Predictive accuracy of triage nurses evaluation in risk stratification of syncope in the emergency department

Bonzi, Mattia; Fiorelli, Elisa Maria; Angaroni, Laura; Furlan, Ludovico; Solbiati, Monica; Colombo, Christopher; Dipaola, Franca; Montano, Nicola; Furlan, Raffaello; Costantino, Giorgio

doi:10.1136/emermed-2013-202813

Cited by 8 publications

(8 citation statements)

References 18 publications

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“…A SAD was defined as: (f) haemorrhage causing haemodynamic instability or requiring emergency procedures (e.g. endoscopy); (g) acute neurological disorders; (h) sepsis or septic shock; or (i) urgent surgery in 48 h of the ED evaluation (Bonzi et al, 2014;Numeroso et al, 2017Numeroso et al, , 2019Numeroso et al, , 2021.…”

Section: Outcome Measuresmentioning

confidence: 99%

“…First, the retrospective nature of the study exposes it to the possible bias associated with such a study design. Second, the choice of the acute diseases included in the composite outcome of the study was made a priori on the basis of the literature and similar existing studies (Bonzi et al, 2014;Numeroso et al, 2017Numeroso et al, , 2019Numeroso et al, , 2021. Third, the accuracy of nurse triage was not assessed through inter-rater reliability.…”

Section: Limitationsmentioning

confidence: 99%

“…A SAD was defined as: (a) death in 10 days; (b) need for major cardiological therapeutic procedures, such as pacemaker or implantable cardioverter defibrillator placement, cardiopulmonary resuscitation or acute antiarrhythmic therapy, in 48 h of ED evaluation; (c) acute coronary syndrome; (d) major arrhythmias (such as supraventricular tachycardia with haemodynamic instability, sustained ventricular tachycardia, complete heart block or other critical bradyarrhythmias); (e) aortic syndrome or pulmonary embolism; (f) haemorrhage causing haemodynamic instability or requiring emergency procedures (e.g. endoscopy); (g) acute neurological disorders; (h) sepsis or septic shock; or (i) urgent surgery in 48 h of the ED evaluation (Bonzi et al, 2014; Numeroso et al, 2017, 2019, 2021).…”

Section: The Studymentioning

confidence: 99%

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Triage assessment of transitory loss of consciousness in the emergency department—A retrospective observational study

Zaboli

Ausserhofer

Sibilio

et al. 2021

Journal of Advanced Nursing

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Aim: To establish how the Manchester Triage System can correctly prioritize patients admitted to the emergency department for transitory loss of consciousness in relation to their risk of presenting severe acute disease. Design: A observational retrospective study. Methods: A total of 2291 patients who required a triage evaluation for a transitory loss of consciousness at the emergency department of Merano Hospital between 1 January 2017 and 30 June 2019 were considered. Transitory loss of consciousness was classified according to European Society of Cardiology guidelines. The baseline characteristics of the patients were collected and divided according to the priority level assigned at triage into two different study groups: high priority (red/orange) and low priority (blue/green/yellow). The composite outcome of the study was defined as the diagnosis of a severe acute disease. Results: Of the patients enrolled, 17% (390/2291) had a high-priority code and 83% (1901/2291) received a low-priority code. Overall, a severe acute disease was present in 16.9% of patients (387/2291). The Manchester Triage System had a sensitivity of 42.4%, a specificity of 88.1% and an accuracy of 80.4% for predicting severe acute disease. The discriminatory ability had an area under the receiver operating characteristic curve of 0.651 (CI 95%: 0.618-0.685).Conclusions: Despite the good specificity, the low sensitivity does not currently allow the Manchester Triage System to completely exclude patients with a severe acute disease who presented in the emergency department for a transitory loss of consciousness. Therefore, it is important to develop precise nursing tools or assessments that can improve triage performance. Impact:The assessment of a complex symptom can create difficulties in the stratification of patients in triage, assigning low-priority codes to patients with a severe disease. Additional tools are needed to allow the correct triage assessment of patients presenting with transitory loss of consciousness.

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Section: Outcome Measuresmentioning

confidence: 99%

Section: Limitationsmentioning

confidence: 99%

Section: The Studymentioning

confidence: 99%

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Triage assessment of transitory loss of consciousness in the emergency department—A retrospective observational study

Zaboli

Ausserhofer

Sibilio

et al. 2021

Journal of Advanced Nursing

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“…Clinical bottom line-As it was demonstrated that nursing triage in ED can be inaccurate in identifying high-risk syncope patients [85], it is conceivable that the implementation of prognostic algorithms might lead to the future improvement of this ED operation, as already seen in other clinical conditions [86][87][88]. However, at the present state of the art, this application of ML has not yet been extensively studied and it is to be considered only experimental.…”

Section: Syncope Risk Stratification and Ed Dispositionmentioning

confidence: 99%

Machine Learning and Syncope Management in the ED: The Future Is Coming

Dipaola

Shiffer

Gatti³

et al. 2021

Medicina

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In recent years, machine learning (ML) has been promisingly applied in many fields of clinical medicine, both for diagnosis and prognosis prediction. Aims of this narrative review were to summarize the basic concepts of ML applied to clinical medicine and explore its main applications in the emergency department (ED) setting, with a particular focus on syncope management. Through an extensive literature search in PubMed and Embase, we found increasing evidence suggesting that the use of ML algorithms can improve ED triage, diagnosis, and risk stratification of many diseases. However, the lacks of external validation and reliable diagnostic standards currently limit their implementation in clinical practice. Syncope represents a challenging problem for the emergency physician both because its diagnosis is not supported by specific tests and the available prognostic tools proved to be inefficient. ML algorithms have the potential to overcome these limitations and, in the future, they could support the clinician in managing syncope patients more efficiently. However, at present only few studies have addressed this issue, albeit with encouraging results.

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“…4 Specialist nurses have also been evaluated in triaging patients with syncope and have been found to have low predictive accuracy in identifying high-risk individuals. 5 There has also been a qualitative study of nurses' cardiac triage decisions and they found that the nurse's ultimate goal is to have the patient receive prompt electrocardiography and prompt medical evaluation and to advocate for the patient. 6 While nurses are aware of age and sex differences in myocardial infarction presentation, some nurses still hold cultural biases and stereotypes that may interfere with timely delivery of emergency cardiac healthcare.…”

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confidence: 99%

Description and development of a nurse-led cardiac assessment team

Kwok

Naneishvili

Curry

et al. 2020

Future Healthcare Journal

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A problem was identified where patient care was affected because of delays in receiving specialist cardiology input. This report describes the experience of developing a specialist cardiac assessment where senior cardiac nurses were trained to provide a 24-hour presence in the emergency department (ED). We describe the service and our evaluation of the service. These dedicated specialised nurses can optimise patient management including admission or safely discharge patients with relevant follow-up when necessary. The team also runs three clinics per week with consultant support. The team of 10 nurses provides a cardiology opinion to approximately 400 patients a month in the ED and 100 patients a month in the acute medical unit (AMU). Eighty-seven per cent of patients are seen in the ED within 30 minutes of referral. Approximately 40% of patients reviewed are accepted directly into cardiology beds thus avoiding admission to the AMU. It has been estimated that 6 bed-days are saved each day, which translated to an estimated £400,000 each year. The team also provides outpatient rapid access services which generates £121,792 income for the directorate. We demonstrate that a cardiac nurse assessment team can provide a cost-effective 24-hour presence in the ED. ABSTRACT hospitals, accounting for 10% of all inpatient episodes among men and 6.2% among women. 2 Pressures on hospital resources has led to a need for early specialist review so as to improve the patient journey and reduce unnecessary admissions.

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Predictive accuracy of triage nurses evaluation in risk stratification of syncope in the emergency department

Abstract: Nursing triage was characterised by a low predictive accuracy in identifying high-risk individuals.

Cited by 8 publications

References 18 publications

Triage assessment of transitory loss of consciousness in the emergency department—A retrospective observational study

Triage assessment of transitory loss of consciousness in the emergency department—A retrospective observational study

Machine Learning and Syncope Management in the ED: The Future Is Coming

Description and development of a nurse-led cardiac assessment team

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