Prescription of analgesia in emergency medicine (POEM) secondary analysis: an observational multicentre comparison of pain relief provided to adults and children with an isolated limb fracture and/or dislocation.

BACKGROUND: Acute pain is a common reason for emergency department (ED) attendance. Royal College of Emergency Medicine (RCEM) pain management audits have shown national variation and room for improvement. Previous evidence suggests that children receive less satisfactory pain management than adults. METHODS: Prescription of analgesia in emergency medicine is a cross-sectional observational study of consecutive patients presenting to 12 National Health Service EDs with an isolated long bone fracture and/or dislocation, and was carried out between 2015 and 2017. Using the recommendations in the RCEM Best Practice Guidelines, pain management in ED was assessed for differences of age (adults vs children) and hospital type (children's vs all patients). RESULTS: From the total 8346 patients, 38% were children (median age 8 years). There was better adherence to the RCEM guidance for children than adults (24% (766/3196) vs 11% (579/5123)) for the combined outcome of timely assessment, pain score and appropriate analgesia. In addition, children were significantly more likely than adults to receive analgesia appropriate to the pain score (of those with a recorded pain score 67% (1168/1744) vs 52% (1238/2361)). Children's hospitals performed much better across all reported outcomes compared with general hospitals. CONCLUSIONS: In contrast to previous studies, children with a limb fracture/dislocation are more likely than adults to have a pain score documented and to receive appropriate analgesia. Unexpectedly, children's EDs performed better than general EDs in relation to timely and appropriate analgesia but the reasons for this are not apparent from the present study.

Real-world evaluation of rapid and laboratory-free COVID-19 triage for emergency care: external validation and pilot deployment of artificial intelligence driven screening.

BACKGROUND: Uncertainty in patients' COVID-19 status contributes to treatment delays, nosocomial transmission, and operational pressures in hospitals. However, the typical turnaround time for laboratory PCR remains 12-24 h and lateral flow devices (LFDs) have limited sensitivity. Previously, we have shown that artificial intelligence-driven triage (CURIAL-1.0) can provide rapid COVID-19 screening using clinical data routinely available within 1 h of arrival to hospital. Here, we aimed to improve the time from arrival to the emergency department to the availability of a result, do external and prospective validation, and deploy a novel laboratory-free screening tool in a UK emergency department. METHODS: We optimised our previous model, removing less informative predictors to improve generalisability and speed, developing the CURIAL-Lab model with vital signs and readily available blood tests (full blood count [FBC]; urea, creatinine, and electrolytes; liver function tests; and C-reactive protein) and the CURIAL-Rapide model with vital signs and FBC alone. Models were validated externally for emergency admissions to University Hospitals Birmingham, Bedfordshire Hospitals, and Portsmouth Hospitals University National Health Service (NHS) trusts, and prospectively at Oxford University Hospitals, by comparison with PCR testing. Next, we compared model performance directly against LFDs and evaluated a combined pathway that triaged patients who had either a positive CURIAL model result or a positive LFD to a COVID-19-suspected clinical area. Lastly, we deployed CURIAL-Rapide alongside an approved point-of-care FBC analyser to provide laboratory-free COVID-19 screening at the John Radcliffe Hospital (Oxford, UK). Our primary improvement outcome was time-to-result, and our performance measures were sensitivity, specificity, positive and negative predictive values, and area under receiver operating characteristic curve (AUROC). FINDINGS: 72 223 patients met eligibility criteria across the four validating hospital groups, in a total validation period spanning Dec 1, 2019, to March 31, 2021. CURIAL-Lab and CURIAL-Rapide performed consistently across trusts (AUROC range 0·858-0·881, 95% CI 0·838-0·912, for CURIAL-Lab and 0·836-0·854, 0·814-0·889, for CURIAL-Rapide), achieving highest sensitivity at Portsmouth Hospitals (84·1%, Wilson's 95% CI 82·5-85·7, for CURIAL-Lab and 83·5%, 81·8-85·1, for CURIAL-Rapide) at specificities of 71·3% (70·9-71·8) for CURIAL-Lab and 63·6% (63·1-64·1) for CURIAL-Rapide. When combined with LFDs, model predictions improved triage sensitivity from 56·9% (51·7-62·0) for LFDs alone to 85·6% with CURIAL-Lab (81·6-88·9; AUROC 0·925) and 88·2% with CURIAL-Rapide (84·4-91·1; AUROC 0·919), thereby reducing missed COVID-19 cases by 65% with CURIAL-Lab and 72% with CURIAL-Rapide. For the prospective deployment of CURIAL-Rapide, 520 patients were enrolled for point-of-care FBC analysis between Feb 18 and May 10, 2021, of whom 436 received confirmatory PCR testing and ten (2·3%) tested positive. Median time from arrival to a CURIAL-Rapide result was 45 min (IQR 32-64), 16 min (26·3%) sooner than with LFDs (61 min, 37-99; log-rank p<0·0001), and 6 h 52 min (90·2%) sooner than with PCR (7 h 37 min, 6 h 5 min to 15 h 39 min; p<0·0001). Classification performance was high, with sensitivity of 87·5% (95% CI 52·9-97·8), specificity of 85·4% (81·3-88·7), and negative predictive value of 99·7% (98·2-99·9). CURIAL-Rapide correctly excluded infection for 31 (58·5%) of 53 patients who were triaged by a physician to a COVID-19-suspected area but went on to test negative by PCR. INTERPRETATION: Our findings show the generalisability, performance, and real-world operational benefits of artificial intelligence-driven screening for COVID-19 over standard-of-care in emergency departments. CURIAL-Rapide provided rapid, laboratory-free screening when used with near-patient FBC analysis, and was able to reduce the number of patients who tested negative for COVID-19 but were triaged to COVID-19-suspected areas. FUNDING: The Wellcome Trust, University of Oxford Medical and Life Sciences Translational Fund.

Changes in paediatric respiratory infections at a UK teaching hospital 2016-2021; impact of the SARS-CoV-2 pandemic.

Objective To describe the impact of the SARS-CoV-2 pandemic on the incidence of paediatric viral respiratory tract infection in Oxfordshire, UK. Methods Data on paediatric Emergency Department (ED) attendances (0-15 years inclusive), respiratory virus testing, vital signs and mortality at Oxford University Hospitals were summarised using descriptive statistics. Results Between 1-March-2016 and 30-July-2021, 155,056 ED attendances occurred and 7,195 respiratory virus PCRs were performed. Detection of all pathogens was suppressed during the first national lockdown. Rhinovirus and adenovirus rates increased when schools reopened September-December 2020, then fell, before rising in March-May 2021. The usual winter RSV peak did not occur in 2020/21, with an inter-seasonal rise (32/1,000 attendances in 0-3 yr olds) in July 2021. Influenza remained suppressed throughout. A higher paediatric early warning score (PEWS) was seen for attendees with adenovirus during the pandemic compared to pre-pandemic (p = 0.04, Mann-Witney U test), no other differences in PEWS were seen. Conclusions SARS-CoV-2 caused major changes in the incidence of paediatric respiratory viral infection in Oxfordshire, with implications for clinical service demand, testing strategies, timing of palivizumab RSV prophylaxis, and highlighting the need to understand which public health interventions are most effective for preventing respiratory virus infections.

Predicting treatment outcomes following an exacerbation of airways disease.

BACKGROUND: COPD and asthma exacerbations result in many emergency department admissions. Not all treatments are successful, often leading to hospital readmissions. AIMS: We sought to develop predictive models for exacerbation treatment outcome in a cohort of exacerbating asthma and COPD patients presenting to the emergency department. METHODS: Treatment failure was defined as the need for additional systemic corticosteroids (SCS) and/or antibiotics, hospital readmissison or death within 30 days of initial emergency department visit. We performed univariate analysis comparing characteristics of patients either given or not given SCS at exacerbation and of patients who succeeded versus failed treatment. Patient demographics, medications and exacerbation symptoms, physiology and biology were available. We developed multivariate random forest models to identify predictors of SCS prescription and for predicting treatment failure. RESULTS: Data were available for 81 patients, 43 (53%) of whom failed treatment. 64 (79%) of patients were given SCS. A random forest model using presence of wheeze at exacerbation and blood eosinophil percentage predicted SCS prescription with area under receiver operating characteristic curve (AUC) 0.69. An 11 variable random forest model (which included medication, previous exacerbations, symptoms and quality of life scores) could predict treatment failure with AUC 0.81. A random forest model using just the two best predictors of treatment failure, namely, visual analogue scale for breathlessness and sputum purulence, predicted treatment failure with AUC 0.68. CONCLUSION: Prediction of exacerbation treatment outcome can be achieved via supervised machine learning combining different predictors at exacerbation. Validation of our predictive models in separate, larger patient cohorts is required.

A haemagglutination test for rapid detection of antibodies to SARS-CoV-2.

Serological detection of antibodies to SARS-CoV-2 is essential for establishing rates of seroconversion in populations, and for seeking evidence for a level of antibody that may be protective against COVID-19 disease. Several high-performance commercial tests have been described, but these require centralised laboratory facilities that are comparatively expensive, and therefore not available universally. Red cell agglutination tests do not require special equipment, are read by eye, have short development times, low cost and can be applied at the Point of Care. Here we describe a quantitative Haemagglutination test (HAT) for the detection of antibodies to the receptor binding domain of the SARS-CoV-2 spike protein. The HAT has a sensitivity of 90% and specificity of 99% for detection of antibodies after a PCR diagnosed infection. We will supply aliquots of the test reagent sufficient for ten thousand test wells free of charge to qualified research groups anywhere in the world.

Prescription Of analgesia in Emergency Medicine (POEM): a multicentre observational survey of pain relief in patients presenting with an isolated limb fracture and/or dislocation.

BACKGROUND: Acute pain is one of the most commonly cited reasons for attendance to the emergency department (ED), and the Royal College of Emergency Medicine (RCEM) Best Practice Guideline (2014) acknowledged that the current management of acute pain in UK EDs is inadequate and has a poor evidence base. METHODS: The Prescription Of analgesia in Emergency Medicine (POEM) survey is a cross-sectional observational survey of consecutive patients presenting to 12 National Health Service (NHS) EDs with limb fracture and/or dislocation in England and Scotland and was carried out between 2015 and 2017. The primary outcome was to assess the adequacy of pain management in the ED against the recommendations in the RCEM Best Practice Guidelines. RESULTS: In all, 8346 patients were identified as attending the ED with a limb fracture and/or dislocation but adherence to RCEM guidelines could only be evaluated for the 4160 (49.8%) patients with a recorded pain score. Of these, 2409/4160 (57.9%) patients received appropriate pain relief, but only 1347 patients were also assessed within 20 minutes of their arrival in the ED. Therefore, according to the RCEM guidelines, only 16.1% (1347/8346) of all patients were assessed and had satisfactory pain management in the ED. CONCLUSIONS: The POEM survey has identified that pain relief for patients with an isolated limb fracture remains inadequate when strictly compared to the RCEM Best Practice Guidelines. However, we have found that some patients receive analgesia despite having no pain score recorded, while other analgesic modalities are provided that are not currently encompassed by the Best Practice Guidelines. Future iterations of these guidelines may wish to encompass the breadth of available modalities of pain relief and the whole patient journey. In addition, more work is needed to improve timely and repeated assessment of pain and its recording, which has been better achieved in some EDs than others.

Sleep and intrusive memories immediately after a traumatic event in emergency department patients.

STUDY OBJECTIVES: Intrusive memories of psychological trauma are a core clinical feature of posttraumatic stress disorder (PTSD), and in the early period post-trauma may be a potential target for early intervention. Disrupted sleep in the weeks post-trauma is associated with later PTSD. The impact of sleep and intrusive memories immediately post-trauma, and their relation to later PTSD, is unknown. This study assessed the relationship between sleep duration on the first night following a real-life traumatic event and intrusive memories in the subsequent week, and how these might relate to PTSD symptoms at 2 months. METHODS: Patients (n = 87) recruited in the emergency department completed a sleep and intrusive memory diary from the day of their trauma and for the subsequent week, with optional actigraphy. PTSD, anxiety, and depression symptoms were assessed at 1 week and 2 months. RESULTS: A U-shaped relationship was observed between sleep duration on the first night and intrusive memories over the subsequent week: sleeping "too little" or "too much" was associated with more intrusive memories. Individuals who met Clinician-Administered PTSD Scale (CAPS) criteria for PTSD at 2 months had three times more intrusive memories in the first week immediately post-trauma than those who did not (M = 28.20 vs 9.96). Post hoc analysis showed that the absence of intrusive memories in the first week post-trauma was only observed in those who did not meet CAPS criteria for PTSD at 2 months. CONCLUSIONS: Monitoring intrusive memories and sleep in the first week post-trauma, using a simple diary, may help identify individuals more vulnerable to later psychopathology.

Antibody testing for COVID-19: A report from the National COVID Scientific Advisory Panel.

Background: The COVID-19 pandemic caused >1 million infections during January-March 2020. There is an urgent need for reliable antibody detection approaches to support diagnosis, vaccine development, safe release of individuals from quarantine, and population lock-down exit strategies. We set out to evaluate the performance of ELISA and lateral flow immunoassay (LFIA) devices. Methods: We tested plasma for COVID (severe acute respiratory syndrome coronavirus 2; SARS-CoV-2) IgM and IgG antibodies by ELISA and using nine different LFIA devices. We used a panel of plasma samples from individuals who have had confirmed COVID infection based on a PCR result (n=40), and pre-pandemic negative control samples banked in the UK prior to December-2019 (n=142). Results: ELISA detected IgM or IgG in 34/40 individuals with a confirmed history of COVID infection (sensitivity 85%, 95%CI 70-94%), vs. 0/50 pre-pandemic controls (specificity 100% [95%CI 93-100%]). IgG levels were detected in 31/31 COVID-positive individuals tested ≥10 days after symptom onset (sensitivity 100%, 95%CI 89-100%). IgG titres rose during the 3 weeks post symptom onset and began to fall by 8 weeks, but remained above the detection threshold. Point estimates for the sensitivity of LFIA devices ranged from 55-70% versus RT-PCR and 65-85% versus ELISA, with specificity 95-100% and 93-100% respectively. Within the limits of the study size, the performance of most LFIA devices was similar. Conclusions: Currently available commercial LFIA devices do not perform sufficiently well for individual patient applications. However, ELISA can be calibrated to be specific for detecting and quantifying SARS-CoV-2 IgM and IgG and is highly sensitive for IgG from 10 days following first symptoms.

Factors affecting recruitment and retention of nurses who deliver clinical research: A qualitative study.

AIM: To provide a better understanding of the factors affecting recruitment and retention of clinical research nurses. DESIGN: Qualitative exploratory design. METHODS: An on-line questionnaire comprising open-ended and fixed-choice questions was completed by 121 clinical research nurses. Seven focus groups were held with a subgroup of 26 participants. Data were analysed using inductive thematic analysis. RESULTS: Participants were attracted to a research nurse post by an interest in research itself, a desire for a change or to achieve personal objectives. The majority expected to continue in a research post for the next 5 years, while others expected to move on to research management, a clinical post or retirement; few had ambitions to become an independent researcher. Factors identified in focus groups as leading to intentions to leave research included desire for further change, concern about loss of clinical skills, rebalancing family/work responsibilities, short-term contracts, unsupportive employers and limited career progression.

Whats that noise? Bedside monitoring in the Emergency Department.

OBJECTIVE: To determine the frequency, duration and type of audible monitor alarms in an ED, utilising the standard manufacturer's classification. METHODS: The audible monitor alarms and the timing of any intervention related to the patient monitoring was observed and recorded. RESULTS: 110 Patients admitted to the Majors area or Resuscitation Room were observed for a total of 93 hours. One monitor was observed at a time. Alarm noise was generated 29% of the observation time. Overall, 429 alarms lasting 21 hours 27 minutes were judged to be positive and 143 alarms lasting 5 hours 47 minutes, negative. 74% of Resuscitation Room and 47% of Majors alarms were silenced or paused. Alarm limit parameters were only adjusted after 5% of alarms in Resuscitation Room and 6% of alarms in Majors. CONCLUSIONS: Whilst high level monitoring is desired from a patient safety perspective, it contributes to a significant ambient noise level, which is recognised by all who pass through an ED, and can be detrimental to patients, relatives and staff. We have demonstrated that there is a high probability of near-continuous alarm noise from patient monitoring in a 10-bedded Majors area. We make suggestions for methods of noise reduction and intend to implement some of these within our own ED.