Literature DB >> 25710684

Rapid diagnostic tests for dengue virus infection in febrile Cambodian children: diagnostic accuracy and incorporation into diagnostic algorithms.

Michael J Carter1, Kate R Emary2, Catrin E Moore, Catherine E Moore3, Christopher M Parry2, Soeng Sona4, Hor Putchhat4, Sin Reaksmey4, Ngoun Chanpheaktra4, Nicole Stoesser2, Andrew D M Dobson5, Nicholas P J Day2, Varun Kumar4, Stuart D Blacksell2.   

Abstract

BACKGROUND: Dengue virus (DENV) infection is prevalent across tropical regions and may cause severe disease. Early diagnosis may improve supportive care. We prospectively assessed the Standard Diagnostics (Korea) BIOLINE Dengue Duo DENV rapid diagnostic test (RDT) to NS1 antigen and anti-DENV IgM (NS1 and IgM) in children in Cambodia, with the aim of improving the diagnosis of DENV infection. METHODOLOGY AND PRINCIPAL
FINDINGS: We enrolled children admitted to hospital with non-localised febrile illnesses during the 5-month DENV transmission season. Clinical and laboratory variables, and DENV RDT results were recorded at admission. Children had blood culture and serological and molecular tests for common local pathogens, including reference laboratory DENV NS1 antigen and IgM assays. 337 children were admitted with non-localised febrile illness over 5 months. 71 (21%) had DENV infection (reference assay positive). Sensitivity was 58%, and specificity 85% for RDT NS1 and IgM combined. Conditional inference framework analysis showed the additional value of platelet and white cell counts for diagnosis of DENV infection. Variables associated with diagnosis of DENV infection were not associated with critical care admission (70 children, 21%) or mortality (19 children, 6%). Known causes of mortality were melioidosis (4), other sepsis (5), and malignancy (1). 22 (27%) children with a positive DENV RDT had a treatable other infection.
CONCLUSIONS: The DENV RDT had low sensitivity for the diagnosis of DENV infection. The high co-prevalence of infections in our cohort indicates the need for a broad microbiological assessment of non-localised febrile illness in these children.

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Year:  2015        PMID: 25710684      PMCID: PMC4340051          DOI: 10.1371/journal.pntd.0003424

Source DB:  PubMed          Journal:  PLoS Negl Trop Dis        ISSN: 1935-2727


Introduction

The number of people at risk of infection with one or more of the four dengue viruses (DENV) has increased exponentially over the past half-century, with the immuno-pathological complexity of DENV hampering vaccine design [1-4]. DENV infection first manifests as a non-specific febrile illness before either resolving, or progressing to severe disease characterized by endothelial activation, increased vascular permeability and impaired haemostasis [2,5]. Early diagnosis and identification of those at risk of severe disease is therefore important, leading to the development of rapid diagnostic tests (RDTs) to DENV antigens and anti-DENV antibodies [6-12], and previous work incorporating clinical and laboratory features of the disease (but not RDTs) into decision algorithms [13-18]. DENV infection is highly incident in Cambodia [19,20]. We examined our diagnostic strategy for DENV infection at Angkor Hospital for Children in Siem Reap, north-west Cambodia during the DENV transmission season of 2010. We used a DENV rapid diagnostic test (RDT) for detection of the DENV non-specific 1 (NS1) antigen, anti-DENV IgM, and anti-DENV IgG, [6-12,21] in addition to established clinical diagnostic criteria [22] and basic laboratory markers in children requiring hospitalization for a febrile illness with no clear source at admission. This study was nested within a prospective study of all causes of fever in hospitalized children [20], enabling us assess the DENV RDT in a well-characterised sample of children. In addition, we formalized our diagnostic algorithms with the use of conditional inference trees [13-18], and examined the usefulness of a DENV RDT for determination of risk of critical care admission in the context of highly prevalent co-infections.

Methods

Ethics statement

The parents of all children recruited to the study gave witnessed, written, informed consent before study enrolment. The Oxford Tropical Research Ethics Committee and Angkor Hospital for Children Institutional Review Board approved the study protocol on 24th September 2009 and 2nd October 2009 respectively.

Clinical methods and enrollment

Criteria for enrollment in the parent study [20] were: age <16 years; fever ≥38°C within 48 hours of presentation to hospital; clinically requiring admission (using Integrated Management of Childhood Illness [IMCI] guidelines [23]); and written informed consent from the caretaker. Children <60 days of age were excluded (for reasons of blood volume). In addition, for this nested study, we prospectively excluded children with clear sources of fever on initial assessment: e.g. with clear lower respiratory tract infection, or gastroenteritis, or cellulitis (Fig. 1).
Figure 1

Flowchart depicting enrollment, DENV reference assay results, and outcome of patients into this study of a DENV RDT from the main prospective study of cause of fever in the cohort [20].

Children for this study were enrolled from 1st June 2010 to 1st October 2010. At enrollment, resident paediatricians examined all children. If a cause of fever was not clear, children were re-assessed by a senior paediatrician. Urinalysis was performed on all children. Admission findings were recorded on a study-specific clinical record form, which detailed clinical features associated with the diagnosis of dengue [22]. All children in this study had blood taken at enrollment for a DENV RDT, aerobic bacterial and Leptospira spp. culture, complete blood count, including malaria blood smear, nucleic amplification tests (NAATs) for rickettsial pathogens and Leptospira spp., and serum for biochemistry and DENV and Japanese encephalitis virus (JEV) serology. Where possible enrolled children also had a convalescent serum sample taken at 7 days or on hospital discharge for serology. Whole blood for NAATs and sera for serology were stored at -80°C and were analysed retrospectively on conclusion of the study. Children with a recent history of cough or sore throat and increased respiratory effort had nasal and throat swab samples analysed for respiratory virus detection. Samples of pus, cerebrospinal fluid (CSF), and other clinical tests were done as clinically indicated. Full methods are detailed in reference [20].

RDT methods

We used the Standard Diagnostics (Korea) BIOLINE Dengue Duo [21] kit as the RDT in the study. This is an in vitro immunochromatographic, one-step assay for the detection of NS1 antigen and anti-DENV IgM and IgG from whole blood or serum, with manufacturer published sensitivity of 92.8% and specificity of 98.4% for NS1, and sensitivity of 99.4% and specificity of 93.0% for anti-DENV IgG and anti-DENV IgM [21]. NS1 antigenaemia is known to occur before IgM and/or IgG rise, thus assay of NS1 increases the sensitivity of DENV RDTs in early infection [6-12]. All testing was performed according to the manufacturer's instructions. In brief, 100μL of whole blood or serum sample was transferred by pipette into the sample well of the freshly unpackaged test device, and left for 20 minutes. A laboratory technician (one of five with experience in this RDT method), blinded to the clinical features of the child, interpreted the colour lines on the immunochromatographic strip. Indeterminate assay, or failed control, results were repeated once and counted as negative if the result was still indeterminate. Whole blood and serum intended for use with the DENV RDT was either used immediately following sampling, or refrigerated for a maximum of 48 hours at 5°C before being equilibrated to room temperature (approximately 25°C) prior to testing.

Reference laboratory methods

The Panbio Japanese Encephalitis Dengue IgM Combo ELISA was retrospectively used for reference serology (Panbio, Australia; Cat. # E-JED01C; Lot # 110061) [24]. Panbio Units were calculated by multiplying the index value (calculated by dividing the sample absorbance by the cut-off value) by 10. The results were classed as negative for DENV and JEV if PanBio units were <9, indeterminate if 9–11 and positive if >11. If both anti-DENV and anti-JEV IgM results were positive, the anti-JEV result was divided by the anti-DENV result to give a ratio, with >1 indicating JEV infection and <1 indicating DENV infection (S1 Table). All ELISAs were repeated once if the positive, negative or calibrator samples were out of range, or the results indeterminate (repeated indeterminate results counted as negative). NS1 antigen ELISA (Standard Diagnostics, Korea; Lot # 224007) was used to detect DENV NS1 antigen [25]. To maximise specificity for the reference DENV assay we considered only children with a ≥4-fold rise in anti-DENV IgM titres or NS1 antigen positivity to be reference assay positive for acute DENV infection. We therefore excluded children who had a single high anti-DENV IgM titre (and no convalescent serum sample) (S2 Table).

Statistical methods

All data was recorded onto a study-specific, password-encrypted database. Descriptive statistical analyses, summary statistics for the DENV RDT, and logistic regression analyses of clinical and laboratory data were undertaken on Stata v.12.1 (Stata Corp, TX, USA). To capture the sequential availability of clinical/laboratory data available to an admitting paediatrician, we created three multivariate logistic regressions with reference assay positive DENV infection as the outcome variable. The first logistic regression included WHO clinical diagnostic criteria [22]: nausea and vomiting, rash, abdominal pain, mucosal bleeding (including rectal), reduced consciousness or confusion (infant/child Glasgow Coma Score ≤13 or disoriented in time or space), or palpable hepatomegaly, as independent binary variables. A second logistic regression included basic laboratory parameters (white cell count, platelet count, haematocrit, alanine transferase (ALT) level, C-reactive protein (CRP) level, malaria blood films), in addition to clinical features (above). The third logistic regression included clinical, laboratory, and DENV RDT variables (NS1 assay and IgM assay) to represent the addition of the DENV RDT to results to the decisive capabilities of the admitting paediatrician. Three identical multivariate logistic regressions were undertaken (clinical data only; clinical data and basic laboratory parameters; and clinical data, basic laboratory parameters and DENV RDT results) but with critical care admission as the outcome variable. Clinical, laboratory, and DENV RDT variables significantly associated (p<0.05) with either reference diagnosis of DENV infection or with admission to the critical care unit were entered into decision algorithms. We used recursive partitioning within a conditional inference framework, with statistical significance (permutation) testing for the generation of splits amongst independent variables (eliminating the need for a cross-validation step) using the R package party [26-28]. Similar analyses have been used previously [13-18] to develop diagnostic algorithms, although with variation in the statistical methods used. We report the results using the Standards for the Report of Diagnostic accuracy studies (STARD)[29].

Results

Description of the cohort

399 febrile episodes in children ≥60 days of age were assessed between 1st June 2010 and 1st October 2010. Of these, 337 (84.5%) were tested with a DENV RDT. 62 (15.5%) children had clearly localised infections, were not tested with a DENV RDT, and are excluded from later analyses (Fig. 1, Table 1).
Table 1

Demographics, co-morbidities, clinical progress and final diagnosis for children with episodes of fever admitted to hospital during the dengue season 2010.

RDT done n = 337RDT not done n = 62Significance
Demographics
Male178 (52.8%)31 (50.0%)p = 0.68 a
Age (median, inter-quartile range [IQR])3.4 (1.1, 8.1)4.3 (1.7, 8.6)p = 0.26 b
Comorbidities
Comorbid HIV infection17 (5.0%)1 (1.6%)p = 0.23 a
Mean z-score weight-for-age (95% confidence intervals [CI]) c –2.2 (–2.5, –2.0)–2.2 (–2.5, –1.8)p = 0.39 d
Comorbid heart disease17 (5.0%)4 (6.5%)p = 0.65 a
Clinical progress
Days of fever at presentation (95% CI)4.4 (4.0, 4.8)4.6 (3.5, 5.6)p = 0.39 d
Blood culture positive17 (5.0%)2 (3.2%)p = 0.75 e
Admission to critical care unit70 (20.8%)13 (21.0%)p = 0.97 a
Mechanical ventilation26 (7.7%)5 (8.1%)p = 0.93 a
Mortality19 (5.6%)2 (3.2%)p = 0.42 a f
Final diagnosis
Reference ≥4-fold rise in anti-dengue IgM or NS1 antigen positive71 (21.1%) g 2 (3.2%) i p<0.0001 e

a Chi-squared test.

b Mann-Whitney U test.

c For those <5 years of age (n = 204 and n = 34, respectively).

d Unpaired two sample t-test.

e Fisher's exact test (2-sided).

f 11 lost to follow-up.

g 14 missing data and excluded (see Fig. 1).

i 10 missing data.

a Chi-squared test. b Mann-Whitney U test. c For those <5 years of age (n = 204 and n = 34, respectively). d Unpaired two sample t-test. e Fisher's exact test (2-sided). f 11 lost to follow-up. g 14 missing data and excluded (see Fig. 1). i 10 missing data. Of children tested with a DENV RDT, 71/337 (21.1%) were reference assay positive for DENV infection (Table 1), 70 (20.8%) children were admitted to the critical care unit, and 19 (5.6%) children died. Comorbidities were prevalent: mean weight-for-age z-score was -2.2 (i.e. underweight, 95% confidence intervals [95% CI] –2.5, –2.0), known HIV infection was present in 17 (5.0%) children, and comorbid congenital or rheumatic heart disease in 17 children. The median number of days between acute and convalescent sera was 4 days (Interquartile Range [IQR] 3, 7).

DENV RDT diagnostic accuracy evaluation

DENV RDT NS1 antigen alone had a sensitivity of 60.8% in comparison to reference NS1 assay, and RDT anti-DENV IgM had a sensitivity of 32.7% in comparison to reference anti-DENV IgM assay (Table 2). DENV RDT NS1 antigen was highly specific when compared to reference assay NS1 antigen (specificity 97.5%), but RDT anti-DENV IgM was less specific for reference assay anti-DENV IgM (specificity 86.2%). When combined, DENV RDT NS1 antigen and/or RDT anti-DENV IgM positivity had a sensitivity of 57.8%, specificity of 85.3%, positive predictive value of 52.6% and negative predictive value of 87.8% for reference assay positive DENV infection (Table 2).
Table 2

Sensitivity and specificity testing for a) DENV RDT NS1 versus reference assay NS1, b) RDT anti-DENV IgM versus reference assay anti-DENV IgM, and c) DENV RDT NS1 and/or RDT anti-DENV IgM versus reference assay positive DENV infection (see text for details of diagnostic criteria).

a)DENV RDT NS1
PositiveNegativeTotal
Reference NS1 assay Positive312051
Negative7270277
Total38297328
Missing279
Sensitivity = 60.8% (95% CI 46.1, 74.2)
Specificity = 97.5% (95% CI 94.9, 99.0)
b) DENV RDT IgM
PositiveNegativeTotal
Reference IgM assay (≥4-fold rise in titres) Positive163349
Negative38237275
Total54270324
Missing5813
Sensitivity = 32.7% (95% CI 20.0, 47.5)
Specificity = 86.2% (95% CI 81.5, 90.0)
c) DENV RDT NS1 and/or IgM
Reference diagnosis of DENV infection PositiveNegativeTotal
Positive413071
Negative37215252
Total78245323
Missing41014
Sensitivity = 57.8% (95% CI 45.4, 69.4)
Specificity = 85.3% (95% CI 80.3, 89.5)
Positive predictive value = 52.6% (95% CI 40.9, 64.0)
Negative predictive value = 87.8% (95% CI 83.0, 91.6)

Missing data was excluded from the sensitivity and specificity analysis.

Missing data was excluded from the sensitivity and specificity analysis.

Covariates associated with DENV infection by reference assay or critical care admission

Table 3 shows adjusted Odds Ratios (aOR) and 95% CI for covariates associated with reference assay positive DENV infection, and critical care admission (for unadjusted variables see S3 Table).
Table 3

Adjusted odds ratios (aOR) for clinical features, laboratory parameters (including malaria blood films), and DENV RDT results, versus reference diagnosis of DENV infection, or all cause admission to the critical care unit (see text for details of regression analyses and adjusting covariates).

Adjusted OR for reference diagnosis of DENV infection (95% CI)Adjusted OR for all cause admission to critical care unit (95% CI)
Clinical features nn
Nausea and vomiting a 2.72 (1.42, 5.20) 243 0.37 (0.18, 0.77) 255
Rash a 1.01 (0.35, 2.90)2430.42 (0.09, 1.97)255
Abdominal pain b 2.63 (1.37, 5.06) 2430.61 (0.27, 1.34)255
Mucosal bleeding b 0.23 (0.06, 0.80) 2431.01 (0.34, 3.02)255
Reduced GCS or confusion b 0.39 (0.11, 1.42)243 7.04 (2.82, 17.57) 255
Hepatomegaly b 1.21 (0.64, 2.31)243 2.98 (1.42, 6.26) 255
Laboratory parameters
Leukocyte levels (every 1.0 x109/mm3 increase)0.96 (0.89, 1.04)191 1.12 (1.04, 1.20) 181
Platelet levels (every 10 x 109/mm3 increase) 0.95 (0.92, 0.98) 1911.00 (0.97, 1.02)181
Haematocrit (every 1 percent increase)0.99 (0.94, 1.06)1911.02 (0.96, 1.08)181
Alanine transaminase (every 10 units/L increase)1.00 (0.98, 1.02)1911.01 (0.98, 1.03)181
C-reactive protein (every 1 mg/dL increase) 0.76 (0.60, 0.95) 191 1.28 (1.05, 1.55) 181
Blood films for malaria0.22 (0.02, 2.04)1910.66 (0.07, 6.63)181
DENV RDT results
NS1 positive 31.75 (6.79, 148.5) 1911.35 (0.25, 7.24)181
NS1 and/or IgM positive 4.19 (1.74, 10.11) 1910.64 (0.19, 2.12)181
IgG positive and NS1 and/or IgM positive 25.00 (6.15, 101.5) 1910.68 (0.15, 3.00)181

a Clinical signs of probable dengue [22];

b clinical warning signs of dengue requiring inpatient management [22]

Bold type indicates p<0.05 for an association between covariate and outcome variable association. See S3 Table for unadjusted results.

a Clinical signs of probable dengue [22]; b clinical warning signs of dengue requiring inpatient management [22] Bold type indicates p<0.05 for an association between covariate and outcome variable association. See S3 Table for unadjusted results. At presentation, nausea and vomiting were associated with reference assay positive DENV infection (aOR 2.72, 95% CI 1.42, 5.20), as was abdominal pain (aOR 2.63, 95% CI 1.37, 5.06), whilst mucosal bleeding (including rectal) was negatively associated with reference assay positive DENV infection (aOR 0.23, 95% CI 0.06, 0.80). Children with mucosal bleeding were more likely to be diagnosed with gastroenteritis/dysentery as the cause of their febrile illness than those without mucosal bleeding: 21/59 (35.6%) versus 21/274 (7.6%) (χ2, p <0.001). Of laboratory parameters, platelet levels and CRP were negatively associated with reference assay positivity (aOR 0.97 per 10 x109/mm3 increase, 95% CI 0.95, 0.99; and aOR 0.81 per 1 mg/dL increase, 95% CI 0.67, 0.99, respectively). DENV RDT NS1 antigen positivity was strongly associated with reference assay positive DENV infection (aOR 31.75, 95% CI 6.79, 148.5), as was DENV RDT NS1 antigen and/or IgM (aOR 4.19, 95% CI 1.74, 10.11). Addition of DENV RDT IgG with NS1 antigen and/or IgM increased odds of reference diagnosis (aOR 25.00, 95% CI 6.15, 101.5). 70 (20.8%) children required admission to the critical care unit, 7 of whom were reference assay positive for DENV infection (no sub-analysis of these 7 children was possible). Amongst all causes, reduced consciousness and hepatomegaly were positively associated with admission to the critical care unit (aOR 7.04, 95% CI 2.82, 17.57; and aOR 2.98 95% CI 1.42, 6.26, respectively). Increased leukocyte level (aOR 1.12, 95% CI 1.04, 1.20 per 10 x109/mm3 increase) and increased CRP level (aOR 1.28, 95% CI 1.05, 1.55 per 1 mg/dL increase) were also associated with critical care unit admission. Nausea and vomiting were negatively associated with admission to the critical care unit (aOR 0.37, 95% CI 0.18, 0.77). No other covariates, including the results of the DENV RDT, were associated with critical care unit admission. Children with missing observations within the variables regressed were excluded (Table 3).

Decision algorithms with conditional inference trees

From clinical covariates, nausea and vomiting and abdominal pain were selected as independent predictors of reference assay positive DENV infection (Fig. 2). When clinical and laboratory covariates were analysed together, children with a platelet level ≤154 x109/mm3 were most likely to have reference assay positive DENV infection (although with an error rate of 50.0%) (Fig. 3). Children with a platelet level >154 x109/mm3 and a leukocyte level >7.4 x109/mm3 had a low likelihood of being reference assay positive for DENV infection (error rate 5.5%).
Figure 2

Conditional inference tree for the prediction of reference diagnosis of DENV infection using clinical diagnostics with an association (p<0.05) with reference diagnosis of DENV infection (nausea and vomiting and abdominal pain).

Figure 3

Conditional inference tree for the prediction of reference diagnosis of DENV infection using clinical features and laboratory parameters with an association (p<0.05) with the reference diagnosis of DENV infection (platelet levels and white cell levels; note the model removes clinical features from the tree).

Combining clinical, laboratory and DENV RDT covariates created five classifications (four, if node 6 [hepatomegaly] is combined) for likelihood of reference assay positive DENV infection (Fig. 4). Children with a positive DENV RDT result and platelet count ≤313 x109/mm3 had the highest probability (error rate of 37.1%), particularly if they showed hepatomegaly (error rate 31.9%). Alternatively children with a negative DENV RDT, and white cell count >7.4 x109/mm3 had a low likelihood (error rate 4.8%). Other classifications showed intermediate likelihood.
Figure 4

Conditional inference tree for the prediction of reference diagnosis of DENV infection using clinical diagnostics, laboratory parameters and DENV RDT results with an association (p<0.05) with reference diagnosis of DENV infection (DENV RDT, platelet levels, white cell levels, hepatomegaly).

Decreased consciousness was the most important classifier for all cause critical care admission (error rate 46.3%), whilst children with a white cell count ≤15.1 x109/mm3 and CRP level <7 mg/dL were least likely to require critical care admission (error rate 8.3%) (Fig. 5).
Figure 5

Conditional inference tree for the prediction of critical care unit admission using clinical diagnostics, laboratory parameters and DENV RDT results with an association with either the reference diagnosis of DENV infection, or all cause critical care admission.

The problem of multiple diagnoses

Both DENV RDT positive and negative groups were infected with a range of other pathogens (Table 4). 22/82 (26.8%) children in whom a DENV RDT was positive had evidence of treatable infections: from serology, Orientia tsutsugamushi (eight children), Rickettsia typhi (five children); from direct stains, Mycobacterium tuberculosis (two children), Plasmodium falciparum (one child); from blood culture, Burkholderia pseudomallei, Klebsiella pneumoniae, Salmonella enterica serovar Typhi (all one child each); and from NAATs, Leptospira spp. (two children) and herpes simplex virus (one child, from CSF).
Table 4

Final microbiological (including virological/parasitological) diagnoses for patients, categorised by indication of acute DENV infection on DENV RDT result (NS1 and/or IgM positive; or NS1 and IgM negative).

DENV RDT positiveDENV RDT negative
n = 82n = 255
Flaviviruses
Dengue virus41 (50.0%)30 (11.8%)
Indeterminate flavivirus1 (1.2%)4 (1.6%)
Japanese encephalitis virus5 (6.1%)9 (3.5%)
Rickettsioses
Orientia tsutsugamushi8 (9.8%)29 (11.4%)
Rickettsia typhi5 (6.1%)10 (3.9%)
Unknown Rickettsia spp.03 (1.2%)
Respiratory viruses
Respiratory syncytial virus1 (1.2%)4 (1.6%)
Influenza A H1N1-pdm0904 (1.6%)
Parainfluenza virus 303 (1.2%)
Parainfluenza virus 101 (0.4%)
Cultured bacteria
Salmonella enterica serovar Typhi1 (1.2%)8 (3.1%)
Burkholderia pseudomallei1 (1.2%)4 (1.6%)
Streptococcus pneumoniae03 (1.2%)
Staphylococcus aureus03 (1.2%)
Escherichia coli02 (0.8%)
Haemophilus influenzae01 (0.4%)
Acinetobacter spp.01 (0.4%)
Klebsiella pneumoniae1 (1.2%)0
Bacteria of unknown significance1 (1.2%)2 (0.8%)
Other
Leptospira spp2 (2.4%)2 (0.8%)
Mycobacterium tuberculosis2 (2.4%)1 (0.4%)
Plasmodium falciparum1 (1.2%)1 (0.4%)
P. falciparum and Plasmodium vivax 02 (0.8%)
P. vivax01 (0.4%)
Enterovirus01 (0.4%)
Herpes simplex virus1 (1.2%)0
Yeast (non-cryptococcal)01 (0.4%)
Haematological malignancy01 (0.4%)
Contaminant from blood culture10 (12.1%)18 (7.1%)
Clinical diagnosis only 8 (9.8%)118 (46.3%)

Discussion

During a single wet season in Cambodia a DENV RDT had a positive predictive value of 53% and negative predictive value of 88% for reference assay positive DENV infection in febrile children admitted to hospital. The high negative predictive value indicates that a negative DENV RDT may practicably "rule-out" DENV infection in this cohort (but not "rule-out" other co-infections). As with other studies of diagnostic accuracy [6-18], this study is reliant on a gold standard test for its accuracy. The DENV RDT sensitivity of 58% was lower than similar studies [6-12], where sensitivity has ranged from 88% to 95% for identical or similar NS1/IgM combined proprietary DENV RDTs. Our study showed a lower incidence of reference assay positive DENV infection in comparison to these studies (possibly due to our deliberately broad inclusion criteria to encapsulate the breadth of DENV infection in infants and children [5], and high incidence of other infections), which may account for the apparent lower sensitivity. Alternative explanations for low sensitivity include differential sensitivity of the DENV RDT to circulating anti-DENV antibodies to different DENVs (DENVs 1–3 circulate in Cambodia [19]), or due to differing incidence of primary and secondary infections from other studies (both not assessed in this study). The exclusion of 14 children with only single acute serum samples (and NS1 antigen negative) did not adversely affect test sensitivity. We found no evidence for a lower early IgM response in children in the cohort with younger age, or malnutrition, and no evidence that the variable length of time between acute and convalescent samples (and from onset of fever to presentation) reduce the sensitivity of the DENV RDT by producing false negatives by reference assay. Further studies would benefit from increased sample size, and sampling of convalescent sera after a fixed interval from the acute sample (although this may not be always feasible). Incorporation of the DENV RDT result into conditional inference trees, with the use of platelet count (of ≤313 x109/mm3), classified a high likelihood group (Fig. 4, nodes 7 and 8, error rate 37%) and a large low likelihood group (node 4, error rate 5%), with approximately a quarter of the cohort classified into one of two intermediate groups (nodes 3 and 9). However, a conditional inference tree generated by the same methods using platelet count (of ≤154 x109/mm3) and leukocyte count (of ≤7.4 x109/mm3) generated a more simple decision algorithm, with a high likelihood group (Fig. 3, node 2, error rate 50%), large low likelihood group (node 5, error rate 6%), and 15% in an intermediate group (node 4). Additionally, a positive DENV RDT result was not predictive of disease severity as judged by admission to the critical care unit; rather, critical care unit admission was predicted by reduced consciousness and increased leukocyte levels, and CRP ≥ 7 mg/dL (Fig. 5). In brief, in this setting, the benefit of adding the DENV RDT to the diagnostic decision algorithm is therefore questionable, given presumed cost constraints. A complete blood count (with leukocyte and platelet levels), and CRP level were helpful for clinical decision-making regarding both diagnosis and disease severity, and should be undertaken on all children. Was a positive DENV RDT indicative of the final diagnosis? No. Unlike many studies of DENV RDTs [6-12] and decision algorithms [13-18], our cohort of children had been thoroughly investigated in a study designed specifically to describe the microbiological causes of their febrile illness [20]. In this cohort nearly half of children with a positive DENV RDT result had a co-infection, over a quarter with a bacterial co-infection (Table 4). The results of this study appear to contradict previous data on the utility of DENV RDTs. Retrospective analysis of the sensitivity and specificity of the RDT in known cases and controls, with a high "incidence" and clear-cut cases, would increase estimates of the diagnostic accuracy of the RDT [7-9]. Prospective studies, with higher DENV infection incidence (thus higher pre-test probability), have not integrated clinical and laboratory parameters into decision algorithms, increasing the apparent utility of DENV RDTs [6,11]. Amongst the elaboration of decision algorithms for DENV infection diagnosis, none have yet assessed the role of DENV RDTs [13-18]. Our emphasis on assessing DENV RDTs alongside other information attempts a realistic description of clinical decision-making. In future, improved DENV RDTs used in combination with RDTs to other important and locally prevalent pathogens may be helpful. In the meantime, good clinical observation, basic laboratory testing (including complete blood count, platelet levels and CRP), well-conceived "sepsis bundles" including antibiotic guidelines and resuscitation protocols, and sentinel microbiology facilities must continue [30,31].

Classification of the Panbio Japanese Encephalitis Dengue IgM Combo and DENV NS1 antigen ELISA used for DENV reference assay: "Positive", "Negative" or "Missing" within the boxed region describes the final interpretation of the DENV reference assay (i.e. accounting both serology and NS1 antigen assay).

Rise in titres is defined as ≥2 Panbio units between acute and discharge samples. (DOC) Click here for additional data file.

Sensitivity and specificity testing for a) RDT anti-DENV IgM and b) DENV RDT NS1 and/or RDT anti-DENV IgM versus reference assay positive DENV infection (specified as reference NS1 antigen assay positive, or either ≥4-fold rise between acute and convalescent sera or, exceptionally in this Supplementary Material table, a single high titre of anti-DENV IgM on acute serology).

Missing data was excluded from the sensitivity and specificity analysis. (DOC) Click here for additional data file.

Unadjusted odds ratios (OR) for clinical features, malaria testing dengue RDT results and laboratory parameters, against DENV RDT NS1 antigen or RDT anti-DENV IgM positivity, or against reference assay positive DENV infection, or against critical care admission.

OR in bold indicates p<0.05 for an association between covariate and outcome variable. (DOC) Click here for additional data file.

a) Sensitivity and specificity of DENV RDT NS1, RDT anti-DENV IgM and RDT NS1 and/or anti-DENV IgM for confirmed reference diagnosis of DENV infection, by age of child.

b) Sensitivity and specificity of DENV RDT NS1, RDT anti-DENV IgM and RDT NS1 and/or anti-DENV IgM for confirmed reference diagnosis of DENV infection, by the carer reported number of days of fever before presentation. (DOC) Click here for additional data file.

STandards for the Reporting of Diagnostic accuracy studies (STARD) statement checklist.

(DOC) Click here for additional data file.
  22 in total

1.  Early diagnosis of Dengue infection using a commercial Dengue Duo rapid test kit for the detection of NS1, IGM, and IGG.

Authors:  Seok Mui Wang; Shamala Devi Sekaran
Journal:  Am J Trop Med Hyg       Date:  2010-09       Impact factor: 2.345

2.  Evaluation of six commercial point-of-care tests for diagnosis of acute dengue infections: the need for combining NS1 antigen and IgM/IgG antibody detection to achieve acceptable levels of accuracy.

Authors:  Stuart D Blacksell; Richard G Jarman; Mark S Bailey; Ampai Tanganuchitcharnchai; Kemajittra Jenjaroen; Robert V Gibbons; Daniel H Paris; Ranjan Premaratna; H Janaka de Silva; David G Lalloo; Nicholas P J Day
Journal:  Clin Vaccine Immunol       Date:  2011-10-19

3.  Comparison of seven commercial antigen and antibody enzyme-linked immunosorbent assays for detection of acute dengue infection.

Authors:  Stuart D Blacksell; Richard G Jarman; Robert V Gibbons; Ampai Tanganuchitcharnchai; Mammen P Mammen; Ananda Nisalak; Siripen Kalayanarooj; Mark S Bailey; Ranjan Premaratna; H Janaka de Silva; Nicholas P J Day; David G Lalloo
Journal:  Clin Vaccine Immunol       Date:  2012-03-21

4.  Clinical and virological features of Dengue in Vietnamese infants.

Authors:  Tran Nguyen Bich Chau; Katherine L Anders; Le Bich Lien; Nguyen Thanh Hung; Lu Thi Minh Hieu; Nguyen Minh Tuan; Tran Thi Thuy; Le Thi Phuong; Nguyen Thi Hong Tham; Mai Ngoc Lanh; Jeremy J Farrar; Stephen S Whitehead; Cameron P Simmons
Journal:  PLoS Negl Trop Dis       Date:  2010-04-13

5.  Dengue incidence in urban and rural Cambodia: results from population-based active fever surveillance, 2006-2008.

Authors:  Sirenda Vong; Virak Khieu; Olivier Glass; Sowath Ly; Veasna Duong; Rekol Huy; Chantha Ngan; Ole Wichmann; G William Letson; Harold S Margolis; Philippe Buchy
Journal:  PLoS Negl Trop Dis       Date:  2010-11-30

6.  Prediction of dengue disease severity among pediatric Thai patients using early clinical laboratory indicators.

Authors:  James A Potts; Robert V Gibbons; Alan L Rothman; Anon Srikiatkhachorn; Stephen J Thomas; Pra-On Supradish; Stephenie C Lemon; Daniel H Libraty; Sharone Green; Siripen Kalayanarooj
Journal:  PLoS Negl Trop Dis       Date:  2010-08-03

7.  Decision tree algorithm in deciding hospitalization for adult patients with dengue haemorrhagic fever in Singapore.

Authors:  V J Lee; D C Lye; Y Sun; Y S Leo
Journal:  Trop Med Int Health       Date:  2009-07-14       Impact factor: 2.622

Review 8.  Surviving sepsis in low-income and middle-income countries: new directions for care and research.

Authors:  Joseph U Becker; Christian Theodosis; Shevin T Jacob; Charles R Wira; Nora Ellen Groce
Journal:  Lancet Infect Dis       Date:  2009-09       Impact factor: 25.071

Review 9.  Commercial dengue rapid diagnostic tests for point-of-care application: recent evaluations and future needs?

Authors:  Stuart D Blacksell
Journal:  J Biomed Biotechnol       Date:  2012-05-10

10.  Utility of the tourniquet test and the white blood cell count to differentiate dengue among acute febrile illnesses in the emergency room.

Authors:  Christopher J Gregory; Olga D Lorenzi; Lisandra Colón; Arleene Sepúlveda García; Luis M Santiago; Ramón Cruz Rivera; Liv Jossette Cuyar Bermúdez; Fernando Ortiz Báez; Delanor Vázquez Aponte; Kay M Tomashek; Jorge Gutierrez; Luisa Alvarado
Journal:  PLoS Negl Trop Dis       Date:  2011-12-06
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  10 in total

1.  Use of a Rapid Test for Diagnosis of Dengue during Suspected Dengue Outbreaks in Resource-Limited Regions.

Authors:  Elizabeth A Hunsperger; Tyler M Sharp; Paul Lalita; Kini Tikomaidraubuta; Yolanda Rebello Cardoso; Taina Naivalu; Aalisha Sahu Khan; Maria Marfel; W Thane Hancock; Kay M Tomashek; Harold S Margolis
Journal:  J Clin Microbiol       Date:  2016-05-25       Impact factor: 5.948

2.  Correction: Rapid diagnostic tests for dengue virus infection in febrile Cambodian children: diagnostic accuracy and incorporation into diagnostic algorithms.

Authors: 
Journal:  PLoS Negl Trop Dis       Date:  2015-03-19

3.  Correction: Rapid Diagnostic Tests for Dengue Virus Infection in Febrile Cambodian Children: Diagnostic Accuracy and Incorporation into Diagnostic Algorithms.

Authors:  Michael J Carter; Kate R Emary; Catherine E Moore; Christopher M Parry; Soeng Sona; Hor Putchhat; Sin Reaksmey; Ngoun Chanpheaktra; Nicole Stoesser; Andrew D M Dobson; Nicholas P J Day; Varun Kumar; Stuart D Blacksell
Journal:  PLoS Negl Trop Dis       Date:  2016-02-05

4.  Predicting the severity of dengue fever in children on admission based on clinical features and laboratory indicators: application of classification tree analysis.

Authors:  Khansoudaphone Phakhounthong; Pimwadee Chaovalit; Podjanee Jittamala; Stuart D Blacksell; Michael J Carter; Paul Turner; Kheng Chheng; Soeung Sona; Varun Kumar; Nicholas P J Day; Lisa J White; Wirichada Pan-Ngum
Journal:  BMC Pediatr       Date:  2018-03-13       Impact factor: 2.125

5.  Burden of dengue among febrile patients at the time of chikungunya introduction in Piedecuesta, Colombia.

Authors:  Mabel Carabali; Jacqueline K Lim; Diana C Palencia; Anyela Lozano-Parra; Rosa Margarita Gelvez; Kang Sung Lee; Janeth P Florez; Victor Mauricio Herrera; Jay S Kaufman; Elsa M Rojas; Luis Angel Villar
Journal:  Trop Med Int Health       Date:  2018-09-19       Impact factor: 2.622

6.  Accuracy of the SD BIOLINE Dengue Duo for rapid point-of-care diagnosis of dengue.

Authors:  Mariana Kikuti; Jaqueline S Cruz; Moreno S Rodrigues; Aline S Tavares; Igor A D Paploski; Monaise M O Silva; Perla M Santana; Laura B Tauro; Greice A O F Silva; Gúbio S Campos; Josélio M G Araújo; Uriel Kitron; Mitermayer G Reis; Guilherme S Ribeiro
Journal:  PLoS One       Date:  2019-03-06       Impact factor: 3.240

7.  Evaluation of novel rapid detection kits for dengue virus NS1 antigen in Dhaka, Bangladesh, in 2017.

Authors:  Keita Suzuki; Emi E Nakayama; Akatsuki Saito; Akio Egawa; Tairyu Sato; Juthamas Phadungsombat; Rummana Rahim; Abu Hasan; Hisahiko Iwamoto; Mizanur Rahman; Tatsuo Shioda
Journal:  Virol J       Date:  2019-08-15       Impact factor: 4.099

8.  Diagnostic accuracy and utility of three dengue diagnostic tests for the diagnosis of acute dengue infection in Malaysia.

Authors:  Zhuo Lin Chong; Shamala Devi Sekaran; Hui Jen Soe; Devi Peramalah; Sanjay Rampal; Chiu-Wan Ng
Journal:  BMC Infect Dis       Date:  2020-03-12       Impact factor: 3.090

9.  Comparative assessment of commercial enzyme-linked immunosorbent assay & rapid diagnostic tests used for dengue diagnosis in India.

Authors:  Ruta Kulkarni; Meera Modak; Mrunal Gosavi; Dileep Wani; Akhilesh C Mishra; Vidya A Arankalle
Journal:  Indian J Med Res       Date:  2020-01       Impact factor: 2.375

10.  Diagnostic Accuracy of Various Immunochromatographic Tests for NS1 Antigen and IgM Antibodies Detection in Acute Dengue Virus Infection.

Authors:  Mughees Haider; Saira Yousaf; Asifa Zaib; Azza Sarfraz; Zouina Sarfraz; Ivan Cherrez-Ojeda
Journal:  Int J Environ Res Public Health       Date:  2022-07-19       Impact factor: 4.614

  10 in total

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