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.

Molecular epidemiology of SARS-CoV-2 isolated from COVID-19 family clusters.

Background: Transmission within families and multiple spike protein mutations have been associated with the rapid transmission of SARS-CoV-2. We aimed to: (1) describe full genome characterization of SARS-CoV-2 and correlate the sequences with epidemiological data within family clusters, and (2) conduct phylogenetic analysis of all samples from Yogyakarta and Central Java, Indonesia and other countries.

Methods: The study involved 17 patients with COVID-19, including two family clusters.

Predictor Factors of Continuous Positive Airway Pressure Failure in Preterm Infants with Respiratory Distress.

Respiratory distress contributes significantly to mortality, and morbidity in preterm infants. The incidence of nasal continuous positive airway pressure (CPAP) failure is remarkably high. There are limited data available regarding nasal CPAP failure in Indonesia, and this study is expected to be a reference in taking preventive measures to reduce mortality and morbidity in preterm infants.

Cough sound analysis - a new tool for diagnosing pneumonia.

Pneumonia kills over 1,800,000 children annually throughout the world. Prompt diagnosis and proper treatment are essential to prevent these unnecessary deaths. Reliable diagnosis of childhood pneumonia in remote regions is fraught with difficulties arising from the lack of field-deployable imaging and laboratory facilities as well as the scarcity of trained community healthcare workers.

Neural network based algorithm for automatic identification of cough sounds.

Cough is the most common symptom of the several respiratory diseases containing diagnostic information. It is the best suitable candidate to develop a simplified screening technique for the management of respiratory diseases in timely manner, both in developing and developed countries, particularly in remote areas where medical facilities are limited. However, major issue hindering the development is the non-availability of reliable technique to automatically identify cough events.

Cough sound analysis can rapidly diagnose childhood pneumonia.

Pneumonia annually kills over 1,800,000 children throughout the world. The vast majority of these deaths occur in resource poor regions such as the sub-Saharan Africa and remote Asia. Prompt diagnosis and proper treatment are essential to prevent these unnecessary deaths.

Automatic identification of wet and dry cough in pediatric patients with respiratory diseases.

Cough is the most common symptom of several respiratory diseases. It is a defense mechanism of the body to clear the respiratory tract from foreign materials inhaled accidentally or produced internally by infections. The identification of wet and dry cough is an important clinical finding, aiding in the differential diagnosis especially in children.