Interobserver agreement on signs and symptoms of patients with acute febrile illness

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.

Rickettsia parkeri in Amblyomma dubitatum ticks in a spotted fever focus from the Brazilian Pampa

Spotted fever is an acute febrile illness, which is considered severely underreported and misdiagnosed in the Brazilian Pampa, caused by tick-borne Rickettsiae. Here, we report an eco-epidemiological investigation of Rickettsia spp. in ticks from a spotted fever focus in Toropi, southern Brazil. Ticks were collected from capybara carcasses and processed individually to obtain genomic DNA. Rickettsia was investigated using PCR that amplified the rickettsial fragments of the gltA, ompA and htrA genes. DNA from Rickettsia parkeri was found in four of 14 Amblyomma dubitatum ticks collected from capybara carcasses in Toropi and the nearby municipality of Quevedos. We also tested 210A. dubitatum ticks obtained from road-killed capybaras of other localities from the Pampa biome; none of them were positive for Rickettsiae. Thus, in Rio Grande do Sul, two Rickettsia species can be potentially associated to spotted fever: Rickettsia sp. strain Atlantic Rainforest, associated with Amblyomma ovale ticks in the Atlantic Rainforest biome, and R. parkeri, associated both with Amblyomma tigrinum and A. dubitatum ticks in the Pampa biome. Our results reinforce that R. parkeri may be the agent associated with spotted fever in the Brazilian Pampa.

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.

Clinical and laboratory features that discriminate dengue from other febrile illnesses: a diagnostic accuracy study in Rio de Janeiro, Brazil

BACKGROUND

Dengue is an acute febrile illness caused by an arbovirus that is endemic in more than 100 countries. Early diagnosis and adequate management are critical to reduce mortality. This study aims to identify clinical and hematological features that could be useful to discriminate dengue from other febrile illnesses (OFI) up to the third day of disease.

METHODS

We conducted a sectional diagnostic study with patients aged 12 years or older who reported fever lasting up to three days, without any evident focus of infection, attending an outpatient clinic in the city of Rio de Janeiro, Brazil, between the years 2005 and 2008. Logistic regression analysis was used to identify symptoms, physical signs, and hematological features valid for dengue diagnosis. Receiver-operating characteristic (ROC) curve analyses were used to define the best cut-off and to compare the accuracy of generated models with the World Health Organization (WHO) criteria for probable dengue.

RESULTS

Based on serological tests and virus genome detection by polymerase chain reaction (PCR), 69 patients were classified as dengue and 73 as non-dengue. Among clinical features, conjunctival redness and history of rash were independent predictors of dengue infection. A model including clinical and laboratory features (conjunctival redness and leukocyte counts) achieved a sensitivity of 81% and specificity of 71% and showed greater accuracy than the WHO criteria for probable dengue.

CONCLUSIONS

We constructed a predictive model for early dengue diagnosis that was moderately accurate and performed better than the current WHO criteria for suspected dengue. Validation of this model in larger samples and in other sites should be attempted before it can be applied in endemic areas.