New Uses for Thromboelastography and Other Forms of Viscoelastic Monitoring in the Emergency Department: A Narrative Review.

Patients frequently visit the emergency department with conditions that place them at risk of worse outcomes when accompanied by coagulopathy. Routine tests of coagulation-prothrombin time, partial thromboplastin time, platelets, and fibrinogen-have shortcomings that limit their use in providing emergency care. One alternative is to investigate coagulation disturbance with viscoelastic monitoring (VEM), a coagulation test that measures the timing and strength of blood clot development in real time. VEM is widely used and studied in cardiac surgery, liver transplant surgery, anesthesia, and trauma. In this article, we review the technique of VEM and the biologic rationale of using it in addition to routine tests of coagulation in emergency clinical situations. Then, we review the evidence (or lack thereof) for using VEM in the diagnosis and treatment of specific conditions. Finally, we describe the limitations of the test and future directions for clinical use and research in emergency medicine.

Fluid-limiting treatment strategies among sepsis patients in the ICU: a retrospective causal analysis.

OBJECTIVE: In septic patients, multiple retrospective studies show an association between large volumes of fluids administered in the first 24 h and mortality, suggesting a benefit to fluid restrictive strategies. However, these studies do not directly estimate the causal effects of fluid-restrictive strategies, nor do their analyses properly adjust for time-varying confounding by indication. In this study, we used causal inference techniques to estimate mortality outcomes that would result from imposing a range of arbitrary limits ("caps") on fluid volume administration during the first 24 h of intensive care unit (ICU) care. DESIGN: Retrospective cohort study SETTING: ICUs at the Beth Israel Deaconess Medical Center, 2008-2012 PATIENTS: One thousand six hundred thirty-nine septic patients (defined by Sepsis-3 criteria) 18 years and older, admitted to the ICU from the emergency department (ED), who received less than 4 L fluids administered prior to ICU admission MEASUREMENTS AND MAIN RESULTS: Data were obtained from the Medical Information Mart for Intensive Care III (MIMIC-III). We employed a dynamic Marginal Structural Model fit by inverse probability of treatment weighting to obtain confounding adjusted estimates of mortality rates that would have been observed had fluid resuscitation volume caps between 4 L-12 L been imposed on the population. The 30-day mortality in our cohort was 17%. We estimated that caps between 6 and 10 L on 24 h fluid volume would have reduced 30-day mortality by - 0.6 to - 1.0%, with the greatest reduction at 8 L (- 1.0% mortality, 95% CI [- 1.6%, - 0.3%]). CONCLUSIONS: We found that 30-day mortality would have likely decreased relative to observed mortality under current practice if these patients had been subject to "caps" on the total volume of fluid administered between 6 and 10 L, with the greatest reduction in mortality rate at 8 L.

Later emergency provider shift hour is associated with increased risk of admission: a retrospective cohort study.

BACKGROUND: Understanding factors that drive admissions is critical to containing cost and optimising hospital operations. We hypothesised that, due to multiple factors, emergency physicians would be more likely to admit a patient seen later in their shift. METHODS: Retrospective study examining all patient visits at a large academic hospital from July 2010 to July 2016. Patients with missing data (n=191) were excluded. 294 031 emergency department (ED) visits were included in the final analysis. The exposure of interest was the time during the shift at which a patient was first evaluated by the clinician, and outcome was hospital admission. We used a generalised estimating equation with physician as the clustering level to adjust for patient age, gender, Emergency Severity Index (ESI, 1=most severe illness, 5=least severe illness) and 24 hours clock time. We also conducted a stratified analysis by three ESI categories. RESULTS: From the 294 031 ED visits, 5977 were seen in the last hour of the shift. Of patients seen in the last shift hour, 43% were admitted versus 39% seen at any other time during the shift. There was a significant association between being evaluated in the last hour (RR 1.03, 95% CI 1.01 to 1.06) and last quarter (RR 1.02, 1.01 to 1.03) of shift and the likelihood of admission. Patients with an ESI Score of 4-5 saw the largest effect sizes (RR 1.62, 0.996-2.635 for last hour and RR 1.24, 0.996-1.535 for last quarter) but these were not statistically significant. Additionally, there was a trend towards increased likelihood of admission later in shift; the relative risk of admission was 1.04 in hour 6, (1.02-1.05), 1.03 in hour 7 (1.01-1.05), 1.04 in hour 8 (1.01-1.06) and 1.06 in hour 9 (1.013-1.101). CONCLUSIONS: There is a small but significant association between a patient being evaluated later in an emergency physician's shift and their likelihood of being admitted to the hospital.

Intravenous fluid resuscitation is associated with septic endothelial glycocalyx degradation.

BACKGROUND: Intravenous fluids, an essential component of sepsis resuscitation, may paradoxically worsen outcomes by exacerbating endothelial injury. Preclinical models suggest that fluid resuscitation degrades the endothelial glycocalyx, a heparan sulfate-enriched structure necessary for vascular homeostasis. We hypothesized that endothelial glycocalyx degradation is associated with the volume of intravenous fluids administered during early sepsis resuscitation. METHODS: We used mass spectrometry to measure plasma heparan sulfate (a highly sensitive and specific index of systemic endothelial glycocalyx degradation) after 6 h of intravenous fluids in 56 septic shock patients, at presentation and after 24 h of intravenous fluids in 100 sepsis patients, and in two groups of non-infected patients. We compared plasma heparan sulfate concentrations between sepsis and non-sepsis patients, as well as between sepsis survivors and sepsis non-survivors. We used multivariable linear regression to model the association between volume of intravenous fluids and changes in plasma heparan sulfate. RESULTS: Consistent with previous studies, median plasma heparan sulfate was elevated in septic shock patients (118 [IQR, 113-341] ng/ml 6 h after presentation) compared to non-infected controls (61 [45-79] ng/ml), as well as in a second cohort of sepsis patients (283 [155-584] ng/ml) at emergency department presentation) compared to controls (177 [144-262] ng/ml). In the larger sepsis cohort, heparan sulfate predicted in-hospital mortality. In both cohorts, multivariable linear regression adjusting for age and severity of illness demonstrated a significant association between volume of intravenous fluids administered during resuscitation and plasma heparan sulfate. In the second cohort, independent of disease severity and age, each 1 l of intravenous fluids administered was associated with a 200 ng/ml increase in circulating heparan sulfate (p = 0.006) at 24 h after enrollment. CONCLUSIONS: Glycocalyx degradation occurs in sepsis and septic shock and is associated with in-hospital mortality. The volume of intravenous fluids administered during sepsis resuscitation is independently associated with the degree of glycocalyx degradation. These findings suggest a potential mechanism by which intravenous fluid resuscitation strategies may induce iatrogenic endothelial injury.

The Potential Role of Ultrasound in the Work-up of Appendicitis in the Emergency Department.

BACKGROUND: Acute appendicitis is common in the adult emergency department (ED). Computed tomography (CT) scan is frequently used to diagnose this condition, but ultrasound (US)-commonly used in pediatric diagnosis-may also have a role. OBJECTIVES: Review the clinical utility and define the frequency and diagnostic accuracy of US to diagnose appendicitis in an adult population in the ED setting. METHODS: Retrospective cohort study of patients who underwent appendiceal US in an academic, tertiary ED from July 2013-October 2015. RESULTS: There were 174 patients included, of which 39 (22%) had pathology-confirmed appendicitis. There were 25 patients who had an US scan that was positive for appendicitis, 146 (84%) were indeterminate, and 3 (1.7%) were negative. Among patients with a positive US, 25/25 (100%, 95% confidence interval [CI] 84-100%) had appendicitis, 32/146 (22%, 95% CI 16-29%) with an indeterminate US had appendicitis, and 0/3 (0%, 95% CI 0-6.2%) with a negative US had appendicitis. In the 28 definitive cases, US had a sensitivity of 64%, specificity of 2%, positive predictive value of 100%, and negative predictive value of 100%. The likelihood ratio positive and negative were 173 and 0, respectively. CONCLUSION: Our initial data suggest that an US that shows appendicitis seems to be reliable; however, a high prevalence of indeterminate studies limits the diagnostic utility as a universal approach in adult patients in the ED setting. Larger studies are needed to identify which patient populations would benefit from US as the initial imaging modality, what factors contribute to the large numbers of indeterminate results, and if any interventions may reduce the number of indeterminate results.

Behind the scenes: A medical natural language processing project.

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

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

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

A Framework for Tracking Former Patients in the Electronic Health Record Using an Educational Registry.

One challenge of contemporary medical education is that shorter lengths of stay and time-limited clerkships often interrupt a student's relationship with a patient before a diagnosis is made or treatment is completed, limiting the learning experience. Medical students sometimes use electronic health records (EHRs) to overcome these limitations. EHRs provide access to patients' future medical records, enabling students to track former patients across care venues to audit their diagnostic impressions and observe outcomes. While this activity has potential to improve clinical training, there is a risk of unintended harm to patients through loss of privacy. Students need guidance on how to perform this activity appropriately. This article describes an ethical framework for tracking using an "educational registry," a list of former patients housed within the EHR that one follows longitudinally for educational purposes. Guiding principles include obtaining permission from patients, having legitimate educational intent, and restricting review of records to those essential for training. This framework could serve as a foundation for institutions seeking to develop a policy on tracking former patients, and may facilitate research on the use of EHRs to improve medical education, such as reducing diagnostic error and promoting self-directed learning.

Outcomes of Ventilated Patients With Sepsis Who Undergo Interhospital Transfer: A Nationwide Linked Analysis.

OBJECTIVES: The outcomes of critically ill patients who undergo interhospital transfer are not well understood. Physicians assume that patients who undergo interhospital transfer will receive more advanced care that may translate into decreased morbidity or mortality relative to a similar patient who is not transferred. However, there is little empirical evidence to support this assumption. We examined country-level U.S. data from the Nationwide Readmissions Database to examine whether, in mechanically ventilated patients with sepsis, interhospital transfer is associated with a mortality benefit. DESIGN: Retrospective data analysis using complex survey design regression methods with propensity score matching. SETTING: The Nationwide Readmissions Database contains information about hospital admissions from 22 States, accounting for roughly half of U.S. hospitalizations; the database contains linkage numbers so that admissions and transfers for the same patient can be linked across 1 year of follow-up. PATIENTS: From the 2013 Nationwide Readmission Database Sample, 14,325,172 hospital admissions were analyzed. There were 61,493 patients with sepsis and on mechanical ventilation. Of these, 1,630 patients (2.7%) were transferred during their hospitalization. A propensity-matched cohort of 1,630 patients who did not undergo interhospital transfer was identified. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: The exposure of interest was interhospital transfer to an acute care facility. The primary outcome was hospital mortality; the secondary outcome was hospital length of stay. The propensity score included age, gender, insurance coverage, do not resuscitate status, use of renal replacement therapy, presence of shock, and Elixhauser comorbidities index. After propensity matching, interhospital transfer was not associated with a difference in in-hospital mortality (12.3% interhospital transfer vs 12.7% non-interhospital transfer; p = 0.74). However, interhospital transfer was associated with a longer total hospital length of stay (12.8 d interquartile range, 7.7-21.6 for interhospital transfer vs 9.1 d interquartile range, 5.1-17.0 for non-interhospital transfer; p < 0.01). CONCLUSIONS: Patients with sepsis requiring mechanical ventilation who underwent interhospital transfer did not have improved outcomes compared with a cohort with matched characteristics who were not transferred. The study raises questions about the risk-benefit profile of interhospital transfer as an intervention.

Racial and Geographic Disparities in Interhospital ICU Transfers.

OBJECTIVES: Interhospital transfer, a common intervention, may be subject to healthcare disparities. In mechanically ventilated patients with sepsis, we hypothesize that disparities not disease related would be found between patients who were and were not transferred. DESIGN: Retrospective cohort study. SETTING: Nationwide Inpatient Sample, 2006-2012. PATIENTS: Patients over 18 years old with a primary diagnosis of sepsis who underwent mechanical ventilation. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We obtained age, gender, length of stay, race, insurance coverage, do not resuscitate status, and Elixhauser comorbidities. The outcome used was interhospital transfer from a small- or medium-sized hospital to a larger acute care hospital. Of 55,208,382 hospitalizations, 46,406 patients met inclusion criteria. In the multivariate model, patients were less likely to be transferred if the following were present: older age (odds ratio, 0.98; 95% CI, 0.978-0.982), black race (odds ratio, 0.79; 95% CI, 0.70-0.89), Hispanic race (odds ratio, 0.79; 95% CI, 0.69-0.90), South region hospital (odds ratio, 0.79; 95% CI, 0.72-0.88), teaching hospital (odds ratio, 0.31; 95% CI, 0.28-0.33), and do not resuscitate status (odds ratio, 0.19; 95% CI, 0.15-0.25). CONCLUSIONS: In mechanically ventilated patients with sepsis, we found significant disparities in race and geographic location not explained by medical diagnoses or illness severity.

Assessment of Intensive Care Unit Laboratory Values That Differ From Reference Ranges and Association With Patient Mortality and Length of Stay.

Importance: Laboratory data are frequently collected throughout the care of critically ill patients. Currently, these data are interpreted by comparison with values from healthy outpatient volunteers. Whether this is the most useful comparison has yet to be demonstrated. Objectives: To understand how the distribution of intensive care unit (ICU) laboratory values differs from the reference range, and how these distributions are related to patient outcomes. Design, Setting, and Participants: Cross-sectional study of a large critical care database, the Medical Information Mart for Intensive Care database, from January 1, 2001, to October 31, 2012. The database is collected from ICU data from a large tertiary medical center in Boston, Massachusetts. The data are collected from medical, cardiac, neurologic, and surgical ICUs. All patients in the database from all ICUs for 2001 to 2012 were included. Common laboratory measurements over the time window of interest were sampled. The analysis was conducted from March to June 2017. Main Outcomes and Measures: The overlapping coefficient and Cohen standardized mean difference between distributions were calculated, and kernel density estimate visualizations for the association between laboratory values and the probability of death or quartile of ICU length of stay were created. Results: Among 38 605 patients in the ICU (21 852 [56.6%] male; mean [SD] age, 74.5 [55.1] years), 8878 (23%) had the best outcome (ICU survival, shortest quartile length of stay) and 3090 (8%) had the worst outcome (ICU nonsurvival). Distribution curves based on ICU data differed significantly from the hospital standard range (mean [SD] overlapping coefficient, 0.51 [0.32-0.69]). All laboratory values for the best outcome group differed significantly from those in the worst outcome group. Both the best and worst outcome group curves revealed little overlap with and marked divergence from the reference range. Conclusions and Relevance: The standard reference ranges obtained from healthy volunteers differ from the analogous range generated from data from patients in intensive care. Laboratory data interpretation may benefit from greater consideration of clinically contextual and outcomes-related factors.

Diagnostic and Therapeutic Nanoparticles in Cardiovascular Diseases.

Cardiovascular diseases are the major cause of non-communicable illness in both developing and developed nations, representing 30% of global deaths. New therapeutic approaches are desperately needed. Nanomedicine represents one such approach, and involves using molecular entities on the scale of 10-150 nanometers, for purposes of diagnosing, treating, and preventing disease. This review provides a basic overview of nanotechnology, then reviews specific applications of nanotechnology to cardiovascular diseases. Most research has focused on diagnosing and treating atherosclerosis using nanoparticles (NPs). However, researchers are beginning to study NPs for use in acute coronary syndromes, revascularization procedures, and heart failure. Antimicrobial NPs directed at biofilms likely have applicability to identifying and treating endocarditis. Despite the large disease burden of cardiovascular diseases, there are fewer researchers and less funding being applied to this research. Additional investment in NP therapies would pay great dividends once these therapies come of age.

Should medical students track former patients in the electronic health record? An emerging ethical conflict.

Medical students are increasingly using electronic health records (EHRs) in clerkships, and medical educators should seek opportunities to use this new technology to improve training. One such opportunity is the ability to "track" former patients in the EHR, defined as following up on patients in the EHR for educational purposes for a defined period of time after they have left one's direct care. This activity offers great promise in clinical training by enabling students to audit their diagnostic impressions and follow the clinical history of illness in a manner not possible in the era of paper charting. However, tracking raises important questions about the ethical use of protected health information, including concerns about compromising patient autonomy, resulting in a conflict between medical education and patient privacy. The authors offer critical analysis of arguments on both sides and discuss strategies to balance the ethical conflict by optimizing outcomes and mitigating harms. They observe that tracking improves training, thus offering long-lasting benefits to society, and is supported by the principle of distributive justice. They conclude that students should be permitted to track for educational purposes, but only with defined limits to safeguard patient autonomy, including obtaining permission from patients, having legitimate educational intent, and self-restricting review of records to those essential for training. Lastly, the authors observe that this conflict will become increasingly important with completion of the planned Nationwide Health Information Network and emphasize the need for national guidelines on tracking patients in an ethically appropriate manner.

MR imaging enables measurement of therapeutic nanoparticle uptake in rat N1-S1 liver tumors after nanoablation.

PURPOSE: To test the hypothesis that magnetic resonance (MR) imaging can quantify intratumoral superparamagnetic iron oxide (SPIO) nanoparticle uptake after nanoablation. MATERIALS AND METHODS: SPIO nanoparticles functionalized with doxorubicin were synthesized. N1-S1 hepatomas were successfully induced in 17 Sprague-Dawley rats distributed into three dosage groups. Baseline tumor R2* values (the reciprocal of T2*) were determined using 7-tesla (T) MR imaging. After intravenous injection of SPIO nanoparticles, reversible electroporation (1,300 V/cm, 8 pulses, 100-µs pulse duration) was applied. Imaging of rats was performed to determine tumor R2* values after the procedure, and change in R2* (ΔR2*) was calculated. Inductively coupled plasma mass spectrometry was used to determine intratumoral iron (Fe) concentration after the procedure, which served as a proxy for SPIO nanoparticle uptake. Mean tumor Fe concentration [Fe] and ΔR2* for each subject were assessed for correlation with linear regression, and mean [Fe] for each dosage group was compared with analysis of variance. RESULTS: ΔR2* significantly correlated with tumor SPIO nanoparticle uptake after nanoablation (r = 0.50, P = .039). On average, each 0.1-ms(-1) increase in R2* corresponded to a 0.1394-mM increase in [Fe]. There was no significant difference in mean SPIO nanoparticle uptake among dosage groups (P = .57). CONCLUSIONS: Intratumoral SPIO nanoparticle uptake after nanoablation can be successfully quantified noninvasively with 7-T MR imaging. Imaging can be used as a method to estimate localized drug delivery after nanoablation.

Seven-tesla magnetic resonance imaging accurately quantifies intratumoral uptake of therapeutic nanoparticles in the McA rat model of hepatocellular carcinoma: preclinical study in a rodent model.

OBJECTIVES: After inducing McA tumors in Sprague-Dawley rats (McA-SD), the following hypotheses were tested: first, that hypervascular McA tumors grown in Sprague-Dawley rats provide a suitable platform to investigate drug delivery; and second, that high-field MRI can be used to measure intratumoral uptake of DOX-SPIOs. MATERIALS AND METHODS: McA cells were implanted into the livers of 18 Sprague-Dawley rats. In successfully inoculated animals, 220-µL DOX-SPIOs were delivered to tumors via the intravenous or intra-arterial route. Pretreatment and posttreatment T2*-weighted images were obtained using 7-T MRI, and change in R2* value (ΔR2*) was obtained from mean signal intensities of tumors in these images. Tumor iron concentration ([Fe]), an indicator of DOX-SPIO uptake, was measured using mass spectroscopy. The primary outcome variable was the Pearson correlation between ΔR2* and [Fe]. RESULTS: Tumors grew successfully in 13 of the 18 animals (72%). Mean (SD) maximum tumor diameter was 0.83 (0.25) cm. The results of phantom studies revealed a strong positive correlation between ΔR2* and [Fe], with r = 0.98 (P < 0.01). The results of in vivo drug uptake studies demonstrated a positive correlation between ΔR2* and [Fe], with r = 0.72 (P = 0.0004). CONCLUSIONS: The McA tumors grown in the Sprague-Dawley rats demonstrated uptake of nanoparticle-based therapeutic agents. Magnetic resonance imaging quantification of intratumoral uptake strongly correlated with iron concentrations in pathological specimens, suggesting that MRI may be used to quantify uptake of iron-oxide nanotherapeutics.