World Health Organization , 2020. Dengue and Severe Dengue. Available at: https://www.who.int/news-room/fact-sheets/detail/dengue-and-severe-dengue. Assessed June 5, 2021.
Ministry of Health (MOH) Malaysia , 2010. Clinical Practice Guidelines: Management of Dengue Infection in Adults. Available at: https://www.moh.gov.my/moh/attachments/5502.pdf. Assessed June 5, 2021.
Daumas RP, Passos SR, Oliveira RV, Nogueira RM, Georg I, Marzochi KB, Brasil P, 2013. Clinical and laboratory features that discriminate dengue from other febrile illnesses: a diagnostic accuracy study in Rio de Janeiro, Brazil. BMC Infect Dis 13: 77.
Low JG et al., 2011. The early clinical features of dengue in adults: challenges for early clinical diagnosis. PLoS Negl Trop Dis 5: e1191.
Huang SY, Lee IK, Wang L, Liu JW, Hung SC, Chen CC, Chang TY, Huang WC, 2014. Use of simple clinical and laboratory predictors to differentiate influenza from dengue and other febrile illnesses in the emergency room. BMC Infect Dis 14: 623.
Ngim CF et al., 2021. Rapid testing requires clinical evaluation for accurate diagnosis of dengue disease: a passive surveillance study in Southern Malaysia. PLoS Negl Trop Dis 15: e0009445.
Leber AL et al., 2018. Multicenter evaluation of BioFire FilmArray Respiratory Panel 2 for detection of viruses and bacteria in nasopharyngeal swab samples. J Clin Microbiol 56: e01945–e17.
WHO , 2009. Dengue: Guidelines for Diagnosis, Treatment, Prevention and Control: New Edition. Geneva, Switzerland: World Health Organization. Available at: https://www.who.int/tdr/publications/documents/dengue-diagnosis.pdf. Assessed September 18, 2021.
US Centers for Disease Control and Prevention (CDC) , 2015. Dengue Virus Infections 2015 Case Definition. Available at: https://ndc.services.cdc.gov/case-definitions/dengue-virus-infections-2015/ Assessed July 13, 2021.
Expert Consultation WHO , 2004. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet 363: 157–163.
Wangdi K, Kasturiaratchi K, Nery SV, Lau CL, Gray DJ, Clements ACA, 2019. Diversity of infectious aetiologies of acute undifferentiated febrile illnesses in south and Southeast Asia: a systematic review. BMC Infect Dis 19: 577.
Tomashek KM et al., 2017. Clinical and epidemiologic characteristics of dengue and other etiologic agents among patients with acute febrile illness, Puerto Rico, 2012–2015. PLoS Negl Trop Dis 11: e0005859.
Lorenzi OD et al., 2013. Acute febrile illness surveillance in a tertiary hospital emergency department: comparison of influenza and dengue virus infections. Am J Trop Med Hyg 88: 472–480.
Kuchar E, Miśkiewicz K, Nitsch-Osuch A, Szenborn L, 2015. Pathophysiology of clinical symptoms in acute viral respiratory tract infections. Adv Exp Med Biol 857: 25–38.
|Past two years||Past Year||Past 30 Days|
|Full Text Views||52||28||6|
This study explored the contribution of viral respiratory infections (VRIs) in dengue-like illness (DLI) patients and their distinguishing clinicolaboratory parameters. Two hundred DLI patients were prospectively recruited (July 1– October 1, 2019) from a community clinic in Southern Malaysia. Patients ≥ 18 years with acute fever and fulfilling the WHO criteria of probable dengue were recruited. They underwent blood testing: blood counts, rapid dengue tests (nonstructural antigen-1/IgM) and polymerase chain reaction (PCR) for dengue, Zika, chikungunya, and Leptospira. Nasopharyngeal swabs (NPSs) were collected for FilmArray®RP2plus testing. From the 200 NPSs, 58 respiratory viruses (RVs) were detected in 54 patients. Of the 96 dengue-confirmed cases, 86 had dengue mono-infection, and 10 were coinfected with RVs. Of the 104 nondengue, 44 were RV positive and 4 Leptospira positive. Zika and chikungunya virus were not detected. Overall, the etiological diagnosis was confirmed for 72% of patients. Clinicolaboratory parameters were compared between dengue mono-infection and VRI mono-infection. Patients with coinfections were excluded. Multiple logistic regression showed that recent household/neighborhood history of dengue (adjusted odds ratio [aOR]: 5.9, 95% CI = 1.7–20.7), leukopenia (aOR: 12.5, 95% CI = 2.6–61.4) and thrombocytopenia (aOR: 5.5, 95% CI = 1.3–23.0) predicted dengue. Inversely, rhinorrhoea (aOR: 0.1, 95% CI = 0.01–0.3) and cough (aOR: 0.3, 95% CI = 0.1–0.9) favored VRI. Thus, VRIs comprise many infections diagnosed initially as DLIs. Early clinicolaboratory parameters can guide physicians screen patients for further testing.
Financial support: This paper is based on work supported by the United States Naval Medical Research Unit-2 under contract number N6264518D5058—Southeast Asia Biosurveillance and Epidemiology Research (SABER) program, Task Order No. N6264518F0740, Subcontract No. SC-N6264518D5058—Monash-001. This work was funded by the Armed Forces Health Surveillance Division (AFHSD)—Global Emerging Infections Surveillance Branch (GEIS) to the United States Naval Medical Research Unit-2 and approved for human use under IRB Protocol No. NMRR-19-514-47307 and HRPO Project Number: HRPO.NMRCA.2018.003.
Authors’ addresses: Amreeta Dhanoa, Chin Fang Ngim, Lian Yih Pong, and Sharifah Syed Hassan, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, E-mails: firstname.lastname@example.org, email@example.com, firstname.lastname@example.org, and email@example.com. Nor’azim Mohd Yunos, Jeffrey Cheah School of Medicine and Health Sciences, Monash University Malaysia, and Faculty of Medicine, University of Malaya, Malaysia, E-mail: firstname.lastname@example.org. Syed M. Tupur Husain and Robert D. Hontz, United States Naval Medical Research Unit-2, Singapore, E-mails: email@example.com and firstname.lastname@example.org. Wan Fadhilah Wan Ismail, Mahmoodiah Health Clinic, Ministry of Health, Johor Bahru, Malaysia, E-mail: email@example.com.