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Background Central airway occlusion is a feared complication of general anesthesia in patients with mediastinal masses. Maintenance of spontaneous ventilation and avoiding neuromuscular blockade are recommended to reduce this risk. Physiologic arguments supporting these recommendations are controversial and direct evidence is lacking. The authors hypothesized that, in adult patients with moderate to severe mediastinal mass–mediated tracheobronchial compression, anesthetic interventions including positive pressure ventilation and neuromuscular blockade could be instituted without compromising central airway patency. Methods Seventeen adult patients with large mediastinal masses requiring general anesthesia underwent awake intubation followed by continuous video bronchoscopy recordings of the compromised portion of the airway during staged induction. Assessments of changes in anterior–posterior airway diameter relative to baseline (awake, spontaneous ventilation) were performed using the following patency scores: unchanged = 0; 25 to 50% larger = +1; more than 50% larger = +2; 25 to 50% smaller = −1; more than 50% smaller = −2. Assessments were made by seven experienced bronchoscopists in side-by-side blinded and scrambled comparisons between (1) baseline awake, spontaneous breathing; (2) anesthetized with spontaneous ventilation; (3) anesthetized with positive pressure ventilation; and (4) anesthetized with positive pressure ventilation and neuromuscular blockade. Tidal volumes, respiratory rate, and inspiratory/expiratory ratio were similar between phases. Results No significant change from baseline was observed in the mean airway patency scores after the induction of general anesthesia (0 [95% CI, 0 to 0]; P = 0.953). The mean airway patency score increased with the addition of positive pressure ventilation (0 [95% CI, 0 to 1]; P = 0.024) and neuromuscular blockade (1 [95% CI, 0 to 1]; P < 0.001). No patient suffered airway collapse or difficult ventilation during any anesthetic phase. Conclusions These observations suggest a need to reassess prevailing assumptions regarding positive pressure ventilation and/or paralysis and mediastinal mass–mediated airway collapse, but do not prove that conventional (nonstaged) inductions are safe for such patients. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

BACKGROUND AND PURPOSE The Medicare Value-Based Purchasing (VBP) program established performance-based financial incentives for hospitals. We hypothesized that total performance scores (TPS) would vary by hospital type. METHODS Value-Based Purchasing reports were collected from 2015 to 2017 and merged with the Centers for Medicare and Medicaid Services (CMS) Impact File data. A total of 3,005 hospitals were grouped into physician-owned surgical hospitals (POSH), accountable care organizations (ACO), Kaiser, Vizient, and General hospitals. Longitudinal linear mixed-effects models compared temporal differences of TPS and secondary composite outcome, process, patient satisfaction, safety, and cost efficiency measures between hospital types. RESULTS Total performance scores decreased across all hospital types (p < .001). Physician-owned surgical hospitals had the highest TPS (59.9), followed by Kaiser (49.2), ACO (36.7), General (34.8), and Vizient (30.7) (p < .001). Hospital types differed significantly in size, geography, mean case-mix index, Medicare patient discharges, percent Medicare days to inpatient days, Disproportionate Share Hospital payments, and uncompensated care per claim. Scores improved in 84% of POSH and 14.6% of Kaiser hospitals using score reallocations. CONCLUSION In comparison with General hospitals, the TPS was higher for POSH and Kaiser and lower for Vizient in part due to weighting reallocation and individual domain scores. IMPLICATIONS Centers for Medicare and Medicaid Services scoring system changes have not addressed the methodological biases favoring certain hospital types.

Objective: Automated driving systems (ADS) are actively being deployed within the driving fleet. ADS are designed to safely navigate roadways, which entails an expectation of encountering varying degrees of potential conflict with other road users. The ADS design and evaluation process benefits from estimating injury severity probabilities for collisions that may occur. Current regression models in the literature are typically bespoke analyses involving targeted principal directions of force (PDOFs) and occupant positions. It is preferable to rely on injury severity models derived from a single source to provide a continuous function of risk for all planar collisions, while also accounting for specific vehicle and occupant characteristics. The novel feature of the proposed models is continuous, parametric injury risk surfaces that encompass the full spectrum of available United States field data. Methods: We used years 2001���2015 of the National Automotive Sampling System, Crashworthiness Data System (NASS-CDS) and years 2017���2019 of the Crash Investigation Sampling System (CISS) to estimate injury risk at the maximum abbreviated injury scale (MAIS) 3 and higher (3+) and 5 and higher (5+) levels for all adult occupants traveling in 2002 or newer passenger vehicles which were less than 10 years old at the time of the crash. The models account for occupant, vehicle, and crash characteristics. Interactions with vulnerable road users (e.g., pedestrian, bicyclist) were not considered. Results: We present statistical models suitable to predict injury in all non-rollover crashes at the maximum MAIS3+ and 5+ levels, and show that these models can be comparable to similar single scenario (e.g., frontal) crash models. We discuss challenges with imputing missing field data, and discuss handling of covariates that may not be known at the time of the crash. Conclusions: Collision severity assessment is a vital component of the ADS design process. We developed a novel injury risk function that can assess occupant injury risks across the spectrum of foreseeable planar collisions. These models can provide insight on potential outcomes of counterfactual simulations, injury risk and crashworthiness considerations for human driven vehicles, and provide an evaluation tool that can be applied in ADS safety impact evaluation.

While errors can harm patients they remain poorly studied. This study characterized errors in the care of surgical patients and examined the association of errors with morbidity and mortality.Errors have been reported to cause10% or60% of adverse events. Such discordant results underscore the need for further exploration of the relationship between error and adverse events.Patients with operations performed at a single institution and abstracted into the American College of Surgeons National Surgical Quality Improvement Program from January 1, 2018, to December 31, 2018 were examined. This matched case control study comprised cases who experienced a postoperative morbidity or mortality. Controls included patients without morbidity or mortality, matched 2:1 using age (±10 years), sex, and Current Procedural Terminology (CPT) group. Two faculty surgeons independently reviewed records for each case and control patient to identify diagnostic, technical, judgment, medication, system, or omission errors. A conditional multivariable logistic regression model examined the association between error and morbidity.Of 1899 patients, 170 were defined as cases who experienced a morbidity or mortality. The majority of cases (n=93; 55%) had at least 1 error; of the 329 matched control patients, 112 had at least 1 error (34%). Technical errors occurred most often among both cases (40%) and controls (23%). Logistic regression demonstrated a strong independent relationship between error and morbidity (odds ratio=2.67, 95% confidence interval: 1.64-4.35, P0.001).Errors in surgical care were associated with postoperative morbidity. Reducing errors requires measurement of errors.

BackgroundCurrent EMS stroke screening tools facilitate early detection and triage, but the tools' accuracy and reliability are limited and highly variable. An automated stroke screening tool could improve stroke outcomes by facilitating more accurate prehospital diagnosis and delivery. We hypothesize that a machine learning algorithm using video analysis can detect common signs of stroke. As a proof-of-concept study, we trained a computer algorithm to detect presence and laterality of facial weakness in publically available videos with comparable accuracy, sensitivity, and specificity to paramedics.Methods and ResultsWe curated videos of people with unilateral facial weakness (n = 93) and with a normal smile (n = 96) from publicly available web-based sources. Three board certified vascular neurologists categorized the videos according to the presence or absence of weakness and laterality. Three paramedics independently analyzed each video with a mean accuracy, sensitivity and specificity of 92.6% [95% CI 90.1–94.7%], 87.8% [95% CI 83.9–91.7%] and 99.3% [95% CI 98.2–100%]. Using a 5-fold cross validation scheme, we trained a computer vision algorithm to analyze the same videos producing an accuracy, sensitivity and specificity of 88.9% [95% CI 83.5–93%], 90.3% [95% CI 82.4–95.5%] and 87.5 [95% CI 79.2–93.4%].ConclusionsThese preliminary results suggest that a machine learning algorithm using computer vision analysis can detect unilateral facial weakness in pre-recorded videos with an accuracy and sensitivity comparable to trained paramedics. Further research is warranted to pursue the concept of augmented facial weakness detection and external validation of this algorithm in independent data sets and prospective patient encounters.

BACKGROUND Readmissions are costly and inconvenient for patients, and occur frequently in hepatopancreatobiliary (HPB) surgery practice. Readmission prediction tools exist, but most have not been designed or tested in the HPB patient population. METHODS Pancreatectomy and hepatectomy operation-specific readmission models defined as subspecialty readmission risk assessments (SRRA) were developed using clinically relevant data from merged 2014-15 ACS NSQIP Participant Use Data Files and Procedure Targeted datasets. The two derived procedure-specific models were tested along with 6 other readmission models in institutional validation cohorts in patients who had pancreatectomy or hepatectomy, respectively, between 2013 and 2017. Models were compared using area under the receiver operating characteristic curves (AUC). RESULTS A total of 16,884 patients (9169 pancreatectomy and 7715 hepatectomy) were included in the derivation models. A total of 665 patients (383 pancreatectomy and 282 hepatectomy) were included in the validation models. Specialty-specific readmission models outperformed general models. AUC characteristics of the derived pancreatectomy and hepatectomy SRRA (pancreatectomy AUC=0.66, hepatectomy AUC=0.74), modified Readmission After Pancreatectomy (AUC=0.76), and modified Readmission Risk Score for hepatectomy (AUC=0.78) outperformed general models for readmission risk: LOS/2 + ASA integer-based score (pancreatectomy AUC=0.58, hepatectomy AUC=0.66), LACE Index (pancreatectomy AUC=0.54, hepatectomy AUC=0.62), Unplanned Readmission Nomogram (pancreatectomy AUC=0.52, hepatectomy AUC=0.55), and institutional ARIA (pancreatectomy AUC=0.46, hepatectomy AUC=0.58). CONCLUSION HPB readmission risk models using 30-day subspecialty-specific data outperform general readmission risk tools. Hospitals and practices aiming to decrease readmissions in HPB surgery patient populations should use specialty-specific readmission reduction strategies.

Objective: Medicare beneficiaries are eligible to receive free Annual Wellness Visits (AWVs) for assessing preventive care needs, identifying care resources, and scheduling visits. We previously reported that AWVs are associated with increased use of preventive care for patients with diabetes. In this study, our objective is to conduct a case-control study to examine whether AWVs are associated more strongly with preventive care use in the Diabetes Belt than in surrounding areas. Methods: We used a sample of ∼900,000 Medicare Fee-for-Service beneficiaries who lived in the Diabetes Belt and surrounding areas in 2014 - 2015. We identified patients who have used an annual foot exam, eye exam, A1c test, and microalbuminuria (MA) test and those who did not in 2015. We used the dates of service receipt and the last day of the year (12/31) as the event date for users and non-users, respectively. We looked one full year before the event date to identify any AWVs. We used propensity-score stratification to estimate log odds of 4 preventive care use of annual foot exam, eye exam, A1c test, and MA test. Results: For all four services, AWV users had significantly higher preventive care use compared to non-users. In 3 preventive services, AWVs were more strongly associated with preventive care use in the Belt than in the surrounding areas (foot exam, ORs = 2.38 vs 2.16, p < 0.001; A1c test, ORs = 1.44 vs. 1.36, p = 0.002; MA test, ORs = 1.70 vs. 1.44, p < 0.001; eye exam, ORs 1.22 vs. 1.19, p=0.063) . Discussion: AWVs appear to have stronger effects on preventive care use for patients with diabetes in the more healthcare resource-poor Diabetes Belt than in the surrounding areas. AWVs may help to reduce disparities in the use of recommended preventive care for patients with diabetes. Disclosure M.Sohn: None. T.L.Mcmurry: None. H.Kang: None. S.Kim: None. J.M.Lobo: n/a. Funding NIDDK R01DK113295

BACKGROUND. The US military has historically higher tobacco use compared to civilians, and tobacco use increases following enlistment. While the military is vulnerable to tobacco use, current surveillance of tobacco among this high-risk population is lacking. METHODS. Recently enlisted Airmen (N= 43,597) between 2013 and 2018 were asked about tobacco use prior to enlistment across nine products: (1) cigarettes/ roll your own tobacco, (2) smokeless tobacco/ snus, (3) cigars, cigarillos/little cigars, (4) hookah/ pipe, and (5) e-cigarettes. RESULTS. Hookah/pipe use, cigarettes/roll your own, smokeless tobacco/snus, and cigars/little cigars/cigarillos use decreased significantly between 2013 to 2018, which the prevalence of e-cigarette use increased (p’s

Our objective was to examine the associations between early discharge and readmission after major abdominal operations.Advances in patient care resulted in earlier patient discharge after complex abdominal operations. Whether early discharge is associated with patient readmissions remains controversial.Patients who had colorectal, liver, and pancreas operations abstracted in 2011-2017 American College of Surgeons National Surgical Quality Improvement Program Participant Use Data Files were included. Patient readmission was stratified by 6 operative groups. Patients who were discharged before median discharge date within each operative group were categorized as an early discharge. Analyses tested associations between early discharge and likelihood of 30-day postoperative unplanned readmission.A total of 364,609 patients with major abdominal operations were included. Individual patient groups and corresponding median day of discharge were: laparoscopic colectomy (n = 152,575; median = 4), open colectomy (n =137,462; median = 7), laparoscopic proctectomy (n = 12,238; median = 5), open proctectomy (n = 24,925; median = 6), major hepatectomy (n = 9,805; median = 6), pancreatoduodenectomy (n = 27,604; median = 8). Early discharge was not associated with an increase in proportion of readmissions in any operative group. Early discharge was associated with a decrease in average proportion of patient readmissions compared to patients discharged on median date in each of the operative groups: laparoscopic colectomy 6% versus 8%, open colectomy 11% versus 14%, laparoscopic proctectomy 13% versus 16%, open proctectomy 13% vs 17%, major hepatectomy 8% versus 12%, pancreatoduodenectomy 16% versus 20% (all P ≤ 0.02). Serious morbidity composite was significantly lower in patients who were discharged early than those who were not in each operative group (all P0.001).Early discharge in selected patients after major abdominal operations is associated with lower, and not higher, rate of 30-day unplanned readmission.

Background Shigella is a leading cause of childhood diarrhea and target for vaccine development. Microbiologic and clinical case definitions are needed for pediatric field vaccine efficacy trials. Methods We compared characteristics of moderate to severe diarrhea (MSD) cases in the Global Enteric Multicenter Study (GEMS) between children with culture positive Shigella to those with culture-negative, quantitative polymerase chain reaction (qPCR)-attributable Shigella (defined by an ipaH gene cycle threshold, Molecular methods identified Shigella more commonly than microbiologic culture in younger and stunted children. A simplified clinical score containing dehydration, hospitalization, and diarrhea duration could be used to stratify vaccine trial endpoints by severity based on its ability to predict death.

Background Prolonged enteropathogen shedding after diarrhea complicates the identification of etiology in subsequent episodes and is an important driver of pathogen transmission. A standardized approach has not been applied to estimate the duration of shedding for a wide range of pathogens. Methods We used a multisite birth cohort of children 0–24 months of age from whom diarrheal and monthly nondiarrheal stools were previously tested by quantitative polymerase chain reaction for 29 enteropathogens. We modeled the probability of detection of the etiologic pathogen before and after diarrhea using a log-normal accelerated failure time survival model and estimated the median duration of pathogen carriage as well as differences in subclinical pathogen carriage 60 days after diarrhea onset in comparison to a prediarrhea baseline. Results We analyzed 3247 etiologic episodes of diarrhea for the 9 pathogens with the highest attributable burdens of diarrhea. The median duration of postdiarrheal carriage varied widely by pathogen, from about 1 week for rotavirus (median, 8.1 days [95% confidence interval {CI}, 6.2–9.6]) to >1 month for Cryptosporidium (39.5 days [95% CI, 30.6–49.0]). The largest increases in subclinical pathogen carriage before and after diarrhea were seen for Cryptosporidium (prevalence difference between 30 days prior and 60 days after diarrhea onset, 0.30 [95% CI, .23–.39]) and Shigella (prevalence difference, 0.21 [95% CI, .16–.27]). Conclusions Postdiarrheal shedding was widely variable between pathogens, with strikingly prolonged shedding seen for Cryptosporidium and Shigella. Targeted antimicrobial therapy and vaccination for these pathogens may have a relatively large impact on transmission., In a multisite birth cohort study of children 0–24 months of age and with quantitative polymerase chain reaction detection of diarrheal pathogens, we estimate the duration of postdiarrheal carriage in low-resource settings, with strikingly prolonged shedding seen for Cryptosporidium and Shigella.

The Wold decomposition gives a moving average (MA) representation of a purely non‐deterministic stationary process. In this article, we derive estimates of the Wold matrices for a d‐dimensional process by using a Cholesky decomposition of a banded and tapered version of the sample autocovariance matrix, and we derive convergence rates for the estimation error of the (possibly infinite) sequence of Wold matrices. By analogy to lag‐window estimates of the spectral density, this method can be used to obtain finite vector MA models with an adaptive lag‐order. We additionally show how these results can be applied to impulse response analysis and to derive a bootstrap procedure. Our theoretical results are complemented by simulations which investigate the finite sample performance of the estimator.

The relationship between laboratory and on-field performance of football helmets was assessed for 31 football helmet models selected from those worn by players in the 2015–2019 National Football League (NFL) seasons. Linear impactor tests were conducted with helmets placed on an instrumented Hybrid III head and neck assembly mounted on a sliding table. Based on impacts to each helmet at six impact locations and three velocities, a helmet performance score (HPS) was calculated using a linear combination of the head injury criterion (HIC) and the diffuse axonal multi-axis general evaluation (DAMAGE). To determine the on-field performance of helmets, helmet model usage, player participation, and incident concussion data were collected from the five NFL seasons and used to calculate helmet model-specific concussion rates. Comparison of laboratory HPS to the helmet model-specific concussion rates on a per play basis showed a positive correlation (r2 = 0.61, p

OBJECTIVE To examine trends in uninsured rates between 2012 and 2016 among low-income adults aged RESEARCH DESIGN AND METHODS Data for 3,129 U.S. counties, obtained from the Small Area Health Insurance Estimates and Area Health Resources Files, were used to analyze trends in uninsured rates among populations with a household income ≤138% of the federal poverty level. Multivariable analysis adjusted for the percentage of county populations aged 50–64 years, the percentage of women, Distressed Communities Index value, and rurality. RESULTS In 2012, 39% of the population in the Diabetes Belt and 34% in non-Belt counties were uninsured (P < 0.001). In 2016 in states where Medicaid was expanded, uninsured rates declined rapidly to 13% in Diabetes Belt counties and to 15% in non-Belt counties. Adjusting for county demographic and economic factors, Medicaid expansion helped reduce uninsured rates by 12.3% in Diabetes Belt counties and by 4.9% in non-Belt counties. In 2016, uninsured rates were 15% higher for both Diabetes Belt and non-Belt counties in the nonexpansion states than in the expansion states. CONCLUSIONS ACA-driven Medicaid expansion was more significantly associated with reduced uninsured rates in Diabetes Belt than in non-Belt counties. Initial disparities in uninsured rates between Diabetes Belt and non-Belt counties have not existed since 2014 among expansion states. Future studies should examine whether and how Medicaid expansion may have contributed to an increase in the use of health services in order to prevent and treat diabetes in the Diabetes Belt.

Many modern experiments, such as microarray gene expression and genome-wide association studies, present the problem of estimating a large number of parallel effects. Bayesian inference is a popular approach for analyzing such data by modeling the large number of unknown parameters as random effects from a common prior distribution. However, misspecification of the prior distribution can lead to erroneous estimates of the random effects, especially for the largest and most interesting effects. This paper has two aims. First, we propose a robustified posterior distribution for a parametric Bayesian hierarchical model that can substantially reduce the impact of a misspecified prior. Second, we conduct a systematic comparison of the standard parametric posterior, the proposed robustified parametric posterior, and a nonparametric Bayesian posterior which uses a Dirichlet process mixture prior. The proposed robustifed posterior when combined with a flexible parametric prior can be a superior alternative to nonparametric Bayesian methods.

Introduction Military personnel have among the highest rates of tobacco use in the United States. Unfortunately, there are few interventions aimed at reducing tobacco use among this vulnerable population. The current study addresses this need by evaluating the short-term effectiveness of a Brief Tobacco Intervention (BTI), a 40-min group-based intervention designed to reduce contemporary patterns of tobacco use among a sample of US military enlistees during an 11-week period of involuntary tobacco abstinence. Aims and Methods Participants were 2999 US Air Force Technical Trainees at Joint Base San Antonio-Lackland Air Force Base in San Antonio, Texas from April 2017 through January 2018. Participants were cluster randomized to three conditions: (1) BTI + Airman’s Guide to Remaining Tobacco Free (AG), (2) AG intervention, or (3) standard smoking cessation intervention. The primary analysis was a comparison of the interventions’ efficacies in preventing tobacco use during Technical Training, conducted using a generalized estimating equations logistic regression model controlling for covariates. Multiple imputation was used to account for loss to follow-up. Results There was not a significant difference by condition in the use of tobacco products at follow-up (p = .454). The BTI + AG condition did produce short-term changes in perceived harm, intentions to use tobacco, knowledge about tobacco products, and normative beliefs. Conclusions These findings suggest that while the intervention was effective in the short term, it was not potent enough over a 12-week period to prevent Airmen from initiating tobacco use. Future studies should examine whether adding a booster session or media campaign enhances the effectiveness of the intervention. Implications Despite the fact that most Airmen believe they will remain tobacco free following the ban in Technical Training, a large percentage of these Airmen resume and initiate tobacco use during this high-risk period. As a result, there is a need for interventions targeting the range of tobacco available to military trainees during a teachable moment when they report intentions to remain tobacco free. The current study shows that a BTI has promise in reducing long-term tobacco use, when coupled with additional interventions, such as a booster session or a media campaign.

Background Not One More Life (NOML), a health and faith partnership, aims to engage African Americans at risk for asthma morbidity into community-partnered asthma programs. Methods Not One More Life programs consisted of interactive presentations, a questionnaire, and spirometry. Results 4,522 individuals attended NOML programs at 136 Atlanta churches over nine years. Over 90% of attendees were African American. Attendees with asthma had high rates of obesity (9.4% of children, 47.9% of adults) and airflow obstruction (34.6% of children, 17.2%, of adults). Over 20% of attendees with asthma reported past hospitalization for asthma. Among those with a history of hospitalizations for asthma, just 17.6% reported treatment with inhaled corticosteroids Conclusion. Not One More Life program attendees with asthma report considerable morbidity including exceptionally high rates of asthma hospitalizations. Participants have multiple remediable characteristics associated with poorly controlled asthma, including medication undertreatment and obesity.

Objective: Older adults make up a rapidly increasing proportion of motor vehicle occupants and previous studies have demonstrated that this population is more susceptible to traumatic injuries. The CDC recommends that patients anticipated to have severe injuries (Injury Severity Score [ISS] ≥ 16) be transported to a trauma center. The recommended target rate for undertriage is ≤ 5% and for overtriage is ≤ 50%. Several regression-based algorithms for injury prediction have been developed in order to predict severe injury in occupants involved in a motor vehicle collision (MVC). The objective of this study to was to determine if the accuracy of regression-based injury severity prediction algorithms decreases for older adults. Methods: Data were obtained from the National Automotive Sampling System – Crashworthiness Data System (NASS-CDS) from the years 2000–2015. Adult occupants involved in non-rollover MVCs were included. Regression-based injury risk models to predict severe injury (ISS ≥ 16) were developed using random split-samples with the following variables: age, delta-V, direction of impact, belt status, and number of impacts. Separate models were trained using data from the following age groups: (1) all adults, (2) 15–54 years, (3) ≥45 years, (4) ≥55 years, and (5) ≥65 years. The models were compared using the mean receiver operating characteristic area under curve (ROC-AUC) after 1,000 iterations of training and testing. The predicted rates of overtriage were then determined for each group in order to achieve an undertriage rate of 5%. Results: There were 24,577 occupants (6,863,306 weighted) included in this analysis. The injury prediction model trained using data from all adults did not perform as well when tested on older adults (ROC-AUC: 15–54 years: 0.874 [95% CI: [0.851–0.895]; 45+ years: 0.837 [95% CI: 0.802–869]; 55+ years: 0.821 [95% CI: 0.775–0.864]; and 65+ years: 0.813 [95% CI: 0.754–0.866]). The accuracy of this model decreased in each decade of life. The performance did not change significantly when age-specific data were used to train the prediction models (ROC-AUC: 18–54 years: 0.874 [95% CI: 0.851–0.896]; 45+ years: 0.836 [95% CI: 0.798–0.871]; 55+ years: 0.822 [95% CI: 0.779–0.864]; and 65+ years: 0.808 [95% CI: 0.748–0.868]). In order to achieve an undertriage rate of 5%, the predicted overtriage rate by these models were 50% for occupants 15–54 years, 61% for occupants ≥ 55 years, 70% for occupants ≥ 55 years, and 71% for occupants ≥ 65 years. Conclusion: The results of this study indicate that it is more difficult to accurately predict severe injury in older adults involved in MVCs, which has the potential to result in significant overtriage. This decreased accuracy is likely due to variations in fragility in older adults. These findings indicate that special care should be taken when using regression-based prediction models to determine the appropriate hospital destination for older occupants.

Previous studies have shown that occupants with obesity are at a greater risk of fatality and serious injury than other occupants in motor vehicle crashes. To provide a more complete description of the most frequent injuries and the most frequently injured body regions for occupants with obesity. Sampled cases (n = 13,470) representing ~4.7 million adult occupants involved in frontal crashes (between 2000 and 2015) were selected from the U.S. National Automotive Sampling System—Crashworthiness Data System database. A retrospective cohort study was performed to study the effect of BMI on the risk of injury to different body regions and to identify the most frequent injuries to occupants with different BMIs. Lastly, in-depth crash analysis cases from the U.S. Crash Injury Research and Engineering Network (CIREN) database were studied to elucidate the source of the most common injuries to occupants with obesity. Occupants with obesity experienced a higher risk of upper extremity (4.79 vs 2.92%), lower extremity (8.37 vs 3.23%), and spine (1.53 vs 1.09%) injuries than other occupants. After adjusting for other variables, the risks of spinal, thoracic, and extremities injuries were found to be affected by the BMI class. Seven out of the ten most common injuries sustained by occupants with obesity were lower extremity injuries, and talus fractures were the most common overall. Direct loading through the plantar surface of the foot by the vehicle toe pan was found to be a likely cause of many of those injuries based on CIREN cases. The injuries of occupants with obesity are different than other occupants which can be attributed to their different interaction with the seat belt and vehicle interior. The findings of this study should be considered for designing restraint systems to protect occupants with obesity in car crashes.

We sought to determine the effect of active versus passive voiding trials on time to hospital discharge and rates of urinary tract infection (UTI) and urinary retention (UR). We performed a prospective, randomized trial comparing active (AVT) versus passive (PVT) void trials of inpatients requiring urethral catheter removal. Of 329 eligible patients, 274 were randomized to AVT (bladder filled with saline before catheter removal) or PVT (spontaneous bladder filling after catheter removal). Primary outcome was time to hospital discharge. Secondary outcomes were UTI (NSQIP criteria) and UR (requiring repeat catheterization) within 2 weeks of void trial. The median time to void was 18 (5–115) versus 236 (136–360) min in the AVT and PVT groups, respectively (p

For patients with diabetes, annual preventive care is essential to reduce the risk of complications. Local healthcare resources affect the utilization of diabetes preventive care. Our objectives were to evaluate the relative efficiency of counties in providing diabetes preventive care and explore potential to improve efficiencies. The study setting is public and private healthcare providers in US counties with available data. County-level demographics were extracted from the Area Health Resources File using data from 2010 to 2013, and individual-level information of diabetes preventive service use was obtained from the 2010 Behavioral Risk Factor Surveillance System. 1112 US counties were analyzed. Cluster analysis was used to place counties into three similar groups in terms of economic wellbeing and population characteristics. Group 1 consisted of metropolitan counties with prosperous or comfortable economic levels. Group 2 mostly consisted of non-metropolitan areas between distress and mid-tier levels, while Group 3 were mostly prosperous or comfortable counties in metropolitan areas. We used data enveopement analysis to assess efficiencies within each group. The majority of counties had modest efficiency in providing diabetes preventive care; 36 counties (57.1%), 345 counties (61.1%), and 263 counties (54.3%) were inefficient (efficiency scores

OBJECTIVE Transporting severely injured pediatric patients to a trauma center has been shown to decrease mortality. A decision support tool to assist emergency medical services (EMS) providers with trauma triage would be both as parsimonious as possible and highly accurate. The objective of this study was to determine the minimum set of predictors required to accurately predict severe injury in pediatric patients. METHODS Crash data and patient injuries were obtained from the NASS and CISS databases. A baseline multivariable logistic model was developed to predict severe injury in pediatric patients using the following predictors: age, sex, seat row, restraint use, ejection, entrapment, posted speed limit, any airbag deployment, principal direction of force (PDOF), change in velocity (delta-V), single vs. multiple collisions, and non-rollover vs. rollover. The outcomes of interest were injury severity score (ISS) ≥16 and the Target Injury List (TIL). Accuracy was measured by the cross-validation mean of the receiver operator curve (ROC) area under the curve (AUC). We used Bayesian Model Averaging (BMA) based on all subsets regression to determine the importance of each variable separately for each outcome. The AUC of the highest performing model for each number of variables was compared to the baseline model to assess for a statistically significant difference (p

Self-generated identification codes (SGICs) are strings of information based on stable participant characteristics. They are often used in longitudinal research to match data between time points while protecting participant anonymity. However, the use of SGICs with military personnel has been infrequent, even though military personnel do not have the same privacy protections as civilians. The current paper reports results from two studies that tested the feasibility, reliability, and validity of using a SGIC to collect sensitive longitudinal data among military personnel. In study one, a team of 105 participants was tracked three times over a period of 12 weeks. The 10-item SGIC produced optimal matching over the 12-weeks. In study two, 1,844 participants were randomly assigned to a SGIC group or an anonymous control group, and then were asked to provide information about their alcohol use. Although match rates declined over time, there were no observed differences between study groups in participants’ beliefs about the use of a SGIC. However, differences were identified in reported alcohol use behaviors between the groups, with controls reporting significantly more drinks per week and higher AUDIT-10 scores. While these findings raise potential concerns about using SGICs for epidemiological assessments of highly sensitive problem behaviors, these codes may still be useful in determining group differences in behavior change in randomized studies.

The ability to perform automated neurological assessment could enhance diagnosis and treatment in the pre-hospital setting such as during telemedicine or emergency medical services (EMS) encounters. In this pilot study we present the preliminary analysis of a video-based eye movement assessment workflow (NeuroGaze) for neurological eye examinations. Our workflow uses a pupil detector to detect the center of the pupil for both eyes for a given video and determine the conjugacy of eye movement. The study evaluated the proposed workflow on 18 healthy volunteers while performing a digitally adapted neurological eye examination (NeuroEye) to assess conjugacy of gaze in all cardinal positions. The NeuroGaze performance was compared to the COTS eye tracker. The video-based eye movement assessment workflow reported an average Pearson correlation coefficient of 0.84, compared to the COTS eye tracker with an average of 0.95. The preliminary analysis indicates that NeuroGaze can be used to determine the individuals ability to perform conjugate eye movements. Future study will assess the performance of NeuroGaze in patients with pathological eye movements.

IntroductionDiarrhoea remains a leading cause of child morbidity and mortality. Systematically collected and analysed data on the aetiology of hospitalised diarrhoea in low-income and middle-income countries are needed to prioritise interventions.MethodsWe established the Global Pediatric Diarrhea Surveillance network, in which children under 5 years hospitalised with diarrhoea were enrolled at 33 sentinel surveillance hospitals in 28 low-income and middle-income countries. Randomly selected stool specimens were tested by quantitative PCR for 16 causes of diarrhoea. We estimated pathogen-specific attributable burdens of diarrhoeal hospitalisations and deaths. We incorporated country-level incidence to estimate the number of pathogen-specific deaths on a global scale.ResultsDuring 2017–2018, 29 502 diarrhoea hospitalisations were enrolled, of which 5465 were randomly selected and tested. Rotavirus was the leading cause of diarrhoea requiring hospitalisation (attributable fraction (AF) 33.3%; 95% CI 27.7 to 40.3), followed by Shigella (9.7%; 95% CI 7.7 to 11.6), norovirus (6.5%; 95% CI 5.4 to 7.6) and adenovirus 40/41 (5.5%; 95% CI 4.4 to 6.7). Rotavirus was the leading cause of hospitalised diarrhoea in all regions except the Americas, where the leading aetiologies were Shigella (19.2%; 95% CI 11.4 to 28.1) and norovirus (22.2%; 95% CI 17.5 to 27.9) in Central and South America, respectively. The proportion of hospitalisations attributable to rotavirus was approximately 50% lower in sites that had introduced rotavirus vaccine (AF 20.8%; 95% CI 18.0 to 24.1) compared with sites that had not (42.1%; 95% CI 33.2 to 53.4). Globally, we estimated 208 009 annual rotavirus-attributable deaths (95% CI 169 561 to 259 216), 62 853 Shigella-attributable deaths (95% CI 48 656 to 78 805), 36 922 adenovirus 40/41-attributable deaths (95% CI 28 469 to 46 672) and 35 914 norovirus-attributable deaths (95% CI 27 258 to 46 516).ConclusionsDespite the substantial impact of rotavirus vaccine introduction, rotavirus remained the leading cause of paediatric diarrhoea hospitalisations. Improving the efficacy and coverage of rotavirus vaccination and prioritising interventions against Shigella, norovirus and adenovirus could further reduce diarrhoea morbidity and mortality.

To examine whether Annual Wellness Visits (AWVs) were associated with increased use of preventive services in Medicare patients with diabetes living in the Diabetes Belt.We used a case-control design where outcomes were utilization of preventive services recommended for patients with diabetes (foot exam, eye exam, A1c test, and microalbuminuria test) and the exposure was AWVs using data for Medicare patients with diabetes in 2014 - 2015 residing in the Diabetes Belt (N = 412,009).Only 13.4% of patients in 2014 and 17.4% in 2015 used AWVs. Eye exams (61% vs 53%), foot exams (93% vs 79%), A1c tests (81% vs 71%), and microalbuminuria tests (45% vs 28%) were more common among patients who had an AWV in the preceding year compared with those who did not. These differences remained significant after adjusting for patient demographics, comorbidities, county level medical resources, and geographic factors.AWVs were significantly associated with increased preventive care use among patients with diabetes living in the Diabetes Belt. Low AWV utilization by patients with diabetes in and around the Diabetes Belt is concerning.

Background: The Affordable Care Act created annual wellness visits (AWVs) for Medicare beneficiaries to have one yearly visit to primary care physicians and discuss preventive care for the upcoming year. We assessed whether AWVs were associated with increased use of these preventive services in Medicare patients with diabetes living in the Diabetes Belt and surrounding counties. Methods: We used claims files from a longitudinal sample of ∼1,000,000 Medicare patients with diabetes living in the diabetes belt or surrounding counties, covering years 2014-2015. The Diabetes Belt was identified by the CDC as 644 counties across Appalachian and southeastern counties in the US that had diabetes prevalence ≥ 11% in 2008. We used these data to examine associations between AWVs and preventive service use in the next year. We examined four preventive services recommended annually for patients with diabetes by the ADA, including A1c tests, foot exam, eye exam, and microalbuminuria (MA) tests. Results: Of all patients, only 19.6% used AWVs in 2015. Eye exams (61% vs. 56%), foot exams (92% vs. 83%), A1C tests (78% vs. 73%), and MA tests (42% vs. 31%) were more common among patients who had an AWV in the preceding year compared with those who did not. These differences remained after adjusting for patient demographics, comorbidities, county level medical resources, and geographic factors: eye exam (Odds Ratio 1.13, 95% CI 1.12-1.15); A1c Test (1.28, CI 1.26-1.31); Foot Exam (2.06, CI 2.01-2.11); MA Test (1.45, CI 1.42-1.47). Conclusions: This study shows that AWVs were significantly associated with increased recommended preventive care use among patients with diabetes living in and near the diabetes belt. The low rates of AWV utilization by patients with diabetes in and around the Diabetes Belt is concerning and should receive more policy attention. Disclosure T. L. Mcmurry: None. S. Kim: None. J. M. Lobo: None. H. Kang: None. M. Sohn: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK113295)

Objective: Rates for non-traumatic lower-extremity amputations (LEA) have been declining, but concerns exist over disparities in rates between races/ethnicities. Our objective is to track changes in major LEA (MLEA) rates before and after the Affordable Care Act (ACA) among Medicare beneficiaries residing in the Diabetes Belt compared to those in the surrounding areas. Methods: We used Medicare claims files for a sample of ~1 million Fee-for-Service beneficiaries in 2006 - 2015 to compute rates per 1000 patients with diabetes. The Diabetes Belt was identified by the CDC as 644 counties across Appalachian and southeastern counties in the US that had diabetes prevalence ≥ 11% in 2008. Results: MLEA rates for the Diabetes Belt and surrounding counties as well as rates for Non-Hispanic (NH) Black and NH White are in Figure. Patients in the Belt experienced one full MLEA more per 1000 patients than those in the surrounding area. Although amputation rates declined rapidly in both areas, NH blacks consistently had > 3 times higher rates than NH whites in the Belt. Trends did not show noticeable changes in MLEAs before and after the ACA. Discussion: Our data show persistent disparities in MLEA rates between the Diabetes Belt and surrounding counties. Racial disparities were much larger in the Belt. Targeted policies to prevent MLEAs among NH black patients are needed to reduce the disparities in this region. Disclosure J. M. Lobo: None. S. Kim: None. H. Kang: None. T. L. Mcmurry: None. M. Sohn: None. Funding National Institutes of Health (R01DK113295)

Objective: Preventive care has been shown to reduce both the incidence and progression of diabetic complications. American Diabetes Association treatment guidelines recommend annual preventive care such as annual doctor visits and A1c tests. Our objective is to compare utilization rates of four annually recommended preventive services for persons with diabetes in the Diabetes Belt and those in the surrounding area. Methods: We used 2015 Medicare claims data to identify preventive service utilization using ICD9/10 and CPT/HCPCS codes. Diabetes Belt consists of 644 counties in the Appalachian region and southeastern part of US that had diabetes prevalence over 11% in 2008 compared to ~8.5% in the rest of the country. Surrounding counties include 118 counties that are adjacent but not contiguous to the Diabetes Belt counties. Results: Patients in the Belt had significantly lower utilization than those in surrounding counties for all four preventive services: foot exam, 81% vs. 88%; eye exam, 53% vs. 58%; microalbuminuria test, 31% vs. 34%; one or more A1c tests, 73% vs. 74%. After adjusting for age, sex, and race/ethnicity, patients in the Diabetes Belt had 38%, 18%, 16%, and 11% lower odds of using foot exams, microalbuminuria tests, eye exams, and A1c tests, respectively, compared to those in the surrounding counties (p for all comparisons < 0.001). Even after adjusting for socioeconomic, access-to-care factors, and service availability, patients in the Diabetes Belt had consistently lower rates of utilization for these four services than surrounding counties. Conclusion: Patients with diabetes in the Diabetes Belt are doubly jeopardized for diabetic complications because of higher prevalence diabetes and lower preventive care utilization than surrounding counties. Health policy makers may want to pay more attention to the Diabetes Belt in reducing the regional differences in the utilization of these services. Disclosure M. Sohn: None. H. Kang: None. T. L. Mcmurry: None. S. Kim: None. J. M. Lobo: None. Funding National Institute of Diabetes and Digestive and Kidney Diseases (R01DK113295)

This cohort study examines the prevalence of and risk factors for mental illness among current and former coal miners in the United States.

Using quantitative PCR diagnostics in a phase 3 clinical trial of Rotasiil in Niger, we identified Shigella, Cryptosporidium, rotavirus, and heat-stabile toxin-producing Escherichia coli to be the top 4 leading etiologies of moderate-to-severe diarrhea in children 0-2 years of age., Background High-resolution data on the etiology of childhood diarrhea in countries with the highest burden and mortality remain sparse and are needed to inform burden estimates and prioritize interventions. Methods We tested stool specimens collected between October 2014 and December 2017 from children under 2 years of age from the per-protocol population of a placebo-controlled clinical trial of a bovine rotavirus pentavalent vaccine (Rotasiil) in Niger. We tested 1729 episodes of moderate-to-severe diarrhea (Vesikari score ≥ 7) using quantitative PCR and estimated pathogen-specific burdens by age, season, severity, and trial intervention arm. Results The 4 pathogens with the highest attributable incidence of diarrhea were Shigella (7.2 attributable episodes per 100 child-years; 95% confidence interval: 5.2, 9.7), Cryptosporidium (6.5; 5.8, 7.2), rotavirus (6.4; 5.9, 6.7), and heat-stabile toxin-producing enterotoxigenic Escherichia coli (ST-ETEC) (6.2; 3.1, 7.7). Cryptosporidium was the leading etiology of severe diarrhea (Vesikari score ≥ 11) and diarrhea requiring hospitalization. Shigella was the leading etiology of diarrhea in children 12-23 months of age but also had a substantial burden in the first year of life, with 60.5% of episodes of severe shigellosis occurring in infants. Shigella, Cryptosporidium, and ST-ETEC incidence peaked during the warmer and wetter period and coincided with peak all-cause diarrhea incidence. Conclusions In this high-burden setting, the leading diarrheal pathogens were Shigella, Cryptosporidium, rotavirus, and ST-ETEC, and each was disproportionately seen in infants. Vaccine development should target these pathogens, and the impact of vaccine schedule on diarrhea burden in the youngest children will need to be considered.

BACKGROUND: The purpose of this study was to compare the long-term effectiveness of three lymphadenectomy strategies. We hypothesized that, compared to the traditional standard (D2) lymph node dissection strategy, the less aggressive modified standard (mD2) lymphadenectomy may offer superior effectiveness due to reduced operative morbidity and comparable long-term recurrence-free survival. METHODS: A Markov decision analysis model was created to simulate five-year outcomes across three lymphadenectomy approaches for gastric cancer: limited regional (D1), traditional standard (D2), and modified standard (mD2). The primary outcome was discounted quality adjusted life-years (dQALY). Model variable estimates were derived from outcomes data and quality of life estimates published in Europe and Americas within the last 15 years. One-way and probabilistic sensitivity analyses were performed for clinically-relevant variables. RESULTS: The mD2 lymphadenectomy offered 3.03 dQALY over five years, outperforming D2 (2.62 dQALY) and D1 (2.37 dQALY). Monte Carlo simulations indicated that both mD2 and D2 lymph node dissection strategies outperformed D1 in 94.9% of simulations. Sensitivity analyses demonstrated that the mD2 approach would be less effective than D2 if the perioperative mortality rate of mD2 was greater than 6.9% (3.2% baseline). CONCLUSIONS: Across modern series, the modified standard mD2 lymphadenectomy is an effective alternative to the traditional D2 lymphadenectomy for patients with gastric cancer. A D1 limited regional lymphadenectomy is not recommended during gastric cancer resection.

Objective: As vehicle safety technologies and evaluation procedures advance, it is pertinent to periodically evaluate injury trends to identify continuing and emerging priorities for intervention. This study examined detailed injury distributions and injury risk trends in belted occupants in frontal automobile collisions (10 o'clock to 2 o'clock) using NASS-CDS (1998-2015). Methods: Injury distributions were examined by occupant age and vehicle model year (stratified at pre- and post-2009). Logistic regression models were developed to examine the effects of various factors on injury risk (by body region), controlling for delta-V, sex, age, height, body mass index (BMI), vehicle model year (again stratified at 2009). Results: Among other observations, these analyses indicate that newer model year vehicles (model year [MY] 2009 and later) carry less risk of Abbreviated Injury Scale (AIS) 2+ and AIS 3+ injury compared to older model year vehicles, with odds ratios of 0.69 (AIS 2+) and 0.45 (AIS 3+). The largest reductions in risk between newer model year vehicles and older model year vehicles occur in the lower extremities and in the risk of skull fracture. There is no statistically significant change in risk of AIS 3+ rib fracture or sternum injury between model year categories. Females are at greater risk of AIS 2+ and AIS 3+ injury compared to males, with increased risk across most injury types. Conclusions: For belted occupants in frontal collisions, substantial reductions in injury risk have been realized in many body regions in recent years. Risk reduction in the thorax has lagged other body regions, resulting in increasing prevalence among skeletal injuries in newer model year vehicles (especially in the elderly). Injuries also remain common in the arm and hand/wrist for all age ranges studied. These results provide insight into where advances in the field have made gains in occupant protection and what injury types remain to be addressed.

Background Rotavirus vaccine efficacy (VE) estimates in low-resource settings are lower than in developed countries. We detected coinfections in cases of severe rotavirus diarrhea in a rotavirus VE trial to determine whether these negatively impacted rotavirus VE estimates. Methods We performed TaqMan Array Card assays for enteropathogens on stools from rotavirus enzyme immunoassay–positive diarrhea episodes and all severe episodes (Vesikari score ≥11), from a phase 3 VE trial of Rotavac, a monovalent human–bovine (116E) rotavirus vaccine, carried out across 3 sites in India. We estimated pathogen-specific etiologies of diarrhea, described associated clinical characteristics, and estimated the impact of coinfections on rotavirus VE using a test-negative design. Results A total of 1507 specimens from 1169 infants were tested for the presence of coinfections. Rotavirus was the leading cause of severe diarrhea even among vaccinated children, followed by adenovirus 40/41, Shigella/enteroinvasive Escherichia coli, norovirus GII, sapovirus, and Cryptosporidium species. Bacterial coinfections in rotavirus-positive diarrhea were associated with a longer duration of diarrhea and protozoal coinfections with increased odds of hospitalization. Using the test-negative design, rotavirus VE against severe rotavirus gastroenteritis increased from 49.3% to 60.6% in the absence of coinfections (difference, 11.3%; 95% confidence interval, –10.3% to 30.2%). Conclusions While rotavirus was the dominant etiology of severe diarrhea even in vaccinated children, a broad range of other etiologies was identified. Accounting for coinfections led to an 11.3% increase in the VE estimate. Although not statistically significant, an 11.3% decrease in VE due to presence of coinfections would explain an important fraction of the low rotavirus VE in this setting., Quantitative molecular testing of stool samples for enteropathogens from diarrheal episodes from a phase 3 rotavirus vaccine efficacy trial revealed high coinfection rates, and there was a 11.3% improvement in vaccine efficacy estimates after accounting for these coinfections.

Background: Posterior circulation stroke (PCS) accounts for ~20% of ischemic strokes. Existing EMS screening tools lack accuracy in the diagnosis of PCS. We aim to develop an automated screening tool to detect abnormal eye movements in patients presenting with PCS. Methods: As an initial step, we built a portable platform called RoADIE (Rolling Apparatus to Detect Impairment of the Eyes), equipped with eye-tracking software to acquire gaze data from patients presenting with PCS, acute vestibular syndrome, and normal controls. We first performed a validation study in 19 healthy controls comparing calibration (C) vs non-calibration (NC) techniques. Eye movements were captured using a standard H-Test exam. The NC condition was performed first for each volunteer to avoid a learning effect. Correlation between C and NC tests was determined using the Spearman coefficient (r). Results: Conjugate gaze (i.e. ability of eyes to track in unison) demonstrated strong correlation along the horizontal [r = 0.976 (C), 0.922 (NC)] and vertical axes [r= 0.866 (C), 0.881(NC)]. Smooth pursuit (i.e. ability of each eye to track moving target) also showed strong correlation in the horizontal plane: right eye [r = 0.945 (C), 0.946 (NC), left eye [r=0.945 (C), 0.943 (NC)]. Vertical tracking showed moderate correlation: right eye [r=0.652 (C), 0.575 (NC), left eye [r=0.678 (C), 0.550 (NC)]. Conclusion: In this initial validation test of a portable eye tracking platform, we demonstrated strong correlation for both conjugate gaze and smooth pursuit in the horizontal axis, and moderate correlation for eye tracking in the vertical axis. Given similar performance in non-calibrated tests, a calibration procedure may not be necessary for future data capture. Next steps will include validation of the eye tracking device in prospective patients presenting with PCS and acute vestibular syndrome. Acknowledgement: Funding support through AHA Innovative Project Award 19IPLOI34760692

Automated eye tracking technology could enhance diagnosis and treatment for many neurological diseases, including posterior circulation stroke. Much of the current literature focuses on gaze estimation through a form of calibration. Unlike other fields, medicine has a clear need to better track eye symmetry during movement for better detection of abnormal conjugacy, ductions, and vestibulo-ocular function in a variety of neurological diseases. However, patients with neuro-ocular deficits may have a difficult time completing a calibration procedure due to inattention and other associated neurologic deficits. Here, we investigate the need for calibration to measure the symmetry of eye movements in healthy individuals including testing fixations, smooth pursuits, and saccades. The results of this feasibility study suggest that calibration may not be necessary to measure and track binocular eye movements in tandem. The structure or shape which the eyes draw during visual tracking remain intact even without a calibration procedure. The preliminary study suggests that this technology can be deployed without a calibration procedure within this clinical context. Further research is needed to validate these findings in populations with neuro-ophthalmologic disease, including posterior circulation stroke.

Objective: Compare injuries for occupants in multiple event (ME) crashes where a less severe event preceded a more severe event to occupants in similar single event (SE) crashes. Methods: Occupants in ME crashes from NASS-CDS years 2000–2015 where the most severe event occurred subsequent to a less severe event were matched to occupants in SE crashes where the SE was similar to the most severe event in the ME crash. Occupants were matched based on occupant, vehicle, and crash characteristics and were compared across 21 detailed body regions using conditional logistic regression. Finite element (FE) simulations were performed with human surrogate models (detailed GHBMC and Hybrid III) and in both low- and high-speed conditions (n = 8 total simulations). At each speed, the crash simulations with both human body models reproduced a common multidirectional ME crash scenario, where the second impulse was more severe and similar to the SE impulse. Relative injury risk was assessed, and ME versus SE were computed and compared to those from the field data. Results: 1,663 ME occupants were matched to 3,217 SE occupants. ME occupants had higher MAIS2+ and MAIS3+ injury risk, and showed directionally higher injury risk in all but one body region. Eleven out of the 27 injury groups had higher injury risk in ME (false discovery rate (FDR)1.54). In FE simulations, ME displayed larger anterior and lateral displacement compared to SE. Head and thorax injury risk was increased in ME simulations by up to 5-fold. The detailed GHBMC and Hybrid III exhibited different kinematics and injury risk across all simulations, as did low- and high-speed conditions. Conclusions: The field data and FE simulations suggest that a first, less severe crash event results in occupants having greater injury risk when they are involved in a second, more severe crash event than if they were involved only in the second event. Several factors could cause this increase in injury risk, such as improper interaction with safety systems and airbags after the first event renders the occupant out-of-position.

Readmissions are costly and inconvenient for patients, and occur frequently in hepatopancreatobiliary (HPB) surgery practice. Readmission prediction tools exist, but most have not been designed or tested in the HPB patient population.Pancreatectomy and hepatectomy operation-specific readmission models defined as subspecialty readmission risk assessments (SRRA) were developed using clinically relevant data from merged 2014-15 ACS NSQIP Participant Use Data Files and Procedure Targeted datasets. The two derived procedure-specific models were tested along with 6 other readmission models in institutional validation cohorts in patients who had pancreatectomy or hepatectomy, respectively, between 2013 and 2017. Models were compared using area under the receiver operating characteristic curves (AUC).A total of 16,884 patients (9169 pancreatectomy and 7715 hepatectomy) were included in the derivation models. A total of 665 patients (383 pancreatectomy and 282 hepatectomy) were included in the validation models. Specialty-specific readmission models outperformed general models. AUC characteristics of the derived pancreatectomy and hepatectomy SRRA (pancreatectomy AUC=0.66, hepatectomy AUC=0.74), modified Readmission After Pancreatectomy (AUC=0.76), and modified Readmission Risk Score for hepatectomy (AUC=0.78) outperformed general models for readmission risk: LOS/2 + ASA integer-based score (pancreatectomy AUC=0.58, hepatectomy AUC=0.66), LACE Index (pancreatectomy AUC=0.54, hepatectomy AUC=0.62), Unplanned Readmission Nomogram (pancreatectomy AUC=0.52, hepatectomy AUC=0.55), and institutional ARIA (pancreatectomy AUC=0.46, hepatectomy AUC=0.58).HPB readmission risk models using 30-day subspecialty-specific data outperform general readmission risk tools. Hospitals and practices aiming to decrease readmissions in HPB surgery patient populations should use specialty-specific readmission reduction strategies.

Unplanned reoperations and unplanned readmissions can increase morbidity and mortality. Few studies however, have explored the association of reoperation and readmission among general surgery patients. Our aim was to examine this relationship in selected abdominal operations.Data from the American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) Participant Use Data Files from 2014 to 2018 were utilized. Six groups of operations, defined by ACS NSQIP procedure codes for ventral hernia repair, colectomy, appendectomy, proctectomy, small bowel resection, and gastrectomy, were assessed. Patients discharged ≤ 14 days after operation were included in the study. This time period was selected to reduce ACS NSQIP 30 day post-surgery follow-up bias. Unplanned reoperations were defined as those occurring during the index hospitalization. The primary outcome was unplanned readmission that occurred ≤ 14 days from the date of discharge. Logistic regression models were used to examine variables associated with unplanned readmission for each procedure group.A total of 787,118 patients were included: ventral hernia repair 35.2%, colectomy 30.6%, appendectomy 26.5%, proctectomy 3.7%, small bowel resection 3.2%, and gastrectomy 0.8%. Unplanned reoperation was independently associated with unplanned readmission for ventral hernia repair (OR 2.84, 95% CI 2.28-3.54, P0.001), colectomy (OR 1.58, CI 1.42- 1.76, P0.001), appendectomy (OR 2.91, CI 2.21-3.84, P0.001), and proctectomy (OR 1.41, CI 1.10-1.81, P = 0.006). Other clinically relevant covariates associated with readmission were partially dependent functional status before colectomy (OR 1.34, CI 1.23-1.46, P0.001), ventral hernia repair (OR 1.79, CI 1.54-2.09, P0.001), and small bowel resection (OR 1.44, CI 1.18-1.77, P0.001; and ASA 4/5 classification for colectomy (OR 2.71, CI 2.36-3.11, P0.001), proctectomy (OR 2.10, CI 1.48-2.97, P0.001), ventral hernia repair (OR 8.19, CI 6.78-9.88, P0.001), appendectomy (OR 2.80, CI 2.35-3.34, P0.001), and small bowel resection (OR 3.42, CI 2.20-5.32, P0.001). ASA 2, ASA 3 classification, age, and sex were also associated with unplanned readmission for most procedures.Unplanned reoperations are associated with an increase in unplanned readmission after selected abdominal operations included in this study. This factor should be considered in discharge and follow-up planning to help reduce unplanned readmissions.

Alcohol use is common among military personnel. However, alcohol use and problems are challenging to measure because military personnel do not have similar levels of confidentiality as civilians and can face sanctions for reporting illegal behavior (e.g., underage drinking) or for drinking during prohibited times (e.g., during basic training). The current study aimed to determine if the use of the alcohol purchase task (APT), which has previously been associated with alcohol use and alcohol-related problems in civilian populations, is a valid measure of alcohol-related risk in the military when asking about alcohol consumption is less feasible. Participants were 26,231 Air Force airmen who completed surveys including questions about sensation seeking, alcohol expectancies, perception of peer drinking, intent to drink, and family history of alcohol misuse, which are known predictors of alcohol use, and the APT, from which demand indices of intensity and Omax were derived. Individuals who were single, male, White, and had a high school diploma/GED had higher intensity and Omax scores, and non-Hispanic individuals had higher intensity scores. Age was negatively correlated with intensity and Omax. Regressions were used to determine if intensity and Omax were associated with known predictors of alcohol use and risk. Intensity and Omax showed significant but small associations with all included predictors of alcohol consumption and alcohol risk. Effect sizes were larger for individuals ages 21+ compared to individuals under 21. Thus, this study provides initial support for the validity of the APT as an index of alcohol-related risk among military personnel. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Background Enhanced Recovery (ER) is a change management framework in which a multidisciplinary team of stakeholders utilizes evidence-based medicine to protocolize all aspects of a surgical care to allow more rapid return of function. While service-specific reports of ER adoption are common, institutional-wide adoption is complex, and reports of institution-wide ER adoption are lacking in the United States. We hypothesized that ER principles were generalizable across an institution and could be implemented across a multitude of surgical disciplines with improvements in length of stay, opioid consumption, and cost of care. Methods Following the establishment of a formal institutional ER program, ER was adopted in 9 distinct surgical subspecialties over 5 years at an academic medical center. We compared length of stay, opioid consumption, and total cost of care in all surgical subspecialties as a function of time using a segmented regression/interrupted time series statistical model. Results There were 7774 patients among 9 distinct surgical populations including 2155 patients in the pre-ER cohort and 5619 patients in the post-ER cohort. The introduction of an ER protocol was associated with several significant changes: a reduction in length of stay in 5 of 9 specialties; reduction in opioid consumption in 8 specialties; no change or reduction in maximum patient-reported pain scores; and reduction or no change in hospital costs in all specialties. The ER program was associated with an aggregate increase in profit over the study period. Conclusions Institution-wide efforts to adopt ER can generate significant improvements in patient care, opioid consumption, hospital capacity, and profitability within a large academic medical center.

The relationship between laboratory and on-field performance of football helmets was assessed for 31 football helmet models selected from those worn by players in the 2015-2019 National Football League (NFL) seasons. Linear impactor tests were conducted with helmets placed on an instrumented Hybrid III head and neck assembly mounted on a sliding table. Based on impacts to each helmet at six impact locations and three velocities, a helmet performance score (HPS) was calculated using a linear combination of the head injury criterion (HIC) and the diffuse axonal multi-axis general evaluation (DAMAGE). To determine the on-field performance of helmets, helmet model usage, player participation, and incident concussion data were collected from the five NFL seasons and used to calculate helmet model-specific concussion rates. Comparison of laboratory HPS to the helmet model-specific concussion rates on a per play basis showed a positive correlation (r

BackgroundWe present a method of randomly drawing a longitudinal sample of Medicare patients to 1) conduct longitudinal analysis of care use and outcomes over a ten-year follow-up; 2) provide a representative cross-sectional sample in each year during this time period; and 3) provide adequate precision for estimates in comparisons that involve minority patients at the county level. This method was applied to patients with diabetes in the Diabetes Belt (a region in the Appalachian and southern US with higher rates of diabetes) and surrounding counties.MethodsWe used the Medicare Master Beneficiary Summary Files (A/B/C/D and Chronic Conditions segments) to identify eligible patients for each year. We targeted a sample of just under 900,000 patients per year. The 2006 sample is stratified by county and white/minority status, and targeted at least 250 patients in each stratum with the remaining sample allocated proportional to county size with oversampling of the minority population. Patients who were alive, did not move between counties, and stayed enrolled in Medicare fee-for-service (FFS) were retained in the sample for subsequent years. Non-retained patients were replaced with a sample of patients in their first year of Medicare FFS (e.g., new enrollees) or patients who moved into a sampled county during the previous year.ResultsThe resulting sample contains an average of 899,266 patients each year and closely matches population demographics and chronic conditions. For all years in the sample, the weighted sample average age and the population age differ by < 0.01 years; the proportion white is within 0.01%; and the proportion female is within 0.08%. No difference was statistically significant at the α = 0.05 level.ConclusionsThis carefully constructed survey sample will allow us to to perform longitudinal and cross-sectional analysis on healthcare utilization and outcomes. This sampling strategy can be easily adapted to other projects that require random samples of Medicare beneficiaries for longitudinal follow-up with possible oversampling of some sub-populations.

Objective: As the U.S. population ages, there have been projections that the number of people living with diabetes would double in the next two decades. Our objective is to track how diabetes prevalence rates have changed over time before and after the Affordable Care Act (ACA) among Medicare beneficiaries residing in the Diabetes Belt compared to those residing outside. Methods: We used complete Medicare Beneficiary Summary Files for 2006 - 2015 (A/B/C/D and Chronic Conditions segments) to compute prevalence rates of diabetes as identified in the CMS Chronic Conditions Warehouse. The Diabetes Belt in this study was defined as 644 counties across southeastern counties in the U.S. that had diabetes prevalence ≥ 11% in 2008 (Barker et al. 2012). Results: Overall diabetes prevalence increased from 24.4% in 2006 to 27.2% in 2011 and slightly decreased to 26.7% in 2015. In the Diabetes Belt, the prevalence rates were 29.1% in 2006, reaching 32.0% in 2012. The prevalence rates were 5.2% higher in absolute percentages in the Belt than outside in 2006. This difference steadily increased to 5.6% in 2015. After adjusting for age, sex, race, rurality, health professional shortage area designation, and economic level in counties, individuals in the Diabetes Belt experienced 8.1% higher risk (OR = 1.081; 95% CI = 1.078, 1.083) of having diabetes compared to those outside the Belt in 2015. Discussion: Diabetes prevalence was stable among Medicare beneficiaries in 2011-2015, but the gap between the Diabetes Belt and the non-Belt counties widened throughout the study period. The ACA and the concerted efforts at diabetes prevention have succeeded in “bending the curve” on the projected increased in the number of persons with diabetes, but growing disparities in diabetes prevalence between the Diabetes Belt and other regions is a concern that requires more policy attention. Disclosure M. Sohn: None. S. Kim: None. H. Kang: None. T.L. McMurry: None. J.M. Lobo: None. Funding National Institutes of Health (R01DK113295)

Background Relationships between surgical errors and adverse events have not been fully explored and were examined in this study. Materials and methods This retrospective cohort study reviewed records of deceased surgical patients over 12 months. Bivariate associations between predictors and errors were examined. Results 84 deaths occurred following 5,209 operations. Errors in care (63%) compared to those without had significantly more adverse events, (98% vs 80% respectively, p = 0.004). Significant association occurred between error and emergency status, p = 0.016); length of stay >10 days, p = 0.011; adverse events, p = 0.005). Regression results indicated number of adverse events (OR = 1.27, 95% CI (1.08–1.49), p = 0.003) and length of stay (OR = 1.05, 95% CI (1.01–1.09), p = 0.008) were associated with surgical errors. Conclusions Examining postoperative adverse events in error cases identified opportunities for improvement. Reducing medical errors requires measuring medical errors.

Objective: Knee airbags (KABs) have become increasingly common in the vehicle fleet. Previous studies (Weaver et al., 2013, Patel et al. 2013) showed indications that KABs may be protective for some lower extremity injuries and associated with increased risk for others. Since KABs have become significantly more common in recent model year vehicles, we revisited these findings using the most recent available data.Methods: We compared injury rates below the knee, from the knee to the hip, and above the hip in years 2000-2015 of the National Automotive Sampling System, Crashworthiness Data System (NASS-CDS) and the Crash Injury Research and Engineering Network (CIREN). Injury rates were compared with matched analyses and with Bayesian multiple logistic regression.Results: Both analyses showed that KAB to have an Odds Ratio of approximately 0.6 for knee to hip injuries, with the Bayesian model strongly significant and the matched model borderline insignificant. In the Bayesian model, KAB was borderline significant for a decrease in above the waist injuries, while the matched model pointed toward a protective effect but was not significant. Both models pointed toward an increased risk of below knee injuries, but neither was statistically significant.Conclusions: Knee airbags may be protective for knee to hip injuries and above waist injuries. If KABs continue to be widely implemented in the vehicle fleet, the field should continue to monitor and evaluate below knee injuries.

BACKGROUND: Independent associations between chronic liver disease, MELD, and postoperative outcomes among patients selected for liver resection have not been completely established. We hypothesized independent associations between MELD, cirrhosis, and postoperative mortality. METHODS: Patient-level data from the targeted hepatectomy module and ACS NSQIP PUF during 2014–2015 were merged. Multivariable regression models with interaction effect between MELD and liver texture (normal vs congested/fatty vs cirrhotic) tested the independent effects of covariates on mortality and morbidity. RESULTS: 3,530 patients were included, of whom 668 patients (19%) had cirrhosis. ACS NSQIP defined mortality (3.9%vs1.1%) and morbidity (23.5%vs15.8%) were higher in patients with cirrhosis (both p