 years old. 16 patients were rated as grade I and 4 patients as grade II. No cases had grade III. We present a new grading system that can be used to assess the success of secondary bone grafting in patients who underwent alveolar cleft repair. [ABSTRACT FROM AUTHOR]

Digital health tools can improve health care access and outcomes for individuals with limited access to health care, particularly those residing in rural areas. This scoping review examines the existing literature on using digital tools in patients with limited access to health care in rural areas. It assesses their effectiveness in improving health outcomes. The review adopts a comprehensive search strategy to identify relevant studies from electronic databases, and the selected studies are analyzed descriptively. The findings highlight the advantages and barriers of digital health interventions in rural populations. The advantages include increased access to health care practitioners through teleconsultations, improved health care outcomes through remote monitoring, better disease management through mobile health applications and wearable devices, and enhanced access to specialized care and preventive programs. However, limited internet connectivity and a lack of familiarity with digital tools are barriers that must be addressed to ensure equitable access to digital health interventions in rural areas. Overall, digital tools improve health outcomes for individuals with limited health care access in rural areas. [ABSTRACT FROM AUTHOR]

Chronic pain affects over 50 million people in the United States, particularly older adults, making effective assessment and treatment essential in primary care. Actigraphy, which monitors and records limb movement to estimate wakefulness and sleep, has emerged as a valuable tool for assessing pain by providing insights into activity patterns. This review highlights the non-invasive, cost-effective nature of actigraphy in pain monitoring, along with its ability to offer continuous, detailed data on patient movement. However, actigraphy's reliance on physical activity as a proxy for pain, and its inability to directly measure pain intensity, limit its applicability to certain pain types, such as neuropathic pain. Further research is needed to overcome these limitations and to improve the effectiveness of actigraphy in diverse clinical settings. [ABSTRACT FROM AUTHOR]

Medical researchers are increasingly utilizing advanced LLMs like ChatGPT-4 and Gemini to enhance diagnostic processes in the medical field. This research focuses on their ability to comprehend and apply complex medical classification systems for breast conditions, which can significantly aid plastic surgeons in making informed decisions for diagnosis and treatment, ultimately leading to improved patient outcomes. Fifty clinical scenarios were created to evaluate the classification accuracy of each LLM across five established breast-related classification systems. Scores from 0 to 2 were assigned to LLM responses to denote incorrect, partially correct, or completely correct classifications. Descriptive statistics were employed to compare the performances of ChatGPT-4 and Gemini. Gemini exhibited superior overall performance, achieving 98% accuracy compared to ChatGPT-4's 71%. While both models performed well in the Baker classification for capsular contracture and UTSW classification for gynecomastia, Gemini consistently outperformed ChatGPT-4 in other systems, such as the Fischer Grade Classification for gender-affirming mastectomy, Kajava Classification for ectopic breast tissue, and Regnault Classification for breast ptosis. With further development, integrating LLMs into plastic surgery practice will likely enhance diagnostic support and decision making. [ABSTRACT FROM AUTHOR]

Background: Large language models (LLMs) represent a recent advancement in artificial intelligence with medical applications across various healthcare domains. The objective of this review is to highlight how LLMs can be utilized by clinicians and surgeons in their everyday practice. Methods: A systematic review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Six databases were searched to identify relevant articles. Eligibility criteria emphasized articles focused primarily on clinical and surgical applications of LLMs. Results: The literature search yielded 333 results, with 34 meeting eligibility criteria. All articles were from 2023. There were 14 original research articles, four letters, one interview, and 15 review articles. These articles covered a wide variety of medical specialties, including various surgical subspecialties. Conclusions: LLMs have the potential to enhance healthcare delivery. In clinical settings, LLMs can assist in diagnosis, treatment guidance, patient triage, physician knowledge augmentation, and administrative tasks. In surgical settings, LLMs can assist surgeons with documentation, surgical planning, and intraoperative guidance. However, addressing their limitations and concerns, particularly those related to accuracy and biases, is crucial. LLMs should be viewed as tools to complement, not replace, the expertise of healthcare professionals. [ABSTRACT FROM AUTHOR]

In the U.S., diagnostic errors are common across various healthcare settings due to factors like complex procedures and multiple healthcare providers, often exacerbated by inadequate initial evaluations. This study explores the role of Large Language Models (LLMs), specifically OpenAI's ChatGPT-4 and Google Gemini, in improving emergency decision-making in plastic and reconstructive surgery by evaluating their effectiveness both with and without physical examination data. Thirty medical vignettes covering emergency conditions such as fractures and nerve injuries were used to assess the diagnostic and management responses of the models. These responses were evaluated by medical professionals against established clinical guidelines, using statistical analyses including the Wilcoxon rank-sum test. Results showed that ChatGPT-4 consistently outperformed Gemini in both diagnosis and management, irrespective of the presence of physical examination data, though no significant differences were noted within each model's performance across different data scenarios. Conclusively, while ChatGPT-4 demonstrates superior accuracy and management capabilities, the addition of physical examination data, though enhancing response detail, did not significantly surpass traditional medical resources. This underscores the utility of AI in supporting clinical decision-making, particularly in scenarios with limited data, suggesting its role as a complement to, rather than a replacement for, comprehensive clinical evaluation and expertise. [ABSTRACT FROM AUTHOR]

Background: OpenAI's ChatGPT (San Francisco, CA, USA) and Google's Gemini (Mountain View, CA, USA) are two large language models that show promise in improving and expediting medical decision making in hand surgery. Evaluating the applications of these models within the field of hand surgery is warranted. This study aims to evaluate ChatGPT-4 and Gemini in classifying hand injuries and recommending treatment. Methods: Gemini and ChatGPT were given 68 fictionalized clinical vignettes of hand injuries twice. The models were asked to use a specific classification system and recommend surgical or nonsurgical treatment. Classifications were scored based on correctness. Results were analyzed using descriptive statistics, a paired two-tailed t-test, and sensitivity testing. Results: Gemini, correctly classifying 70.6% hand injuries, demonstrated superior classification ability over ChatGPT (mean score 1.46 vs. 0.87, p-value < 0.001). For management, ChatGPT demonstrated higher sensitivity in recommending surgical intervention compared to Gemini (98.0% vs. 88.8%), but lower specificity (68.4% vs. 94.7%). When compared to ChatGPT, Gemini demonstrated greater response replicability. Conclusions: Large language models like ChatGPT and Gemini show promise in assisting medical decision making, particularly in hand surgery, with Gemini generally outperforming ChatGPT. These findings emphasize the importance of considering the strengths and limitations of different models when integrating them into clinical practice. [ABSTRACT FROM AUTHOR]

In postoperative care, patient education and follow-up are pivotal for enhancing the quality of care and satisfaction. Artificial intelligence virtual assistants (AIVA) and large language models (LLMs) like Google BARD and ChatGPT-4 offer avenues for addressing patient queries using natural language processing (NLP) techniques. However, the accuracy and appropriateness of the information vary across these platforms, necessitating a comparative study to evaluate their efficacy in this domain. We conducted a study comparing AIVA (using Google Dialogflow) with ChatGPT-4 and Google BARD, assessing the accuracy, knowledge gap, and response appropriateness. AIVA demonstrated superior performance, with significantly higher accuracy (mean: 0.9) and lower knowledge gap (mean: 0.1) compared to BARD and ChatGPT-4. Additionally, AIVA's responses received higher Likert scores for appropriateness. Our findings suggest that specialized AI tools like AIVA are more effective in delivering precise and contextually relevant information for postoperative care compared to general-purpose LLMs. While ChatGPT-4 shows promise, its performance varies, particularly in verbal interactions. This underscores the importance of tailored AI solutions in healthcare, where accuracy and clarity are paramount. Our study highlights the necessity for further research and the development of customized AI solutions to address specific medical contexts and improve patient outcomes. [ABSTRACT FROM AUTHOR]

With abundant information and interconnectedness among people, identifying knowledgeable individuals in specific domains has become crucial for organizations. Artificial intelligence (AI) algorithms have been employed to evaluate the knowledge and locate experts in specific areas, alleviating the manual burden of expert profiling and identification. However, there is a limited body of research exploring the application of AI algorithms for expert finding in the medical and biomedical fields. This study aims to conduct a scoping review of existing literature on utilizing AI algorithms for expert identification in medical domains. We systematically searched five platforms using a customized search string, and 21 studies were identified through other sources. The search spanned studies up to 2023, and study eligibility and selection adhered to the PRISMA 2020 statement. A total of 571 studies were assessed from the search. Out of these, we included six studies conducted between 2014 and 2020 that met our review criteria. Four studies used a machine learning algorithm as their model, while two utilized natural language processing. One study combined both approaches. All six studies demonstrated significant success in expert retrieval compared to baseline algorithms, as measured by various scoring metrics. AI enhances expert finding accuracy and effectiveness. However, more work is needed in intelligent medical expert retrieval. [ABSTRACT FROM AUTHOR]

This study aims to explore how artificial intelligence can help ease the burden on caregivers, filling a gap in current research and healthcare practices due to the growing challenge of an aging population and increased reliance on informal caregivers. We conducted a search with Google Scholar, PubMed, Scopus, IEEE Xplore, and Web of Science, focusing on AI and caregiving. Our inclusion criteria were studies where AI supports informal caregivers, excluding those solely for data collection. Adhering to PRISMA 2020 guidelines, we eliminated duplicates and screened for relevance. From 947 initially identified articles, 10 met our criteria, focusing on AI's role in aiding informal caregivers. These studies, conducted between 2012 and 2023, were globally distributed, with 80% employing machine learning. Validation methods varied, with Hold-Out being the most frequent. Metrics across studies revealed accuracies ranging from 71.60% to 99.33%. Specific methods, like SCUT in conjunction with NNs and LibSVM, showcased accuracy between 93.42% and 95.36% as well as F-measures spanning 93.30% to 95.41%. AUC values indicated model performance variability, ranging from 0.50 to 0.85 in select models. Our review highlights AI's role in aiding informal caregivers, showing promising results despite different approaches. AI tools provide smart, adaptive support, improving caregivers' effectiveness and well-being. [ABSTRACT FROM AUTHOR]

Background: Amelanotic melanoma is an extremely rare subtype of cutaneous melanoma. The tumor characteristics are still not well understood, especially for those located in the head and neck. Methods: Tumor characteristics of patients diagnosed with amelanotic melanoma of the head and neck (AMHN) from January 1, 2004, to December 31, 2015, were analyzed by querying the National Cancer Database. Characteristics of AMHN were subsequently compared with common malignant melanoma of the head and neck (CMMHN). Results: Three hundred and sixty‐eight patients were diagnosed with AMHN, and 69,267 were diagnosed with CMMHN. Of those with AMHN, 128 (34.8%) had melanoma located on the scalp and neck, and 172 (46.7%) were diagnosed with an early disease stage (i.e., 0, I, or II). When compared with CMMHN, patients with AMHN were more likely to be diagnosed after 80 years of age (25.3% vs. 18.2%; odds ratio [OR], 3.28; 95% CI, 1.09–9.84; P = 0.03), when Breslow depth was between 2.01 and 4.00 mm (28.5% vs. 6.5%; OR, 1.92; 95% CI, 1.15–3.19; P = 0.01), when ulceration was present (36.7% vs. 9.0%; OR, 1.99; 95% CI, 1.34–2.97; P = 0.001), and when mitotic count was 1 or more/mm2 (40.5% vs. 12.8%; OR; 2.53; 95% CI, 1.09–5.89; P = 0.03). No statistical difference was found for sex, specific location, stage, or lymph node involvement. Conclusion: Our study determined that AMHN is associated with older age, increased Breslow depth, presence of ulceration, and greater mitotic count when compared with CMMHN. [ABSTRACT FROM AUTHOR]

Background  Chronic tenosynovitis of the upper extremities caused by Mycobacterium kansasii (M. kansasii) is uncommon, but symptoms may overlap with other more common diseases. Late diagnosis and treatment can lead to disfiguration of structures and rupture of tendons, resulting in worse cosmetic outcomes after reconstruction. Methods  We present a clinical case and literature review of M. kansasii in patients with chronic tenosynovitis of upper extremities. PubMed was queried for cases of upper extremities tenosynovitis caused by M. kansasii. The keywords " M. kansasii ," "tenosynovitis" and synonyms were used for search in different combinations. Manuscripts, with no specific data or another condition, where the infection was not located in the upper extremities, were reviews, or not in English, were excluded from the study. Results  We described 23 reported cases of tenosynovitis of the upper extremity caused by M. kansasii. An immunosuppressed state was present in eight (34.8%) cases, and 12 (52.2%) patients received immunosuppressive treatment. A long-time period between the first appearance of symptoms and the definitive diagnosis was identified (median: 7 months, interquartile range: 9). The most frequent symptoms were local swelling (65.2%), pain (56.5%), mass effect (26%), and stiffness (13%). Tendon rupture was found in three (13%) patients as a complication of the disease. Moreover, seven (30.4%) patients underwent previous surgeries to try to relieve the symptoms before definitive diagnosis was achieved. Conclusion M. kansasii is an important differential causal pathogen for tenosynovitis of the upper extremities. Although rare, raising awareness about this infectious disease is imperative to avoid inadequate management and hazardous aesthetic sequelae. [ABSTRACT FROM AUTHOR]

Goals/Background. To evaluate children's growth in the first year of life, who have cleft palate and lip, without the use of palatal plates. Materials/Method. Chart review was conducted, retrospectively, in the Center for Integral Assistance of Cleft Lip and Palate (CAIF), in Brazil, between 2008 and 2009. Results for both genders were compared to the data published by the World Health Organization (WHO) regarding average weight gain in children during their first year of life. Results. Patients with syndromic diagnosis and with cleft classified as preforamen were excluded, resulting in a final number of 112 patients: 56 male and 56 female. Similar patterns were seen comparing the two genders. Although it was observed weight gain below the average until the 11th month in male patients and until 9 months in female patients, both genders remained at the 50th percentile (p50) and improved after the 4th month of age for boys and the 9th month of age for girls. Conclusion. Children with cleft palate weigh less than regular children during their first months of life. At the end of the first year, weight gain is similar comparing normal and affected children. However, factors that optimized weight gain included choosing the best treatment for each case, proper guidance, and multiprofessional integrated care. [ABSTRACT FROM AUTHOR]

In 1955, Millard developed the concept of rotation-advancement flap to treat cleft lip. Almost 6 decades later, it remains the most popular technique worldwide. Since the technique evolved and Millard published many technical variations, we decided to ask 10 experienced cleft surgeons how they would mark Millard's 7 points in two unilateral cleft lip patient photos and compared the results. In both pictures, points 1 and 2 were marked identically among surgeons. Points 3 were located adjacent to each other, but not coincident, and the largest distances between points 3 were 4.95mm and 4.03mm on pictures 1 and 2, respectively. Similar patterns were obtained for points 4, eight of them were adjacent, and the greatest distance between the points was 4.39 mm. Points 5 had the most divergence between the points among evaluators, which were responsible for the different shapes of the C-flap. Points 6 also had dissimilar markings, and such difference accounts for varying resection areas among evaluators. The largest distances observed were 11.66mm and 7mm on pictures 1 and 2, respectively. In summary, much has changed since Millard's initial procedure, but his basic principles have survived the inexorable test of time, proving that his idea has found place among the greatest concepts of modern plastic surgery. [ABSTRACT FROM AUTHOR]