Abstract
Background:
Fast and accurate COVID-19 identification is important to population and epidemic monitoring in hospitals. Visual triage or respiratory triage should be efficient and utilized as visual clues to alert HCWs on the case definitions.
Objective:
This study aims to evaluate the diagnostic value of the respiratory triage for COVID-19 infections and to evaluate the efficacy of the MOH triage tool in identifying low risk patients.
Methods:
A single-center retrospective chart review that was conducted at King Fahd Hospital of the University (KFHU), Khober, KSA on all adult patients admitted to the hospital through the ED. The visual triage checklist comprises two main sections, with one focused on the risk of exposure and the other related to patient clinical signs and symptoms, each with a defined score where any score ≥ 4 will need to isolate and assessed by the physician while a score of less than 4 means that the patient can be admitted with other patients. The hospital swabbed all admitted patients regardless of their score. We compared their PCR result with their case definition score. The collected data was entered and analyzed using the Statistical Package for the Social Science (SPSS Inc. Chicago, IL, USA) version 23.
Results:
The study included 7258 participants. 20% of participants aged between 21 to 30 years old, 52.2% of sample were females, and 78% were Saudi nationality. Visual triage score was less than 4 in n= 4745 participants (65.4%) and 4 or more in n= 2513 (34.6%). The test had sensitivity of 75% and specificity 21%.
Conclusion:
Most studies shows that COVID 19 has an infectivity rate of 18 to 30%. Based on this low sensitivity result, using the screening tool alone puts patients and HCWs at risk of getting infected with COVID 19.
Keywords: COVID-19, SARS-2, PCR, MERS-CoV, Respiratory, Triage, Pandemic, Saudi Arabia
1. BACKGROUND
The A major worldwide million people are affected by the emergent COVID-19 pandemic of serious acute respiratory coronavirus-2 syndrome (SARS-CoV-2) (1). There have been a number of pathogens of infection from epidemiology in the past (2), and the pandemic of 'Spanish influenza' in 1918 had its greatest impact on the international economy and on public health (2). In December 2019 in Wuhan, China, the newly discovered SARS-CoV-2 emerged (3). This is the third extremely deadly human coronavirus after 2002-3 SARS-CoV (renamed SARS-CoV-1) and the 2012-13 Middle East Cow (MERS-CoV) outbreaks (HCoV) (4). Similar to MERS-CoV infections, the incubation time for SARS-CoV-2 is 2-14 days with symptoms of fever, toxicity and breathing difficulty which range from moderate pneumonia to severe disease and even death (1, 4). Too far, the total confirmed cases of COVID-19 after nearly a year after the onset of the virus have risen to more than 76.9 million, including > 1.7 million deaths (5).
Although COVID-19 spreads quickly among many other circulating air viruses, it needs comprehensive diagnostic techniques and screening to track its progress. The chest X and CT scans are the medical procedures for the non-invasive lung test. Suggested test specimens include nasopharyngeal and oropharyngeal swabs as well as sputum, tracheal aspirate, and bronchoalveolary lavage, which may be the reverse transcription-polymerase-chain reaction (RT-PCR). In case of intestinal problems, examining rectal swabs and stool testing is justified in individuals with COVID-19 (7). Pan-Coronavirus-based serological or antibody assessment tests are also popular for defence immunity in several countries in patients recovering with COVID-19. While SARS-CoV-2 immunity and its durability are not well understood, such antibodies can be employed for a broader range of treatments such as plasma therapy.
The WHO has proposed case definitions for COVID-19 that may vary over time in nations or in certain area. Cases with COVID-19 during the fourteen days preceding symptoms (1) are suspected of significant acute respiratory infections necessitating hospitalisation and appropriate description of the clinical look and experience of visiting a high-risk zone or other populated area. Contact, operate in and share health facilities where COVID-19 patients have been treated. In any instance contact a confirmed or alleged case. Consequently, it is probable that people who do not pass the COVID-19 test or for which the SARS-CoV-2 tests are positive and negative for laboratory evidence of other air viruses. The WHO states that a healthy case has laboratory evidence of SARS-CoV-2 infection independent of clinical signs (1, 6).
Fast and accurate COVID-19 identification is important to population and epidemic monitoring in hospitals (8). Present diagnostic methods for coronaviruses include RT-PCR, real-time RT-PCR (rRT-PCR) and reverse-transcription loop (RT-LAMP) isothermal amplification (9). RT-sensitivity LAMP's to the rRT-PCR is quite accurate and is utilised for the detection of MERS-CoV(10). The typical diagnostic evaluation of COVID-19 infection, in accordance with present diagnostic recommendations published by health authorities in many countries, is a laboratory assessment, comprising nasopharyngeal and oropharyngeal swab examinations. The RT-PCR Identification average of SARS-CoV-2 was 38% positive in 4880 patients in one hospital in Wuhan (11). The positive PCR rates are not particularly high in oropharyngeal swabs: 53.3 percent only had positive oral swab tests for COVID-19 patients (12). The findings for RT-PCR are usually positive after two to eight days (13). 71 percent of RT-PCR patients in 51 patients with reported COVID-19 infections were first done for throat swab checks or for sputum samples (14).
Current tests are time-consuming with the absence of commercial kits and can delay or prevent diagnosis. In patients with fever, sore throat, tiredness, coughing, or dyspnea, in conjunction with recent exposures, COVID-19 should be identified with standard chest-computed tomography (CT) features pending negative RT PCR results (15). Of the 1014 patients, 59% got satisfactory results of RT-PCR and 88% had chest CT scans(16). It is not unexpected thus, that COVID-19 is closely related to those found in the SARS-CoV and the MERS-CoV group (17).
The Saudi Ministry of Health (MoH) developed and deployed a visual triage system to be utilised in hospitals to detect acute respiratory illness patients at early stage in EDs, dialysis units and clinics during the MERS CoV spread (18). It comprises nine items separated into two sections, one related to the patient's symptoms and signs, and the other related to the potential risk of patient exposure to MERS-CoV, each with a predefined score. Symptoms of patients include fever, cough, shortness of breath, nausea, vomiting or diarrhoea, sore throat or runny nose, and medical disorders such as diabetes mellitus, chronic kidney failure, coronary artery disease, or heart failure. Before ruling out MERS-CoV, any patient scoring four would require isolation and examination by a doctor.
Since the MERS-CoV illness was initially detected in Saudi Arabia (19), more than six hundred individuals have been killed by the disease. In some instances, visual triage scores may play a crucial role with effective clinical studies in the diagnosis of disease. Due to overpowerment of ED, ED visual triage is important to separating individuals, particularly during an illness epidemic, that may transfer germs to other patients or health professionals. The triage aims to use the data from an unbiased observation of the patient's characteristics to organise emergency care, according to Fitzgerald., et al. (20) The ED visual triage scores play an important role in the first diagnosis of MERS-CoV. Different types of the illness have been explored in prior studies using triage for early detection with encouraging findings. The triage process has two phases: the stage of diagnosis, when the triage band is assigned and processed, and the stage of action to assist the provision of emergency treatment for the patient. Triage findings may be characterised as correct, anticipated, excessive and understated. The proper triage is achieved as the patient is evaluated in the right timeline and reflects a satisfactory clinical result. Triage may usually be seen as a sub-triage that reflects an accuracy greater or lower than necessary. Previous studies suggest that overcontrol and undercontrol can have costly clinical implications which would result in overcrowding of emergency services, increased waiting time for patients and other similar issues (21).Al Marshed et al. shows that visual triage is successful in enforcing quarantine steps for public health and protecting the lives of both patients and healthcare workers, even though only 2% of their sample is diagnosed with the virus molecularly. The study also reported that a very good indicator of infection is the effects of MERS-CoV fever, cough, shortness of breath, runny nose, sore throat, body pain, and prior exposure to the virus. The results of this study reflect the use of MERS-CoV visual triage scoring in Saudi Arabia and other countries experiencing such viral infections (21).
2. OBJECTIVE
The aim of this study was to evaluate the diagnostic value of the respiratory triage for COVID-19 infections and to assess the association between a low score in the visual triage and a negative COVID-19 RT-PCR.
3. MATERIAL AND METHODS
Study setting and design
This is a single-center retrospective chart review that was conducted in a tertiary hospital. As per hospital protocol, any patient going to be admitted was swapped (nasopharyngeal) for COVID-19 for laboratory diagnosis (RT-PCR).
Population
The study was conducted on all adult patients admitted to the KFHU hospital.
Sample size
The study aims for a total coverage sampling technique, including all ED visitors complying to the selection criteria as follows.
Inclusion criteria
a) All patient admitted to hospital for any reason; b) Aged 18 years or above.
Exclusion criteria
a) Any patient known COVID-19 positive or recently infect; b) Any patient who was assessed with primary suspension of COVID-19.
Data collection tool
The visual triage checklist comprises two main sections, with one focused on the risk of exposure and the other related to patient clinical signs and symptoms, each with a defined score where any score ≥ 4 will need to isolate and assessed by the physician. The patient’s symptoms include fever, cough, shortness of breath, headache, sore throat, rhinorrhea, nausea, vomiting, diarrhea, or the presence of comorbidity (Appendix 1). COVID 19 swapping was done using nasopharyngeal swabs and diagnosed based on positive RT-PCR.
Data management and statistical analysis
The collected data was entered and analyzed using the Statistical Package for the Social Science. Descriptive statistics was performed. Percentages was given for qualitative variables. The determinant factors was determined using the Chi-square test. P-value was considered significant if P < 0.05. Specificity and sensitivity analyses was performed to determine the diagnostic value of the respiratory visual triad for COVID-19 patients. Approval was obtained from the Research Ethics Committee of Imam Abdulrahman Bin Faisal University.
4. RESULTS
According to Table, 1 20% of participants aged between 21 to 30 years old, 21.2% between 31- 40 years old, and 12.2% between 41- 50 years old. 52.2% of sample were females. 78% were Saudi nationality.
Co-morbidities among participants in Table 2, 23.25% of study sample had hypertension, 23.3% had diabetes mellitus.
Table 2. Co-morbidities and admitting diagnosis of study sample (n=7258).
| Parameter | No. | Percent | |
|---|---|---|---|
| Co-Morbidities | Cardiology | 504 | 6.9 |
| Renal | 313 | 4.3 | |
| Anemia | 26 | 0.35 | |
| Respiratory | 282 | 3.88 | |
| Neurological | 158 | 2.17 | |
| Hypertension | 1688 | 23.25 | |
| Dyslipidemia | 530 | 7.3 | |
| DM | 1695 | 23.3 | |
| Stroke | 114 | 1.57 | |
| GIT | 14 | 0.19 | |
| Other | 180 | 2.4 | |
| Unknown | 1754 | 24.2 | |
| Admitting diagnosis/ compliant | Abdominal pain/GIT compliant | 789 | 10.87 |
| Headache/ Migraine | 151 | 2.08 | |
| Chest pain | 20 | 0.27 | |
| Supervision of other normal pregnancy | 606 | 8.34 | |
| General weakness/ Myalgia | 290 | 4.0 | |
| Respiratory compliant | 364 | 5.01 | |
| Emergent situation | 116 | 1.6 | |
| Unspecified compliant | 2218 | 30.6 | |
| Suspected COVI-19 | 127 | 1.74 | |
| Other | 2577 | 35.5 | |
Chief compliant was respiratory in 5.01% of our sample, general myalgia in 4%, GIT compliant in 10.87%, unspecified compliant 30.6%, and suspected COVID-19 in 1.74% of studied sample as in Table 2.
As illustrated in Table 3. VTS was less than 4 in n= 4745 participants (65.4%) and 4 or more in n= 2513 (34.6%). The test had sensitivity of 27% and specificity 75%.
Table 3. Visual triage test scores among study participants (n= 7258).
| Parameter | No. | Percent | |
|---|---|---|---|
| COVID-19 Screening Score (Visual Triage assessment) | less than 4 | 4745 | 65.4 |
| 4 or more | 2513 | 34.6 | |
According to Table 4, 6% of participants had COVID-19 PCR test while 90.3% had SARS-CoV-2 PCR. Only 9.4% of studied sample tested positive for COVID-19 test. Hospital outcome was admission in 0.1%, 1.5% expired, 0.1% absconded and 97.6% discharged.
Table 4. COVID-19 confirmatory test results, test type and outcome, hospital outcome and admission days among participants (n= 7258).
| Parameter | No. | Percent | |
|---|---|---|---|
| Covid-19 Test Result | POSTIVE | 679 | 9.4 |
| Neg | 6320 | 87 | |
| Passed | 259 | 3.5 | |
| Test | COVID-19 PCR | 435 | 6 |
| sARS-CoV-2 PCR | 6561 | 90.3 | |
| NON | 262 | 3.6 | |
| Hospital Outcome | ABSCONDED | 4 | 0.1 |
| Discharged | 7084 | 97.6 | |
| EXPIRED | 108 | 1.5 | |
| Admitted | 4 | 0.1 | |
| No Data | 58 | 0.8 | |
| Number of days admitted | 0 - 10 | 6053 | 82.3 |
| 11 -20 | 746 | 10.1 | |
| 21 - 30 | 233 | 233 | |
| 31 - 40 | 143 | 2 | |
| 41-50 | 61 | 0.8 | |
| 51 - 60 | 30 | 0.4 | |
| 61 - 70 | 29 | 0.4 | |
| 71 - 80 | 14 | 0.2 | |
| 81 - 90 | 7 | 0.1 | |
| 90 - 100 | 17 | 0.2 | |
| more than 100 | 23 | 0.3 | |
Table 1. Sociodemographic characteristics of participants (n=7258).
| Parameter | No. | Percent | |
|---|---|---|---|
| Age | Less than 10 | 819 | 11.3 |
| 11 - 20 years | 464 | 6.4 | |
| 21 - 30 years | 1448 | 20.0 | |
| 31 – 40 years | 1541 | 21.2 | |
| 41 - 50 years | 888 | 12.2 | |
| 51 - 60 years | 852 | 11.7 | |
| more than 60 | 1246 | 17.2 | |
| Gender | Male | 3472 | 47.8 |
| Female | 3786 | 52.2 | |
| Nationality | Saudi | 5659 | 78.0 |
| Non-Saudi | 1599 | 22.0 | |
In Table 5, there was a significant correlation between respiratory VTS and COVID-19 test result as lower scores indicated negative results and higher scores indicated positive results (P= 0.001).
Table 5. Association between respiratory visual triages.
| Hospital Outcome | total | P value | ||||
|---|---|---|---|---|---|---|
| Negative | passed | POSTIVE | ||||
| COVID-19 Screening Score (Visual Triage assessment) | less than 4 | 4488 | 51 | 206 | 4745 | 0.001 |
| 71.0% | 36.7% | 25.8% | 65.4% | |||
| 4 or more | 1831 | 88 | 594 | 2513 | ||
| 29.0% | 63.3% | 74.3% | 34.6% | |||
5. DISCUSSION
Separating MERS-CoV patients from non–MERS-CoV patients has proven difficult. As the pandemic progresses and the healthcare system becomes increasingly stressed, this innovative, world-first risk tool has the potential to assist healthcare systems in responding to the COVID-19 pandemic (22).
It is critical that HCWs are well-versed on the case definitions for any new infectious illness to identify and isolate such patients immediately. Case diagnoses are often based on the existence of symptoms and epidemiologic relationships. It is critical to ensure that isolation is carried out correctly and with as little exposure to the patients as possible (18). This necessitates a frequent assessment of MERS-CoV case definition and a reevaluation of the visual triage score to verify its correctness and to prevent overcrowding isolation rooms and straining MoH financial resources by testing suspected MERS-CoV patients excessively (23).
Rever-transcriptase PCR testing for MERS-CoV is the reference standard test for MERS-CoV. 6% of our study participants had COVID-19 PCR test while 90.3% had SARS-CoV-2 PCR. Only 9.4% of studied sample tested positive for COVID-19 test. The study of Alfaraj et al. included 2435 alleged MERS cases occurred during the study period. Of these, 1823 (75%) tested negative and, by PCR assay, the remaining 25% tested positive for MERS-CoV. A comparable proportion of MERS-CoV and non-MERS-CoV patients were found using the visual triage score (VTS), with each score varying from 0 to 11. The sensitivity and accuracy of the scoring system were limited, and for better prediction of MERS-CoV infection, more improvement of the score is needed (22). In our study, VTS was less than 4 in n= 4745 participants (65.4%) and 4 or more in n= 2513 (34.6%). The test had sensitivity of 27% and specificity 75%. There was a significant correlation between respiratory VTS and COVID-19 test result as lower scores indicated negative results and higher scores indicated positive results (P= 0.001). In Alfaraj et al. retrospective examination of the visual triage, the number of patients with a four cutoff rate was 75 percent in MERS-CoV infected patients and 85 percent in non-MERS-CoV infected patients, respectively. For MERS-CoV infection, the sensitivity and accuracy of this cutoff score were 74.1 percent and 18.6 percent, respectively. However, the study found that clinical scoring is not predictive of MERS infection since the results are robust and demonstrate that MERS cannot be discriminated from other respiratory illnesses based on risk factors and clinical characteristics. As a result, all patients with nonspecific symptoms in a MERS-endemic area will have to be quarantined until MERS can be ruled out via PCR testing (23).
Visual triage or respiratory triage should be efficient and used as visual cues to notify HCWs on differential diagnosis in the emergency room (ER), haemodialysis unit, and urgent care units. In the instance of MERS-CoV (24), such visual triage was utilised. The goal of such visual triage is to identify potential cases that satisfy the case description through the use of information derived from objective observation of the patient's features in order to prioritise emergency care (25).
A cross-sectional study was conducted using a scenario-based questionnaire in the Emergency Department (ED) in Bahrain as participants were all Visual Triage nurses and ED triage nurses, nurses rated 66.79% of the cases correctly. Nurses who worked in the ED had an accuracy rate of 66.05%, and those who were from other departments had an accuracy rate of 64.09% (26). In comparison of other studies identified the accuracy of nurses in using emergency triage systems, the destination chosen for patients depended on the score given as cases with scores of less than 6 were considered to be low risk and did not need isolation. A score of 6 or more indicated a high-risk case that must be placed in an isolation room (27, 28).
6. CONCLUSION
Low scores of respiratory visual triages indicates negative COVID-19 test results. VTS had sensitivity of 27% and specificity 75%. This approach has a significant consequence in standings of public health to limit the spread of COVID-19 infection. This is principally applicable in countries where access to quick diagnosis is rare. Future studies with large sample size are recommended to support our results.
Authors contribution:
The all authors were involved in all steps of preparation this article. Final proofreading was made by the first author.
Conflict of interest statement:
The authors have no conflicts of interest to disclose.
Financial support and sponsorship:
The authors received no specific funding for this work.
REFERENCES
- 1.World Health Organization (WHO): Coronavirus disease (COVID-19) outbreak situation. [December 20, 2020]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
- 2.Parvez MK, Parveen S. Evolution and emergence of pathogenic viruses: Past, present, and future. Intervirology. 2017;60:1–7. doi: 10.1159/000478729. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Ren LL, Wang YM, Wu ZQ, Xiang ZC, Guo L, Xu T, Jiang YZ, Xiong Y, Li YJ, Li XW, et al. Identification of a novel coronavirus causing severe pneumonia in human: A descriptive study. Chin Med J (Engl) 2020;133:1015–1024. doi: 10.1097/CM9.0000000000000722. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.World Health Organization (WHO): Director-General’s opening remarks at the media briefing on COVID-19. https://www.who.int/dg/speeches/detail/who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19-18-march-2020. [Google Scholar]
- 5.Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis. doi: 10.1016/S1473-3099(20)30120-1. published online February 19. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Jin YH, Cai L, Cheng ZS, Cheng H, Deng T, Fan YP, Fang C, Huang D, Huang LQ, Huang Q, et al. A rapid advice guideline for the diagnosis treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version) Mil Med Res. 2020;7(4) doi: 10.1186/s40779-020-0233-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Gu J, Han B Wang J. COVID-19: Gastrointestinal manifestations and potential fecal-oral transmission. Gastroenterology. 2020;158(1518):1519. doi: 10.1053/j.gastro.2020.02.054. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.To KK, Tsang OT, Yip CC, Chan KH, Wu TC, Chan JM, Leung WS, Chik TS, Choi CY, Kandamby DH, Lung DC. Consistent detection of 2019 novel coronavirus in saliva. Clinical Infectious Diseases. 2020 February 12; doi: 10.1093/cid/ciaa149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Chan JF, Choi GK, Tsang AK, Tee KM, Lam HY, Yip CC, To KK, Cheng VC, Yeung ML, Lau SK, Woo PC. Development and evaluation of novel real-time reverse transcription-PCR assays with locked nucleic acid probes targeting leader sequences of human-pathogenic coronaviruses. Journal of clinical microbiology. 2015 August 1;53(8):2722–2726. doi: 10.1128/JCM.01224-15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Lee SH, Baek YH, Kim YH, Choi YK, Song MS, Ahn JY. One-pot reverse transcriptional loop-mediated isothermal amplification (RT-LAMP) for detecting MERS-CoV. Frontiers in microbiology. 2017 January 9;7:2166. doi: 10.3389/fmicb.2016.02166. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Liu R, Han H, Liu F, Lv Z, Wu K, Liu Y, Feng Y, Zhu C. Positive rate of RT-PCR detection of SARS-CoV-2 infection in 4880 cases from one hospital in Wuhan, China, from Jan to Feb 2020. Clinica Chimica Acta. 2020 March 7; doi: 10.1016/j.cca.2020.03.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Zhang W, Du RH, Li B, Zheng XS, Yang XL, Hu B, Wang YY, Xiao GF, Yan B, Shi ZL, Zhou P. Molecular and serological investigation of2019-nCoV infected patients: implication of multiple shedding routes. Emerging microbes & infections. 2020 Jan 1;9(1):386–389. doi: 10.1080/22221751.2020.1729071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Huang P, Liu T, Huang L, Liu H, Lei M, Xu W, Hu X, Chen J, Liu B. Use of chest CT in combination with negative RT-PCR assay for the 2019 novel coronavirus but high clinical suspicion. Radiology. 2020 Apr;295(1):22–23. doi: 10.1148/radiol.2020200330. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, Ji W. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020 Feb;19:200432. doi: 10.1148/radiol.2020200432. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Xie X, Zhong Z, Zhao W, Zheng C, Wang F, Liu J. Chest CT for typical2019-nCoV pneumonia: relationship to negative RT-PCR testing. Radiology. 2020 Feb;12:200343. doi: 10.1148/radiol.2020200343. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, Tao Q, Sun Z, Xia L. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020 Feb;26:200642. doi: 10.1148/radiol.2020200642. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Das KM, Lee EY, Jawder SE, Enani MA, Singh R, Skakni L, Al-Nakshabandi N, AlDossari K, Larsson SG. Acute Middle East respiratory syndrome coronavirus: temporal lung changes observed on the chest radiographs of 55 patients. American Journal of Roentgenology. 2015 Sep;205(3):W267–S274. doi: 10.2214/AJR.15.14445. [DOI] [PubMed] [Google Scholar]
- 18.Command and Control Center Ministry of Health Kingdom of Saudi Arabia Scientific Advisory Board. Infection prevention and control guidelines for the Middle East respiratory syndrome coronavirus (MERS-CoV) infection. 4th. 2017. http://www.moh.gov.sa/endepts/Infection/Documents/Guidelines-for-MERS-CoV.PDF.
- 19.Sherbini N, et al. Middle East respiratory syndrome coronavirus in Al-Madinah City, Saudi Arabia: Demographic, clinical and survival data. Journal of Epidemiology and Global Health. 2017;7(1):29–36. doi: 10.1016/j.jegh.2016.05.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Al-Dorzi HM, et al. The critical care response to a hospital outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) infection: an observational study. Annals of Intensive Care. 2016;6(1):101. doi: 10.1186/s13613-016-0203-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Wuerz R, et al. Inconsistency of emergency department triage. Emergency Department Operations Research Working Group. Annals of Emergency Medicine. 1998;32(4):431–435. doi: 10.1016/s0196-0644(98)70171-4. [DOI] [PubMed] [Google Scholar]
- 22.Al Qahtani Reem Shadaid, et al. Visual Triage Contributes Toward Early Detection and Management of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) EC Microbiology. 2017;9(3):121–130. [Google Scholar]
- 23.Alfaraj SH, Al-Tawfiq JA, Gautret P, Alenazi MG, Asiri AY, Memish ZA. Evaluation of visual triage for screening of Middle East respiratory syndrome coronavirus patients. New Microbes New Infect. 2018;26:49–52. doi: 10.1016/j.nmni.2018.08.008. Published 2018 Aug 11. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Al-Tawfiq Jaffar, Garout Mohammed, Gautret Philippe. Preparing for emerging respiratory pathogens such as SARS-CoV, MERS-CoV, and SARS-CoV-2.. Le infezioni in medicina : rivista periodica di eziologia, epidemiologia, diagnostica, clinica e terapia delle patologie infettive. 2020;28(suppl 1):64–70. ffhal-03141923. [PubMed] [Google Scholar]
- 25.Manoochehry Shahram, Saboori Fatemeh, Faraji Mehrdad, Behzadnia Mohammad. Coronavirus disease 2019: a revolution in biological triage in the emergency setting. Universa Medicina. 2020;39:212. doi: 10.18051/UnivMed.2020.v39.212-223. [DOI] [Google Scholar]
- 26.Falamarzi H, Alghanem S, Alqassim G, Almusaifer S. Accuracy among nurses in using COVID-19 visual triage in the Emergency Medicine Department of a Tertiary Hospital in the Kingdom of Bahrain. Saudi Journal of Emergency Medicine. 2021;2(1):60–64. [Google Scholar]
- 27.Dalwai MK, Twomey M, Maikere J, Said S, Wakeel M, Jemmy JP, et al. Reliability and accuracy of the south African triage scale when used by nurses in the emergency department of Timergara Hospital, Pakistan. S Afr Med J. 2014;104(5):372–375. doi: 10.7196/samj.7604. [DOI] [PubMed] [Google Scholar]
- 28.Chen SS, Chen JC, Ng CJ, Chen PL, Lee PH, Chang WY. Factors that influence the accuracy of triage nurses’ judgement in emergency departments. Emerg Med J. 2010;27(6):451–455. doi: 10.1136/emj.2008.059311. [DOI] [PubMed] [Google Scholar]