Bronchiolitis in Abha, Southwest Saudi Arabia: viral etiology and predictors for hospital admission

Alshehri, Mohammed; Sadeq, Ali; Quli, Kazim

doi:10.4314/wajm.v24i4.28193

Cited by 31 publications

(50 citation statements)

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“…These results are in concordance with previous studies from Ghana [17] and Saudi Arabia [19], in which adenovirus was the second most frequently detected virus following RSV infection. However, other studies carried out in Saudi Arabia [18,20] showed that parainfluenza was the second most frequently detected virus following RSV.…”

Section: Discussionsupporting

confidence: 93%

“…RSV was the most predominant respiratory virus with a prevalence of 22.9%. The overall incidence is comparable to previous studies conducted in other developing countries [15][16][17] and to studies conducted in Middle Eastern countries [18][19][20]. The predominance of RSV is in concordance with the assertion that this virus is the single most frequently identified lower respiratory tract pathogen in hospitalized infants and young children worldwide [21][22][23][24].…”

Section: Discussionsupporting

confidence: 87%

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Risk factors of prolonged hospital stay in children with viral severe acute respiratory infections

El-Kholy

Mostafa

Ali

et al. 2014

J Infect Dev Ctries

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Introduction: Severe acute lower respiratory infections (SARIs) are one of the major causes of morbidity and mortality in young children, especially in developing countries. The present study focused on detection of risk factors for prolonged hospital stays among children with viral SARIs. Methodology: A sentinel surveillance study was conducted at Cairo University Hospital (CUH) between February 2010 and May 2011. Nasopharyngeal (NP) and oropharyngeal (OP) swabs were collected from all children admitted with SARIs. Viruses were identified using reverse transcription polymerase chain reaction (RT-PCR). Results: Out of 1,046 children, 380 (36%) were positive for one or more viruses; these included respiratory syncytial virus (RSV) (22.9%), adenovirus (6.2%), parainfluenza viruses (PIVs1-3) (5.1%), human metapneumovirus (HMPV) (4.5%), influenza A (1.4%), and influenza B (0.6%). Viral etiology was mainly detected in children under one year of age (88.9%). Prolonged length of stay was independently associated with the presence of cyanosis and underlying chronic illness (OR 7.4, CI: 1.8-30.32 [p = 0.005], OR 2.5, CI: 1.36-4.64 [p = 0.004], respectively). Virus type did not affect the length of hospital stay (p > 0.05). Oxygen therapy was required in 91% of the patients. A total of 43 patients (11.6%) required intensive care admission. Twenty-one patients (5.5%) died, and 15 of them (71.4%) had an underlying chronic illness. Conclusions: The study demonstrated the important burden of respiratory viruses as a cause of SARI in hospitalized children in a tertiary Egyptian hospital. Cyanosis and underlying chronic illness were significantly associated with prolonged length of stay.

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Section: Discussionsupporting

confidence: 93%

Section: Discussionsupporting

confidence: 87%

Risk factors of prolonged hospital stay in children with viral severe acute respiratory infections

El-Kholy

Mostafa

Ali

et al. 2014

J Infect Dev Ctries

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“…In Saudi Arabia, the health and economic burden of HPIV-3 infections is largely undetermined. Only few reports have identified the virus as a potential cause of infant hospitalization in Abha, Qassim and Riyadh districts of the kingdom [10,11,12,13,14]. …”

Section: Tablementioning

confidence: 99%

Hemagglutinin-Neuraminidase Gene Sequence-Based Reclassification of Human Parainfluenza Virus 3 Variants

Almajhdi¹

2015

Intervirology

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The most comprehensive phylogenetic classification of human parainfluenza virus 3 (HPIV-3) was recently developed [PLoS One 2012;7:e43893]. This classification included three distinct clusters (A, B and C) with subdivision of cluster C into four subclusters (C1-4). In the present report, the classification of HPIV-3 was refined by inclusion of 27 overlooked beside newly characterized Saudi variants. The new phylogram was developed and included the same clusters described before, in which cluster A remained unchanged and cluster B contained more recent isolates. The organization of cluster C was altered through inclusion of a new subcluster (C5), subdivision of C1 into two lineages C1a and C1b and subdivision of C3 into three lineages C3a, C3b and C3c. The majority of Saudi variants were classified as members of subcluster C1b, whereas only one variant was placed in each of subclusters C2 and C5. This study illustrates an up-to-date phylogenetic classification of HPIV-3 variants.

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“…For bronchiolitis patients in the ED, Al-Shehri et al [44][45][46][47][48] identified several predictors of hospital admission: prematurity, chronic lung disease (primarily bronchopulmonary dysplasia), atopic dermatitis, pure formula feeding (no breast feeding), passive smoking, age ≤ one year, nasopharyngeal lactate dehydrogenase value, low dew point, enterovirus infection, absence of familial atopy, rhinovirus, and co-infection. Voets et al [35] identified three predictors of hospital and ICU admission: age < six months, respiratory rate > 45 breaths per minute, and oxygen saturation < 95% at sea level.…”

Section: Predicting Hospital Admission From the Edmentioning

confidence: 99%

A systematic review of predictive modeling for bronchiolitis

Luo

Nkoy

Gesteland

et al. 2014

International Journal of Medical Informatics

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Purpose: Bronchiolitis is the most common cause of illness leading to hospitalization in young children. At present, many bronchiolitis management decisions are made subjectively, leading to significant practice variation among hospitals and physicians caring for children with bronchiolitis. To standardize care for bronchiolitis, researchers have proposed various models to predict the disease course to help determine a proper management plan. This paper reviews the existing state of the art of predictive modeling for bronchiolitis. Predictive modeling for respiratory syncytial virus (RSV) infection is covered whenever appropriate, as RSV accounts for about 70% of bronchiolitis cases.Methods: A systematic review was conducted through a PubMed search up to April 25, 2014. The literature on predictive modeling for bronchiolitis was retrieved using a comprehensive search query, which was developed through an iterative process.Search results were limited to human subjects, the English language, and children (birth-18 years). Results:The literature search returned 2,312 references in total. After manual review, 168 of these references were determined to be relevant and are discussed in this paper. We identify several limitations and open problems in predictive modeling for bronchiolitis, and provide some preliminary thoughts on how to address them, with the hope to stimulate future research in this domain. Conclusions:Many problems remain open in predictive modeling for bronchiolitis. Future studies will need to address them to achieve optimal predictive models.

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Bronchiolitis in Abha, Southwest Saudi Arabia: viral etiology and predictors for hospital admission

Cited by 31 publications

References 0 publications

Risk factors of prolonged hospital stay in children with viral severe acute respiratory infections

Risk factors of prolonged hospital stay in children with viral severe acute respiratory infections

Hemagglutinin-Neuraminidase Gene Sequence-Based Reclassification of Human Parainfluenza Virus 3 Variants

A systematic review of predictive modeling for bronchiolitis

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