Background: Acute respiratory infections (ARIs), primarily pneumonia, are the leading infectious cause of under-5 mortality worldwide. Manually counting respiratory rate (RR) for 60 seconds using an ARI timer is commonly practiced by community health workers to detect fast breathing, an important sign of pneumonia. However, correctly counting breaths manually and classifying the RR is challenging, often leading to inappropriate treatment. A potential solution is to introduce RR counters, which count and classify RR automatically. Objective: This study aims to determine how the RR count of an Automated Respiratory Infection Diagnostic Aid (ARIDA) agrees with the count of an expert panel of pediatricians counting RR by reviewing a video of the child’s chest for 60 seconds (reference standard), for children aged younger than 5 years with cough and/or difficult breathing. Methods: A cross-sectional study aiming to enroll 290 children aged 0 to 59 months presenting to pediatric in- and outpatient departments at a teaching hospital in Addis Ababa, Ethiopia, was conducted. Enrollment occurred between April and May 2017. Once enrolled, children participated in at least one of three types of RR evaluations: (1) agreement—measure the RR count of an ARIDA in comparison with the reference standard, (2) consistency—measure the agreement between two ARIDA devices strapped to one child, and (3) RR fluctuation—measure RR count variability over time after ARIDA attachment as measured by a manual count. The agreement and consistency of expert clinicians (ECs) counting RR for the same child with the Mark 2 ARI timer for 60 seconds was also measured in comparison with the reference standard. Results: Primary outcomes were (1) mean difference between the ARIDA and reference standard RR count (agreement) and (2) mean difference between RR counts obtained by two ARIDA devices started simultaneously (consistency). Conclusions: Study strengths included the design allowing for comparison between both ARIDA and the EC with the reference standard RR count. A limitation is that exactly the same set of breaths were not compared between ARIDA and the reference standard since ARIDA can take longer than 60 seconds to count RR. Also, manual RR counting, even when aided by a video of the child’s chest movements, is subject to human error and can result in low interrater reliability. Further work is needed to reach global consensus on the most appropriate reference standard and an acceptable level of agreement to provide ministries of health with evidence to make an informed decision on whether to scale up new automated RR counters.
This study aims to understand whether an ARIDA RR count agrees with an expert panel of pediatricians counting RR by reviewing a video of the child’s chest for 60 seconds (reference standard) for children aged younger than 5 years with cough and/or difficult breathing. The primary objective of this study is to determine the performance of an ARIDA, as defined by agreement and consistency, in children aged younger than 5 years with cough and/or difficulty breathing. The secondary objective is to determine the performance of expert clinicians (ECs) counting RR, as defined by agreement and consistency, in children aged younger than 5 years with cough and/or difficulty breathing. The third objective is to measure RR fluctuation over time after ARIDA device attachment in normal breathing children aged 2 to 59 months. The study is a cross-sectional study comprising three types of RR evaluations: agreement, consistency, and RR fluctuation over time. The study was conducted in the pediatric in- and outpatient departments at Saint Paul’s Hospital and Millennium Medical College in Addis Ababa, Ethiopia. This hospital was selected based on the high incidence of pneumonia in outpatient and inpatient departments, interest and willingness of hospital managers to host the study, availability of Integrated Management of Neonatal and Child Illness (IMNCI)-trained [14] expert clinicians (ECs), and availability of a suitable study room, reliable electricity supply, and access to treatment including amoxicillin and oxygen. Ethical approval was obtained from the Armauer Hansen Research Institute/ALERT Ethics Review Committee (a biomedical research institute in Ethiopia) on March 7, 2017 (ref. PO02/17) and favorable ethical opinion received by the Liverpool School of Tropical Medicine Ethics Committee. All participants consented to the study by reading and signing the information and consent form. All children attending in- and outpatient departments at Saint Paul’s Hospital and Millennium Medical College in Addis Ababa between April 5 and May 22, 2017, were potential participants in the study and were systematically screened for eligibility. Children aged 0 to <2 months were excluded from the consistency evaluation due to the anticipated difficulty in attaching two devices at once to a small child. Children aged 0 to <2 months and those with fast breathing were excluded from the fluctuation evaluation due to anticipated difficulty in measuring RR in this group for an extended period of time and also to isolate the effect of the ChARM attachment on RR from other causes of RR fluctuation. All other children aged younger than 5 years who were accompanied by a caregiver aged 18 years and older, not too agitated to be assessed by a research nurse, who did not present with general danger signs or IMNCI referral signs or device manufacturer safety exclusion criteria (wearing supportive device at area of chest/belly, skin not intact in chest/belly, born before 37 weeks of gestation [<2 months only]), were not an inpatient being managed by barrier nursing (such as severe burns, child with neutropenia, severe infectious diseases), and were not advised against research procedures by the supervising clinician were eligible to participate in the study. General danger signs for newborns (±2 bpm), a third VEP member reviewed the video and if two out of three counts agreed (≤±2 bpm), the mean of the two closest RR counts was used. If all three VEP members disagreed (>±2 bpm), the video was sent for review to a fourth VEP member. If the fourth VEP member’s count agreed (≤±2 bpm) with any of the first three VEP members’ counts, the mean of the two closest counts was used. If all four panel members disagreed (>±2 bpm), the data from this evaluation were excluded from the agreement analysis. The primary outcome on which sample size was based was the agreement between the ARIDA and VEP RR counts. As per Bland-Altman [17], we conducted a precision-based sample size calculation based on the confidence interval for the 95% limits of agreement. The formula estimates the required number of children per age group (n) based on the desired width of the confidence interval. Using normal approximation and allowing a confidence interval of ±0.5 standard deviations of the difference between the two devices, a sample size of 46 children per age group was required for the agreement and consistency evaluations, adjusted to 52 per group for failure to get a reference standard count. For the RR fluctuation evaluation, a sample size of 30 children was used. Data analysis for all three RR evaluations was conducted in Stata 13 (StataCorp LLC) and Excel (Microsoft Corp). First, the number of children screened, eligible, consented, and enrolled in each type of evaluation was described. Baseline characteristics (age and sex) by screening breathing status (normal/fast) for those enrolled were described. All full-length source videos were reviewed for quality assurance purposes, and descriptive information on the video quality was recorded, including those where all four VEP members disagreed on the RR count. For the ARIDA and EC agreement and consistency evaluations, mean difference, root mean square difference, absolute mean difference, proportion of RR counts ±2 bpm from the reference standard, and positive and negative percentage agreement with 95% confidence intervals were calculated in Stata 13 by age group, and Bland-Altman plots with limits of agreement and 95% confidence intervals by age group and breathing status were created. Percentage of unsuccessful attempts and failures (defined by three unsuccessful attempts) and mean time to get an ARIDA RR count were calculated. A per-protocol analysis was used whereby children were excluded from the analysis if an RR could not be obtained simultaneously by the ARIDA and by the EC, with a VEP RR reading where at least two of the panel members were within ±2 bpm of each other. For the RR fluctuation evaluation, mean difference in the RR count between baseline and 1 minute, 1 and 3 minutes, and 3 and 5 minutes were calculated. The proportion of children with fast or normal RR classification at baseline and the change between RR classifications over time were analyzed. Malaria Consortium and UNICEF (Supply Division and Ethiopia Country Office) conducted quality assurance visits every 2 weeks to the research site during data collection. All data collected from the screening and RR evaluations were checked and verified by the data manager daily. A sample of three videos was sent weekly to an independent study advisor for RR evaluation using WHO IMCI guidelines [3] and to Malaria Consortium HQ for quality assurance. The project had an 11-person Advisory Committee made up of experts on maternal and child health who provided technical oversight and reviewed the study protocol.
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