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ABSTRACT: Diagnosing influenza in children aged 5âyears and under can be challenging because of their difficulty in verbalizing symptoms. This study aimed to explore the value of the triage heart rate (HR), respiratory rate (RR), and temperature, either alone or when combined with individual symptoms and signs, in predicting influenza infection in this age group.This was a retrospective study covering 4 influenza seasons from 2017 to 2019 in an emergency department (ED) in Hong Kong. We recruited patients ≤5âyears of age who had an reverse transcription polymerase chain reaction influenza test within 48âhours of ED presentation. The diagnostic performance of the triage HR, RR, and temperature was evaluated as dichotomized or categorized values with diagnostic odds ratios (DORs) calculated based on different age-appropriate thresholds. Linear discriminant analysis was performed to assess the combined discriminatory effect of age, HR, RR, and temperature as continuous variables.Of 322 patients (median age 26âmonths), 99 had influenza A and 13 had influenza B infection. For HR and RR dichotomized based on age-appropriate thresholds, the DORs ranged from 1.16 to 1.54 and 0.78 to 1.53, respectively. A triage temperature ≥39.0â°C had the highest DOR (3.32) among different degrees of elevation of temperature. The diagnostic criteria that were based on the presence of fever and cough and/or rhinitis symptoms had a higher DOR compared with the Centers for Disease Control and Prevention influenza-like illness criteria (4.42 vs 2.41). However, combining HR, RR, or temperature with such diagnostic criteria added very little to the diagnostic performance. The linear discriminant analysis model had a high specificity of 92.5%, but the sensitivity (18.3%) was too low for clinical use.Triage HR, RR, and temperature had limited value in the diagnosis of influenza in children ≤5âyears of age in the ED. Fever and cough and/or rhinitis symptoms had a better diagnostic performance than the Centers for Disease Control and Prevention influenza-like illness criteria in predicting influenza in this age group.
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Febre/etiologia , Influenza Humana/diagnóstico , Triagem/métodos , Pré-Escolar , Tosse/etiologia , Estudos Transversais , Serviço Hospitalar de Emergência , Febre/diagnóstico , Humanos , Lactente , Recém-Nascido , Influenza Humana/epidemiologia , Estudos Retrospectivos , Reação em Cadeia da Polimerase Via Transcriptase Reversa , Rinite/diagnóstico , Sinais VitaisRESUMO
BACKGROUND: Despite its continued use in many low-volume emergency departments (EDs), 3-level triage systems have not been extensively studied, especially on live triage cases. We have modified from the Australasian Triage Scale and developed a 3-level triage scale, and sought to evaluate its validity, reliability, and over- and under-triage rates in real patient encounters in our setting. METHOD: This was a cross-sectional study in a single ED with 24,000 attendances per year. At triage, each patient was simultaneously assessed by a triage nurse, an adjudicator (the "criterion standard"), and a study nurse independently. Predictive validity was determined by comparing clinical outcomes, such as hospitalization, across triage levels. The discriminating performance of the triage tool in identifying patients requiring earlier medical attention was determined. Inter-observer reliability between the triage nurse and criterion standard, and across providers were determined using kappa statistics. RESULTS: In total, 453 triage ratings of 151 triage cases, involving 17 ED triage nurses and 57 nurse pairs, were analysed. The proportion of hospital admission significantly increased with a higher triage rating. The performance of the scale in identifying patients requiring earlier medical attention was as follows: sensitivity, 68.2% (95% CI 45.1-86.1%); specificity, 99.2% (95% CI 95.8-100%); positive predictive value, 93.8% (95% CI 67.6-99.1%); and negative predictive value, 94.8% (95% CI 90.8-97.1%). The over-triage and under-triage rates were 0.7% and 4.6%, respectively. Agreement between the triage nurse and criterion standard was substantial (quadratic-weighted kappa = 0.76, 95% CI, 0.60-0.92, p < 0.001), so was the agreement across nurses (quadratic-weighted kappa = 0.81, 95% CI 0.65-0.97, p < 0.001). CONCLUSIONS: The 3-level triage system appears to have good validity and reasonable reliability in a low-volume ED setting. Further studies comparing 3-level and prevailing 5-level triage scales in live triage encounters and different ED settings are warranted.
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Objectives: Little is known about the value of routine clinical assessment in identifying patients with coronavirus disease 2019 (COVID-19) in the emergency department (ED). We aimed to compare the exposure history, signs and symptoms, laboratory, and radiographic features of ED patients who tested positive and negative for COVID-19. Methods: This was a case-control study in 7 EDs in Hong Kong from 20 January to 29 February 2020. Thirty-seven patients with laboratory-confirmed COVID-19 were age- and sex-matched to 111 controls. We compared the groups with univariate analysis and calculated the odds ratio (OR) of having COVID-19 for each characteristic that was significantly different between the groups with adjustment for age and presumed location of acquiring the infection. Results: There were no significant differences in patient characteristics and reported symptoms between the groups. A positive contact history within 14 days (adjusted OR 37.61, 95% CI: 10.86-130.19), bilateral chest radiograph shadow (adjusted OR 13.19, 95% CI: 4.66-37.35), having prior medical consultation (adjusted OR 7.43, 95% 2.89-19.09), a lower white blood cell count (adjusted OR 1.30, 95% CI: 1.11-1.51), and a lower platelet count (adjusted OR 1.07, 95% CI: 1.01-1.12) were associated with a higher odds of COVID-19 separately. A higher neutrophil count was associated with a lower odds of COVID-19 (adjusted OR 0.77, 95% CI: 0.65-0.91). Conclusion: This study highlights a number of clinical features that may be useful in identifying high-risk patients for early testing and isolation while waiting for the test result. Further studies are warranted to verify the findings.
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OBJECTIVE: To evaluate participant reactions and attitudes to crew resource management teamwork classroom-based training by comparing Likert responses before and after the intervention and exploring potential differences in attitudes across the different healthcare professionals. METHODS: Between 26 January and 27 March, 2015, a randomly selected sample of 240 frontline healthcare professionals offering direct patient care were recruited to undergo a 4-hour crew resource management classroom-based training programme. Participants were asked to complete a 22-item human factors attitude survey before and after training and a 10-item end-of-programme evaluation. Paired samples t-test was used to assess differences between the participants' pretest and posttest scores on each item. RESULTS: A total of 167 (70%) from 17 different specialties underwent the training and 164 (68.3%) completed (139 nurses, 25 doctors) the survey. The nurses were of similar age to the doctors (38.2 vs 36.9, p=0.83) and were more likely to be women (75.6% vs 24.6%, p <0.001). Human factors attitude survey findings indicated that nurses valued the experience highly compared to doctors. The responses among the nurses revealed significant attitude shifts (p <0.05) in 20 of the 22 items whereas this was the case only for 9 items among the doctors. CONCLUSIONS: Overall, the crew resource management classroom-based training programme appeared to have a positive effect on frontline healthcare professionals' attitudes. The implementation of such programme is feasible and acceptable, especially for nurses, in a public hospital setting in Hong Kong.