Pitfalls in acute febrile illness diagnosis: Interobserver agreement of signs and symptoms during a dengue outbreak.

AIMS AND OBJECTIVES: To compare and evaluate interobserver (nurses and physicians) agreement for dengue clinical signs and symptoms, including the World Health Organization diagnostic algorithm. BACKGROUND: Agreement of clinical history defines the capacity of the examiner to measure a given clinical parameter in a reproducible and consistent manner, which is prerequisite for diagnosis validity. Nurses play a major role in the triage and care of dengue patients in many countries. STUDY DESIGN: This is a sub-study on interobserver agreement performed as part of a cross-sectional diagnostic accuracy study for acute febrile illness (AFI) using the checklist STARD. METHODS: A previously validated semi-structured sign and symptom standardised questionnaire for AFI was independently administered to 374 patients by physician and nurse pairs. The interobserver agreement was estimated using kappa statistics. RESULTS: For a set of 27 signs and symptoms, we found six interobserver discrepancies (examiner detected red eyes, lethargy, exanthema, dyspnoea, bleeding and myalgia) as identified by regular and moderate kappa indexes. Four signs (patient observed red eyes, cough, diarrhoea and vomiting) and one symptom (earache) had near-perfect agreement. Most signs and symptoms showed substantial agreement. The WHO (Dengue guidelines for diagnosis, treatment, prevention and control: new edition, World Health Organization, 2009) clinical criteria for dengue comprise a group of symptoms known as "pains and aches." Interobserver agreement for abdominal pain, retro-orbital pain and arthralgia exceed that found for headache and myalgia. CONCLUSIONS: During a dengue outbreak, the interobserver agreement for most of the signs and symptoms used to assess AFI was substantial. RELEVANCE TO CLINICAL PRACTICE: This result suggests good potential applicability of the tool by health professionals following training. A well-trained health professional is qualified to apply the standardised questionnaire to evaluate suspected dengue cases during outbreaks.

Accuracy of clinical criteria and an immunochromatographic strip test for dengue diagnosis in a DENV-4 epidemic.

BACKGROUND: Early diagnosis of dengue infection is important for decision-making and timely implementation of therapeutic measures. Although rapid NS1 assays have been used for dengue diagnosis since 2008, their performance in DENV-4 cases has not yet been fully assessed. METHODS: We evaluated the accuracy of NS1 Bioeasy™ immunochromatographic strip test and of three clinical criteria for dengue diagnosis. Patients presenting at an emergency care center within 72 h of an acute febrile illness during the 2013 DENV-4 epidemic in Rio de Janeiro were consecutively enrolled for clinical and laboratory evaluation. We classified patients as suspected dengue or not according to three clinical criteria: WHO 2009, WHO 1997, and INI-FIOCRUZ. Dengue diagnosis was defined by RNA detection using RT-PCR and the negative cases were negative for all dengue serotypes and also Platelia™ NS1 ELISA. We obtained accuracy indices for NS1 Bioeasy™ alone and in combination with the clinical criteria. RESULTS: RT-PCR for DENV-4 was positive in 148 out of 325 patients. Positive likelihood ratio, sensitivity, and specificity of NS1 Bioeasy™ with WHO 2009, WHO 1997, and INI-FIOCRUZ criteria were 22.6 (95% CI 7.2-70.6), 40.6% (95% CI 32.3-49.3), and 98.2% (95% CI 94.9-99.6); 18.3 (95% CI 6.8-49.2), 44.2 (95% CI 35.8-52.9), 97.6 (95% CI 94.0-99.3); 26.2 (95% CI 6.5-106.5), 29.7 (95% CI 22.4-37.8), 98.9 (95% CI 96.0-99.9), respectively. WHO 1997 clinical criteria presented high sensitivity to rule out disease, but extremely low specificity. INI-FIOCRUZ had moderate sensitivity and specificity, and could target a group to a more specific test. CONCLUSIONS: Although the large rates of false negative results using NS1 Bioeasy™ rapid test advise against its use for triaging (rule out) purposes in DENV-4 epidemics, it could be used as a confirmatory tool in a bedside algorithm.