David W. Grant

Long-Term Outcomes of Rectosigmoid Neocolporrhaphy in Male-to-Female Gender Reassignment Surgery.

Background: Favorable outcomes of rectosigmoid neocolporrhaphy have previously been reported. Unfortunately, rectosigmoid transfers are still perceived negatively, usually relegated to secondary vaginoplasties. This study aims to provide an objective investigation into the safety and efficacy of rectosigmoid neocolporrhaphy for vaginoplasty in male-to-female transsexual patients. Methods: A retrospective review was performed on male-to-female patients who had undergone rectosigmoid neocolporrhaphy performed by the senior author. Patient data including demographics, medical history, complications, and the need for revision surgery were obtained. Direct inquires were conducted to determine patients’ level of satisfaction with appearance, sexual function, and ease of postoperative recovery. Results: Eighty-three patients were included over the course of 22 years, with an average clinical follow-up of 2.2 years (83 patients) and phone interview follow-up of 23 years (21 patients). Overall, the patients were healthy, with minimal comorbidities. Forty-eight patients (58 percent) had complications, but the majority (83.3 percent) were minor and consisted mainly of introital stricture or excessive protrusion of the corpus spongiosum. Smoking was associated with higher complication rates (p = 0.05), especially stricture formation. Excessive mucorrhea occurred in 28.6 percent but resolved after the first year. Overall patient satisfaction with appearance and sexual function was high. Conclusions: This study is one of the largest and longest reported series of rectosigmoid transfers for vaginoplasty in transsexual patients. Rectosigmoid neocolporrhaphies have many times been recommended for secondary or revision surgery when other techniques, such as penile inversion, have failed. However, the authors believe the rectosigmoid transfer is safe and efficacious, and it should be offered to male-to-female patients for primary vaginoplasty. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, IV.

Educational Exposure to Transgender Patient Care in Plastic Surgery Training.

Background: Gender dysphoria is estimated to occur in up to 0.9 percent of the U.S. population. With increasing awareness and decreasing stigma surrounding transgender issues, it is predicted that more patients will begin to seek medical and surgical transition. This study aims to determine the current state of transgender-related education in U.S. plastic surgery residency programs and to evaluate trainee perceptions regarding the importance of such training. Methods: Plastic surgery trainees from a representative sample of 21 U.S. training programs were asked to complete a cross-sectional eight-question survey between November of 2015 and January of 2016. Respondents were queried regarding demographics, transgender curricular exposure (didactic versus clinical), and perceived importance of training opportunities in transgender patient care. Results: A total of 322 residents or fellows responded to the survey (80 percent response rate) from four U.S. Census regions. Sixty-four percent of respondents had education on or direct exposure to transgender patient care during residency. Among those with experiences in gender-confirming surgery, more than half were exposed to chest and genital surgery. Overall, the majority of respondents believed that training in gender-confirming surgery is important, and 72 percent endorsed the necessity for gender-confirming surgery fellowship training opportunities. Conclusions: A significant number of plastic surgery trainees are exposed to transgender patient care, although exposure type is variable. The majority of trainees endorsed the importance of residency and fellowship training in gender-confirming surgery. To better serve the transgender population, formal fellowship training in gender-confirming surgery should be offered.

Race and Breast Cancer Reconstruction: Is There a Health Care Disparity?

Background: Racial disparity continues to be a well-documented problem afflicting contemporary health care. Because the breast is a symbol of femininity, breast reconstruction is critical to mitigating the psychosocial stigma of a breast cancer diagnosis. Whether different races have equitable access to breast reconstruction remains unknown. Methods: Two thousand five hundred thirty-three women underwent first-time autologous versus implant-based reconstruction following mastectomy. Information regarding age, smoking, diabetes, obesity, provider, race, pathologic stage, health insurance type, charge to insurance, and socioeconomic status was recorded. Established statistics compared group medians and proportions. A backward-stepwise multivariate logistic regression model identified independent predictors of breast reconstruction type. Results: Compared with whites, African Americans were more likely to be underinsured (p < 0.01), face a lesser charge for reconstruction (p < 0.01), smoke (p < 0.01), have diabetes (p < 0.01), suffer from obesity (p < 0.01), live in a zip code with a lower median household income (p < 0.01), and undergo autologous-based reconstruction (p = 0.01). On multivariate analysis, only African American race (OR, 2.23; p < 0.01), charge to insurance (OR, 1.00; p < 0.01), and provider (OR, 0.96; p < 0.01) independently predicted type of breast reconstruction, whereas age (OR, 1.02; p = 0.06) and diabetes (OR, 0.48; p = 0.08) did not. Conclusions: African American race remains the most clinically significant predictor of autologous breast reconstruction, even after controlling for age, obesity, pathologic stage, health insurance type, charge to patient, socioeconomic status, smoking, and diabetes. Future research may address whether this disparity stems from patient preferences or more profound sociocultural and economic forces, including discrimination. CLINICAL QUESTION/LEVEL OF EVIDENCE: Risk, III.

Penile Replantation: A Retrospective Analysis of Outcomes and Complications

Purpose Penile replantation is an uncommonly performed procedure, which can alleviate physical and psychosocial sequelae of penile amputation. This study critically appraises the current literature on penile replantation. Methods A comprehensive literature search of the Medline, PubMed, and Google Scholar databases was conducted with multiple search terms related to penile replantation. Data on outcomes, complications, and patient satisfaction were collected. Results A total of 74 articles met inclusion criteria. One hundred and six patients underwent penile replantation, but outcome, complication, and satisfaction data were not standardized across all patients. Penile amputation most often resulted from self‐mutilation or trauma. The majority were complete amputations (74.8%). Full sensation was maintained in 68.4% of patients. Most reported adequate urinary function (97.4%) and normal erection (77.5%). Skin necrosis (54.8%) and venous congestion (20.2%) were the most common complications. Urethral stricture (11.0%) and fistula (6.6%) were common urethral complications. Most (91.6%) patients reported overall satisfaction although there was a lack of patient‐reported outcomes. Multivariate analysis suggested that complete amputation (&bgr; = 3.15, 95% CI 0.41‐5.89, p = 0.024), anastomosis of the superficial dorsal artery (&bgr; = 9.88, 95% CI 0.74‐19.02, p = 0.034), and increasing number of nerves coapted (&bgr; = 1.75, 95% CI 0.11‐3.38, p = 0.036) were associated with favorable sexual, urinary, and sensation outcomes. Increasing number of vessels anastomosed (&bgr; = ‐3.74, 95% CI ‐7.15 to ‐0.32, p = 0.032) was associated with unfavorable outcomes. Conclusion Although penile replantation is associated with complications, it has a high rate of satisfaction and efficacy. Coaptation of multiple nerves and anastomosis of the superficial dorsal artery should be completed.

The Impact of Race on Choice of Post-Mastectomy Reconstruction: Is There a Healthcare Disparity?

Disclosure: No author has a financial interest in any product, device, or drug mentioned in this manuscript. A preliminary portion of this research was presented at MAPS, Chicago, 2015. An abstract published in The Annals of Plastic Surgery, June 2015, ‘Post-operative Drain Time Analysis, Outcomes and Complication Rates in Patients Receiving “Meshed” Versus “Un-Meshed” Acellular Dermal Matrix (ADM) in Partial SubMuscular Breast Reconstruction’.

Comparing deep learning and concept extraction based methods for patient phenotyping from clinical narratives

In secondary analysis of electronic health records, a crucial task consists in correctly identifying the patient cohort under investigation. In many cases, the most valuable and relevant information for an accurate classification of medical conditions exist only in clinical narratives. Therefore, it is necessary to use natural language processing (NLP) techniques to extract and evaluate these narratives. The most commonly used approach to this problem relies on extracting a number of clinician-defined medical concepts from text and using machine learning techniques to identify whether a particular patient has a certain condition. However, recent advances in deep learning and NLP enable models to learn a rich representation of (medical) language. Convolutional neural networks (CNN) for text classification can augment the existing techniques by leveraging the representation of language to learn which phrases in a text are relevant for a given medical condition. In this work, we compare concept extraction based methods with CNNs and other commonly used models in NLP in ten phenotyping tasks using 1,610 discharge summaries from the MIMIC-III database. We show that CNNs outperform concept extraction based methods in almost all of the tasks, with an improvement in F1-score of up to 26 and up to 7 percentage points in area under the ROC curve (AUC). We additionally assess the interpretability of both approaches by presenting and evaluating methods that calculate and extract the most salient phrases for a prediction. The results indicate that CNNs are a valid alternative to existing approaches in patient phenotyping and cohort identification, and should be further investigated. Moreover, the deep learning approach presented in this paper can be used to assist clinicians during chart review or support the extraction of billing codes from text by identifying and highlighting relevant phrases for various medical conditions.

Behind the Scenes: A Medical Natural Language Processing Project

Advancement of Artificial Intelligence (AI) capabilities in medicine can help address many pressing problems in healthcare. However, AI research endeavors in healthcare may not be clinically relevant, may have unrealistic expectations, or may not be explicit enough about their limitations. A diverse and well-functioning multidisciplinary team (MDT) can help identify appropriate and achievable AI research agendas in healthcare, and advance medical AI technologies by developing AI algorithms as well as addressing the shortage of appropriately labeled datasets for machine learning. In this paper, our team of engineers, clinicians and machine learning experts share their experience and lessons learned from their two-year-long collaboration on a natural language processing (NLP) research project. We highlight specific challenges encountered in cross-disciplinary teamwork, dataset creation for NLP research, and expectation setting for current medical AI technologies.