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in category emergency medicine

151 results found. For more information, click each entry to expand.

41: Occupational Exposures and Programmatic Response to COVID-19 Pandemic: An Emergency Medical Services Experience
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Posted 24 May 2020

Occupational Exposures and Programmatic Response to COVID-19 Pandemic: An Emergency Medical Services Experience
656 downloads medRxiv emergency medicine

David L Murphy, Leslie M Barnard, Christopher J Drucker, Betty Y Yang, Jamie M Emert, Leilani Schwarcz, Catherine R Counts, Tracie Y Jacinto, Andrew M McCoy, Tyler A Morgan, Jim E Whitney, Joel V Bodenman, Jeffrey S Duchin, Michael R Sayre, Thomas D Rea

Background Rigorous assessment of occupational COVID-19 risk and personal protective equipment (PPE) use are not well-described. We evaluated 9-1-1 emergency medical services (EMS) encounters for patients with COVID-19 to assess occupational exposure, programmatic strategies to reduce exposure, and PPE use. Methods We conducted a retrospective cohort investigation of lab-confirmed COVID-19 patients in King County, WA who received 9-1-1 EMS responses from February 14, 2020 to March 26, 2020. We reviewed dispatch, EMS, and public health surveillance records to evaluate the temporal relationship between exposure and programmatic changes to EMS operations designed to identify high-risk patients, protect the workforce, and conserve PPE. Results There were 274 EMS encounters for 220 unique COVID-19 patients involving 700 unique EMS providers with 988 EMS person-encounters. Use of full PPE including mask, eye protection, gown and gloves (MEGG) was 67%. There were 151 person-exposures among 129 individuals, who required 981 quarantine days. Of the 700 EMS providers, 3 (0.4%) tested positive within 14 days of encounter. Programmatic changes were associated with a temporal reduction in exposures. When stratified at the study encounters midpoint, 94% (142/151) of exposures occurred during the first 137 EMS encounters compared to 6% (9/151) during the second 137 EMS encounters (p<0.01). By the final week of the study period, EMS deployed MEGG PPE in 34% (3579/10,468) of all EMS person-encounters. Conclusion Less than 0.5% of EMS providers experienced COVID-19 illness within 14 days of occupational encounter. Programmatic strategies were associated with a reduction in exposures, while achieving a measured use of PPE.

42: Out of hospital cardiac arrests in the Gulf Region: a scoping review
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Posted 11 Dec 2019

Out of hospital cardiac arrests in the Gulf Region: a scoping review
652 downloads medRxiv emergency medicine

Alan M Batt, Chelsea Lanos, Dalal Al Hasan, Assim Alhmoudi, Megan Anderson, Shane Knox, Shannon Delport, Saleh Fares, Fergal H Cummins

Background Out-of-hospital cardiac arrest (OHCA) is a major cause of mortality worldwide. Recent studies demonstrated low survival rates in Middle Eastern countries. Anecdotally there are unique demographic, cultural and logistical challenges in this region. However, there remains a paucity of data published on OHCA in the Middle East. In order to address OHCA in a meaningful manner in the region, we first need to quantify the issue. Methods We conducted a scoping review of published and grey literature on OHCA in the Gulf Cooperative Council region that utilised Arksey and O'Malley's framework. Electronic databases and grey literature sources were identified and searched. Subject matter experts in the region were consulted. All types of studies in English and Arabic were included. Results A total of 24 studies were included from Saudi Arabia, the UAE, Oman, Kuwait, and Qatar. No literature was identified from the state of Bahrain. OHCA victims in the region are younger, predominantly male, and more co-morbid than those in Western studies. We observed low Emergency Medical Service utilisation, low bystander cardiopulmonary resuscitation, return of spontaneous circulation, and survival to discharge rates across the region. There are differences in characteristics of OHCA among ethnic groups. Discussion and conclusions We identified unique characteristics associated with OHCA in the region, variances in processes and outcomes when compared to Western studies, and a lack of coordinated effort to research and address OHCA. We recommend creating lead agencies responsible for coordinating and developing strategies such as community response, public education, and reporting databases.

43: Hospital-based autonomous pre-clinical screening of COVID-19: An emergency triage using a vital signs recording system, Paris-Ile de France region.
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Posted 20 Jun 2020

Hospital-based autonomous pre-clinical screening of COVID-19: An emergency triage using a vital signs recording system, Paris-Ile de France region.
638 downloads medRxiv emergency medicine

Albert Brizio, Valerie Faure, Franck Baudino, Arnaud Wilmet, Jean-Paul GONZALEZ

The COVID-19 pandemic has had a dramatic toll worldwide on the populations but also has been essentially supported by the existing public health system, particularly hospital-based emergency wards and intensive care units. In France, the first cases were identified on the 24th of January 2020. The first epidemic sprout emerged in the Eastern part of the country and spread in two weeks towards the center to the Paris-region where it peaked on the 14th of April 2020. In Paris and the region around it, the intensity of the epidemic has increased significantly to have a strong impact on all public and private hospital systems in a few weeks. During France's 2020 COVID-19 epidemic, a private hospital went into a major organizational change of its Emergency Department which mainly included the use of a Telemedicine Booth for vitals automatic recording during triage procedures. The present study describes the organizational scheme adopted by the hospital and discusses the data of 1,844 patients that attended the facility over a month. While among them, 766 patients were engaged in an automated triage process supported by a Telemedicine Booth. Patients' clinical characteristics are comparable to those found in international literature during the COVID-19 pandemic. The use of the Telemedicine Booth as a screening process facilitated patients' flow. It usefully participated in the patient rapid orientation, relieving the hospital emergency department, actively contributes in a safe and secure environment highly trusted by the hospital staff and health workers. To our knowledge, the Telemedicine Booth use as a screening process during an epidemic constitutes the first contribution to such an innovative approach.

44: Diagnostic accuracy of physical examination to detect the pelvic fractures among the blunt trauma patients; systematic review and meta-analysis
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Posted 13 Jan 2020

Diagnostic accuracy of physical examination to detect the pelvic fractures among the blunt trauma patients; systematic review and meta-analysis
632 downloads medRxiv emergency medicine

Yohei Okada, Norihiro Nishioka, Yasushi Tsujimoto

BackgroundThe study aims to perform systematic review and meta-analysis to identify the diagnostic accuracy of physical examination for pelvic fracture among the blunt trauma patients. MethodWe will perform a systematic review and meta-analysis for diagnostic test accuracy (DTA). We will include all reports on the diagnostic accuracy of physical examinations for detecting pelvic fractures. We will include the studies designed as prospective or retrospective observational (cohort or cross-sectional) studies or secondary analysis of randomized controlled trials. The target participants are blunt trauma patients with potential pelvic injury. The target condition is pelvic fracture. The index test being investigated is physical examination for pelvic fracture. The reference standard is X-ray or computed tomography to confirm the target condition. We will search MEDLINE, EMBASE and The Cochrane Library inclusive of Cochrane Controlled Trials Register. Two authors will independently screen the study eligibility and extract data. Screening will be a two-step process with initial title/abstract screening followed by full-text screening. We will evaluate the risk of bias independently by two investigators and reported according to the QUADAS-2 tool. In the meta-analysis, we will use a bivariate random-effects model to report the summary receiver operating characteristic (SROC) point (summary values for sensitivity and specificity) and the 95% confidence region around the summary ROC point. Trial registrationThis review is submitted with University hospital medical information network clinical trial registry (UMIN-CTR) [UMIN000038785].

45: Paediatric Attendances and Acuity in the Emergency Department during the COVID-19 Pandemic
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Posted 06 Aug 2020

Paediatric Attendances and Acuity in the Emergency Department during the COVID-19 Pandemic
614 downloads medRxiv emergency medicine

Katy Rose, Kerry Van-Zyl, Rachel Cotton, Susan Wallace, Francesca Cleugh

Aim: To investigate the difference in both numbers and acuity of presentations to the Paediatric Emergency Department (PED) during the peak time period of the current global SARS-CoV-2 pandemic. Design: This single centre retrospective observational study used routinely collected electronic health data to compare patient presentation characteristics between 21st March and 26th April 2020 compared to the equivalent time period in 2019. Results: There was a 90% decrease in attendances to PED, with a 10.23% reduction re-attendance rate. Children presenting were younger during the pandemic, with a median age difference of 2 years. They were more likely to present in an ambulance (9.63%), be admitted to hospital (5.75%) and be assigned the highest two Manchester triage categories (6.26%). There was a non-significant trend towards longer lengths of stay. The top 10 presenting complaints remained constant (although the order changed) between time periods. There was no difference in mortality or admission to PICU. Implications: Our data demonstrates that there has been a significant decrease in numbers of children seeking emergency department care. It suggests that presenting patients were proportionally sicker during the pandemic; however, we would argue that this is more in keeping with appropriate acuity for PED presentations, as there were no differences in PICU admission rate or mortality. We explore some of the possible reasons behind the decrease in presentations and the implications for service planning ahead of the winter months.

46: Identifying Homeless Population Needs in the Emergency Department Using Community-Based Participatory Research
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Posted 26 May 2020

Identifying Homeless Population Needs in the Emergency Department Using Community-Based Participatory Research
603 downloads medRxiv emergency medicine

Andrew Franco, MD, Jonathan Meldrum, MBBS, Christine Ngaruiya, MD, MSc

Background: Annually 1.5 million Americans face housing insecurity, and compared to their domiciled counterparts are three times more likely to utilize the Emergency Department (ED). Community Based Participatory Research (CBPR) methods have been employed in underserved populations, but use in the ED has been limited. We employed CBPR with a primary goal of improved linkage to care, reduced ED recidivism, and improved homeless health care. Methods: A needs analysis was performed using semi-structured individual interviews with participants experiencing homelessness as well as with stakeholders. Results were analyzed using principles of grounded theory. At the end of the interviews, respondents were invited to join the CBPR team. At CBPR team meetings, results from interviews were expounded upon and discussions on intervention development were conducted. Results: Twenty-five stakeholders were interviewed including people experiencing housing insecurity, ED staff, inpatient staff, and community shelters and services. Three themes emerged from the interviews. First, the homeless population lack access to basic needs, thus management of medical needs must be managed alongside social ones. Second, specific challenges to address homeless needs in the ED include episodic care, inability to recognize housing insecurity, timely involvement of ancillary staff, and provider attitudes towards homeless patients affecting quality of care. Lastly, improved discharge planning and communication with outside resources is essential to improving homeless health and decreasing ED overutilization. A limitation of results is bias towards social networks influencing included stakeholders. Conclusion: CBPR is a promising approach to address gaps in homeless health care as it provides a comprehensive view incorporating various critical perspectives. Key ED-based interventions addressing recidivism include improved identification of housing insecurity, reinforced relationships between ED and community resources, and better discharge planning.

47: The effect of a specialist paramedic primary care rotation on appropriate non-conveyance decisions (SPRAINED) study: a controlled interrupted time series analysis
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Posted 07 Aug 2020

The effect of a specialist paramedic primary care rotation on appropriate non-conveyance decisions (SPRAINED) study: a controlled interrupted time series analysis
595 downloads medRxiv emergency medicine

Richard Pilbery, Tracey Young, Andrew Hodge

IntroductionNHS ambulance service conveyance rates in the UK are almost 70%, despite an increase in non-emergency cases. This is increasing the demands on crowded emergency departments (ED) and contributes to increased ambulance turnaround times. Yorkshire Ambulance Service introduced a specialist paramedic (SP) role to try and address this, but non-conveyance rates in this group have not been as high as expected. MethodsWe conducted a controlled interrupted time series analysis of appropriate non-conveyance rates in the 12 months before and after an SP primary care placement, using matched groups of patients cared for by SPs and control paramedics. A costing analysis examined the average cost per appropriate non-conveyance and the cost-effectiveness ratio between groups. ResultsBetween June 2017 and December 2019 there were 7349 incidents attended by intervention group SPs and eligible for inclusion. Following removal of cases with missing data, 5537/7349 (75.3%) cases remained. Post-placement, the intervention group demonstrated an increase in appropriate non-conveyance rate by 35.0% (95%CI 23.8-46.2%, p<0.001) and a reduction in the trend of appropriate non-conveyance relative to the control group of -1.2% (95%CI -2.8-0.5%, p=0.156). Post-placement, the cost per appropriate non-conveyance for intervention paramedics was a mean of {pound}509.42 (95% bootstrapped CI {pound}485.94-{pound}535.41) versus {pound}1124.41 (95% bootstrapped CI {pound}1041.89-{pound}1218.31) for the control group. This represents a mean saving of {pound}615 per appropriate non-conveyance (95% bootstrapped CI {pound}545.31-{pound}686.69) for SPs compared to the control group, and a cost-effectiveness ratio of {pound}1758.89 per percentage increase in appropriate non-conveyance (95% bootstrapped CI {pound}1477-76-{pound}2133.08). ConclusionIn this single UK NHS ambulance service study, we found a clinically important and statistically significant increase in appropriate non-conveyance rates by specialist paramedics who had completed a 10-week GP placement. This improvement persisted for the 12-month period following the placement and demonstrated cost savings compared to usual care.

48: Global health security capacity against COVID-19 outbreak and its association with the case fatality rate: an analysis of annual data from 210 countries and territories
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Posted 29 Apr 2020

Global health security capacity against COVID-19 outbreak and its association with the case fatality rate: an analysis of annual data from 210 countries and territories
583 downloads medRxiv emergency medicine

Elham Maraghi, Amal Saki Malehi, Fakher Rahim

Background: Because infectious diseases, such as COVID-19, do not have specific boundaries, all countries must prioritize and use the necessary capabilities to prevent, detect, and respond quickly to public health emergencies. In this context, we aimed to review most recent GHS index annual report to observe the regional and global level of health security against COVID-19 outbreak, as well as their relationship with case fatality rate, among 210 countries and territories worldwide. Methods: We reviewed and analyzed October 2019 GHS index co-leaders joint report, to review health security capacities on the basis of the GHS index in the context of six categories. we prioritized not only the capacities of 210 countries and territories around the world using the GHS Index, but also the existence of functional, tested, proven capabilities for stopping outbreaks at the source. Data were collected from global databases including Worldometer, WHO, and Disease Control and Prevention Center (CDC). Findings: This study recruited data on 210 countries and territories, of which up to 14 April 2020, 72 countries (34.28%) with more than 1000 total COVID-19 cases were presents. In most prepared group, number of total COVID-19 diagnostic tests had a significant positive relation with GHS index (r=0.713; p=0.006). Case fatality rate was directly associated with the detection index (r=0.304; p=0.023) in more prepared group. In Lower-middle-income economies group, case fatality rate positively related to detection, response and risk environment indices. Implementation: With the exception of a very small number, countries that were ranked as most prepared countries, they were more likely to be affected by the COVID-19 outbreak of the virus and its health consequences, and needed to seriously reconsider their capabilities and health security in the context of detection, prevention, rapid response, health system facilities, and risk environment against disease outbreak

49: Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study
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Posted 11 Aug 2020

Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study
578 downloads medRxiv emergency medicine

Steve Goodacre, Ben Thomas, Ellen Lee, Laura Sutton, Katie Biggs, Carl Marincowitz, Amanda Loban, Simon Waterhouse, Richard Simmonds, Jose Schutter, Sarah Connelly, Elena Sheldon, Jamie Hall, Emma Young, Andrew Bentley, Kirsty Challen, Chris Fitzsimmons, Tim Harris, Fiona Lecky, Andrew Lee, Ian Maconochie, Darren Walter

Background Measurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19. Methods We undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis. Results We analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019). Conclusions Post-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19.

50: THE ROLE OF POINT-OF-CARE ULTRASONOGRAPHY IN THE INITIAL CHARACTERIZATION OF COVID-19 PATIENTS: RESULTS FROM A PROSPECTIVE MULTICENTRIC STUDY.
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Posted 20 May 2020

THE ROLE OF POINT-OF-CARE ULTRASONOGRAPHY IN THE INITIAL CHARACTERIZATION OF COVID-19 PATIENTS: RESULTS FROM A PROSPECTIVE MULTICENTRIC STUDY.
542 downloads medRxiv emergency medicine

yale tung chen, Rafael Llamas Fuentes, Pablo Rodriguez Fuertes

INTRODUCTION: Coronavirus Disease 2019 (COVID-19) is a highly contagious illness caused by the Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). There is growing evidence regarding the imaging findings of COVID-19, in Chest X-ray and CT scan, however their availability in this pandemic outbreak might be compromised. At this moment, the role of Point-of-care ultrasonography (POCUS) has yet to be explored. OBJECTIVES: The main purpose of this study is to describe the POCUS findings of the disease in COVID-19 patients admitted to the emergency department (ED). Determining the correlation of these parameters with vital signs, laboratory results and chest X-ray, as well as, therapeutic decisions and prognosis. METHODS: Prospective study carried out in the emergency department (ED) of two academic hospitals. High suspicion or confirmed COVID-19 patients were subjected to the ultrasonographic measurement of the inferior vena cava (IVC), focused cardiac ultrasound (FOCUS), and Lung Ultrasonography (Lung POCUS). RESULTS: Between March and April 2020, ninety-six patients were enrolled. The mean age was 68.2 years (SD 17.5). The most common finding in Lung POCUS was an irregular pleural line (63.2%) followed by bilateral confluent (55.2%) and isolated B-lines (53.1%), which was associated with a positive RT-PCR (OR 4.729, 95% CI: 1.989-11.246; p<0.001), and correlated with IL-6 levels (rho = 0.622; p = 0.002). The IVC moderately correlated with levels of pO2, expiratory (rho = -0.539; p =0.014) and inspiratory (rho = -0.527; p =0.017), with troponin I (rho = 0.509; p=0.03). After POCUS exam, almost 20% of the patients had an associated condition that required a change in the treatment or management. CONCLUSION: In this pandemic era, as the shortage of resources constitutes an undeniable public health threat, POCUS presents the potential to impact in diagnosis, management and prognosis of our confirmed or suspected COVID-19 patients.

51: A 29-mRNA Host Response Test from Blood Accurately Distinguishes Bacterial and Viral Infections Among Emergency Department Patients
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Posted 04 Dec 2020

A 29-mRNA Host Response Test from Blood Accurately Distinguishes Bacterial and Viral Infections Among Emergency Department Patients
530 downloads medRxiv emergency medicine

Asimina Safarika, James W Wacker, Konstantinos Katsaros, Nicky Solomonidi, George Giannikopoulos, Antigoni Kotsaki, Ioannis M Koutelidakis, Sabrina M Coyle, Henry K. Cheng, Oliver Liesenfeld, Timothy E Sweeney, Evangelos Giamarellos-Bourboulis

Abstract Study design: Whether or not to administer antibiotics is a common and challenging clinical decision in patients with suspected infections presenting to the emergency department (ED). We prospectively validate InSep, a 29-mRNA blood-based host response test for the prediction of bacterial and viral infections. Methods: The PROMPT trial is a prospective, non-interventional, multi-center randomized, controlled clinical trial that enrolled 397 adult patients presenting to the ED with signs of acute infection and at least one vital sign change. The infection status was adjudicated using chart review (including a syndromic molecular respiratory panel, procalcitonin and C-reactive protein) by three infectious disease physicians blinded to InSep results. InSep (version BVN-2) was performed using PAXgene Blood RNA processed and quantified on NanoString nCounter SPRINT. InSep results (likelihood of bacterial and viral infection) were compared to the adjudicated infection status. Results: Subject mean age was 64 years, comorbidities were significant for diabetes (17.1%), chronic obstructive pulmonary disease (13.6%), and severe neurological disease (6.8%); 16.9% of subjects were immunocompromised. Infections were adjudicated as bacterial (14.1%), viral (11.3%) and noninfected (0.25%): 74.1% of subjects were adjudicated as indeterminate. InSep distinguished bacterial vs. viral/noninfected patients and viral vs. bacterial/noninfected patients using consensus adjudication with AUROCs of 0.94 (95% CI 0.90-0.99) and 0.90 (95% CI 0.83-0.96), respectively. AUROCs for bacterial vs. viral/noninfected patients were 0.88 (95%CI 0.79-0.96) for PCT, 0.80 (95% CI 0.72-89) for CRP and 0.78 (95% CI 0.69-0.87) for white blood cell counts (of note, the latter biomarkers were provided as part of clinical adjudication). To enable clinical actionability, InSep incorporates score cutoffs to allocate patients into interpretation bands. The Very Likely (rule in) InSep bacterial band showed a specificity of 98% compared to 94% for the corresponding PCT band (>0.5 ug/L); the Very Unlikely (rule-out) band showed a sensitivity of 95% for InSep compared to 86% for PCT. For the detection of viral infections, InSep demonstrated a specificity of 93% for the Very Likely band (rule in) and a sensitivity of 96% for the Very Unlikely band (rule out). Conclusion: InSep demonstrated high accuracy for predicting the presence of both bacterial and viral infections in ED patients with suspected acute infections or suspected sepsis. When translated into a rapid, point-of-care test, InSep will provide ED physicians with actionable results supporting early informed treatment decisions to improve patient outcomes while upholding antimicrobial stewardship.

52: Predicting Progression to Septic Shock in the Emergency Department using an Externally Generalizable Machine Learning Algorithm
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Posted 04 Nov 2020

Predicting Progression to Septic Shock in the Emergency Department using an Externally Generalizable Machine Learning Algorithm
519 downloads medRxiv emergency medicine

Gabriel Wardi, Morgan Carlile, Andre Holder, Supreeth Shashikumar, Stephen R Hayden, Shamim Nemati

ObjectiveMachine-learning (ML) algorithms allow for improved prediction of sepsis syndromes in the ED using data from electronic medical records. Transfer learning, a new subfield of ML, allows for generalizability of an algorithm across clinical sites. We aimed to validate the Artificial Intelligence Sepsis Expert (AISE) for the prediction of delayed septic shock in a cohort of patients treated in the ED and demonstrate the feasibility of transfer learning to improve external validity at a second site. MethodsObservational cohort study utilizing data from over 180,000 patients from two academic medical centers between 2014 and 2019 using multiple definitions of sepsis. The AISE algorithm was trained using 40 input variables at the development site to predict delayed septic shock (occurring greater than 4 hours after ED triage) at varying prediction windows. We then validated the AISE algorithm at a second site using transfer learning to demonstrate generalizability of the algorithm. ResultsWe identified 9354 patients with severe sepsis of which 723 developed septic shock at least 4 hours after triage. The AISE algorithm demonstrated excellent area under the receiver operating curve (>0.8) at 8 and 12 hours for the prediction of delayed septic shock. Transfer learning significantly improved the test characteristics of the AISE algorithm and yielded comparable performance at the validation site. ConclusionsThe AISE algorithm accurately predicted the development of delayed septic shock. The use of transfer learning allowed for significantly improved external validity and generalizability at a second site. Future prospective studies are indicated to evaluate the clinical utility of this model.

53: Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study.
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Posted 29 Jun 2020

Higher clinical acuity and 7-day hospital mortality in non-COVID-19 acute medical admissions: prospective observational study.
516 downloads medRxiv emergency medicine

Marcus J Lyall, Nazir I Lone

Abstract Objectives: To understand the effect of COVID-19 lockdown measures on severity of illness and mortality in non-COVID-19 acute medical admissions. Design: A prospective observational study Setting: 3 large acute medical receiving units in NHS Lothian, Scotland. Participants: Non-covid-19 acute admissions (n = 1756) were examined over the first 31 days after the implementation of the COVID-19 lockdown policy in the United Kingdom on 23rd March 2019. Patients admitted over a matched interval in the previous 5 years were used as a comparator cohort (n = 14961). Main outcome measures: Patient demography, biochemical markers of clinical acuity and 7-day hospital inpatient mortality. Results: Non-covid-19 acute medical admissions reduced by a mean 43.8% (95% CI 27.3, 59.4) across all 3 sites in comparison to the mean of the preceding 5 years P < 0.001. The reduction in admissions predominated in the over 75 age category and a greater proportion arrived by emergency ambulance transport. Non-covid-19 admissions during lockdown had a greater incidence of severe renal injury, hyperlactataemia and over twice the risk of hospital death within 7 days 5.01% vs 2.49% which persisted after adjustment for confounders (OR 2.17, 95% CI 1.70,2.73, P < 0.0001) Conclusions: These data support current fears that patients are delaying seeking medical attention for acute illness which is associated with worsening clinical parameters and a higher risk of death following admission.

54: Performance of popular pulse oximeters compared with simultaneous arterial oxygen saturation or clinical-grade pulse oximetry: a cross-sectional validation study in intensive care patients
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Posted 12 Mar 2021

Performance of popular pulse oximeters compared with simultaneous arterial oxygen saturation or clinical-grade pulse oximetry: a cross-sectional validation study in intensive care patients
511 downloads medRxiv emergency medicine

Ralf Harskamp, Luuk Bekker, Jelle Himmelreich, Lukas De Clercq, Evert Karregat, Mengalvio Sleeswijk, Wim Lucassen

Background: The demand for pulse oximeters is high in the current COVID-19 pandemic. Despite their popularity, clinical studies to evaluate the reliability in obtaining information on a patient's oxygenation status, are lacking. Aim: To evaluate the performance of pulse oximeters under clinical conditions, with arterial blood gas measurement (SaO2) as reference standard. Methods: We studied the accuracy of ten top-selling pulse oximeters in Europe and the USA in an intensive care population at the Flevoziekenhuis in Almere, the Netherlands. The studied pulse oximeters were: AFAC FS10D, AGPTEK FS10C, ANAPULSE ANP 100, Cocobear, Contec CMS50D1, HYLOGY MD-H37, Mommed YM101, PRCMISEMED F4PRO, PULOX PO-200, and Zacurate Pro Series 500DL. Adult patients in whom an SaO2 measurement was obtained as part of routine care were asked for inclusion. Directly after obtaining the SaO2 blood sample we obtained the pulse oximeter readings (SpO2) of the investigational devices, in random order. Outcomes were bias (SpO2-SaO2) mean, root mean square difference (ARMS), mean absolute error (MAE), and accuracy in identifying hypoxemia (SaO2<=90%). As a clinical index test, we included a hospital-grade SpO2-monitor. Results: In 35 consecutive patients we obtained 2,258 SpO2-readings and 234 SaO2-samples. Mean bias ranged from -0.6 to -4.8. None of the pulse oximeters had an ARMS<=3%, the requirement set by ISO-standards and required for FDA 501(k) clearance. The MAE ranged from 2.3 to 5.1, and 5 out of 10 pulse oximeters met the requirements of [&le;]3%. For hypoxemia, negative predictive values were 98-99%. Positive predictive values ranged from 11-30%. Highest accuracy (95%CI) were found for Contec CMS50D1; 91% (86-94) and Zacurate Pro Series 500DL; 90% (85-94). The hospital-grade SpO2-monitor had an ARMS of 3.0 and MAE of 1.9, and an accuracy of 95% (91-97%). Conclusion: Direct-to-consumer pulse oximeters do not meet ISO-standards required for FDA-clearance, but can accurately rule out hypoxemia.

55: Deep multitask ensemble classification of emergency medical call incidents combining multimodal data improves emergency medical dispatch
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Posted 26 Jun 2020

Deep multitask ensemble classification of emergency medical call incidents combining multimodal data improves emergency medical dispatch
509 downloads medRxiv emergency medicine

Pablo Ferri, Carlos Sáez, Antonio Félix-De Castro, Javier Juan-Albarracín, Vicent Blanes-Selva, Purificación Sánchez-Cuesta, Juan M. Garcia-Gomez

The objective of this work was to develop a predictive model to aid non-clinical dispatchers to classify emergency medical call incidents by their life-threatening level (yes/no), admissible response delay (undelayable, minutes, hours, days) and emergency system jurisdiction (emergency system/primary care) in real time. We used a total of 1 244 624 independent incidents from the Valencian emergency medical dispatch service in Spain, compiled in retrospective from 2009 to 2012, including clinical features, demographics, circumstantial factors and free text dispatcher observations. Based on them, we designed and developed DeepEMC2, a deep ensemble multitask model integrating four subnetworks: three specialized to context, clinical and text data, respectively, and another to ensemble the former. The four subnetworks are composed in turn by multi-layer perceptron modules, bidirectional long short-term memory units and a bidirectional encoding representations from transformers module. DeepEMC2 showed a macro F1-score of 0.759 in life-threatening classification, 0.592 in admissible response delay and 0.757 in emergency system jurisdiction. These results show a substantial performance increase of 12.5%, 17.5% and 5.1%, respectively, with respect to the current in-house triage protocol of the Valencian emergency medical dispatch service. Besides, DeepEMC2 significantly outperformed a set of baseline machine learning models, including naive bayes, logistic regression, random forest and gradient boosting (=0.05). Hence, DeepEMC2 is able to: 1) capture information present in emergency medical calls not considered by the existing triage protocol, and model complex data dependencies not feasible by the tested baseline models. Likewise, our results suggest that most of this unconsidered information is present in the free text dispatcher observations. To our knowledge, this study describes the first deep learning model undertaking emergency medical call incidents classification. Its adoption in medical dispatch centers would potentially improve emergency dispatch processes, resulting in a positive impact in patient wellbeing and health services sustainability.

56: Derivation and validation of a triage tool for acutely ill adults with suspected COVID-19: The PRIEST observational cohort study
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Posted 14 Oct 2020

Derivation and validation of a triage tool for acutely ill adults with suspected COVID-19: The PRIEST observational cohort study
506 downloads medRxiv emergency medicine

Steve Goodacre, Ben Thomas, Laura Sutton, Matthew Bursnall, Ellen Lee, Mike Bradburn, Amanda Loban, Simon Waterhouse, Richard Simmonds, Katie Biggs, Carl Marincowitz, Jose Schutter, Sarah Connelly, Elena Sheldon, Jamie Hall, Emma Young, Andrew Bentley, Kirsty Challen, Chris Fitzimmons, Tim Harris, Fiona Lecky, Andrew Lee, Ian Maconochie, Darren Walter

ObjectivesWe aimed to derive and validate a triage tool, based on clinical assessment alone, for predicting adverse outcome in acutely ill adults with suspected COVID-19 infection. MethodsWe undertook a mixed prospective and retrospective observational cohort study in 70 emergency departments across the United Kingdom (UK). We collected presenting data from 22445 people attending with suspected COVID-19 between 26 March 2020 and 28 May 2020. The primary outcome was death or organ support (respiratory, cardiovascular, or renal) by record review at 30 days. We split the cohort into derivation and validation sets, developed a clinical score based on the coefficients from multivariable analysis using the derivation set, and the estimated discriminant performance using the validation set. ResultsWe analysed 11773 derivation and 9118 validation cases. Multivariable analysis identified that age, sex, respiratory rate, systolic blood pressure, oxygen saturation/inspired oxygen ratio, performance status, history of renal impairment, and respiratory distress were retained in analyses restricted to the ten or fewer predictors. We used findings from multivariable analysis and clinical judgement to develop a score based on the NEWS2 score, age, sex, and performance status. This had a c-statistic of 0.80 (95% confidence interval 0.79-0.81) in the validation cohort and predicted adverse outcome with sensitivity 0.98 (0.97-0.98) and specificity 0.38 (0.38-0.39) for scores above four points. ConclusionA clinical score based on NEWS2, age, sex, and performance status predicts adverse outcome with good discrimination in adults with suspected COVID-19 and can be used to support decision-making in emergency care. RegistrationISRCTN registry, ISRCTN28342533, http://www.isrctn.com/ISRCTN28342533

57: Agreement between arterial and capillary pH, pCO2 and lactate in patients in the emergency department
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Posted 12 Jun 2020

Agreement between arterial and capillary pH, pCO2 and lactate in patients in the emergency department
488 downloads medRxiv emergency medicine

Vincent Collot, Stefano Malinverni, Eric Schweitzer, Jabir Haltout, Pierre Mols, Magali Bartiaux

Study objective The primary objective of the study was a quantitative analysis to assess the mean difference and 95% confidence interval of the difference between capillary and arterial blood gas analyses for pH, pCO2 and lactate. Secondary objective was to measure the sensitivity and specificity of capillary samples to detect altered pH, hypercarbia and lactic acidosis. Methods Adults admitted to the ED for whom the treating physician deemed necessary an arterial blood gas analysis (BGA) were screened for inclusion. Simultaneous arterial and capillary samples were drawn for BGA. Agreement between the two methods for pH, pCO2 and lactate were studied with Bland-Altman bias plot analysis. Sensitivity, specificity, positive and negative predictive value as well as AUC were calculated for the ability of capillary samples to detect pH values outside normal ranges, hypercarbia and hyperlactatemia. Results 197 paired analyses were included in the study. Mean difference for pH, between arterial and capillary BGA was 0.0095, 95% limits of agreement were -0.048 to 0.067. For pCO2, mean difference was -0.3 mmHg, 95% limits of agreement were -8.5 to 7.9 mmHg. Lactate mean difference was -0.93 mmol/L, 95% limits of agreement were -2.7 to 0.8 mmol/L. At a threshold of 7.34 for capillary pH had 98% sensitivity and 97% specificity to detect acidemia; at 45.9 mmHg capillary pCO2 had 89% sensitivity and 96% specificity to detect hypercarbia. Finally at a threshold of 3.5 mmol/L capillary lactate had 66% sensitivity to detect lactic acidosis. Conclusion Capillary measures of pH, pCO2 and lactate cannot replace arterial measurements although there is high concordance between the two methods for pH and pCO2 and moderate concordance for lactate. Capillary blood gas analysis had good accuracy when used as a screening tool to detect altered pH and hypercarbia but insufficient sensitivity and specificity when screening for lactic acidosis.

58: LUNG ULTRASOUND FINDINGS IN PATIENTS WITH COVID-19 IN AN URBAN EMERGENCY DEPARTMENT IN THE UK
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Posted 30 Sep 2020

LUNG ULTRASOUND FINDINGS IN PATIENTS WITH COVID-19 IN AN URBAN EMERGENCY DEPARTMENT IN THE UK
487 downloads medRxiv emergency medicine

Julia Burkert, Hannah Dunlop, Rachel Stewart, Adam Treacy, Robert Jarman, Paramjeet Deol

COVID-19 can present with respiratory symptoms ranging from mild cough to viral pneumonia and ARDS. Lung ultrasonography has emerged as a promising imaging modality during the pandemic, but there is still a paucity of systematic analysis of lung ultrasound findings. In this retrospective observational study, 12 Zone ultrasound scans of COVID-19 positive patients were systematically analysed for pleural irregularities, subpleural consolidations, B lines, deep consolidations and effusions. Lung abnormalities were analysed according to overall frequency, frequency distribution in coronal and sagittal lung planes and were also correlated to clinical severity groups as determined by oxygenation deficit. Our results show that lung zones with abnormalities can occur juxtaposed to normal lung. Irregular pleural and small subpleural consolidations appear ubiquitously distributed throughout both lungs and occur early in the disease process. Wide B-lines are a predominant feature in COVID-19 infection. B-lines are found in a variety of patterns with number and width correlated to disease severity. In our analysis we also describe a previously unrecognised finding of small peri-pleural effusions in 8.7% of scans occurring in all areas of the lung. The current results form the basis for a more thorough understanding of the lung changes occurring in COVID-19 and the incorporation of lung ultrasound in the setting of COVID-19 infection including triage, diagnosis, treatment approach and prognosis.

59: Characteristics of patients presenting, and not presenting, to the emergency department during the early days of COVID-19
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Posted 08 May 2020

Characteristics of patients presenting, and not presenting, to the emergency department during the early days of COVID-19
486 downloads medRxiv emergency medicine

Bjorn C Westgard, Matthew W Morgan, Gabriela Vazquez-Benitez, Lauren O Erickson, Michael D. Zwank

Objective: Societal responses to the COVID-19 pandemic have had a substantial effect upon the number of patients seeking healthcare. An initial step in estimating the impact of these changes is characterizing the patients, visits, and diagnoses for whom care is being delayed or deferred. Methods: We conducted an observational study, examining demographics and diagnoses for all patient visits to the ED of an urban Level-1 trauma center before and after the state declaration and compared them to visits from a similar period in 2019. We estimated the ratios of the before and after periods using Poisson regression, calculated the percent change with respect to 2019 for total ED visits, patient characteristics, and diagnoses, and then evaluated the interactions between each factor and the overall change in ED visits. Results: There was a significant 35.2% drop in overall ED visits after the state declaration. Disproportionate declines were seen in visits by pediatric and older patients, women, and Medicare recipients as well as for presentations of syncope, cerebrovascular accidents, urolithiasis, abdominal and back pain. Significantly disproportionate increases were seen in ED visits for potential symptoms of COVID-19, including URIs, shortness of breath, and chest pain. Conclusions: Patient concerns about health care settings and public health have significantly altered care-seeking during the COVID-19 pandemic. Overall and differential declines in ED visits for certain demographic groups and disease processes should prompt efforts to encourage care-seeking and research to monitor for the morbidity and mortality that is likely to result from delayed or deferred care.

60: A validation of machine learning-based risk scores in the prehospital setting
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Posted 05 Oct 2019

A validation of machine learning-based risk scores in the prehospital setting
473 downloads medRxiv emergency medicine

Douglas Spangler, Thomas Hermansson, David Smekal, Hans Blomberg

BackgroundThe triage of patients in pre-hospital care is a difficult task, and improved risk assessment tools are needed both at the dispatch center and on the ambulance to differentiate between low- and high-risk patients. This study develops and validates a machine learning-based approach to predicting hospital outcomes based on routinely collected prehospital data. MethodsDispatch, ambulance, and hospital data were collected in one Swedish region from 2016 - 2017. Dispatch center and ambulance records were used to develop gradient boosting models predicting hospital admission, critical care (defined as admission to an intensive care unit or in-hospital mortality), and two-day mortality. Model predictions were used to generate composite risk scores which were compared to National Early Warning System (NEWS) scores and actual dispatched priorities in a similar but prospectively gathered dataset from 2018. ResultsA total of 38203 patients were included from 2016-2018. Concordance indexes (or area under the receiver operating characteristics curve) for dispatched priorities ranged from 0.51 - 0.66, while those for NEWS scores ranged from 0.66 - 0.85. Concordance ranged from 0.71 - 0.80 for risk scores based only on dispatch data, and 0.79 - 0.89 for risk scores including ambulance data. Dispatch data-based risk scores consistently outperformed dispatched priorities in predicting hospital outcomes, while models including ambulance data also consistently outperformed NEWS scores. Model performance in the prospective test dataset was similar to that found using cross-validation, and calibration was comparable to that of NEWS scores. ConclusionsMachine learning-based risk scores outperformed a widely-used rule-based triage algorithm and human prioritization decisions in predicting hospital outcomes. Performance was robust in a prospectively gathered dataset, and scores demonstrated adequate calibration. Future research should investigate the generality of these results to prehospital triage in other settings, and establish the impact of triage tools based on these methods by means of randomized trial.

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