Epidemiologic, clinical, and serum markers may improve discrimination between bacterial and viral etiologies of childhood pneumonia

Background

Discrimination of bacterial and viral etiologies of childhood community-acquired pneumonia (CAP) is often challenging. Unnecessary antibiotic administration exposes patients to undue risks and may engender antimicrobial resistance. This study aimed to develop a prediction model using epidemiological, clinical and laboratory data to differentiate between bacterial and viral CAP.

Methods

Data from 155 children with confirmed bacterial or mixed bacterial and viral infection (N = 124) and viral infection (N = 31) were derived from a comprehensive assessment of causative pathogens [Partnerships for Enhanced Engagement in Research-Pneumonia in Pediatrics (PEER-PePPeS)] conducted in Indonesia. Epidemiologic, clinical and biomarker profiles (hematology and inflammatory markers) were compared between groups. The area under the receiver operating characteristic curve (AUROC) for varying biomarker levels was used to characterize performance and determine cut-off values for discrimination of bacterial and mixed CAP versus viral CAP. Diagnostic predictors of bacterial and mixed CAP were assessed by multivariate logistic regression.

Results

Diarrhea was more frequently reported in bacterial and mixed CAP, while viral infections more frequently occurred during Indonesia's rainy season. White blood cell counts (WBC), absolute neutrophil counts (ANC), neutrophil-lymphocyte ratio (NLR), C-reactive protein (CRP), and procalcitonin (PCT) were significantly higher in bacterial and mixed cases. After adjusting for covariates, the following were the most important predictors of bacterial or mixed CAP: rainy season (aOR 0.26; 95% CI 0.08-0.90; p = 0.033), CRP ≥5.70 mg/L (aOR 4.71; 95% CI 1.18-18.74; p = 0.028), and presence of fever (aOR 5.26; 95% CI 1.07-25.91; p = 0.041). The model assessed had a low R-squared (Nagelkerke R² = 0.490) but good calibration (p = 0.610 for Hosmer Lemeshow test). The combination of CRP and fever had moderate predictive value with sensitivity and specificity of 62.28 and 65.52%, respectively.

Conclusion

Combining clinical and laboratory profiles is potentially valuable for discriminating bacterial and mixed from viral pediatric CAP and may guide antibiotic use. Further studies with a larger sample size should be performed to validate this model.

Coinfection With SARS-CoV-2 and Dengue Virus: A Case Report Highlighting Diagnostic Challenges

Background

Since its emergence in China, SARS-CoV-2 has infected more than 240 million people worldwide, including in regions where dengue virus (DENV) is hyperendemic such as Latin America and Southeast Asia, including Indonesia. Diagnosis of COVID-19 in dengue endemic regions as well as DENV and SARS-CoV-2 co-infection can be challenging.

Case Presentation

We describe a 68-year-old woman with diabetes mellitus type II who was admitted to the Tangerang District Hospital on 14 April 2020. She lived in a neighborhood where a few people were contracting dengue fever. She presented with five days of fever, malaise, anorexia, nausea, myalgia, and arthralgia. Hematology revealed anemia, thrombocytopenia, normal leukocyte count, increased neutrophil proportion, and decreased lymphocyte proportion and absolute lymphocytes. Her chest X-ray showed right pericardial infiltrates. Although dengue was clinically suspected, she was also tested for SARS-CoV-2 infection as she met screening criteria. After being confirmed SARS-CoV-2 positive by RT-PCR, she was treated with ceftriaxone, paracetamol, azithromycin, oseltamivir, and chloroquine. She was clinically improved four days later and discharged from the hospital on 25 April 2020 after SARS-CoV-2 RT-PCR was negative on two consecutive samples. Dengue was diagnosed retrospectively based on sero-conversion of dengue IgM and a very high dengue IgG index (ELISA, Focus Diagnostics®, Cypress, CA, USA), and sero-conversion of dengue IgM and positive IgG (Rapid test, PanBio ®Dengue duo cassette, Inverness Medical Innovations, QLD, AU), which was equivalent to high Hemagglutination Inhibition (HI) antibody titer (≥1280) found in secondary dengue infection.

Conclusion

The overlapping clinical presentations of COVID-19 and dengue; limited diagnostic capacity of laboratories in resource constrained settings; and complexities of interpreting results make identification of COVID-19 in the dengue endemic setting challenging. Clinicians in endemic areas must be aware of diagnostic challenges and maintain a high index of suspicion for COVID-19 coinfection with DENV and other tropical pathogens.