The accuracy of the Manchester Triage System in an emergency service

Expectations of emergency patients regarding triage system knowledge upon arrival: an interpretive study

BACKGROUND

One of the most important aspects of healthcare knowledge is having a thorough understanding of the triage system which is used in emergency departments. This study aims to assess the level of awareness of Jordanian patients who visit the ED about the triage procedure.

METHODS

A descriptive, cross-sectional design was utilized in the emergency department at the biggest public hospital in Jordan. A convenience sample of a self-administrated questionnaire utilizing a Discounted Cash Flow Interview (DCF) survey was filled out.

RESULTS

A total of 726 participants were recruited with a response rate of 90.8%. The mean age of the participants was M = 38.1 (SD = 12.9), and the age of the participants varied from 18 to 89 years. More than half of the participants were male (n = 383, 52.8%) and married (n = 425, 58.5%). A significant relationship between the overall perception of knowing what a teaching hospital is and patients' educational level (X2 = 11.9, P < 0.003), current job (X2 = 25.2, P < 0.001), nationality (X2 = 7.20, P < 0.007), and family income (X2 = 15.9, P < 0.001).

CONCLUSION

More investigation is required to determine the causes of the low knowledge of the triage system. The study suggests increasing staffing levels, giving nursing staff ongoing education and training, and integrating technology and automation to reduce the load of patient care.

Safety of Triage Self-assessment Using a Symptom Assessment App for Walk-in Patients in the Emergency Care Setting: Observational Prospective Cross-sectional Study

Background

Increasing use of emergency departments (EDs) by patients with low urgency, combined with limited availability of medical staff, results in extended waiting times and delayed care. Technological approaches could possibly increase efficiency by providing urgency advice and symptom assessments.

Objective

The purpose of this study is to evaluate the safety of urgency advice provided by a symptom assessment app, Ada, in an ED.

Methods

The study was conducted at the interdisciplinary ED of Marburg University Hospital, with data collection performed between August 2019 and March 2020. This study had a single-center cross-sectional prospective observational design and included 378 patients. The app’s urgency recommendation was compared with an established triage concept (Manchester Triage System [MTS]), including patients from the lower 3 MTS categories only. For all patients who were undertriaged, an expert physician panel assessed the case to detect potential avoidable hazardous situations (AHSs).

Results

Of 378 participants, 344 (91%) were triaged the same or more conservatively and 34 (8.9%) were undertriaged by the app. Of the 378 patients, 14 (3.7%) had received safe advice determined by the expert panel and 20 (5.3%) were considered to be potential AHS. Therefore, the assessment could be considered safe in 94.7% (358/378) of the patients when compared with the MTS assessment. From the 3 lowest MTS categories, 43.4% (164/378) of patients were not considered as emergency cases by the app, but could have been safely treated by a general practitioner or would not have required a physician consultation at all.

Conclusions

The app provided urgency advice after patient self-triage that has a high rate of safety, a rate of undertriage, and a rate of triage with potential to be an AHS, equivalent to telephone triage by health care professionals while still being more conservative than direct ED triage. A large proportion of patients in the ED were not considered as emergency cases, which could possibly relieve ED burden if used at home. Further research should be conducted in the at-home setting to evaluate this hypothesis.

Trial Registration

German Clinical Trial Registration DRKS00024909; https://www.drks.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00024909

Prognostic accuracy of qSOFA at triage in patients with suspected infection in a Brazilian emergency department

OBJECTIVE

To evaluate the prognostic accuracy of qSOFA for predicting in-hospital mortality among patients with suspected infection presenting to the ED of a public tertiary hospital in Brazil.

METHODS

We performed a retrospective cohort study of consecutive adult patients (age ≥ 18 years) with suspected infection who presented to an academic tertiary ED in Porto Alegre (Southern Brazil) during an 18-month period. The qSOFA was calculated by using information collected at triage and patients were followed throughout hospitalization for the primary outcome of in-hospital mortality. Sensitivity, specificity, positive and negative likelihood ratios, and diagnostic odds ratios with corresponding 95% CIs were calculated for the qSOFA and qSOFA65.

RESULTS

A total of 7523 ED visits of patients with suspected infection in which an intravenous antibiotic was administered within 24 h were included, which resulted in 908 in-hospital deaths (12.1%). There were 690 (9.2%) patients whose triage qSOFA was ≥2 points. When such cutoff was used, the sensitivity for in-hospital death was 24.6% (95% CI 21.8 to 27.4%) and the specificity was 92.9% (95% CI 92.3% to 93.5%). The sensitivity increased to 67.4% (95% CI 64.2% to 70.3%) when a cutoff of ≥1 was tested, but the specificity decreased to 55.3% (95% CI 54.1% to 56.5%). Using a cutoff of ≥2, the qSOFA65 had a sensitivity of 51.0% (95% CI 47.7% to 54.3%) and a specificity of 75.7% (95% CI 74.6% to 76.7%).

CONCLUSIONS

The qSOFA score yielded very low sensitivity in predicting in-hospital mortality. Emergency physicians or ED triage nurses in low-to-middle income countries should not be using qSOFA or qSOFA65 as "rule-out" screening tools in the initial evaluation of patients with suspected infection.

[Evolution of patients infected with SARS-CoV-2 according to previous metabolic status]

INTRODUCTION

coronavirus disease 2019 (COVID-19) encompasses a wide spectrum of symptoms, including respiratory, gastrointestinal, hematological, and dermatological manifestations. The virus interaction with cells located in the respiratory tract causes the release of inflammatory mediators, whose involvement could be exacerbated by co-existing obesity, diabetes, and cardiovascular events.

OBJECTIVES

the objective of this research was to analyze the clinically metabolic status in patients who have suffered COVID-19 disease in order to predict the outcome.

METHODS

this research is a retrospective study based on a cohort of 165 consecutively admitted patients with criteria for COVID-19 pneumonia according to WHO guidelines at the Hospital Universitario Puerta de Hierro between March and April 2020. Recorded variables included demographic and epidemiological data plus diagnoses as well as morbid complications during hospitalization. The Biochemistry Unit Laboratory carried out laboratory analyses according to validated operational procedures. The statistical tests included univariate and multivariate models adjusted for baseline characteristics and clinically relevant features.

RESULTS

the most frequent comorbidity in our cohort was arterial hypertension (44.0 %), followed by dyslipidemia (32.1 %), obesity (30.9 %), and diabetes mellitus (20.0 %). The association between admission to the intensive care unit (ICU) with body mass index (BMI) in a multivariate model was statistically significant, evidencing that obese subjects (BMI ≥ 30 kg/m2) have a 19 % higher risk of requiring ICU care. The univariate model revealed a statistically significant association between obesity and ICU admission and length of hospital stay (p < 0.05). The relationship between baseline blood glucose and in-hospital mortality was also statistically significant (p = 0.03), as well as with total cholesterol and ICU admission (p = 0.007).

CONCLUSIONS

obesity is related to a longer time of hospitalization and a higher rate of admissions to the ICU. Low total cholesterol levels and abnormal baseline blood glucose were risk factors for ICU requirement and in-hospital mortality. Patient categorization based on obesity could be valuable in the development of a precision medicine model within the COVID-19 pandemic.