Service users' preferences and feasibility - which alternative care pathway for adult ambulance users achieves the optimal balance? Workshops for the COLLABORATE project.

INTRODUCTION: Adults presenting to the ambulance service for diagnosed epilepsy are often transported to emergency departments (EDs) despite no clinical need. An alternative care pathway (CP) could allow paramedics to divert them from ED and instigate ambulatory care improvements. To identify the most promising CP configuration for subsequent testing, the COLLABORATE project surveyed people with epilepsy and family/friends who had recently used the English ambulance service to elicit preferences for 288 CP configurations for different seizures. This allowed CPs to be ranked according to alignment with service users' preferences. However, as well as being acceptable to users, a CP must be feasible. We thus engaged with paramedics, epilepsy specialists and commissioners to identify the optimal configuration. METHODS: Three Knowledge Exchange workshops completed. Participants considered COLLABORATE's evidence on service users' preferences for the different configurations. Nominal group techniques elicited views on the feasibility of users' preferences according to APEASE criteria. Workshop groups specified the configuration/s considered optimum. Qualitative data was analysed thematically. Utility to users of the specified CP configurations estimated using the COLLABORATE preference survey data. RESULTS: Twenty-seven participants found service users' preferences broadly feasible and outlined delivery recommendations. They identified enough commonality in preferences for different seizures to propose a single CP. Its configuration comprised: 1) patients staying where they were; 2) paramedics having access to medical records; 3) care episodes lasting <6 h; 4) paramedics receiving specialist advice on the day; 5) patient's GP being notified; and 6) a follow-up appointment being arranged with an epilepsy specialist. Preference data indicated higher utility for this configuration compared to current care. DISCUSSION: Stakeholders are of the view that the CP configuration favoured by service users could be NHS feasible. It should be developed and evaluated.

Developing an alternative care pathway for emergency ambulance responses for adults with epilepsy: A Discrete Choice Experiment to understand which configuration service users prefer. Part of the COLLABORATE project.

INTRODUCTION: To identify service users' preferences for an alternative care pathway for adults with epilepsy presenting to the ambulance service. METHODS: Extensive formative work (qualitative, survey and knowledge exchange) informed the design of a stated preference discrete choice experiment (DCE). This hypothetical survey was hosted online and consisted of 12 binary choices of alternative care pathways described in terms of: the paramedic's access to medical records/ 'care plan', what happens next (described in terms of conveyance), time, availability of epilepsy specialists today, general practitioner (GP) notification and future contact with epilepsy specialists. DCE scenarios were described as: (i) typical seizure at home. (ii) typical seizure in public, (iii) atypical seizure. Respondents were recruited by a regional English ambulance service and by national public adverts. Participants were randomised to complete 2 of the 3 DCEs. RESULTS: People with epilepsy (PWE; n = 427) and friends/family (n = 167) who completed the survey were representative of the target population. PWE preferred paramedics to have access to medical records, non-conveyance, to avoid lengthy episodes of care, availability of epilepsy specialists today, GP notification, and contact with epilepsy specialists within 2-3 weeks. Significant others (close family members or friends) preferred PWE experiencing an atypical seizure to be conveyed to an Urgent Treatment Centre and preferred shorter times. Optimal configuration of services from service users' perspective far out ranked current practice (rank 230/288 possible configurations). DISCUSSION: Preferences differ to current practice but have minimal variation by seizure type or stakeholder. Further work on feasibility of these pathways in England, and potentially beyond, is required.

Evaluation of venous thromboembolism risk assessment models for hospital inpatients: the VTEAM evidence synthesis.

Background: Pharmacological prophylaxis during hospital admission can reduce the risk of acquired blood clots (venous thromboembolism) but may cause complications, such as bleeding. Using a risk assessment model to predict the risk of blood clots could facilitate selection of patients for prophylaxis and optimise the balance of benefits, risks and costs. Objectives: We aimed to identify validated risk assessment models and estimate their prognostic accuracy, evaluate the cost-effectiveness of different strategies for selecting hospitalised patients for prophylaxis, assess the feasibility of using efficient research methods and estimate key parameters for future research. Design: We undertook a systematic review, decision-analytic modelling and observational cohort study conducted in accordance with Enhancing the QUAlity and Transparency Of health Research (EQUATOR) guidelines. Setting: NHS hospitals, with primary data collection at four sites. Participants: Medical and surgical hospital inpatients, excluding paediatric, critical care and pregnancy-related admissions. Interventions: Prophylaxis for all patients, none and according to selected risk assessment models. Main outcome measures: Model accuracy for predicting blood clots, lifetime costs and quality-adjusted life-years associated with alternative strategies, accuracy of efficient methods for identifying key outcomes and proportion of inpatients recommended prophylaxis using different models. Results: We identified 24 validated risk assessment models, but low-quality heterogeneous data suggested weak accuracy for prediction of blood clots and generally high risk of bias in all studies. Decision-analytic modelling showed that pharmacological prophylaxis for all eligible is generally more cost-effective than model-based strategies for both medical and surgical inpatients, when valuing a quality-adjusted life-year at £20,000. The findings were more sensitive to uncertainties in the surgical population; strategies using risk assessment models were more cost-effective if the model was assumed to have a very high sensitivity, or the long-term risks of post-thrombotic complications were lower. Efficient methods using routine data did not accurately identify blood clots or bleeding events and several pre-specified feasibility criteria were not met. Theoretical prophylaxis rates across an inpatient cohort based on existing risk assessment models ranged from 13% to 91%. Limitations: Existing studies may underestimate the accuracy of risk assessment models, leading to underestimation of their cost-effectiveness. The cost-effectiveness findings do not apply to patients with an increased risk of bleeding. Mechanical thromboprophylaxis options were excluded from the modelling. Primary data collection was predominately retrospective, risking case ascertainment bias. Conclusions: Thromboprophylaxis for all patients appears to be generally more cost-effective than using a risk assessment model, in hospitalised patients at low risk of bleeding. To be cost-effective, any risk assessment model would need to be highly sensitive. Current evidence on risk assessment models is at high risk of bias and our findings should be interpreted in this context. We were unable to demonstrate the feasibility of using efficient methods to accurately detect relevant outcomes for future research. Future work: Further research should evaluate routine prophylaxis strategies for all eligible hospitalised patients. Models that could accurately identify individuals at very low risk of blood clots (who could discontinue prophylaxis) warrant further evaluation. Study registration: This study is registered as PROSPERO CRD42020165778 and Researchregistry5216. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR127454) and will be published in full in Health Technology Assessment; Vol. 28, No. 20. See the NIHR Funding and Awards website for further award information.

People who are admitted to hospital are at risk of blood clots that can cause serious illness or death. Patients are often given low doses of blood-thinning drugs to reduce this risk. However, these drugs can cause side effects, such as bleeding. Hospitals currently use complex risk assessment models (risk scores, which usually include patient, disease, mobility and intervention factors) to determine the individual risk of blood clots and identify people most likely to benefit from blood-thinning drugs. There are a lot of different risk scores and we do not know which one is best. We also do not know how these scores compare to each other or whether using scores to decide who should get blood-thinning drugs provides good value for money to the NHS. We reviewed all previous studies of risk scores. We found that they did not predict blood clots very well and we could not recommend one score over another. We then created a mathematical model to simulate the use of blood-thinning drugs in people admitted to hospital. The model suggested that giving blood-thinning drugs to everyone who could have them would probably provide the best value for money, in medical patients. Our findings were the same, but less certain, for surgical patients. We also collected information from four NHS hospitals to explore possibilities for future research. Our work showed that routinely collected electronic data on blood clots and bleeding events is not very accurate and that using different scores could result in variable use of blood-thinning medications. Our findings suggest that it may be better value to the NHS and better for patients if we were to offer blood-thinning medications to everyone on admission to hospital, without using any risk score. However, this approach needs further research to ensure it is safe and effective. Such research would not be able to rely on routine electronic data to identify blood clots or bleeding events, in isolation.

Prehospital early warning scores for adults with suspected sepsis: the PHEWS observational cohort and decision-analytic modelling study.

Background: Guidelines for sepsis recommend treating those at highest risk within 1 hour. The emergency care system can only achieve this if sepsis is recognised and prioritised. Ambulance services can use prehospital early warning scores alongside paramedic diagnostic impression to prioritise patients for treatment or early assessment in the emergency department. Objectives: To determine the accuracy, impact and cost-effectiveness of using early warning scores alongside paramedic diagnostic impression to identify sepsis requiring urgent treatment. Design: Retrospective diagnostic cohort study and decision-analytic modelling of operational consequences and cost-effectiveness. Setting: Two ambulance services and four acute hospitals in England. Participants: Adults transported to hospital by emergency ambulance, excluding episodes with injury, mental health problems, cardiac arrest, direct transfer to specialist services, or no vital signs recorded. Interventions: Twenty-one early warning scores used alongside paramedic diagnostic impression, categorised as sepsis, infection, non-specific presentation, or other specific presentation. Main outcome measures: Proportion of cases prioritised at the four hospitals; diagnostic accuracy for the sepsis-3 definition of sepsis and receiving urgent treatment (primary reference standard); daily number of cases with and without sepsis prioritised at a large and a small hospital; the minimum treatment effect associated with prioritisation at which each strategy would be cost-effective, compared to no prioritisation, assuming willingness to pay £20,000 per quality-adjusted life-year gained. Results: Data from 95,022 episodes involving 71,204 patients across four hospitals showed that most early warning scores operating at their pre-specified thresholds would prioritise more than 10% of cases when applied to non-specific attendances or all attendances. Data from 12,870 episodes at one hospital identified 348 (2.7%) with the primary reference standard. The National Early Warning Score, version 2 (NEWS2), had the highest area under the receiver operating characteristic curve when applied only to patients with a paramedic diagnostic impression of sepsis or infection (0.756, 95% confidence interval 0.729 to 0.783) or sepsis alone (0.655, 95% confidence interval 0.63 to 0.68). None of the strategies provided high sensitivity (> 0.8) with acceptable positive predictive value (> 0.15). NEWS2 provided combinations of sensitivity and specificity that were similar or superior to all other early warning scores. Applying NEWS2 to paramedic diagnostic impression of sepsis or infection with thresholds of > 4, > 6 and > 8 respectively provided sensitivities and positive predictive values (95% confidence interval) of 0.522 (0.469 to 0.574) and 0.216 (0.189 to 0.245), 0.447 (0.395 to 0.499) and 0.274 (0.239 to 0.313), and 0.314 (0.268 to 0.365) and 0.333 (confidence interval 0.284 to 0.386). The mortality relative risk reduction from prioritisation at which each strategy would be cost-effective exceeded 0.975 for all strategies analysed. Limitations: We estimated accuracy using a sample of older patients at one hospital. Reliable evidence was not available to estimate the effectiveness of prioritisation in the decision-analytic modelling. Conclusions: No strategy is ideal but using NEWS2, in patients with a paramedic diagnostic impression of infection or sepsis could identify one-third to half of sepsis cases without prioritising unmanageable numbers. No other score provided clearly superior accuracy to NEWS2. Research is needed to develop better definition, diagnosis and treatments for sepsis. Study registration: This study is registered as Research Registry (reference: researchregistry5268). Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: 17/136/10) and is published in full in Health Technology Assessment; Vol. 28, No. 16. See the NIHR Funding and Awards website for further award information.

Sepsis is a life-threatening condition in which an abnormal response to infection causes heart, lung or kidney failure. People with sepsis need urgent treatment. They need to be prioritised at the emergency department rather than waiting in the queue. Paramedics attempt to identify people with possible sepsis using an early warning score (based on simple measurements, such as blood pressure and heart rate) alongside their impression of the patient's diagnosis. They can then alert the hospital to assess the patient quickly. However, an inaccurate early warning score might miss cases of sepsis or unnecessarily prioritise people without sepsis. We aimed to measure how accurately early warning scores identified people with sepsis when used alongside paramedic diagnostic impression. We collected data from 71,204 people that two ambulance services transported to four different hospitals in 2019. We recorded paramedic diagnostic impressions and calculated early warning scores for each patient. At one hospital, we linked ambulance records to hospital records and identified who had sepsis. We then calculated the accuracy of using the scores alongside diagnostic impression to diagnose sepsis. Finally, we used modelling to predict how many patients (with and without sepsis) paramedics would prioritise using different strategies based on early warning scores and diagnostic impression. We found that none of the currently available early warning scores were ideal. When they were applied to all patients, they prioritised too many people. When they were only applied to patients whom the paramedics thought had infection, they missed many cases of sepsis. The NEWS2, score, which ambulance services already use, was as good as or better than all the other scores we studied. We found that using the NEWS2, score in people with a paramedic impression of infection could achieve a reasonable balance between prioritising too many patients and avoiding missing patients with sepsis.

Thromboprophylaxis during pregnancy and the puerperium: a systematic review and economic evaluation to estimate the value of future research.

Background: Pharmacological prophylaxis to prevent venous thromboembolism is currently recommended for women assessed as being at high risk of venous thromboembolism during pregnancy or in the 6 weeks after delivery (the puerperium). The decision to provide thromboprophylaxis involves weighing the benefits, harms and costs, which vary according to the individual's venous thromboembolism risk. It is unclear whether the United Kingdom's current risk stratification approach could be improved by further research. Objectives: To quantify the current decision uncertainty associated with selecting women who are pregnant or in the puerperium for thromboprophylaxis and to estimate the value of one or more potential future studies that would reduce that uncertainty, while being feasible and acceptable to patients and clinicians. Methods: A decision-analytic model was developed which was informed by a systematic review of risk assessment models to predict venous thromboembolism in women who are pregnant or in the puerperium. Expected value of perfect information analysis was used to determine which factors are associated with high decision uncertainty and should be the target of future research. To find out whether future studies would be acceptable and feasible, we held workshops with women who have experienced a blood clot or have been offered blood-thinning drugs and surveyed healthcare professionals. Expected value of sample information analysis was used to estimate the value of potential future research studies. Results: The systematic review included 17 studies, comprising 19 unique externally validated risk assessment models and 1 internally validated model. Estimates of sensitivity and specificity were highly variable ranging from 0% to 100% and 5% to 100%, respectively. Most studies had unclear or high risk of bias and applicability concerns. The decision analysis found that there is substantial decision uncertainty regarding the use of risk assessment models to select high-risk women for antepartum prophylaxis and obese postpartum women for postpartum prophylaxis. The main source of decision uncertainty was uncertainty around the effectiveness of thromboprophylaxis for preventing venous thromboembolism in women who are pregnant or in the puerperium. We found that a randomised controlled trial of thromboprophylaxis in obese postpartum women is likely to have substantial value and is more likely to be acceptable and feasible than a trial recruiting women who have had a previous venous thromboembolism. In unselected postpartum women and women following caesarean section, the poor performance of risk assessment models meant that offering prophylaxis based on these models had less favourable cost effectiveness with lower decision uncertainty. Limitations: The performance of the risk assessment model for obese postpartum women has not been externally validated. Conclusions: Future research should focus on estimating the efficacy of pharmacological thromboprophylaxis in pregnancy and the puerperium, and clinical trials would be more acceptable in women who have not had a previous venous thromboembolism. Study registration: This study is registered as PROSPERO CRD42020221094. Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme (NIHR award ref: NIHR131021) and is published in full in Health Technology Assessment; Vol. 28, No. 9. See the NIHR Funding and Awards website for further award information.

Women who are pregnant or who have given birth in the previous 6 weeks are at increased risk of developing blood clots that can cause serious illness or death. Small doses of blood thinners given by injection are safe in pregnancy and can reduce the risk of blood clots, but they can slightly increase the risk of bleeding. Healthcare professionals use risk assessment tools to decide if a woman is at high risk of blood clots and should be offered blood thinners. We wanted to find out what research would be useful to help them make better decisions. We reviewed previous research to establish which risk assessment tools are best at predicting who will have a blood clot. We then created a mathematical model to predict what would happen when using different risk assessment tools to decide who should be offered blood thinners, both during pregnancy and after giving birth. We found that there was a lot of uncertainty about which women should be offered blood thinners. This was mainly because there have only been a few small studies comparing blood thinners to no treatment in pregnant women or women who have recently given birth. We estimated the value of future studies comparing blood thinners to no treatment, in groups of women with different risk factors, by predicting what information we would gain and how this would be used to improve decisions about using blood thinners. To find out whether these studies would be acceptable and feasible, we held workshops with women who have experienced a blood clot or have been offered blood thinners and surveyed healthcare professionals. We found that a study in obese women who have recently given birth would have substantial value and may be more acceptable than a study in pregnant women with a previous blood clot.

Prognostic accuracy of eight triage scores in suspected COVID-19 in an Emergency Department low-income setting: An observational cohort study.

Introduction: Previous studies deriving and validating triage scores for patients with suspected COVID-19 in Emergency Department settings have been conducted in high- or middle-income settings. We assessed eight triage scores' accuracy for death or organ support in patients with suspected COVID-19 in Sudan. Methods: We conducted an observational cohort study using Covid-19 registry data from eight emergency unit isolation centres in Khartoum State, Sudan. We assessed performance of eight triage scores including: PRIEST, LMIC-PRIEST, NEWS2, TEWS, the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS in suspected COVID-19. A composite primary outcome included death, ventilation or ICU admission. Results: In total 874 (33.84 %, 95 % CI:32.04 % to 35.69 %) of 2,583 patients died, required intubation/non-invasive ventilation or HDU/ICU admission . All risk-stratification scores assessed had worse estimated discrimination in this setting, compared to studies conducted in higher-income settings: C-statistic range for primary outcome: 0.56-0.64. At previously recommended thresholds NEWS2, PRIEST and LMIC-PRIEST had high estimated sensitivities (≥0.95) for the primary outcome. However, the high baseline risk meant that low-risk patients identified at these thresholds still had a between 8 % and 17 % risk of death, ventilation or ICU admission. Conclusion: None of the triage scores assessed demonstrated sufficient accuracy to be used clinically. This is likely due to differences in the health care system and population (23 % of patients died) compared to higher-income settings in which the scores were developed. Risk-stratification scores developed in this setting are needed to provide the necessary accuracy to aid triage of patients with suspected COVID-19.

Effectiveness and cost effectiveness of pharmacological thromboprophylaxis for medical inpatients: decision analysis modelling study.

Objective: To determine the balance of costs, risks, and benefits for different thromboprophylaxis strategies for medical patients during hospital admission. Design: Decision analysis modelling study. Setting: NHS hospitals in England. Population: Eligible adult medical inpatients, excluding patients in critical care and pregnant women. Interventions: Pharmacological thromboprophylaxis (low molecular weight heparin) for all medical inpatients, thromboprophylaxis for none, and thromboprophylaxis given to higher risk inpatients according to risk assessment models (Padua, Caprini, IMPROVE, Intermountain, Kucher, Geneva, and Rothberg) previously validated in medical cohorts. Main outcome measures: Lifetime costs and quality adjusted life years (QALYs). Costs were assessed from the perspective of the NHS and Personal Social Services in England. Other outcomes assessed were incidence and treatment of venous thromboembolism, major bleeds including intracranial haemorrhage, chronic thromboembolic complications, and overall survival. Results: Offering thromboprophylaxis to all medical inpatients had a high probability (>99%) of being the most cost effective strategy (at a threshold of £20 000 (€23 440; $25 270) per QALY) in the probabilistic sensitivity analysis, when applying performance data from the Padua risk assessment model, which was typical of that observed across several risk assessment models in a medical inpatient cohort. Thromboprophylaxis for all medical inpatients was estimated to result in 0.0552 additional QALYs (95% credible interval 0.0209 to 0.1111) while generating cost savings of £28.44 (-£47 to £105) compared with thromboprophylaxis for none. No other risk assessment model was more cost effective than thromboprophylaxis for all medical inpatients when assessed in deterministic analysis. Risk based thromboprophylaxis was found to have a high (76.6%) probability of being the most cost effective strategy only when assuming a risk assessment model with very high sensitivity is available (sensitivity 99.9% and specificity 23.7% v base case sensitivity 49.3% and specificity 73.0%). Conclusions: Offering pharmacological thromboprophylaxis to all eligible medical inpatients appears to be the most cost effective strategy. To be cost effective, any risk assessment model would need to have a very high sensitivity resulting in widespread thromboprophylaxis in all patients except those at the very lowest risk, who could potentially avoid prophylactic anticoagulation during their hospital stay.

Diagnostic strategies in postpartum individuals with suspected venous thromboembolism: A scoping review.

BACKGROUND: The risk of venous thromboembolism (VTE) is increased postpartum and contributes to important morbidity and mortality. While there have been advances in evaluating diagnostic algorithms for suspected VTE during pregnancy, there is limited data for postpartum individuals. OBJECTIVE: We conducted a scoping review to describe and evaluate diagnostic strategies used to investigate suspected VTE in postpartum individuals. METHODS: A comprehensive search strategy was conducted in Ovid MEDLINE, Embase and the Cochrane Central Register of Controlled Trials (January 1, 2000-September 30, 2022) to identify original articles that reported on diagnostic strategies in postpartum individuals with suspected VTE. We extracted demographics, clinical decision rules used, D-dimer and imaging completed, including test performance and VTE outcomes. RESULTS: A total of 13 studies conducted across 11 countries with separate postpartum data were included for 759 individuals with suspected PE (n = 634) or DVT (n = 125), including unpublished data (n = 251). Among those with suspected PE, computed tomography pulmonary angiography was conducted more commonly (n = 522) than ventilation-perfusion scans (n = 69), with PE positivity rates that ranged from 4 %-27.6 % and 0-50 % across studies, respectively. Among 131 postpartum individuals with suspected PE who had a D-dimer measured, only 4.6 % (6/131) had a negative D-dimer test. For postpartum individuals with suspected DVT, the most common diagnostic test was compression ultrasonography (positivity rate 12.2 %-18.6 %). There were limited retrospective data evaluating the clinical decision rules. CONCLUSIONS: There are heterogeneous approaches globally in the diagnosis of suspected postpartum VTE. Limited high-quality data available underscores the need for more robust evidence to inform clinical practice.

Estimating the value of future research into thromboprophylaxis for women during pregnancy and after delivery: a value of information analysis.

BACKGROUND: Risk assessment models (RAMs) are used to select women at increased risk of venous thromboembolism (VTE) during pregnancy and the puerperium for thromboprophylaxis. OBJECTIVES: To estimate the value of potential future studies that would reduce the decision uncertainty associated with offering thromboprophylaxis according to available RAMs in the following groups: high-risk antepartum women (eg, prior VTE), unselected postpartum women, and postpartum women with risk factors (obesity or cesarean delivery). METHODS: A decision-analytic model was developed to simulate clinical outcomes, lifetime costs, and quality-adjusted life-years for different thromboprophylaxis strategies, including thromboprophylaxis for all, thromboprophylaxis for none, and RAM-based thromboprophylaxis. The expected value of perfect information analysis was used to determine which factors are associated with high decision uncertainty. The value of future research studies was estimated using expected value of sample information analysis. Costs were assessed from a health and social services perspective. RESULTS: The expected value of perfect information analysis identified high decision uncertainty for high-risk antepartum women (£21.8 million) and obese postpartum women (£13.4 million), which was largely attributable to uncertainty regarding the effectiveness of thromboprophylaxis in reducing VTE. A randomized controlled trial of thromboprophylaxis compared with none in obese postpartum women is likely to have substantial value (£2.8 million; 300 participants per arm). A trial in women with previous VTE would have higher value but would be less acceptable. CONCLUSION: Future research should focus on estimating the effectiveness of thromboprophylaxis in obese postpartum women with additional risk factors who have not had a previous VTE.

Diagnosis of Acute Aortic Syndrome in the Emergency Department (DAShED) study: an observational cohort study of people attending the emergency department with symptoms consistent with acute aortic syndrome.

BACKGROUND: The diagnosis of acute aortic syndrome (AAS) is commonly delayed or missed in the ED. We describe characteristics of ED attendances with symptoms potentially associated with AAS, diagnostic performance of clinical decision tools (CDTs) and physicians and yield of CT aorta angiogram (CTA). METHODS: This was a multicentre observational cohort study of adults attending 27 UK EDs between 26 September 2022 and 30 November 2022, with potential AAS symptoms: chest, back or abdominal pain, syncope or symptoms related to malperfusion. Patients were preferably identified prospectively, but retrospective recruitment was also permitted. Anonymised, routinely collected patient data including components of CDTs, was abstracted. Clinicians treating prospectively identified patients were asked to record their perceived likelihood of AAS, prior to any confirmatory testing. Reference standard was radiological or operative confirmation of AAS. 30-day electronic patient record follow-up evaluated whether a subsequent diagnosis of AAS had been made and mortality. RESULTS: 5548 patients presented, with a median age of 55 years (IQR 37-72; n=5539). 14 (0.3%; n=5353) had confirmed AAS. 10/1046 (1.0%) patients in whom the ED clinician thought AAS was possible had AAS. 5/147 (3.4%) patients in whom AAS was considered the most likely diagnosis had AAS. 2/3319 (0.06%) patients in whom AAS was considered not possible did have AAS. 540 (10%; n=5446) patients underwent CT, of which 407 were CTA (7%). 30-day follow-up did not reveal any missed AAS diagnoses. AUROC (area under the receiver operating characteristic) curve for ED clinician AAS likelihood rating was 0.958 (95% CI 0.933 to 0.983, n=4006) and for individual CDTs were: Aortic Dissection Detection Risk Score (ADD-RS) 0.674 (95% CI 0.508 to 0.839, n=4989), AORTAs 0.689 (95% CI 0.527 to 0.852, n=5132), Canadian 0.818 (95% CI 0.686 to 0.951, n=5180) and Sheffield 0.628 (95% CI 0.467 to 0.788, n=5092). CONCLUSION: Only 0.3% of patients presenting with potential AAS symptoms had AAS but 7% underwent CTA. CDTs incorporating clinician gestalt appear to be most promising, but further prospective work is needed, including evaluation of the role of D-dimer. TRIAL REGISTRATION NUMBER: NCT05582967; NCT05582967.

Prehospital early warning scores for adults with suspected sepsis: retrospective diagnostic cohort study.

BACKGROUND: Ambulance services need to identify and prioritise patients with sepsis for early hospital assessment. We aimed to determine the accuracy of early warning scores alongside paramedic diagnostic impression to identify sepsis that required urgent treatment. METHODS: We undertook a retrospective diagnostic cohort study involving adult emergency medical cases transported to Sheffield Teaching Hospitals ED by Yorkshire Ambulance Service in 2019. We used routine ambulance service data to calculate 21 early warning scores and categorise paramedic diagnostic impressions as sepsis, infection, non-specific presentation or other presentation. We linked cases to hospital records and identified those meeting the sepsis-3 definition who received urgent hospital treatment for sepsis (reference standard). Analysis determined the accuracy of strategies that combined early warning scores at varying thresholds for positivity with paramedic diagnostic impression. RESULTS: We linked 12 870/24 955 (51.6%) cases and identified 348/12 870 (2.7%) with a positive reference standard. None of the strategies provided sensitivity greater than 0.80 with positive predictive value greater than 0.15. The area under the receiver operating characteristic curve for the National Early Warning Score, version 2 (NEWS2) applied to patients with a diagnostic impression of sepsis or infection was 0.756 (95% CI 0.729, 0.783). No other early warning score provided clearly superior accuracy to NEWS2. Paramedic impression of sepsis or infection had sensitivity of 0.572 (0.519, 0.623) and positive predictive value of 0.156 (0.137, 0.176). NEWS2 thresholds of >4, >6 and >8 applied to patients with a diagnostic impression of sepsis or infection, respectively, provided sensitivities and positive predictive values of 0.522 (0.469, 0.574) and 0.216 (0.189, 0.245), 0.447 (0.395, 0.499) and 0.274 (0.239, 0.313), and 0.314 (0.268, 0.365) and 0.333 (0.284, 0.386). CONCLUSION: No strategy is ideal but using NEWS2 alongside paramedic diagnostic impression of infection or sepsis could identify one-third to half of sepsis cases without prioritising unmanageable numbers. No other score provided clearly superior accuracy to NEWS2. TRIAL REGISTRATION NUMBER: researchregistry5268, https://www.researchregistry.com/browse-the-registry%23home/registrationdetails/5de7bbd97ca5b50015041c33/.

Early computed tomography coronary angiography and preventative treatment in patients with suspected acute coronary syndrome: A secondary analysis of the RAPID-CTCA trial.

BACKGROUND: Computed tomography coronary angiography (CTCA) offers detailed assessment of the presence of coronary atherosclerosis and helps guide patient management. We investigated influences of early CTCA on the subsequent use of preventative treatment in patients with suspected acute coronary syndrome. METHODS: In this secondary analysis of a multicenter randomized controlled trial of early CTCA in intermediate-risk patients with suspected acute coronary syndrome, prescription of aspirin, P2Y12 receptor antagonist, statin, renin-angiotensin system blocker, and beta-blocker therapies from randomization to discharge were compared within then between those randomized to early CTCA or to standard of care only. Effects of CTCA findings on adjustment of these therapies were further examined. RESULTS: In 1,743 patients (874 randomized to early CTCA and 869 to standard of care only), prescription of P2Y12 receptor antagonist, dual antiplatelet, and statin therapies increased more in the early CTCA group (between-group difference: 4.6% [95% confidence interval, 0.3-8.9], 4.5% [95% confidence interval, 0.2-8.7], and 4.3% [95% confidence interval, 0.2-8.5], respectively), whereas prescription of other preventative therapies increased by similar extent in both study groups. Among patients randomized to early CTCA, there were additional increments of preventative treatment in those with obstructive coronary artery disease and higher rates of reductions in antiplatelet and beta-blocker therapies in those with normal coronary arteries. CONCLUSIONS: Prescription patterns of preventative treatment varied during index hospitalization in patients with suspected acute coronary syndrome. Early CTCA facilitated targeted individualization of these therapies based on the extent of coronary artery disease.

Training and testing of a gradient boosted machine learning model to predict adverse outcome in patients presenting to emergency departments with suspected covid-19 infection in a middle-income setting.

COVID-19 infection rates remain high in South Africa. Clinical prediction models may be helpful for rapid triage, and supporting clinical decision making, for patients with suspected COVID-19 infection. The Western Cape, South Africa, has integrated electronic health care data facilitating large-scale linked routine datasets. The aim of this study was to develop a machine learning model to predict adverse outcome in patients presenting with suspected COVID-19 suitable for use in a middle-income setting. A retrospective cohort study was conducted using linked, routine data, from patients presenting with suspected COVID-19 infection to public-sector emergency departments (EDs) in the Western Cape, South Africa between 27th August 2020 and 31st October 2021. The primary outcome was death or critical care admission at 30 days. An XGBoost machine learning model was trained and internally tested using split-sample validation. External validation was performed in 3 test cohorts: Western Cape patients presenting during the Omicron COVID-19 wave, a UK cohort during the ancestral COVID-19 wave, and a Sudanese cohort during ancestral and Eta waves. A total of 282,051 cases were included in a complete case training dataset. The prevalence of 30-day adverse outcome was 4.0%. The most important features for predicting adverse outcome were the requirement for supplemental oxygen, peripheral oxygen saturations, level of consciousness and age. Internal validation using split-sample test data revealed excellent discrimination (C-statistic 0.91, 95% CI 0.90 to 0.91) and calibration (CITL of 1.05). The model achieved C-statistics of 0.84 (95% CI 0.84 to 0.85), 0.72 (95% CI 0.71 to 0.73), and 0.62, (95% CI 0.59 to 0.65) in the Omicron, UK, and Sudanese test cohorts. Results were materially unchanged in sensitivity analyses examining missing data. An XGBoost machine learning model achieved good discrimination and calibration in prediction of adverse outcome in patients presenting with suspected COVID19 to Western Cape EDs. Performance was reduced in temporal and geographical external validation.

Using clinical risk models to predict outcomes: what are we predicting and why?

Clinical risk prediction models can support decision making in emergency medicine, but directing intervention towards high-risk patients may involve a flawed assumption. This concepts paper examines prognostic clinical risk prediction and specifically describes the potential impact of treatment effects in model development studies. Treatment effects may lead to models failing to achieve the aim of identifying the patients most likely to benefit from intervention, and may instead identify patients who are unlikely to benefit from intervention. The paper provides practical advice to help clinicians who wish to use clinical prediction scores to assist clinical judgement rather than dictate clinical decision making.

LMIC-PRIEST: Derivation and validation of a clinical severity score for acutely ill adults with suspected COVID-19 in a middle-income setting.

BACKGROUND: Uneven vaccination and less resilient health care systems mean hospitals in LMICs are at risk of being overwhelmed during periods of increased COVID-19 infection. Risk-scores proposed for rapid triage of need for admission from the emergency department (ED) have been developed in higher-income settings during initial waves of the pandemic. METHODS: Routinely collected data for public hospitals in the Western Cape, South Africa from the 27th August 2020 to 11th March 2022 were used to derive a cohort of 446,084 ED patients with suspected COVID-19. The primary outcome was death or ICU admission at 30 days. The cohort was divided into derivation and Omicron variant validation sets. We developed the LMIC-PRIEST score based on the coefficients from multivariable analysis in the derivation cohort and existing triage practices. We externally validated accuracy in the Omicron period and a UK cohort. RESULTS: We analysed 305,564 derivation, 140,520 Omicron and 12,610 UK validation cases. Over 100 events per predictor parameter were modelled. Multivariable analyses identified eight predictor variables retained across models. We used these findings and clinical judgement to develop a score based on South African Triage Early Warning Scores and also included age, sex, oxygen saturation, inspired oxygen, diabetes and heart disease. The LMIC-PRIEST score achieved C-statistics: 0.82 (95% CI: 0.82 to 0.83) development cohort; 0.79 (95% CI: 0.78 to 0.80) Omicron cohort; and 0.79 (95% CI: 0.79 to 0.80) UK cohort. Differences in prevalence of outcomes led to imperfect calibration in external validation. However, use of the score at thresholds of three or less would allow identification of very low-risk patients (NPV ≥0.99) who could be rapidly discharged using information collected at initial assessment. CONCLUSION: The LMIC-PRIEST score shows good discrimination and high sensitivity at lower thresholds and can be used to rapidly identify low-risk patients in LMIC ED settings.

Troponin in acute chest pain to risk stratify and guide effective use of computed tomography coronary angiography (TARGET-CTCA): a randomised controlled trial.

BACKGROUND: The majority of patients with suspected acute coronary syndrome presenting to the emergency department will be discharged once myocardial infarction has been ruled out, although a proportion will have unrecognised coronary artery disease. In this setting, high-sensitivity cardiac troponin identifies those at increased risk of future cardiac events. In patients with intermediate cardiac troponin concentrations in whom myocardial infarction has been ruled out, this trial aims to investigate whether outpatient computed tomography coronary angiography (CTCA) reduces subsequent myocardial infarction or cardiac death. METHODS: TARGET-CTCA is a multicentre prospective randomised open label with blinded endpoint parallel group event driven trial. After myocardial infarction and clear alternative diagnoses have been ruled out, participants with intermediate cardiac troponin concentrations (5 ng/L to 99th centile upper reference limit) will be randomised 1:1 to outpatient CTCA plus standard of care or standard of care alone. The primary endpoint is myocardial infarction or cardiac death. Secondary endpoints include clinical, patient-centred, process and cost-effectiveness. Recruitment of 2270 patients will give 90% power with a two-sided P value of 0.05 to detect a 40% relative risk reduction in the primary endpoint. Follow-up will continue until 97 primary outcome events have been accrued in the standard care arm with an estimated median follow-up of 36 months. DISCUSSION: This randomised controlled trial will determine whether high-sensitivity cardiac troponin-guided CTCA can improve outcomes and reduce subsequent major adverse cardiac events in patients presenting to the emergency department who do not have myocardial infarction. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03952351. Registered on May 16, 2019.

Building an understanding of Ethnic minority people's Service Use Relating to Emergency care for injuries: the BE SURE study protocol.

INTRODUCTION: Injuries are a major public health problem which can lead to disability or death. However, little is known about the incidence, presentation, management and outcomes of emergency care for patients with injuries among people from ethnic minorities in the UK. The aim of this study is to investigate what may differ for people from ethnic minorities compared with white British people when presenting with injury to ambulance and Emergency Departments (EDs). METHODS AND ANALYSIS: This mixed methods study covers eight services, four ambulance services (three in England and one in Scotland) and four hospital EDs, located within each ambulance service. The study has five Work Packages (WP): (WP1) scoping review comparing mortality by ethnicity of people presenting with injury to emergency services; (WP2) retrospective analysis of linked NHS routine data from patients who present to ambulances or EDs with injury over 5 years (2016-2021); (WP3) postal questionnaire survey of 2000 patients (1000 patients from ethnic minorities and 1000 white British patients) who present with injury to ambulances or EDs including self-reported outcomes (measured by Quality of Care Monitor and Health Related Quality of Life measured by SF-12); (WP4) qualitative interviews with patients from ethnic minorities (n=40) and focus groups-four with asylum seekers and refugees and four with care providers and (WP5) a synthesis of quantitative and qualitative findings. ETHICS AND DISSEMINATION: This study received a favourable opinion by the Wales Research Ethics Committee (305391). The Health Research Authority has approved the study and, on advice from the Confidentiality Advisory Group, has supported the use of confidential patient information without consent for anonymised data. Results will be shared with ambulance and ED services, government bodies and third-sector organisations through direct communications summarising scientific conference proceedings and publications.

External validation of triage tools for adults with suspected COVID-19 in a middle-income setting: an observational cohort study.

BACKGROUND: Tools proposed to triage ED acuity in suspected COVID-19 were derived and validated in higher income settings during early waves of the pandemic. We estimated the accuracy of seven risk-stratification tools recommended to predict severe illness in the Western Cape, South Africa. METHODS: An observational cohort study using routinely collected data from EDs across the Western Cape, from 27 August 2020 to 11 March 2022, was conducted to assess the performance of the PRIEST (Pandemic Respiratory Infection Emergency System Triage) tool, NEWS2 (National Early Warning Score, version 2), TEWS (Triage Early Warning Score), the WHO algorithm, CRB-65, Quick COVID-19 Severity Index and PMEWS (Pandemic Medical Early Warning Score) in suspected COVID-19. The primary outcome was intubation or non-invasive ventilation, death or intensive care unit admission at 30 days. RESULTS: Of the 446 084 patients, 15 397 (3.45%, 95% CI 34% to 35.1%) experienced the primary outcome. Clinical decision-making for inpatient admission achieved a sensitivity of 0.77 (95% CI 0.76 to 0.78), specificity of 0.88 (95% CI 0.87 to 0.88) and the negative predictive value (NPV) of 0.99 (95% CI 0.99 to 0.99). NEWS2, PMEWS and PRIEST scores achieved good estimated discrimination (C-statistic 0.79 to 0.82) and identified patients at risk of adverse outcomes at recommended cut-offs with moderate sensitivity (>0.8) and specificity ranging from 0.41 to 0.64. Use of the tools at recommended thresholds would have more than doubled admissions, with only a 0.01% reduction in false negative triage. CONCLUSION: No risk score outperformed existing clinical decision-making in determining the need for inpatient admission based on prediction of the primary outcome in this setting. Use of the PRIEST score at a threshold of one point higher than the previously recommended best approximated existing clinical accuracy.