Emergency medicine journal : EMJ
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As patient numbers presenting to emergency departments (ED) increase, with their myriad of comorbidities, early hospital admission prediction and demand modelling are crucial both in the ED and beyond. The Glasgow admission prediction score (GAPS) (figure 1)1 has already been shown to be accurate in predicting hospital admission from the ED at the point of triage.2 As demand on EDs increase, data driven models such as GAPS will become increasingly important for predicting patient course. However, GAPS has not previously been tested beyond the point of admission.emermed;34/12/A864-b/F1F1F1Figure 1 AIM: To assess whether GAPS has the ability to predict hospital length of stay (LOS), six-month mortality and six-month hospital readmission. ⋯ In total 1420 patients were recruited, 39.6% of these patients were initially admitted to hospital. At six months, 30.6% of patients had been readmitted and 5.6% of patients had died. For those admitted at first presentation, the chance of being discharged at any one time fell by 4.3% (95% confidence interval (CI) 3.2%-5.3%) per GAPS point increase. Figure 2 displays the Kaplan Meier curves for 6 month mortality. Cox regression showed a significant association between GAPS and mortality, with a hazard increase of 9% (95% CI:6.9% to 11.2%) for every point increase on GAPS. Figure 3 displays the Kaplan Meier curves for 6 month hospital readmission.emermed;34/12/A864-b/F2F2F2Figure 2 DISCUSSION: GAPS is a simple tool which utilises data routinely collected at triage. It is predictive of hospital admission, hospital length of stay, six-month all-cause mortality and six-month hospital readmission. Therefore, GAPS could be employed to aid staff in hospital bed planning, clinical decision making and ED resource allocation and utilisation.emermed;34/12/A864-b/F3F3F3Figure 3 REFERENCES: Logan E, et al. Predicating admission at triage. Presented at International Acute Medicine Conference, Edinburgh 2016.Cameron A, et al. A simple tool to predict admission at the time of triage. Emergency Medicine Journal2014.
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To determine whether clinical features (in the form of a clinical decision rule) or d-dimer can be used to select pregnant or postpartum women with suspected PE for diagnostic imaging. ⋯ Clinical decision rules, d-dimer and chest x-ray should not be used to select pregnant or postpartum women with suspected PE for diagnostic imaging.
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Triage is a key principle in the effective management of a major incident. Existing triage tools have demonstrated limited performance at predicting need for life-saving intervention (LSI). Derived on a military cohort, the Modified Physiological Triage Tool (MPTT) has demonstrated improved performance. Using a civilian trauma registry, this study aimed to validate the MPTT in a civilian environment. ⋯ During the study period, 218 985 adult patients were included in the TARN database. 127 233 (58.1%) had complete data: 55.6% male, aged 61.4 (IQR 43.1-80.0) years, Injury Severity Score 9 (IQR 9-16), 96.5% suffered blunt trauma and 24 791 (19.5%) were Priority One. The MPTT (sensitivity 57.6%, specificity 71.5%) outperformed all existing triage methods with a 44.7% absolute reduction in undertriage compared with existing UK civilian methods. AUROC comparison supported the use of the MPTT over other tools (P<0.001.) CONCLUSION: Within a civilian trauma registry population, the MPTT demonstrates improved performance at predicting need for LSI, with the lowest rates of undertriage and an appropriate level of overtriage. We suggest the MPTT be considered as an alternative to existing triage tools.
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Observational Study
19 Accuracy of biomarkers for venous thromboembolism in pregnancy: the diagnosis of pulmonary embolism in pregnancy (DiPEP) biomarker study.
To estimate the accuracy of biomarkers for venous thromboembolism (VTE) in pregnant and postpartum women with suspected pulmonary embolism (PE). ⋯ Currently available biomarkers show little potential for aiding the diagnosis of suspected PE in pregnancy and postpartum.emermed;34/12/A874-a/F1F1F1Figure 1emermed;34/12/A874-a/F2F2F2Figure 2emermed;34/12/A874-a/F3F3F3Figure 3.
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Patient surveys and research have shown that Emergency Department attendees do not receive adequate analgesia. Pain monitoring has not been automated and usually involves a member of staff asking the patient to rate their score with no continuous record, often no specific place to record it and no automated alarm system for scores outside accepted parameters. Few patients have regular monitoring of their pain and our own preliminary research showed that over one week only 58% of patients with moderate to severe pain had a second or subsequent score recorded. ⋯ We aim to recruit 200 patients (100 per arm) from the emergency department at Leicester Royal Infirmary. All patients will use the display. This is a parallel group, two arm superiority trial with a 1:1 allocation ratio. Patients will be randomised to have their pain score on display (intervention) or hidden (control). Blinding is not possible. The display beeps every 15 min to remind patients to enter their pain score. Treatment will not be constrained by study protocol and will depend on the judgment of the treating clinician. The study will continue for up to 6 hours to allow time for the first dose of analgesia to wear off. Data collection will cease when the patient leaves the department. Questionnaires will be given to participants and the staff nursing them.