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Respiratory rate counters in paediatric pneumonia diagnosis

Population Size

Not reported
Population Size statistic card

Years

2021

Years statistic card

Associated BioSamples

None/not available

Associated BioSamples statistic card

Geographic coverage

Bangladesh

Geographic coverage statistic card

Lead time

Other

Lead time statistic card

Summary

The study aims to develop a process of videography of child’s chest movements and interpretation of respiratory rate from video recording by a video expert panel to evaluate automated respiratory rate counters to diagnose paediatric pneumonia.

Documentation

Fast breathing is the most common sign of childhood pneumonia. It is identified by observing the child’s chest and counting respiratory rate (RR). However, manual count of RR is challenging for the health workers often resulting in misdiagnosis of pneumonia. The availability of novel RR counters (e.g., ChARM, Masimo Rad-G, uPM60) can support health workers by detecting fast breathing automatically. However, the absence of an appropriate reference standard to evaluate the performance of these devices is a challenge. The commonly used reference standard is manual RR counts by a human expert which might be biased. If good quality videos could be captured and RR interpretation from these videos could be systematically conducted, it could be an ideal and non-biased reference standard. This study is designed to develop a video expert panel (VEP) as a reference standard to evaluate automated RR counters to identify pneumonia in children. The study will assess the performance of ChARM device in terms of accuracy of counting RR, duration to take the count and any potential influence of the device on RR counts. The study will record the child’s chest movements, and the recorded videos will be interpreted by the VEP. A mechanism to interpret RR from the recorded videos and maintain ongoing quality control will be established. This study will be carried out in Bangladesh in two phases. Eligible children will be 0-2 months old presenting with any illness and 2-59 months old presenting with suspected pneumonia (cough and/or breathing difficulty). In Phase-I, we will develop a process of videography of the child’s chest movements and interpretation of RR by a VEP. We will establish the process of capturing good quality videos, making a set of reference videos and will train and standardise the VEP members using those reference videos. We will record videos from a hospital in Dhaka. We will take videos of child’s chest movements both with and without using of ChARM. In Phase-II, we will conduct a cross-sectional study in rural Sylhet for evaluation of the performance of ChARM device. We will enrol children presenting at first level health facilities and a sub-district hospital. This study will provide evidence to establish the videography of child’s chest movements and its interpretation by a VEP as an appropriate and non-biased reference standard to evaluate the performance of novel RR counters. For further information please visit https://www.ed.ac.uk/usher/respire/phd-studentships/ahad-mahmud-khan.

Dataset type

Health and disease

Dataset sub-type

Not applicable

Keywords

Observations

Observed Node

Disambiguating Description

Measured Value

Measured Property

Observation Date

Findings

1

Count

01 Dec 2021

Provenance

Purpose of dataset collection

Study

Source of data extraction

Paper-based

Collection source setting

Primary care - Clinic, Secondary care - Outpatients, Secondary care - In-patients

Image contrast

Not stated

Biological sample availability

None/not available

Details

Publishing frequency

Static

Version

1.0.0

Modified

08/10/2024

Citation Requirements

RESPIRE Collaboration

Coverage

Start date

01/12/2021

Time lag

Not applicable

Geographic coverage

Bangladesh

Maximum age range

5

Accessibility

Language

en

Controlled vocabulary

LOCAL

Format

csv, mp4

Data Access Request

Dataset pipeline status

Not available

Time to dataset access

Other

Access request cost

None

Access method category

TRE/SDE

Access service description

Datashare

Jurisdiction

BD, GB-GBN

Data Controller

University of Edinburgh

Data Processor

Projahnmo Research Foundation

Dataset Types: Health and disease


Collection Sources: Primary care - Clinic, Secondary care - Outpatients, Secondary care - In-patients

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