Acute Respiratory Tract Infection
Conditions
Keywords
Lung sound analysis, Upper Respiratory Truct Infections, Lower Respiratory Truct Infections
Brief summary
This observational study evaluates whether lung sound analysis with LungPass device can be used to differentiate upper and lower respiratory tract infections (URTI and LRTI)
Detailed description
This is a prospective observational study comprised patients presenting with acute respiratory tract infection symptoms in primary care settings. Patients will undergo routine clinical examination including lung auscultation with conventional stethoscope and LungPass device. Moreover, symptoms and anamnesis data, result of diagnostic questionnaire from the LungPass App, complete blood count, C-reactive protein, procalcitonin (PCT) level, SARS-CoV-2 PCR test and X-ray chest examination or CT chest (in case of preliminary clinical suspicion of LRTI). Patients will be followed up within 5-7 days and at the end of the disease in person or by phone for clinical course of the disease assessment to confirm the final diagnosis (URTI or LRTI). Final diagnosis will be considered as Gold standard for accuracy assessment.
Interventions
Lung auscultation with electronic stethoscope
Sponsors
Belarusian Medical Academy of Post-Graduate Education
University of Manchester
Healthy Networks
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
3 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Adults (over 18 years) and children (3-18 years) of both sexes; * Patients able and willing to sign an informed consent to participate in the study (parents of children younger than 18 years old will be allowed to give an informed consent on behalf of their children). * Patients presenting with a new onset of at least two of listed acute respiratory tract infection symptoms within the last 5 days: cough, purulent sputum, breathlessness, core temperature above 38°C. * Patients who first visit a GP with these symptoms within the first 5 days from the onset of symptoms and was not previously treated with antibiotics during the last month.
Exclusion criteria
* Age up to 3 years; * Patient refusal to participate in the study (or patients' parents); * Children under full State care (orphans, children left without parental care); * Treatment with antibiotics during the last month; * Patients with subcutaneous emphysema, with damaged skin on the surface of the chest, with drainage in the pleural space, patients undergoing mechanical ventilation; * Presence of other known chronic lung conditions such as asthma, COPD, tuberculosis, cystic fibrosis or bronchiectasis; * Mental illness, other known acute diseases or known chronic decompensated diseases, such as a known active malignancy or severe heart failure. * Other known ongoing infection.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of identifying LRTI by abnormal lung sounds | 16.11.2021- 30.11.2021 | Accuracy of differentiation between ULRTI and LRTI by abnormal lung sounds detected with LungPass device |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of identifying LRTI by abnormal lung sounds in subgroups with COVID-19 and non-COVID-19 LRTI | 16.11.2021- 30.11.2021 | Accuracy of differentiation between ULRTI and LRTI by abnormal lung sounds detected with LungPass device in subgroups with COVID-19 and non-COVID-19 LRTI |
| Lung sounds and clinical signs of LRTI correlation in patients with LRTI | 16.11.2021- 30.11.2021 | Correlation between presence of pathological pulmonary sounds detected with LungPass device and presence of clinical signs of LRTI (clinical parameters/radiology results) in patients with LRTI |
Other
| Measure | Time frame | Description |
|---|---|---|
| Accuracy of LRTI detection by LungPass App output | 16.11.2021- 30.11.2021 | Accuracy of of identifying LRTI by LungPass App output which based on abnormal lung sounds detected with LungPass device together with symptoms collected using a questionnaire in the LungPass app\*. \* Final LungPass App output is possible patient condition (acute respiratory infection, acute bronchitis, pneumonia, etc) |
| Accuracy of bacterial LRTI detection by abnormal lung sounds using procalcitonin level as Gold Standard | 16.11.2021- 30.11.2021 | Accuracy of identifying bacterial LRTI by abnormal lung sounds detected with LungPass device using procalcitonin level as Gold Standard |
Countries
Belarus
Outcome results
None listed