Leveraging Electronic Health Record Data and Measuring Interdependence in the Era of Precision Education and Assessment.

PURPOSE: The era of precision education is increasingly leveraging electronic health record (EHR) data to assess residents' clinical performance. But precision in what the EHR-based resident performance metrics are truly assessing is not fully understood. For instance, there is limited understanding of how EHR-based measures account for the influence of the team on an individual's performance-or conversely how an individual contributes to team performances. This study aims to elaborate on how the theoretical understandings of supportive and collaborative interdependence are captured in residents' EHR-based metrics. METHOD: Using a mixed methods study design, the authors conducted a secondary analysis of 5 existing quantitative and qualitative datasets used in previous EHR studies to investigate how aspects of interdependence shape the ways that team-based care is provided to patients. RESULTS: Quantitative analyses of 16 EHR-based metrics found variability in faculty and resident performance (both between and within resident). Qualitative analyses revealed that faculty lack awareness of their own EHR-based performance metrics, which limits their ability to act interdependently with residents in an evidence-informed fashion. The lens of interdependence elucidates how resident practice patterns develop across residency training, shifting from supportive to collaborative interdependence over time. Joint displays merging the quantitative and qualitative analyses showed that residents are aware of variability in faculty's practice patterns and that viewing resident EHR-based measures without accounting for the interdependence of residents with faculty is problematic, particularly within the framework of precision education. CONCLUSIONS: To prepare for this new paradigm of precision education, educators need to develop and evaluate theoretically robust models that measure interdependence in EHR-based metrics, affording more nuanced interpretation of such metrics when assessing residents throughout training.

Descriptive analysis of emergency medical services 72-hour repeat patient encounters in a single, Urban Agency.

INTRODUCTION: Emergency department unscheduled return visits within 72-h of discharge, called a "bounceback", have been used as a metric of quality of care. We hypothesize that specific demographics and dispositions may be associated with Emergency Medical Services (EMS) 72-h bouncebacks. METHODS: For all patient encounters within one calendar year from a large, urban EMS agency, we recorded demographics (name, date of birth, race, gender), primary impression, disposition, and vital signs for EMS encounters. A bounceback was defined as a patient, identified by matching first name, last name and date of birth, with more than one EMS encounter within 72 h. We performed descriptive statistics for patients that did and did not have a subsequent bounceback using median (interquartile range) and Wilcoxon Rank Sum test for age and frequency (percent) and chi square test for gender, race and run disposition. For patients with a bounceback, we describe the frequency and percentage of EMS professional primary impressions on initial encounter. RESULTS: 98,043 encounters from January 1, 2021 to December 31, 2021, were analyzed. The median age was 50 years (IQR 32-65); 49.4% (46,147) were female and 50.7% (47,376) were White patients. 3951 encounters had a subsequent bounceback, and compared to those without bouncebacks, they were more often male patients (58.7% versus 50.2%, p < 0.001) and more commonly not transported (22.3% versus 15.5%, p < 0.001). A multivariable logistic regression model estimated the odds of bounceback were lower for females [OR 0.64 (95% CI 0.61-0.68)], Asian and Latino patients compared to White patients [OR 0.33 (95% CI 0.21-0.53) and 0.42 (95% CI 0.34-0.51)], respectively, no significant difference for Black patients compared to White patients, and higher for non-transported patients [OR 1.25 (95% CI 1.16-1.34)]. The The most common EMS primary impression for initial and subsequent encounters was mental health [576 (14.7%) and 944 (17.0%), respectively]. For subsequent encounters, the primary impression was cardiac arrest or death in 67 (1.2%) of cases. CONCLUSION: Bouncebacks were common in this single year study of a high-volume urban EMS agency. Male and non-transported patients most often experienced bouncebacks. The most common primary impression for encounters with bounceback was mental health related. Out-of-hospital cardiac arrest occurred in 1 % of bounceback cases. Further study is necessary to understand the effect on patient-centered outcomes.

Patient Demographics Are Associated with Differences in Prehospital Pain Management among Trauma Patients.

OBJECTIVE: Disparities have been observed in the treatment of pain in emergency department patients. However, few studies have evaluated such disparities in emergency medical services (EMS). We describe pain medication administration for trauma indications in an urban EMS system and how it varies with patient demographics. METHODS: We performed a retrospective review of the electronic medical records of adult patients transported for isolated trauma (without accompanying medical complaint) from 1/1/18 to 6/30/2020 by a third service EMS agency in a major United States metropolitan area. We performed descriptive statistics on epidemiology, type of pain medications administered, and pain scores. Kruskall-Wallis and chi-square or Fisher's exact tests were used to compare continuous and categorical variables, respectively. We constructed a logistic regression model to estimate the odds of nontreatment of pain by age, race, sex, transport interval, pain score, and Glasgow Coma Scale (GCS) score for patients with pain scores of at least four on a one to ten scale, the threshold for pain treatment per the EMS protocol. RESULTS: Of 32,463 EMS patients with traumatic injuries included in the analysis, 40% (12,881/32,463) were African American, 50% (16,284/32,463) were female, the median age was 27 years (IQR 45-64), and the median initial pain score was 5 (IQR 2-8). Fifteen percent (4,989/32,463) received any analgesic. Initial pain scores were significantly higher for African American and female patients. African American patients were less likely to receive analgesia compared to White and Hispanic patients (19% versus 25% and 23%, respectively, p < 0.0001). Adjusting for age, pain score, transport interval, and GCS, African American compared to White, and female compared to male patients were less likely to be treated for pain, OR 1.59 (95% CI 1.47-1.72) and OR 1.20 (95% CI 1.11-1.28), respectively. CONCLUSION: Among patients with isolated traumatic injuries treated in a single, urban EMS system, African American and female patients were less likely to receive analgesia than White or male patients. Analgesics were given to a small percentage of patients who were eligible for treatment by protocol, and intravenous opioids were used in the vast majority patients who received treatment.

Emergency Medical Services Clinicians Have a High Prevalence of Metabolic Syndrome.

BACKGROUND: Metabolic syndrome is a constellation of risk factors associated with the development of cardiovascular disease and increased all-cause mortality. Data examining the prevalence of metabolic syndrome among emergency medical services (EMS) clinicians are limited. METHODS: We conducted a cross-sectional study of EMS clinicians and firefighters from three fire departments with transport-capable EMS divisions. Data were collected from compulsory annual physical exams for 2021 that included age, sex, race, body mass index (BMI), waist circumference, blood pressure, cholesterol levels, and hemoglobin A1c level. These data were used to determine the prevalence of meeting metabolic syndrome criteria. We calculated descriptive statistics of demographics, anthropometrics, and metabolic syndrome criteria for EMS clinicians and firefighters. We used chi-square tests to compare the proportion of EMS clinicians and firefighters meeting criteria for the whole group and among age groups of <40 years old, 40 to 59 years old, and ≥60 years old. We used logistic regression to estimate the odds of meeting criteria in EMS clinicians compared to firefighters, adjusted for age, sex, race, and BMI. RESULTS: We reviewed data for 65 EMS clinicians and 239 firefighters. For the combined cohort, 13.2% (40/304) were female and 95.1% (289/304) were White. The median age for EMS clinicians was 34 years versus 45 years in firefighters (p < 0.0001). Metabolic syndrome criteria were met in 27.3% (83/304) of the entire group. The prevalence of meeting criteria among EMS clinicians and firefighters was 33.9% (22/65) and 25.5% (61/239), respectively (p = 0.18). Of the participants who were younger than age 40, 36.6% (15/41) of EMS clinicians versus 9.1% (7/74) of firefighters met criteria for metabolic syndrome (p < 0.001). EMS clinicians had significantly higher odds of meeting criteria [OR 4.62 (p = 0.001)] compared to firefighters when adjusted for age, sex, race, and BMI. CONCLUSION: EMS clinicians had a high prevalence of metabolic syndrome at an early age, and had a higher adjusted odds of having metabolic syndrome compared to firefighters.

Factors Predicting Misidentification of Acute Ischemic Stroke and Large Vessel Occlusion by Paramedics.

The emergence of thrombectomy for large vessel occlusions has increased the importance of accurate prehospital identification and triage of acute ischemic stroke (AIS). Despite available clinical scores, prehospital identification is suboptimal. Our objective was to improve the sensitivity of prehospital AIS identification by combining dispatch information with paramedic impression. We performed a retrospective cohort review of emergency medical services and hospital records of all patients for whom a stroke alert was activated in 1 urban, academic emergency department from January 1, 2018, to December 31, 2019. Using admission diagnosis of acute stroke as outcome, we calculated the sensitivity and specificity of dispatch and paramedic impression in identifying AIS and large vessel occlusion. We identified factors that, when included together, would improve the sensitivity of prehospital AIS identification. Two-hundred twenty-six stroke alerts were activated by emergency department physicians after transport by Indianapolis emergency medical services. Forty-four percent (99/226) were female, median age was 58 years (interquartile range, 50-67 years), and median National Institutes of Health Stroke Scale was 6 (interquartile range, 2-12). Paramedics demonstrated superior sensitivity (59% vs. 48%) but inferior specificity (56% vs. 73%) for detection of stroke as compared with dispatch. A strategy incorporating dispatch code of stroke, or paramedic impression of altered mental status or weakness in addition to stroke, would be 84% sensitive and 27% specific for identification of stroke. To optimize rapid and sensitive stroke detection, prehospital systems should consider inclusion of patients with dispatch code of stroke and provider impression of altered mental status or generalized weakness.

Functional movement screen did not predict musculoskeletal injury among emergency medical services professionals.

BACKGROUND: Emergency Medical Services (EMS) professionals frequently experience job-related injuries, most commonly overexertion or movement injuries. Data on injury reduction in EMS professionals is limited. The Functional Movement Screen (FMS) is a movement analysis tool suggested to predict musculoskeletal injury, but it has not previously been evaluated for EMS professionals. OBJECTIVE: To evaluate the effectiveness of the FMS to predict musculoskeletal injury among EMS professionals. METHODS: In October 2014, EMS professionals employed in an urban third-service EMS agency volunteered to participate in FMS administered by certified screeners. Age, sex, height and weight were recorded. After screening, participants were instructed on exercises to correct movement deficiencies. We reviewed recorded injuries from 2013 to 2016. We performed descriptive statistics. With logistic regression modeling, we described factors that predicted musculoskeletal injury. We generated a receiver operating curve (ROC) for FMS prediction of musculoskeletal injury. RESULTS: 147 of 240 full-time employees participated in the FMS. Participants' mean age was 33.7 years (SD = 9.6) and the majority (65%) were male. The median initial FMS score was 14 (IQR 11-16). Area under the ROC curve was 0.603 (p = 0.213) for FMS ability to predict any musculoskeletal injury within two years. Female sex was associated higher odds of injury (OR 3.98, 95% CI 1.61-9.80). Increasing age, body mass index (BMI) category, and FMS score≤14 did not predict musculoskeletal injury. CONCLUSION: The FMS did not predict musculoskeletal injury among EMS professionals.

Increased weight in patients with time-sensitive diagnosis is associated with longer prehospital on-scene times.

BACKGROUND: Obesity is a growing epidemic associated with higher rates of metabolic disease, heart disease and all-cause mortality. Heavier patients may require more advanced resources and specialized equipment. We hypothesize that increasing patient weight will be associated with longer prehospital on-scene times. METHODS: We reviewed electronic patient care records for patients transported by two urban 9-1-1 emergency medical services (EMS) agencies. We collected age, sex, estimated patient weight, vital signs (systolic blood pressure, heart rate, pulse oximetry), provider impression, method of moving patient to ambulance, and on-scene times. We selected patients with time-sensitive diagnoses of stroke, ST-segment elevation myocardial infarction (STEMI), and trauma and compared on-scene times for patients who weighed above or below 300 pounds. We performed descriptive statistics, Mann-Whitney U tests for continuous variables and Chi-square tests for discrete variables. We constructed a generalized linear model to determine the effect of patient weight adjusted for covariates. RESULTS: For a three-year period (May 1, 2018 to April 30, 2021) 48,203 patients were transported with an EMS impression of stroke, ST-segment elevation myocardial infarction (STEMI), and trauma. 23,654 (49.1%) patients were female, and the median age was 52 (IQR 34-68) years. The median weight was 175.0 (IQR 150.0-205.0) pounds. Patients above a dichotomous weight categorization of 300 pounds experienced a longer median scene time with any time-sensitive diagnosis (12.6 versus 11.9 min p < 0.001), STEMI (16.0 versus 13.1 min, p = 0.014) and blunt trauma (12.6 versus 11.9 min, p < 0.001)). They were more likely to be hypoxic (p < 0.001) and more likely to experience cardiac arrest (p < 0.001). They were less likely to walk to the ambulance (22.1% versus 32.2%, p < 0.001). CONCLUSION: Patient weight above 300 pounds was associated with significantly longer on-scene time. These patients were more likely to be hypoxic, sustain a cardiac arrest, and less likely to walk to the ambulance.

Examination of physician characteristics in opioid prescribing in the emergency department.

AIM: We aimed to better understand variation in opioid prescribing practices by investigating physician factors at one academic suburban Emergency Department (ED). METHODS: We retrospectively reviewed the electronic medical records of all patients given opioid prescriptions in the Stanford Health Care ED from 2009 to 2018. We described the variation in opioid prescriptions over time from 2009 to 2018, then dove deeper into a single year (July 1, 2017 to July 1, 2018). We described the number and type of opioid prescriptions at discharge and variation in attending physician opioid prescribing patterns using independent t-tests and a Fischer's exact test. RESULTS: From 2009 to 2018, 657,037 patient visits occurred; 92,612 (14.1%) opioid prescriptions were written. Opioid prescriptions increased from 2009, peaked in 2015, then decreased. Individual providers wrote opioid prescriptions for 1 to 17% of their discharged patients. There was no significant difference in opioid prescribing based on provider gender (p = 0.456), fellow or attending status (p = 0.390), residency completed at Stanford Hospital (p = 0.593), residency completed within California (p = 0.493), or residency completed after 2010 (p = 0.589). Of the 371 providers who wrote opioid prescriptions from 2009 through 2018, 120 wrote prescriptions for patients who had already received at least three opioid prescriptions in the same year from the same department. CONCLUSION: This study could inform policymakers by describing patterns of variation in opioid prescribing over time and between providers. Although we did see significant differences in prescribing patterns from one provider to the next, those were not explained by the factors we examined. Further studies could investigate factors such as provider experience with pain and addiction, bias regarding particular pathologies, and concern around patient satisfaction scores.

Out-of-hospital cardiac arrest volumes and characteristics during the COVID-19 pandemic.

AIM: The COVID-19 pandemic has significantly impacted Emergency Medical Services (EMS) operations throughout the country. Some studies described variation in total volume of out-of-hospital cardiac arrests (OHCA) during the pandemic. We aimed to describe the changes in volume and characteristics of OHCA patients and resuscitations in one urban EMS system. METHODS: We performed a retrospective cohort analysis of all recorded atraumatic OHCA in Marion County, Indiana, from January 1, 2019 to June 30, 2019 and from January 1, 2020 to June 30, 2020. We described patient, arrest, EMS response, and survival characteristics. We performed paired and unpaired t-tests to evaluate the changes in those characteristics during COVID-19 as compared to the prior year. Data were matched by month to control for seasonal variation. RESULTS: The total number of arrests increased from 884 in 2019 to 1034 in 2020 (p = 0.016). Comparing 2019 to 2020, there was little difference in age [median 62 (IQR 59-73) and 60 (IQR 47-72), p = 0.086], gender (38.5% and 39.8% female, p = 0.7466, witness to arrest (44.3% and 39.6%, p = 0.092), bystander AED use (10.1% and 11.4% p = 0.379), bystander CPR (48.7% and 51.4%, p = 0.242). Patients with a shockable initial rhythm (19.2% and 15.4%, p = 0.044) both decreased in 2020, and response time increased by 18 s [6.0 min (IQR 4.5-7.7) and 6.3 min (IQR 4.7-8.0), p = 0.008]. 47.7% and 54.8% (p = 0.001) of OHCA patients died in the field, 19.7% and 19.3% (p = 0.809) died in the Emergency Department, 21.8% and 18.5% (p = 0.044) died in the hospital, 10.8% and 7.4% (p = 0.012) were discharged from the hospital, and 9.3% and 5.9% (p = 0.005) were discharged with Cerebral Performance Category score ≤ 2. CONCLUSION: Total OHCA increased during the COVID-19 pandemic when compared with the prior year. Although patient characteristics were similar, initial shockable rhythm, and proportion of patients who died in the hospital decreased during the pandemic. Further investigation will explore etiologies of those findings.

OpenMRS as an emergency EMR-How we used a global good to create an emergency EMR in a week.

BACKGROUND: As the coronavirus pandemic progressed through the United States, Indianapolis Emergency Medical Services (IEMS) identified a gap between the health system capacity and the projected need to support an overwhelmed health care system. In addressing emergencies or special cases, each medical institution in a metropolitan area typically has a siloed process for capturing emergency patient records. These approaches vary in technical capabilities and may include use of an electronic medical record system (EMR) or a hybrid paper/EMR process. Given the projected volume of patients for the COVID-19 pandemic and the proposed multi-institutional team approach needed in case of significant provider illness, IEMS sought a simple, efficient, consolidated EMR solution to support planning for the potential capacity gap. IEMS approached Regenstrief Institute (RI), an established partner with experience in supporting OpenMRS, a global good EMR platform that had been deployed in multiple settings globally. OBJECTIVE: The purpose of this project was to determine if OpenMRS, a global good, could be used to quickly stand up a system that would meet the needs for health emergency data collection and reporting. DESIGN AND IMPLEMENTATION METHODS: The team used an "all hands on deck" approach, bringing together technical and subject matter experts, and a human-centered and iterative process to ensure the system met the key needs of IEMS. The OpenMRS Reference Application was adapted to the specific need and deployed as Docker containers to servers within the Indiana Health Information Exchange. PROJECT OUTCOMES AND LESSONS LEARNED: In less than two weeks, the Regenstrief team was able to install, configure and set up a working version of OpenMRS to support the desired electronic record requirements for the IEMS disaster field clinics. Using a human-centered approach, the RI team developed, tested, and released a user-friendly, installation-ready solution complete with an end user manual and a base support plan. IEMS and RI are sharing this approach to demonstrate how a global good can quickly generate a solution for COVID-19 and other disaster responses. CONCLUSIONS: Open source global goods can rapidly be adapted to meet local needs in an emergency. OpenMRS can be adapted to meet the needs of basic emergency medical services registration, triage, and basic data collection.

Validation of the NUE Rule to Predict Futile Resuscitation of Out-of-Hospital Cardiac Arrest.

AIM: We validated the NUE rule, using three criteria (Non-shockable initial rhythm, Unwitnessed arrest, Eighty years or older) to predict futile resuscitation of patients with out-of-hospital cardiac arrest (OHCA). METHODS: We performed a retrospective cohort analysis of all recorded OHCA in Marion County, Indiana, from January 1, 2014 to December 31, 2019. We described patient, arrest, and emergency medical services (EMS) response characteristics, and assessed the performance of the NUE rule in identifying patients unlikely to survive to hospital discharge. RESULTS: From 2014 to 2019, EMS responded to 4370 patients who sustained OHCA. We excluded 329 (7.5%) patients with incomplete data. Median patient age was 62 years (IQR 49 - 73), 1599 (39.6%) patients were female, and 1728 (42.8%) arrests were witnessed. The NUE rule identified 290 (7.2%) arrests, of whom none survived to hospital discharge. CONCLUSION: In external validation, the NUE rule (Non-shockable initial rhythm, Unwitnessed arrest, Eighty years or older) correctly identified 7.2% of OHCA patients unlikely to survive to hospital discharge. The NUE rule could be used in EMS protocols and policies to identify OHCA patients very unlikely to benefit from aggressive resuscitation.

Variations in the California Emergency Medical Services Response to Opioid Use Disorder.

INTRODUCTION: Opioids contributed to over 300,000 deaths in the United States in the past 10 years. Most research on drug use occurs in clinics or hospitals; few studies have evaluated the impact of opioid use on emergency medical services (EMS) or the EMS response to opioid use disorder (OUD). This study describes the perceived burden of disease, data collection, and interventions in California local EMS agencies (LEMSA). METHODS: We surveyed medical directors of all 33 California LEMSAs with 25 multiple-choice and free-answer questions. Results were collected in RedCap and downloaded into Excel (Microsoft Corporation, Redmond WA). This study was exempt from review by the Alameda Health System - Highland Hospital Institutional Review Board. RESULTS: Of the 33 California LEMSAs, 100% responded, all indicating that OUD significantly affects their patients. Most (91%) had specific protocols directing care of those patients and repeat naloxone dosing. After naloxone administration, none permitted release to law enforcement custody, 6% permitted patient refusal of care, and 45% directed base hospital contact for refusal of care. Few protocols directed screening or treatment of OUD or withdrawal symptoms. Regular data collection occurred in 76% of LEMSAs, with only 48% linking EMS data with hospital or coroner outcomes. In only 30% did the medical director oversee regular quality improvement meetings. Of respondents, 64% were aware of public health agency-based outreach programs and 42% were aware of emergency department BRIDGE programs (Medication Assisted Treatment and immediate referral). Only 9% oversaw naloxone kit distribution (all under the medical director), and 6% had EMS-based outreach programs. In almost all (94%), law enforcement officers carried naloxone and administered it anywhere from a few times a year to greater than 200 in one LEMSA. CONCLUSION: This study represents an important description of EMS medical directors' approaches to the impact of OUD as well as trends in protocols and interventions to treat and prevent overdoses. Through this study, we can better understand the variable response to patients with OUD across California.

Acetazolamide Treatment Prevents Redistribution of Astrocyte Aquaporin 4 after Murine Traumatic Brain Injury.

After traumatic brain injury (TBI), multiple ongoing processes contribute to worsening and spreading of the primary injury to create a secondary injury. One major process involves disrupted fluid regulation to create vascular and cytotoxic edema in the affected area. Although understanding of factors that influence edema is incomplete, the astrocyte water channel Aquaporin 4 (AQP4) has been identified as an important mediator and therefore attractive drug target for edema prevention. The FDA-approved drug acetazolamide has been administered safely to patients for years in the United States. To test whether acetazolamide altered AQP4 function after TBI, we utilized in vitro and in vivo models of TBI. Our results suggest that AQP4 localization is altered after TBI, similar to previously published reports. Treatment with acetazolamide prevented AQP4 reorganization, both in human astrocyte in vitro and in mice in vivo. Moreover, acetazolamide eliminated cytotoxic edema in our in vivo mouse TBI model. Our results suggest a possible clinical role for acetazolamide in the treatment of TBI.

A simple decision rule predicts futile resuscitation of out-of-hospital cardiac arrest.

AIM: Resuscitation of cardiac arrest involves invasive and traumatic interventions and places a large burden on limited EMS resources. Our aim was to identify prehospital cardiac arrests for which resuscitation is extremely unlikely to result in survival to hospital discharge. METHODS: We performed a retrospective cohort analysis of all cardiac arrests in San Mateo County, California, for which paramedics were dispatched, from January 1, 2015 to December 31, 2018, using the Cardiac Arrest Registry to Enhance Survival (CARES) database. We described characteristics of patients, arrests, and EMS responses, and used recursive partitioning to develop decision rules to identify arrests unlikely to survive to hospital discharge, or to survive with good neurologic function. RESULTS: From 2015-2018, 1750 patients received EMS dispatch for cardiac arrest in San Mateo County. We excluded 44 patients for whom resuscitation was terminated due to DNR directives. Median age was 69 years (IQR 57-81), 563 (33.0%) patients were female, 816 (47.8%) had witnessed arrests, 651 (38.2%) received bystander CPR, 421 (24.7%) had an initial shockable rhythm, and 1178 (69.1%) arrested at home. A simple rule (non-shockable initial rhythm, unwitnessed arrest, and age 80 or greater) excludes 223 (13.1%) arrests, of whom none survived to hospital discharge. CONCLUSION: A simple decision rule (non-shockable rhythm, unwitnessed arrest, age ≥ 80) identifies arrests for which resuscitation is futile. If validated, this rule could be applied by EMS policymakers to identify cardiac arrests for which the trauma and expense of resuscitation are extremely unlikely to result in survival.

Acute Stroke: Current Evidence-based Recommendations for Prehospital Care.

INTRODUCTION: In the United States, emergency medical services (EMS) protocols vary widely across jurisdictions. We sought to develop evidence-based recommendations for the prehospital evaluation and treatment of a patient with a suspected stroke and to compare these recommendations against the current protocols used by the 33 EMS agencies in the state of California. METHODS: We performed a literature review of the current evidence in the prehospital treatment of a patient with a suspected stroke and augmented this review with guidelines from various national and international societies to create our evidence-based recommendations. We then compared the stroke protocols of each of the 33 EMS agencies for consistency with these recommendations. The specific protocol components that we analyzed were the use of a stroke scale, blood glucose evaluation, use of supplemental oxygen, patient positioning, 12-lead electrocardiogram (ECG) and cardiac monitoring, fluid assessment and intravenous access, and stroke regionalization. RESULTS: Protocols across EMS agencies in California varied widely. Most used some sort of stroke scale with the majority using the Cincinnati Prehospital Stroke Scale (CPSS). All recommended the evaluation of blood glucose with the level for action ranging from 60 to 80 mg/dL. Cardiac monitoring was recommended in 58% and 33% recommended an ECG. More than half required the direct transport to a primary stroke center and 88% recommended hospital notification. CONCLUSION: Protocols for a patient with a suspected stroke vary widely across the state of California. The evidence-based recommendations that we present for the prehospital diagnosis and treatment of this condition may be useful for EMS medical directors tasked with creating and revising these protocols.

Endothelial cells downregulate apolipoprotein D expression in mural cells through paracrine secretion and Notch signaling.

Endothelial and mural cell interactions are vitally important for proper formation and function of blood vessels. These two cell types communicate to regulate multiple aspects of vessel function. In studying genes regulated by this interaction, we identified apolipoprotein D (APOD) as one gene that is downregulated in mural cells by coculture with endothelial cells. APOD is a secreted glycoprotein that has been implicated in governing stress response, lipid metabolism, and aging. Moreover, APOD is known to regulate smooth muscle cells and is found in abundance within atherosclerotic lesions. Our data show that the regulation of APOD in mural cells is bimodal. Paracrine secretion by endothelial cells causes partial downregulation of APOD expression. Additionally, cell contact-dependent Notch signaling plays a role. NOTCH3 on mural cells promotes the downregulation of APOD, possibly through interaction with the JAGGED-1 ligand on endothelial cells. Our results show that NOTCH3 contributes to the downregulation of APOD and by itself is sufficient to attenuate APOD transcript expression. In examining the consequence of decreased APOD expression in mural cells, we show that APOD negatively regulates cell adhesion. APOD attenuates adhesion by reducing focal contacts; however, it has no effect on stress fiber formation. These data reveal a novel mechanism in which endothelial cells control neighboring mural cells through the downregulation of APOD, which, in turn, influences mural cell function by modulating adhesion.