Most downloaded biology preprints, all time
in category emergency medicine
151 results found. For more information, click each entry to expand.
465 downloads medRxiv emergency medicine
This study aimed to investigate available resources, Personal Protective Equipment (PPE) availability, sanitation practices, institutional policies, and opinions among EMS professionals in the United States amid the COVID-19 pandemic using a self-report survey questionnaire. METHODS An online 42-question multiple choice survey was randomly distributed between April 1, 2020, and April 12, 2020 to various active Emergency Medical Services (EMS) paid personnel in all 50 U.S. states including the District of Columbia (n=165). We approximate a 95% confidence interval (+/- 0.0755). RESULTS An overwhelming number of EMS providers report having limited access to N95 respirators, receiving little or no benefits from COVID-19 related work, and report no institutional policy on social distancing practices despite CDC recommendations. For providers who do have access to N95 respirators, 31% report having to use the same mask for 1 week or longer. Approximately [1/3] of the surveyed participants were unsure of when a COVID-19 patient is infectious. The data suggests regular decontamination of EMS equipment after each patient contact is not a regular practice. DISCUSSION Current practices to educate EMS providers on appropriate response to the novel coronavirus may not be sufficient, and future patients may benefit from a nationally established COVID-19 EMS response protocol. Further investigation on whether current EMS practices are contributing to the spread of infection is warranted. The data reveals concerning deficits in COVID-19 related education and administrative protocols which pose as a serious public health concern that should be urgently addressed.
436 downloads medRxiv emergency medicine
Luca Santi, Davide Golinelli, Andrea Tampieri, Gabriele Farina, Manfredi Greco, Simona Rosa, Michelle Beleffi, Bianca Biavati, Francesca Campinoti, Stefania Guerrini, Rodolfo Ferrari, Paola Rucci, Maria Pia Fantini, Fabrizio Giostra
ObjectiveThe aim of this was to assess the short-term impact of the pandemic on non-COVID-19 patients living in a one-million inhabitants area in Northern Italy (Bologna Metropolitan Area-BMA), analyzing time trends of Emergency Department (ED) visits, hospitalizations and mortality. MethodsWe conducted a retrospective observational study using data extracted from BMA healthcare informative systems. Weekly trends of ED visits, hospitalizations, in- and out-of-hospital, all-cause and cause-specific mortality between December 1st, 2019 to May 31st, 2020, were compared with those of the same period of the previous year, using Joinpoint regression models and incidence rate ratios. ResultsNon-COVID-19 ED visits and hospitalizations showed a stable trend until the first Italian case of COVID-19 has been recorded, on February 19th, 2020, when they dropped simultaneously. The reduction of ED visits was observed in all age groups and across all severity and diagnosis groups. In the lockdown period a significant increase was found in overall out-of-hospital mortality (43.2%) and cause-specific out-of-hospital mortality related to neoplasms (76.7%), endocrine, nutritional and metabolic (79.5%) as well as cardiovascular (32.7%) diseases. ConclusionsThe pandemic caused a sudden drop of ED visits and hospitalizations of non-COVID-19 patients during the lockdown period, and a concurrent increase in out-of-hospital mortality mainly driven by deaths for neoplasms, cardiovascular and endocrine diseases. The findings of this study might be useful to understand both the population reaction and the healthcare system response at the early phases of the pandemic in terms of reduced demand of care and systems capability in intercepting it.
435 downloads medRxiv emergency medicine
Katie Walker, Melanie Stephenson, Jennie Hutton, Anne Loupis, Keith Joe, Michael Ben-Meir, Ella Martini, Michael Stephenson, Judy Lowthian, Beatrice Yip, Elena Wu, James Ho, Gabriel Blecher, Kim Hansen, Paul Buntine
Background Emergency Departments have the potential ability to predict patient wait times and to display this to patients and other stakeholders. Little is known about whether consumers and stakeholders would want this information and how wait time predictions might be used. The aim of this study was to gain perspectives from consumer, referrer and health services personnel regarding the concept of emergency wait time visibility. Methods In 2019, 103 semi-structured interviews and one focus group were conducted with emergency medicine patients/families, paramedics, well community members and hospital/paramedic administrators. Nine emergency departments and multiple organisations in Victoria, Australia, contributed data. Transcripts were coded and themes are presented. Results Consumers and paramedics face physical and psychological difficulties when wait times are not visible. Consumers believe about a 2-hour wait is tolerable, beyond this most begin to consider alternative strategies for seeking care. Consumers want to see triage to doctor times; paramedics want door to off-stretcher times (for all possible transport destinations); with 47/50 consumers and 30/31 paramedics potentially using this information. Twenty-eight of 50 consumers would use times to inform facility or provider choice, 19/50 want information once in the waiting room. During prolonged waits, 1/52 consumers would consider not seeking care. Visibility of approximate waits would better inform decision-making, improve load-spreading, allow planning and access to basic needs and might reduce anxiety. Conclusions Consumers and paramedics want wait time information visibility. They would use the information in a variety of ways, both pre-hospital and whilst waiting for care.
431 downloads medRxiv emergency medicine
Background: We aimed to compare the pre, lockdown, and post-lockdown aeromedical retrieval (AR) diagnostic reasons and patient demographics during a period of Coronavirus 2019 (COVID-19) social isolation. Methods: An observational study with retrospective data collection, consisting of Australians who received an AR between 26 January and 23 June 2020. The main outcome measures were patient diagnostic category proportions and trends prior (28 January to 15 March), during (16 March to 4 May), and following (5 May to 23 June 2020) social isolation restrictions. Results: There were 16981 ARs consisting of 1959 (11.5) primary evacuations (PEs) and 12724 (88.5) inter-hospital transfers (IHTs), with a population median age of 52 years (interquartile range [IQR] 29.0 69.0), with 49.0% (n= 8283) of the cohort being male and 38.0% (n= 6399) being female. There were a total of six confirmed and 209 suspected cases of COVID-19, with the majority of cases (n=114; 53.0%) in the social isolation period. As compared to pre-restriction, the odds of retrieval for the restriction and post-restriction period differed across time between the major diagnostic groups. This included, an increase in cardiovascular retrieval for both restriction and post-restriction periods (OR 1.12 95% CI 1.02 1.24 and OR 1.18 95% CI 1.08 1.30 respectively), increases in neoplasm in the post restriction period (OR 1.31 95% CI 1.04 1.64), and increases for congenital conditions in the restriction period (OR 2.56 95% CI 1.39 4.71). Cardiovascular and congenital conditions had increased rates of priority 1 patients in the restriction and post restriction periods. There was a decrease in endocrine and metabolic disease retrievals in the restriction period (OR 0.72 95% CI 0.53 0.98). There were lower odds during the post-restriction period for a retrievals of the respiratory system (OR 0.78 95% CI 0.67 0.93), and disease of the skin (OR 0.78 95% CI 0.6 1.0). Distribution between the 2019 and 2020 time periods differed (p<0.05), with the lockdown period resulting in a significant reduction in activity. Conclusion: The lockdown period resulted in increased AR rates of circulatory and congenital conditions. However, this period also resulted in a reduction of overall activity, possibly due to a reduction in other infectious disease rates, such as influenza, due to social distancing.
426 downloads medRxiv emergency medicine
Background : Rapid testing for COVID-19 has been clearly identified as an essential component of the strategy to control the SARS-CoV-2 epidemic, worldwide. The ID NOW COVID-19 assay is a simple, user-friendly, rapid molecular biology test based on nicking and extension amplification reaction (NEAR). Objectives : The aim of this study was to evaluate the ID NOW COVID-19 assay when used as a point-of-care test (POCT) in our Emergency Department (ED). Type of study : This prospective study enrolled 395 consecutive patients; paired nasopharyngeal swabs were collected from each study participant. The first swab was tested with the ID NOW COVID-19 assay at the point-of-care by ED nurses. The second swab was diluted in viral transport medium (VTM) and sent to the clinical microbiology department for analysis by both the RT-PCR Simplexa test COVID-19 Direct assay as the study reference method, and the ID NOW COVID-19 assay performed in the laboratory. Results : Nasopharyngeal swabs directly tested with the ID NOW COVID-19 assay yielded a sensitivity, specificity, PPV and NPV of 98.0%, 97.5%, 96.2% and 98.7%, respectively, in comparison with the RT-PCR study reference assay. When the ID NOW COVID-19 assay was performed in the laboratory using the VTM samples, the sensitivity decreased to 62.5% and the NPV to 79.7%. Three false negative test results were reported with the ID NOW COVID-19 assay when performed using undiluted swabs directly in the ED; these results were obtained from patients with elevated CT values (>30). Conclusion : We demonstrated that the ID NOW COVID-19 assay, performed as a point of care test in the ED using dry swabs, provides a rapid and reliable alternative to laboratory-based RT-PCR methods
426 downloads medRxiv emergency medicine
Katie Biggs, Ben Thomas, Steve Goodacre, Ellen Lee, Laura Sutton, Matthew Bursnall, Amanda Loban, Simon Waterhouse, Richard Simmonds, Carl Marincowitz, 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
Objectives: Emergency department clinicians can use triage tools to predict adverse outcome and support management decisions for children presenting with suspected COVID-19. We aimed to estimate the accuracy of triage tools for predicting severe illness in children presenting to the emergency department (ED) with suspected COVID-19 infection. Methods: We undertook a mixed prospective and retrospective observational cohort study in 44 EDs across the United Kingdom (UK). We collected data from children attending with suspected COVID-19 between 26 March 2020 and 28 May 2020, and used presenting data to determine the results of assessment using the WHO algorithm, swine flu hospital pathway for children (SFHPC), Paediatric Observation Priority Score (POPS) and Childrens Observation and Severity Tool (COAST). We recorded 30-day outcome data (death or receipt of respiratory, cardiovascular or renal support) to determine prognostic accuracy for adverse outcome. Results: We collected data from 1530 children, including 26 (1.7%) with an adverse outcome. C-statistics were 0.80 (95% confidence interval 0.73-0.87) for the WHO algorithm, 0.80 (0.71-0.90) for POPS, 0.76 (0.67-0.85) for COAST, and 0.71 (0.59-0.82) for SFHPC. Using pre-specified thresholds, the WHO algorithm had the highest sensitivity (0.85) and lowest specificity (0.75), but POPS and COAST could optimise sensitivity (0.96 and 0.92 respectively) at the expense of specificity (0.25 and 0.38 respectively) by using a threshold of any score above zero instead of the pre-specified threshold. Conclusion: Existing triage tools have good but not excellent prediction for adverse outcome in children with suspected COVID-19. POPS and COAST could achieve an appropriate balance of sensitivity and specificity for supporting decisions to discharge home by considering any score above zero to be positive.
422 downloads medRxiv emergency medicine
ObjectiveAcute respiratory distress syndrome (ARDS) associated with high mortality is the common complication in acute pancreatitis(AP). The aim of this study was to formulate and validate an individualized predictive nomogram for in-hospital incidence of ARDS in AP patients. MethodFrom January 2017 to December 2018, 779 individuals with AP were included in this study. They were randomly distributed into primary cohort (n=560) and validation cohort (n=219). Based on the primary cohort, risk factors were identified by logistic regression model and a nomogram was performed. The nomogram was validated in the primary and validation cohort by the bootstrap validation method. The calibration curve was applied to evaluate the consistency between nomogram and ideal observation. ResultsThere were 728 patients in the non-ARDS group and 51 in the ARDS group, with an incidence rate of about 6.55%. Five independent factors including white blood counts(WBC), prothrombin time(PT), albumin(ALB), serum creatinine(SCR) and triglyceride (TG) were associated with in-hospital incidence of ARDS in AP patients. A nomogram was constructed based on the five independent factors with primary cohort of AUC 0.821 and validation cohort of AUC 0.822. Calibration curve analysis indicated that the predicted probability was in accordance with the observed probability in both primary and validation cohorts. ConclusionsThe study developed an intuitive nomogram with easily available laboratory parameters for the prediction of in-hospital incidence of ARDS in patients with AP. The incidence of ARDS for an individual patient can be fast and conveniently evaluated by our nomogram.
405 downloads medRxiv emergency medicine
Background Cardiac arrest is common in people admitted with suspected COVID-19 and has a poor prognosis. Do Not Attempt Resuscitation (DNAR) orders can reduce the risk of futile resuscitation attempts but have raised ethical concerns. Objectives We aimed to describe the characteristics and outcomes of adults admitted to hospital with suspected COVID-19 according to their DNAR status and identify factors associated with an early DNAR decision. Methods We undertook a secondary analysis of 13977 adults admitted to hospital with suspected COVID-19 and included in the Pandemic Respiratory Infection Emergency System Triage (PRIEST) study. We recorded presenting characteristics and outcomes (death or organ support) up to 30 days. We categorised patients as early DNAR (occurring before or on the day of admission) or late/no DNAR (no DNAR or occurring after the day of admission). We undertook descriptive analysis comparing these groups and multivariable analysis to identify independent predictors of early DNAR. Results We excluded 1249 with missing DNAR data, and identified 3929/12748 (31%) with an early DNAR decision. They had higher mortality (40.7% v 13.1%) and lower use of any organ support (11.6% v 15.7%), but received a range of organ support interventions, with some being used at rates comparable to those with late or no DNAR (e.g. non-invasive ventilation 4.4% v 3.5%). On multivariable analysis, older age (p<0.001), active malignancy (p<0.001), chronic lung disease (p<0.001), limited performance status (p<0.001), and abnormal physiological variables were associated with increased recording of early DNAR. Asian ethnicity was associated with reduced recording of early DNAR (p=0.001). Conclusions Early DNAR decisions were associated with recognised predictors of adverse outcome, and were inversely associated with Asian ethnicity. Most people with an early DNAR decision survived to 30 days and many received potentially life-saving interventions.
404 downloads medRxiv emergency medicine
Background Emergency Department (ED) attendances have fallen across the UK since the "lockdown" introduced on 23rd March 2020 to limit the spread of coronavirus disease 2019 (COVID-19). We hypothesised that reductions would vary by patient age and disease type. We examined pre- and in-lockdown ED attendances for two COVID-19 unrelated diagnoses; one likely to be affected by lockdown measures (gastroenteritis) and one likely to be unaffected (appendicitis). Methods Retrospective cross-sectional study conducted across two EDs in one London hospital Trust. We compared all adult and paediatric ED attendances, before (January 2020) and during lockdown (March/April 2020). Key patient demographics, method of arrival and discharge location were compared. We used SNOMED codes to define attendances for gastroenteritis and appendicitis. Results ED attendances fell from 1129 per day before lockdown to 584 in-lockdown; 51.7% of pre-lockdown rates. In-lockdown attendances were lowest for under-18s (16.0% of pre-lockdown). The proportion of patients admitted to hospital increased from 17.3% to 24.0% and the proportion admitted to intensive care increased four-fold. Attendances for gastroenteritis fell from 511 to 103; 20.2% of pre-lockdown rates. Attendances for appendicitis also decreased, from 144 to 41; 28.5% of pre-lockdown rates. Conclusion ED attendances fell substantially following lockdown implementation. The biggest reduction was for under-18s. We observed reductions in attendances for gastroenteritis and appendicitis. This may reflect lower rates of infectious disease transmission, though the fall in appendicitis-related attendances suggests that behavioural factors are also important. Larger studies are urgently needed to understand changing patterns of ED use and access to emergency care during the COVID-19 pandemic.
396 downloads medRxiv emergency medicine
Background: While there are numerous reports that describe emergency care during the early Covid-19 pandemic, there is scarcity of data for later stages. This study analyzes hospitalization rates for 37 emergency-sensitive conditions in the largest German-wide hospital network during different pandemic phases. Methods: Using claims data of 80 hospitals, consecutive cases between January 1 and November 17, 2020 were analyzed and compared to a corresponding period in 2019. Incidence-rate ratios (IRR) comparing the both periods were calculated using Poisson regression to model the number of hospitalizations per day. Results: There was a hospitalization deficit between March 12 and June 13, 2020 (coinciding with the 1st pandemic wave) with 32,807 hospitalizations as opposed to 39,379 in 2019 (IRR 0.83, 95% CI 0.82-0.85, P<0.01). During the following period (June 14 to November 17, 2020, including the start of 2nd wave), hospitalizations were reduced from 63,799 in 2019 to 59,910 in 2020, but this reduction was not that pronounced (IRR 0.94, 95% CI 0.93-0.95, P<0.01). There was an increase in hospitalizations for acute myocardial infarction, aortic aneurism/dissection and pulmonary embolism after the 1st wave during which hospitalizations had been reduced for those conditions. In contrast, hospitalizations for sepsis, pneumonia, obstructive pulmonary disease, and intracranial injuries were reduced during the entire pandemic. Conclusions: There was an overall reduction of hospitalizations for emergency-sensitive conditions in Germany during the Covid-19 pandemic with heterogeneous effects on different disease categories. The increase of hospitalizations for acute myocardial infarction, aortic aneurism/dissection and pulmonary embolism is an alarming signal that requires attention and further studies.
394 downloads medRxiv emergency medicine
Acute Stroke (AS) is the most common time-dependent disease attended in the Emergency Medicine Service (EMS) of Madrid (SUMMA 112). Community of Madrid has been one of the most affected regions in Spain by the coronavirus disease 2019 (COVID19) pandemic. A significant reduction in AS hospital admissions has been reported during the COVID-19 pandemic compared to the same period one year before. As international clinical practice guidelines support those patients with suspected acute stroke should be accessed via EMS, it is important to know whether the pandemic has jeopardized urgent pre-hospital stroke care, the first medical contact for most patients. We aimed to examine the impact of the COVID-19 in stroke codes (SC) in our EMS among three periods of time: the COVID-19 period, the same period the year before, and the 2019-2020 seasonal influenza period. Methods: We compared the SC frequency among the periods with high cumulative infection rate (above the median of the series) of the first wave of COVID-19, seasonal influenza, and also with the same period of the year before. Results: 1,130 SC were attended during the three periods. No significant reduction in SC was found during the COVID-19 pandemic. The reduction of hospital admissions might be attributable to patients attending the hospital by their means. The maximum SC workload seen during seasonal influenza has not been reached during the pandemic. We detected a non-significant deviation from the SC protocol, with a slight increase in hospitals' transfers to hospitals without stroke units.
392 downloads medRxiv emergency medicine
Introduction Tracking the COVID-19 pandemic using existing metrics such as confirmed cases and deaths are insufficient for understanding the trajectory of the pandemic and identifying the next wave of cases. In this study, we demonstrate the utility of monitoring the daily number of patients with COVID-like illness (CLI) who present to the Emergency Department (ED) as a tool that can guide local response efforts. Methods Using data from two hospitals in King County, WA, we examined the daily volume of CLI visits, and compare them to confirmed COVID cases and COVID deaths in the County. A linear regression model with varying lags is used to predict the number of daily COVID deaths from the number of CLI visits. Results CLI visits appear to rise and peak well in advance of both confirmed COVID cases and deaths in King County. Our regression analysis to predict daily deaths with a lagged count of CLI visits in the ED showed that the R2 value was maximized at 14 days. Conclusions ED CLI visits are a leading indicator of the pandemic. Adopting and scaling up a CLI monitoring approach at the local level will provide needed actionable evidence to policy makers and health officials struggling to confront this health challenge.
391 downloads medRxiv emergency medicine
Background: The COVID 19 pandemic was associated with social restrictions in the UK from 16th March 2020. It was unclear if the lockdown period was associated with differences in the case-mix of non-COVID acute medical admissions compared with the previous year. Methods: Retrospective data were collected for 1st to 30th April 2019 and 1st to 30th April 2020 from University Hospitals Birmingham NHS Foundation Trust, one of the largest hospitals in the UK with over 2 million patient contacts per year. The latter time period was chosen to coincide with the peak of COVID-19 cases in the West Midlands. All patients admitted under acute medicine during these time periods were included. COVID-19 was confirmed by SARS-Cov-2 swab or a probable case of COVID-19 based on World Health Organization diagnostic parameters. Non-COVID patients were those with a negative SARS-Cov-2 swab and no suspicion of COVID-19. Data was sourced from the UHB in-house electronic health system (EHS). Results: The total number of acute medical admissions fell comparing April 2019 (n=2409) to April 2020 (n=1682). As a proportion of total admissions, those aged under 45 years decreased, while those aged 46 and over did not change. The number of admissions due to psychiatric conditions and overdoses was higher in April 2020 (p < 0.001). When viewed as a proportion of admissions, alcohol-related admissions (p = 0.004), psychiatric conditions and overdoses (p<0.001) increased in April 2020 than in April 2019. The proportion of patients who were in hospital due to falls also increased in April 2020 (p<0.001). In the same period, the absolute number and the proportion of admissions that were due to non-specific chest pain, to musculoskeletal complaints and patients who self-discharged prior to assessment decreased (p=0.02, p=0.01 and p = 0.002 respectively). There were no significant differences in non-COVID-related intensive care admissions or mortality between the same months in the two years. Conclusion: In this large, single-centre study, there was a change in hospitalised case-mix when comparing April 2019 with April 2020: an increase in conditions which potentially reflect social isolation (falls, drug and alcohol misuse and psychiatric illness) and a decrease in conditions which rarely require in-patient hospital treatment (musculoskeletal pain and non-cardiac chest pain) especially among younger adults. These results highlight two areas for further research; the impact of social isolation on health and whether younger adults could be offered alternative health services to avoid potentially unnecessary hospital assessment.
377 downloads medRxiv emergency medicine
Objective: This survey aims at reviewing the actions undertaken by Switzerland's hospital pharmacies during the first wave of COVID-19 pandemic. Methods: A questionnaire covering topics related to the management of the COVID-19 crisis was sent to 65 heads of swiss hospital pharmacy. Results: 59% of pharmacies reported changes in the role of their staff. 41% of pharmacies had existing standard operating procedures or pandemic plans. 51% created new drug lists for: COVID-19-specific treatments (83% of pharmacies), sedatives (81%), anaesthetics (77%) and antibiotics (73%). Drug availability in COVID-19 wards was managed by increasing existing stocks (54% of pharmacies) and creating extra storage space (51%). Two drugs generated the most concern about shortages: propofol (49% of pharmacies) and midazolam (44%). Remdesivir stocks even ran out in 26% of pharmacies. 77% of pharmacies experienced problems procuring hand sanitiser solutions and 53% manufactured these themselves. Specific new documents were drafted to respond to medical needs with regards to drug administration (29% of pharmacies), drug preparation (29%) and treatment choices (24%). 47% of pharmacies implemented internal specific hygiene measures and 28% introduced team debriefings. Conclusions: Swiss hospital pharmacies encountered many challenges related to the COVID-19 crisis and had to find solutions quickly and effectively.
374 downloads medRxiv emergency medicine
Objectives: Accurate and reliable criteria to rapidly estimate the probability of infection with the novel coronavirus-2 that causes the severe acute respiratory syndrome (SARS-CoV-2) and associated disease (COVID-19) remain an urgent unmet need, especially in emergency care. The objective was to derive and validate a clinical prediction rule for SARS-CoV-2 infection that uses simple criteria widely available at the point of care. Methods: Data came from the Registry data from the national REgistry of suspected COVID-19 in EmeRgency care (RECOVER network) comprising 116 hospitals from 25 states in the US. Clinical predictors and 30-day outcomes were abstracted from medical records of 19,850 emergency department (ED) patients tested for SARS-CoV-2. The criterion standard for diagnosis of SARS-CoV-2 required a positive molecular test from a swabbed sample or positive antibody testing within 30 days. The prediction rule was derived from a 50% random sample (n=9,925) using unadjusted analysis of 107 candidate variables as a screening step, followed by stepwise forward logistic regression on 72 variables. Results: Multivariable regression yielded a 13-variable score, which was simplified to 13-point rule: +1 point each for age>50 years, measured temperature>37.5 degrees C, oxygen saturation<95%, Black race, Hispanic or Latino ethnicity, household contact with known or suspected COVID-19, patient reported history of dry cough, anosmia/dysgeusia, myalgias or fever; and -1 point each for White race, no direct contact with infected person, or smoking. In the validation sample (n=9,975), the score produced an area under the receiver operating character curve of 0.80 (95% CI: 0.79-0.81), and this level of accuracy was retained across patients enrolled from the early spring to summer of 2020. In the simplified rule, a score of zero produced a sensitivity of 95.6% (94.8-96.3%), specificity of 20.0% (19.0-21.0%), likelihood ratio negative of 0.22 (0.19-0.26). Increasing points on the simplified rule predicted higher probability of infection (e.g., >75% probability with +5 or more points). Conclusion: Criteria that are available at the point of care can accurately predict the probability of SARS-CoV-2 infection. These criteria could assist with decision about isolation and testing at high throughput checkpoints.
358 downloads medRxiv emergency medicine
Background: Risk stratification of patients presenting to the emergency department (ED) is important for appropriate triage. Diagnostic laboratory tests are an essential part of the work-up and risk stratification of these patients. Using machine learning, the prognostic power and clinical value of these tests can be amplified greatly. In this study, we applied machine learning to develop an accurate and explainable clinical decision support tool model that predicts the likelihood of 31-day mortality in ED patients (the RISKINDEX). This tool was developed and evaluated in four Dutch hospitals. Methods: Machine learning models included patient characteristics and available laboratory data collected within the first two hours after ED presentation, and were trained using five years of data from consecutive ED patients from the Maastricht University Medical Centre+ (Maastricht), Meander Medical Center (Amersfoort), and Zuyderland (Sittard and Heerlen). A sixth year of data was used to evaluate the models using area-under-the-receiver-operating-characteristic curve (AUROC) and calibration curves. The SHapley Additive exPlanations (SHAP) algorithm was used to obtain explainable machine learning models. Results: The present study included 266,327 patients with 7.1 million laboratory results available. Models show high diagnostic performance with AUROCs of 0.94,0.98,0.88, and 0.90 for Maastricht, Amersfoort, Sittard and Heerlen, respectively. The SHAP algorithm was utilized to visualize patient characteristics and laboratory data patterns that underlie individual RISKINDEX predictions. Conclusions: Our clinical decision support tool has excellent diagnostic performance in predicting 31-day mortality in ED patients. Follow-up studies will assess whether implementation of these algorithm can improve clinically relevant endpoints.
357 downloads medRxiv emergency medicine
Background. The Klinikum Hochrhein is responsible as a regional sole provider for the acute and emergency medical treatment of more than 170.000 people. Against the background of the pandemic spread of SARS-CoV-2 with expected high patient inflows and at the same time endangering one's own infrastructure due to intraclinical transmissions, the hospital management defined the maintenance of one's functionality as a priority protection objective in the pandemic. An essential strategic element was a very short-term restructuring of the Emergency Department with the objectives of reducing the number of cases within the clinic, detecting COVID-19 cases as sensitively as possible and separating the patient pathways at an early stage. Methods. The present work is a retrospective analysis of the processes and structures established in the Emergency Department between 27 March 2020 and 20 May 2020. In addition, a retrospective descriptive evaluation of the epidemiological and clinical data of the patients is carried out at the time of first contact during the period mentioned above. Results. After establishing a pre-triage with structured algorithms, all confirmed COVID-19 cases were identified before entering the clinic and assigned to an appropriate treatment pathway. Unprotected entry into hospital structures or nosocomial infections were not observed, although almost 35% of patients with confirmed infection were admitted due to other symptom complexes or injuries. 201 inpatient patients were initially isolated without COVID-19 being confirmed. The number of cases in the Emergency Department was 39% lower than the previous year's period, thus avoiding crowding. Discussion. The reduction in the number of cases was strategically intended and is primarily the result of a restrictive indication of in-clinical treatment but supported by a decline in emergency consultations that can be noticed anyway. The proportion of false positive triage results is probably dependent on epidemiological activity and was accepted for safety reasons as sufficient resources were available for isolation. Conclusion. Short-term organizational, spatial and procedural restructuring of the ZNA has enabled the clinic to achieve its goal of managing the pandemic. The algorithms we developed are particularly well suited to guarantee the desired level of safety in the case of a high pre-test probability.
354 downloads medRxiv emergency medicine
BackgroundAccurate methods of identifying patients with COVID-19 who are at high risk of poor outcomes has become especially important with the advent of limited-availability therapies such as monoclonal antibodies. Here we describe development and validation of a simple but accurate scoring tool to classify risk of hospitalization and mortality. MethodsAll consecutive patients testing positive for SARS-CoV-2 from March 25-October 1, 2020 within the Intermountain Healthcare system were included. The cohort was randomly divided into 70% derivation and 30% validation cohorts. A multivariable logistic regression model was fitted for 14-day hospitalization. The optimal model was then adapted to a simple, probabilistic score and applied to the validation cohort and evaluated for prediction of hospitalization and 28-day mortality. Results22,816 patients were included; mean age was 40 years, 50.1% were female and 44% identified as non-white race or Hispanic/Latinx ethnicity. 6.2% required hospitalization and 0.4% died. Criteria in the simple model included: age (0.5 points per decade); high-risk comorbidities (2 points each): diabetes mellitus, severe immunocompromised status and obesity (body mass index[≥]30); non-white race/Hispanic or Latinx ethnicity (2 points), and 1 point each for: male sex, dyspnea, hypertension, coronary artery disease, cardiac arrythmia, congestive heart failure, chronic kidney disease, chronic pulmonary disease, chronic liver disease, cerebrovascular disease, and chronic neurologic disease. In the derivation cohort (n=16,030) area under the receiver-operator characteristic curve (AUROC) was 0.82 (95% CI 0.81-0.84) for hospitalization and 0.91 (0.83-0.94) for 28-day mortality; in the validation cohort (n=6,786) AUROC for hospitalization was 0.8 (CI 0.78-0.82) and for mortality 0.8 (CI 0.69-0.9). ConclusionA prediction score based on widely available patient attributes accurately risk stratifies patients with COVID-19 at the time of testing. Applications include patient selection for therapies targeted at preventing disease progression in non-hospitalized patients, including monoclonal antibodies. External validation in independent healthcare environments is needed.
353 downloads medRxiv emergency medicine
Background Throughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available. Objective This systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19. Methods Searches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and July 2020 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized. Results A primary review found 292 articles relevant based on title and abstract. After further review, 246 were excluded based on the defined inclusion and exclusion criteria. Forty-six articles were included in the qualitative analysis. Inter observer agreement on inclusion was 0.86 (95% confidence interval: 0.79 - 0.93). When the PROBAST tool was applied, 44 of the 46 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Two studied reported prediction models, 4C Mortality Score from hospital data and QCOVID from general public data from UK, and were rated as low risk of bias and low concerns for applicability. Conclusion Several prognostic models are reported in the literature, but many of them had concerning risks of biases and applicability. For most of the studies, caution is needed before use, as many of them will require external validation before dissemination. However, two articles were found to have low risk of bias and low applicability can be useful tools.
347 downloads medRxiv emergency medicine
ObjectiveIn-hospital mortality rates in patients successfully resuscitated following out-of-hospital cardiac arrest (OHCA) remains high. Little has been published regarding the timing and putative causes of in-hospital death during the post-cardiac arrest resuscitation phase of care. In this study, we aimed to develop a novel two-stage categorization system and investigate the timing and factors associated with post-CA in-hospital death. DesignSingle-centered retrospective observational human study. SettingAdult Emergency Department and ICU in a university affiliated hospital. PatientsTwo hundred and forty-one adult, non-traumatic OHCA patients. InterventionsNone. Measurements and Main ResultsThrough an expert consensus process, a two-stage classification system of hospital deaths was developed. Data abstraction was performed by two researchers and inter-reliability was 0.858. We categorized deaths as being due to withdrawal of life sustaining treatment (WOLST) 159 (66.0%), recurrent in-hospital cardiac arrest 51 (21.1%), and declared dead by neurological criteria 31 (12.9%). Half of WOLST decisions occurred primarily in the setting of isolated neurological injury. Early in-hospital death ([≤] 3 days) was associated with recurrent in-hospital cardiac arrest and WOLST with refractory shock or multi-organ injury. Late in-hospital death (> 3 days) was associated with WOLST due to neurological injury. Age, initial lactate level, duration of CPR exceeding 30 minutes, and vasopressor dependence post ROSC was found to be the dependent predictors for Early death during hospital stay. ConclusionsOur novel two-stage categorization scheme for post-CA deaths demonstrated high inter-rater reliability. The majority of in-hospital post-CA deaths were due to neurological injury associated with WOLST. Early deaths were largely attributed to recurrent in-hospital cardiac arrest, and WOLST due to refractory shock or multi-organ injury while Late deaths occurred in the context of neurological injury demonstrating two phases of injury in the post-CA syndrome.
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