Management of penetrating cardiac injury and tricuspid regurgitation with extracorporeal-membrane oxygenation (ECMO): a case report.

BACKGROUND: Gunshot wounds (GSW) to the heart are lethal, and most patients die before they arrive to the hospital. Survival decreases with number of cardiac chambers involved. We report a case of a 17-year-old male who survived a GSW injury involving two cardiac chambers with acute severe tricuspid regurgitation (TR) who subsequently developed cardiogenic shock requiring extracorporeal membrane oxygenation (ECMO) support. CASE PRESENTATION: A 17-year-old male sustained a single gunshot wound to the left chest, resulting in pericardial tamponade and right hemothorax. Emergency sternotomy revealed injury to the right ventricle and inferior cavoatrial junction with the adjacent pericardium contributing to a right hemothorax. The cardiac injuries were repaired primarily. Tricuspid regurgitation was confirmed immediately postoperatively. Five days after presentation, the patient developed cardiogenic shock secondary to TR requiring emergent stabilization with ECMO. He subsequently underwent successful tricuspid valve replacement. CONCLUSIONS: This is the first report to our knowledge of successful ECMO support of severe TR due to gunshot injury to the heart.

A machine learning framework for optimizing obesity care by simulating clinical trajectories and targeted interventions.

OBJECTIVE: This study aimed to determine the important clinical management bottlenecks that contribute to underuse of weight loss surgery (WLS) and assess risk factors for attrition at each of them. METHODS: A multistate conceptual model of progression from primary care to WLS was developed and used to study all adults who were seen by a primary care provider (PCP) and eligible for WLS from 2016 to 2017 at a large institution. Outcomes were progression from each state to each subsequent state in the model: PCP visit, endocrine weight management referral, endocrine weight management visit, WLS referral, WLS visit, and WLS. RESULTS: Beginning with an initial PCP visit, the respective 2-year Kaplan-Meier estimate for each outcome was 35% (n = 2063), 15.6% (n = 930), 6.3% (n = 400), 4.7% (n = 298), and 1.0% (n = 69) among 5876 eligible patients. Individual providers and clinics differed significantly in their referral practices. Female patients, younger patients, those with higher BMI, and those seen by trainees were more likely to progress. A simulated intervention to increase referrals among PCPs would generate about 49 additional WLS procedures over 3 years. CONCLUSIONS: This study discovered novel insights into the specific dynamics underlying low WLS use rates. This methodology permits in silico testing of interventions designed to optimize obesity care prior to implementation.

Defining Sepsis Phenotypes-Two Murine Models of Sepsis and Machine Learning.

INTRODUCTION: The immunobiology defining the clinically apparent differences in response to sepsis remains unclear. We hypothesize that in murine models of sepsis we can identify phenotypes of sepsis using non-invasive physiologic parameters (NIPP) early after infection to distinguish between different inflammatory states. METHODS: Two murine models of sepsis were used: gram-negative pneumonia (PNA) and cecal ligation and puncture (CLP). All mice were treated with broad spectrum antibiotics and fluid resuscitation. High-risk sepsis responders (pDie) were defined as those predicted to die within 72 h following infection. Low-risk responders (pLive) were expected to survive the initial 72 h of sepsis. Statistical modeling in R was used for statistical analysis and machine learning. RESULTS: NIPP obtained at 6 and 24 h after infection of 291 mice (85 PNA and 206 CLP) were used to define the sepsis phenotypes. Lasso regression for variable selection with 10-fold cross-validation was used to define the optimal shrinkage parameters. The variables selected to discriminate between phenotypes included 6-h temperature and 24-h pulse distention, heart rate (HR), and temperature. Applying the model to fit test data (n = 55), area under the curve (AUC) for the receiver operating characteristics (ROC) curve was 0.93. Subgroup analysis of 120 CLP mice revealed a HR of <620 bpm at 24 h as a univariate predictor of pDie. (AUC of ROC curve = 0.90). Subgroup analysis of PNA exposed mice (n = 121) did not reveal a single predictive variable highlighting the complex physiological alterations in response to sepsis. CONCLUSION: In murine models with various etiologies of sepsis, non-invasive vitals assessed just 6 and 24 h after infection can identify different sepsis phenotypes. Stratification by sepsis phenotypes can transform future studies investigating novel therapies for sepsis.

Volume of Pancreas-Adjacent Operations Favorably Influences Pancreaticoduodenectomy Outcomes at Lower Volume Pancreas Centers.

OBJECTIVE: This study assesses how the volume of pancreatic-adjacent operations (PAO) impacts the outcomes of pancreaticoduodenectomy (PD). SUMMARY BACKGROUND DATA: It is well-established that regionalization benefits outcomes after PD. However, due to a multitude of factors, including geographic, financial, and personal, not all patients receive their care at high-volume pancreas surgery centers. METHODS: The National Cancer Database was queried for pancreatic cancer patients who underwent PD. Hospital volume was calculated for PD and PAO (defined as gastric, hepatic, complex biliary, or pancreatic operations other than PD) and dichotomized as low- and high-volume centers based on the median. Three study cohorts were created: low-volume hospitals (LVH) for both PD and PAO, mixed-volume hospital (MVH) with low-volume PD but high-volume PAO, and high-volume PD hospital (HVH). RESULTS: In total, 24,572 patients were identified, with 41.5%, 7.2%, and 51.3% patients treated at LVH, MVH, and HVH, respectively. Thirty-day mortality for PD was 5.6% in LVH, 3.2% in MVH, and 2.5% in HVH. On multivariable analyses, LVH was predictive for higher 30-day mortality compared to HVH [odds ratio (OR) 2.068; 95% confidence interval (CI) 1.770-2.418; P< 0.0001]. However, patients at MVH demonstrated similar 30-day mortality to patients treated at HVH (OR 1.258; 95% CI 0.942-1.680; P = 0.1203). CONCLUSIONS: PD outcomes at low-volume centers that have experience with complex cancer operations near the pancreas are similar to PD outcomes at hospitals with high PD volume. MVH provides a model for PD outcomes to improve quality and access for patients who cannot, or choose not to, receive their care at high-volume centers.

Machine Learning Prediction of Liver Allograft Utilization From Deceased Organ Donors Using the National Donor Management Goals Registry.

Early prediction of whether a liver allograft will be utilized for transplantation may allow better resource deployment during donor management and improve organ allocation. The national donor management goals (DMG) registry contains critical care data collected during donor management. We developed a machine learning model to predict transplantation of a liver graft based on data from the DMG registry. METHODS: Several machine learning classifiers were trained to predict transplantation of a liver graft. We utilized 127 variables available in the DMG dataset. We included data from potential deceased organ donors between April 2012 and January 2019. The outcome was defined as liver recovery for transplantation in the operating room. The prediction was made based on data available 12-18 h after the time of authorization for transplantation. The data were randomly separated into training (60%), validation (20%), and test sets (20%). We compared the performance of our models to the Liver Discard Risk Index. RESULTS: Of 13 629 donors in the dataset, 9255 (68%) livers were recovered and transplanted, 1519 recovered but used for research or discarded, 2855 were not recovered. The optimized gradient boosting machine classifier achieved an area under the curve of the receiver operator characteristic of 0.84 on the test set, outperforming all other classifiers. CONCLUSIONS: This model predicts successful liver recovery for transplantation in the operating room, using data available early during donor management. It performs favorably when compared to existing models. It may provide real-time decision support during organ donor management and transplant logistics.

Development and validation of machine learning models to predict gastrointestinal leak and venous thromboembolism after weight loss surgery: an analysis of the MBSAQIP database.

BACKGROUND: Postoperative gastrointestinal leak and venous thromboembolism (VTE) are devastating complications of bariatric surgery. The performance of currently available predictive models for these complications remains wanting, while machine learning has shown promise to improve on traditional modeling approaches. The purpose of this study was to compare the ability of two machine learning strategies, artificial neural networks (ANNs), and gradient boosting machines (XGBs) to conventional models using logistic regression (LR) in predicting leak and VTE after bariatric surgery. METHODS: ANN, XGB, and LR prediction models for leak and VTE among adults undergoing initial elective weight loss surgery were trained and validated using preoperative data from 2015 to 2017 from Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program database. Data were randomly split into training, validation, and testing populations. Model performance was measured by the area under the receiver operating characteristic curve (AUC) on the testing data for each model. RESULTS: The study cohort contained 436,807 patients. The incidences of leak and VTE were 0.70% and 0.46%. ANN (AUC 0.75, 95% CI 0.73-0.78) was the best-performing model for predicting leak, followed by XGB (AUC 0.70, 95% CI 0.68-0.72) and then LR (AUC 0.63, 95% CI 0.61-0.65, p < 0.001 for all comparisons). In detecting VTE, ANN, and XGB, LR achieved similar AUCs of 0.65 (95% CI 0.63-0.68), 0.67 (95% CI 0.64-0.70), and 0.64 (95% CI 0.61-0.66), respectively; the performance difference between XGB and LR was statistically significant (p = 0.001). CONCLUSIONS: ANN and XGB outperformed traditional LR in predicting leak. These results suggest that ML has the potential to improve risk stratification for bariatric surgery, especially as techniques to extract more granular data from medical records improve. Further studies investigating the merits of machine learning to improve patient selection and risk management in bariatric surgery are warranted.

Cost effectiveness of a novel device for improving resuscitation of apneic newborns.

BACKGROUND: Intrapartum-related hypoxic events are a major cause of morbidity and mortality in low resource countries. Neonates who receive proper resuscitation may go on to live otherwise healthy lives. However, even when a birth attendant is present, these babies frequently receive suboptimal ventilation with poor outcomes. The Augmented Infant Resuscitator (AIR) is a low-cost, reusable device designed to provide birth attendants real-time objective feedback on measures of ventilation quality during resuscitations and is intended for use in training and at the point of care. The goal of our study was to determine the impact and cost-effectiveness of AIR deployment in conjunction with existing resuscitation training programs in low resource settings. METHODS: We developed a simulation model of the natural history of intrapartum-related neonatal hypoxia and resuscitation deriving parameters from published literature and model calibration. Simulations estimated the number of disability-adjusted life years (DALYs) averted with use of the AIR by birth attendants if deployed at the point of care. Potential decreases in neonatal mortality and long-term subsequent morbidity from disability were modeled over a lifetime horizon. The primary outcome for the analysis was the cost per DALY averted. Model parameters were specific to the Mbeya region of Tanzania. RESULTS: Implementation of the AIR strategy resulted in an additional cost of $24.44 (4.80, 73.62) per DALY averted on top of the cost of existing, validated resuscitation programs. Per hospital, this adds an extra $656 to initial training costs and averts approximately 26.84 years of disability in the cohort of children born in the first year, when projected over a lifetime. The findings were robust to sensitivity analyses. Total roll-out costs for AIR are estimated at $422,688 for the Mbeya region, averting approximately 9018 DALYs on top of existing resuscitation programs, which are estimated to cost $202,240 without AIR. CONCLUSION: Our modeling analysis finds that use of the AIR device may be both an effective and cost-effective tool when used as a supplement to existing resuscitation training programs. Implementation of this strategy in multiple settings will provide data to improve our model parameters and potentially confirm our findings.

Surgical management of obesity.

Weight loss surgery is the most effective intervention for addressing obesity and related metabolic disorders such as diabetes. We describe common surgical procedures as well as emerging and investigational procedures in terms of their capacity to induce weight reduction and their risk profiles. We then discuss the impact of weight loss surgery on important obesity related disorders including diabetes, cardiovascular disease, and non-alcoholic fatty liver disease. The question of operative choice is discussed with respect to benefits and risks of common procedures. Reoperative weight loss surgery, an increasingly common element of weight loss surgical practice, is reviewed. We briefly discuss the metabolic mechanism of action of weight loss surgery. Lack of access to and under-utilization of weight loss surgery represent important challenges to adequate obesity treatment, and we review these topics as well.

Measuring Medical Students' Preparedness and Skills to Provide Cross-Cultural Care.

Purpose: Cross-cultural education is an integral and required part of undergraduate medical curricula. However, the teaching of cross-cultural care varies widely and methods of evaluation are lacking. We sought to better understand medical students' perspectives on their own cultural competency across the 4-year curriculum using a validated survey instrument. Methods:We conducted an annual Internet-based survey at Harvard Medical School with students in all 4 years of training, for four consecutive years. We used a tool previously validated with residents and slightly modified it for medical students, assessing their (1) preparedness, (2) skillfulness, and (3) perspectives on the educational curriculum and learning climate. Results: Of 2592 possible survey responses, we received 1561 (60% response rate). Fourth-year students had significantly higher scores than first-year students (p<0.001) for all but one preparedness item (caring for transgender patients) and all but one skillfulness item (identifying ability to read/write English). Less than 50% of students felt adequately prepared/skilled by their fourth year on 8 of 11 preparedness items and 5 of 10 skillfulness items. Lack of practical experience caring for diverse patients was the most frequently cited challenge. Conclusions: While students reported that preparedness and skillfulness to care for culturally diverse patients seem to increase with training, fourth-year students still felt inadequately prepared and skilled in many important aspects of cross-cultural care. Medical schools can use this tool with students to self-assess cultural competency and to help guide enhancements to their curricula focusing on cross-cultural care.

Cost-effectiveness of Bariatric Surgery in Adolescents With Obesity.

Importance: Severe obesity affects 4% to 6% of US youth and is increasing in prevalence. Bariatric surgery for the treatment of adolescents with severe obesity is becoming more common, but data on cost-effectiveness are limited. Objective: To assess the cost-effectiveness of bariatric surgery for adolescents with obesity using recently published results from the Teen-Longitudinal Assessment of Bariatric Surgery study. Design, Setting, and Patients: A state-transition model was constructed to compare 2 strategies: no surgery and bariatric surgery. In the no surgery strategy, patients remained at their initial body mass index (calculated as weight in kilograms divided by height in meters squared) over time. In the bariatric surgery strategy, patients were subjected to risks of perioperative mortality and complications as well as initial morbidity but also experienced longer-term quality-of-life improvements associated with weight loss. Cohort demographic information-of the 228 patients included, the mean (SD) age was 17 (1.6) years, the mean (range) body mass index was 53 (34-88), and 171 (75.0%) were female-surgery-related outcomes, and base case time horizon (3 years) were based on data from the Teen-Longitudinal Assessment of Bariatric Surgery study. One-way and probabilistic sensitivity analyses were performed. Main Outcomes and Measures: Quality-adjusted life-years (QALYs), total costs (in US dollars adjusted to 2015-year values using the Consumer Price Index), and incremental cost-effectiveness ratios (ICERs). A willingness-to-pay threshold of $100 000 per QALY was used to assess cost-effectiveness. Results: After 3 years, surgery led to a gain of 0.199 QALYs compared with no surgery at an incremental cost of $30 747, yielding an unfavorable ICER of $154 684 per QALY. When the clinical study results were extrapolated to 4 years, the ICER decreased to $114 078 per QALY and became cost-effective by 5 years with an ICER of $91 032 per QALY. Outcomes were robust in most 1-way and probabilistic sensitivity analyses. Conclusions and Relevance: Bariatric surgery incurs substantial initial cost and morbidity. We found that surgery could be a cost-effective treatment for adolescents with severe obesity if assessed over a time horizon of 5 years. Our study underscores the need for long-term clinical trials in adolescents with at least 5 years of follow-up data that capture financial and quality-of-life end points.