ObjectiveTo assess accuracy of telephone triage in identifying need for emergency care among those with suspected COVID-19 infection and identify factors which affect triage ...accuracy.DesignObservational cohort study.SettingCommunity telephone triage provided in the UK by Yorkshire Ambulance Service NHS Trust (YAS).Participants40 261 adults who contacted National Health Service (NHS) 111 telephone triage services provided by YAS between 18 March 2020 and 29 June 2020 with symptoms indicating COVID-19 infection were linked to Office for National Statistics death registrations and healthcare data collected by NHS Digital.OutcomeAccuracy of triage disposition was assessed in terms of death or need for organ support up to 30 days from first contact.ResultsCallers had a 3% (1200/40 261) risk of serious adverse outcomes (death or organ support). Telephone triage recommended self-care or non-urgent assessment for 60% (24 335/40 261), with a 1.3% (310/24 335) risk of adverse outcomes. Telephone triage had 74.2% sensitivity (95% CI: 71.6 to 76.6%) and 61.5% specificity (95% CI: 61% to 62%) for the primary outcome. Multivariable analysis suggested respiratory comorbidities may be overappreciated, and diabetes underappreciated as predictors of deterioration. Repeat contact with triage service appears to be an important under-recognised predictor of deterioration with 2 contacts (OR 1.77, 95% CI: 1.14 to 2.75) and 3 or more contacts (OR 4.02, 95% CI: 1.68 to 9.65) associated with false negative triage.ConclusionPatients advised to self-care or receive non-urgent clinical assessment had a small but non-negligible risk of serious clinical deterioration. Repeat contact with telephone services needs recognition as an important predictor of subsequent adverse outcomes.
National Institute for Health and Care Excellence guidelines used to triage patients with head injury to CT imaging are based on research conducted in populations presenting within 24 h of injury.We ...aim to compare guideline use, and outcomes, in patients with head injury that undergo CT imaging presenting within, and after 24 h of injury.
ED trauma CT head scan requests over a period of 6 months were matched to ED records. Case note review of adult patients with head injury that had undergone CT imaging was completed. Logistic regression was used to assess whether presentation after 24 h affected the guideline's ability to predict significant injuries.
650 case records were available for analysis. 8.6% (56/650) showed a traumatic abnormality, 1.5% (10/650) required neurosurgery or died. 15.5% (101/650) of CT scans were for patients presenting after 24 h. 8.4% (46/549) of those presenting within, and 9.9% (10/101) of those presenting after 24 h had traumatic CT abnormalities.The sensitivity of the guidelines for intracranial injuries was 98% (95% CI 87.0% to 99.9%) in those presenting within 24 h and 70% (95% CI 35.4% to 91.9%) in those presenting after 24 h of injury. The presence of a guideline indication statistically predicted significant injury, and this was unaffected by time of presentation.
Patients with head injury presenting after 24 h of injury are a clinically significant population. Existing guidelines appear to predict traumatic CT abnormalities irrespective of timing of presentation. However, their sole use in patients presenting after 24 h may result in significant injuries not being identified.
•First study to externally validate the only empirically derived European prediction model for identifying majortrauma in undifferentiated pre-hospital patients.•Implementing the Dutch model could ...lower the undertriage rate from 56% to 17%, however it would increase the overtriage rate from 16% to 50%.•Further research is needed to reduce overtriage and determine whether the model can be practically implemented by paramedics and is cost-effective.
This paper investigates the use of a major trauma prediction model in the UK setting. We demonstrate that application of this model could reduce the number of patients with major trauma being incorrectly sent to non-specialist hospitals. However, more research is needed to reduce over-triage and unnecessary transfer to Major Trauma Centres.
To externally validate the Dutch prediction model for identifying major trauma in a large unselected prehospital population of injured patients in England.
External validation using a retrospective cohort of injured patients who ambulance crews transported to hospitals.
South West region of England.
All patients ≥16 years with a suspected injury and transported by ambulance in the year from February 1, 2017. Exclusion criteria: 1) Patients aged ≤15 years; 2) Non-ambulance attendance at hospital with injuries; 3) Death at the scene and; 4) Patients conveyed by helicopter. This study had a census sample of cases available to us over a one year period.
Tested the accuracy of the prediction model in terms of discrimination, calibration, clinical usefulness, sensitivity and specificity and under- and over triage rates compared to usual triage practices in the South West region.
Major trauma defined as an Injury Severity Score>15.
A total of 68799 adult patients were included in the external validation cohort. The median age of patients was 72 (i.q.r. 46-84); 55.5% were female; and 524 (0.8%) had an Injury Severity Score>15. The model achieved good discrimination with a C-Statistic 0.75 (95% CI, 0.73 – 0.78). The maximal specificity of 50% and sensitivity of 83% suggests the model could improve undertriage rates at the expense of increased overtriage rates compared with routine trauma triage methods used in the South West, England.
The Dutch prediction model for identifying major trauma could lower the undertriage rate to 17%, however it would increase the overtriage rate to 50% in this United Kingdom cohort. Further prospective research is needed to determine whether the model can be practically implemented by paramedics and is cost-effective.
International guidelines recommend routine hospital admission for all patients with mild traumatic brain injury (TBI) who have injuries on computed tomography (CT) brain scan. Only a small proportion ...of these patients require neurosurgical or critical care intervention. We aimed to develop an accurate clinical decision rule to identify low-risk patients safe for discharge from the emergency department (ED) and facilitate earlier referral of those requiring intervention. A retrospective cohort study of case notes of patients admitted with initial Glasgow Coma Scale 13-15 and injuries identified by CT was completed. Data on a primary outcome measure of clinically important deterioration (indicating need for hospital admission) and secondary outcome of neurosurgery, intensive care unit admission, or intubation (indicating need for neurosurgical admission) were collected. Multi-variable logistic regression was used to derive models and a risk score predicting deterioration using routinely reported clinical and radiological candidate variables identified in a systematic review. We compared the performance of this new risk score with the Brain Injury Guideline (BIG) criteria, derived in the United States. A total of 1699 patients were included from three English major trauma centers. A total of 27.7% (95% confidence interval CI, 25.5-29.9) met the primary and 13.1% (95% CI, 11.6-14.8) met the secondary outcomes of deterioration. The derived clinical decision rule suggests that patients with simple skull fractures or intracranial bleeding <5 mm in diameter who are fully conscious could be safely discharged from the ED. The decision rule achieved a sensitivity of 99.5% (95% CI, 98.1-99.9) and specificity of 7.4% (95% CI, 6.0-9.1) to the primary outcome. The BIG criteria achieved the same sensitivity, but lower specificity (5%). Our empirical models showed good predictive performance and outperformed the BIG criteria. This would potentially allow ED discharge of 1 in 20 patients currently admitted for observation. However, prospective external validation and economic evaluation are required.
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