The LalelaLung Study: Digital Stethoscope Clinical Evaluation

NCT07631377 | Not Yet Recruiting Phase 4

• 2 other identifiers: IRB00553596R33HD109804
• Study Type: interventional
• Target: 350
• Locations: 0 countries
• Sites: N/A

Brief Summary

Pneumonia is the leading infectious cause of death in children under five years of age worldwide, and most of these deaths occur in low- and middle-income countries. In these settings, frontline health workers diagnose pneumonia using the World Health Organization's Integrated Management of Childhood Illness (IMCI) guidelines, which rely mainly on counting how fast a child is breathing and checking for chest indrawing. This approach has saved many lives, but it is not very specific. As a result, many children who actually have self-limiting viral illnesses that do not require antibiotics are nonetheless treated with antibiotics, contributing to the global rise of antimicrobial resistance. New digital stethoscopes paired with artificial intelligence (AI) can record a child's lung sounds and automatically detect abnormal sounds such as crackles and wheezes with accuracy comparable to physicians. The LaLeLa Lung Study will evaluate whether adding an AI-enabled digital stethoscope to standard IMCI assessment improves the accuracy of pneumonia diagnosis among children aged 2 to 59 months who present with cough and/or difficult breathing at a primary care clinic in Cape Town, South Africa. The main component (Objective 1) is a randomized, triple-blinded diagnostic accuracy study that will enroll 350 children, randomly assigned in a 1:1 ratio to either IMCI care enhanced by the AI-enabled digital stethoscope or standard IMCI care. An independent panel of physicians, blinded to the AI results and to study-arm assignment, will review each case and serve as the reference standard for determining whether pneumonia was truly present. The investigators hypothesize that IMCI enhanced by the AI stethoscope will diagnose pneumonia more accurately, and target antibiotics more appropriately, than standard IMCI alone. Nested sub-studies will additionally evaluate a second AI stethoscope for tuberculosis detection, a wearable lung-sound and respiratory-rate patch, an automated respiratory-rate monitor, and a smartphone-connected pulse oximeter. A separate component (Objective 2) is a mixed-methods implementation study at a second clinic that will assess how easily health workers can use these devices, how acceptable the devices are to health workers and caregivers, and how well the devices fit into routine clinic workflows. Throughout the study, all AI-generated results will remain concealed from clinic staff, study clinicians, and caregivers, so the AI-generated results will not influence the care any child receives. All children continue to receive standard IMCI care. Findings will help inform whether AI-enabled digital auscultation should be integrated into childhood pneumonia care in South Africa and similar low-resource settings, with the goal of improving diagnosis, strengthening antibiotic stewardship, and reducing antimicrobial resistance and child mortality.

Conditions

Pneumonia; Respiratory Tract Infections; Bronchiolitis; Respiratory Sounds; Antibiotic Resistant Strain; Tuberculosis, Pulmonary

Outcome Measures

Primary Outcomes (1)

• Proportion of children correctly classified with Pneumonia (Diagnostic accuracy of pneumonia diagnosis - IMCI enhanced by AI-enabled digital stethoscope vs. standard IMCI)

  Accuracy of pneumonia classification (pneumonia: yes/no), defined as the proportion of children correctly classified relative to the blinded independent physician reference-panel diagnosis, summarized by sensitivity, specificity, and overall accuracy. Compares IMCI enhanced by the StethoMe AI-enabled digital stethoscope (elevated respiratory rate plus crackles ± wheeze) with standard IMCI care; between-arm differences assessed by tests of proportions and ROC area under the curve. Index clinic visit (Day 1); reference-standard diagnosis assigned retrospectively, incorporating 7-day follow-up.

  Index clinic visit (Day 1); 7-day follow-up

Secondary Outcomes (12)

• Accuracy, sensitivity, specificity, and positive/negative predictive values (Diagnostic accuracy relative to routine health care worker (HCW) diagnosis)

  Day 1, 7-day follow-up

• Proportion of correctly indicated antibiotic decisions (Accuracy of antibiotic decision-making)

  Day 1; 7-day follow-up

• Accuracy of pneumonia diagnosis (Expanded lung-sound classification accuracy)

  Day 1; 7-day follow-up

• Agreement between AI lung-sound classification and physician auscultation

  Day 1

• Proportion of digital recordings successfully obtained and interpretable (Feasibility of digital auscultation)

  Day 1

Other Outcomes (4)

• Correct chest positions - fidelity of digital devices in routine care (Objective 2)

  Up to 6 weeks

• Percentage of successful recordings - Technical Performance (Objective 2)

  Up to 6 weeks

• Time per consultation recording -Workflow Integration (Objective 2)

  Up to 6 weeks

Study Arms (2)

AI-enhanced IMCI

EXPERIMENTAL

Participants randomized to this arm undergo Integrated Management of Childhood Illness (IMCI) assessment enhanced by the StethoMe AI-enabled digital stethoscope. After the routine health worker IMCI evaluation, a study clinician performs a structured IMCI-based respiratory assessment and obtains digital lung-sound recordings at four standardized chest positions with the StethoMe device. The embedded algorithm computes respiratory rate and classifies abnormal lung sounds (crackles, wheezes) in real time. AI outputs remain concealed from health workers, study staff, and caregivers and do not influence clinical management. The intervention is the StethoMe AI-enabled digital stethoscope, which is applied during a single clinic encounter.

Device: StethoMe AI-enabled digital stethoscope system

Standard IMCI

ACTIVE COMPARATOR

Participants randomized to this arm receive standard IMCI assessment per WHO guidelines, in which pneumonia is classified using respiratory rate and chest indrawing without AI-enabled digital auscultation. Routine clinic health workers perform the IMCI evaluation and make all management decisions, including antibiotic prescription or referral. The intervention is the standard IMCI assessment, which is delivered during a single clinic encounter.

Diagnostic Test: Standard IMCI assessment

Interventions

StethoMe AI-enabled digital stethoscope system DEVICE

A CE-marked (EU Class IIa) wireless electronic stethoscope paired with a mobile application and an on-device deep convolutional recurrent neural network trained on more than 25,000 labeled lung-sound recordings. The device captures high-fidelity respiratory sounds, automatically computes respiratory rate, and classifies sounds in real time as normal or abnormal (fine/coarse crackles, high-/low-pitched wheezes), with ambient-noise detection to flag low-quality signals. Recordings are obtained at four standardized chest positions; the algorithm's classifications are generated automatically but the output display is permanently disabled for field users so results stay concealed and do not inform care.

Also known as: StethoMe, AI-enhanced IMCI

AI-enhanced IMCI

Standard IMCI assessment DIAGNOSTIC_TEST

The World Health Organization's standardized clinical algorithm for children with cough and/or difficult breathing, in which pneumonia is classified on the basis of age-specific fast breathing and/or chest indrawing in the absence of general danger signs, without digital or AI-assisted auscultation. Conducted by routine clinic health workers using standard equipment, it represents the current WHO-recommended standard of care for outpatient pneumonia assessment.

Also known as: WHO Integrated Management of Childhood Illness, IMCI

Standard IMCI

Eligibility Criteria

• Age: 2 Months - 59 Months
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17)

You may qualify if:

• Age 2 to 59 months at the time of screening
• Presence of cough and/or difficulty breathing
• No WHO-defined emergency/danger signs (e.g., grunting, cyanosis, apnea, convulsions, or altered level of consciousness)
• A legal caregiver is present, able to understand the study information, and willing to provide written informed consent
• Caregiver is willing and able to provide contact information (e.g., mobile phone number) to allow 7-day follow-up after the clinic visit

You may not qualify if:

• Presence of WHO-defined emergency signs requiring immediate referral or hospital admission (grunting, cyanosis, apnea, uncompensated shock, convulsions, diarrhea with severe dehydration, or altered level of consciousness)
• Critical illness or clinical instability judged by the screening clinician or study physician to require urgent medical attention
• Age outside the target range (younger than 2 months or older than 59 months)
• Previous enrollment in the study
• Refusal or withdrawal of informed consent by the legal caregiver at any time prior to randomization

Sponsors & Collaborators

• University of Stellenbosch: collaborator
• Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD): collaborator
• Johns Hopkins University: lead

Related Publications (34)

• Perin J, Mulick A, Yeung D, Villavicencio F, Lopez G, Strong KL, Prieto-Merino D, Cousens S, Black RE, Liu L. Global, regional, and national causes of under-5 mortality in 2000-19: an updated systematic analysis with implications for the Sustainable Development Goals. Lancet Child Adolesc Health. 2022 Feb;6(2):106-115. doi: 10.1016/S2352-4642(21)00311-4. Epub 2021 Nov 17.

  PMID: 34800370 BACKGROUND

• WHO. Integrated Management of Childhood Illness: Chart Booklet. 2014. https://apps.who.int/iris/bitstream/handle/10665/104772/9789241506823_Chartbook_eng.pdf

  BACKGROUND

• Sazawal S, Black RE; Pneumonia Case Management Trials Group. Effect of pneumonia case management on mortality in neonates, infants, and preschool children: a meta-analysis of community-based trials. Lancet Infect Dis. 2003 Sep;3(9):547-56. doi: 10.1016/s1473-3099(03)00737-0.

  PMID: 12954560 BACKGROUND

• Wahl B, O'Brien KL, Greenbaum A, Majumder A, Liu L, Chu Y, Luksic I, Nair H, McAllister DA, Campbell H, Rudan I, Black R, Knoll MD. Burden of Streptococcus pneumoniae and Haemophilus influenzae type b disease in children in the era of conjugate vaccines: global, regional, and national estimates for 2000-15. Lancet Glob Health. 2018 Jul;6(7):e744-e757. doi: 10.1016/S2214-109X(18)30247-X.

  PMID: 29903376 BACKGROUND

• Selwyn BJ. The epidemiology of acute respiratory tract infection in young children: comparison of findings from several developing countries. Coordinated Data Group of BOSTID Researchers. Rev Infect Dis. 1990 Nov-Dec;12 Suppl 8:S870-88. doi: 10.1093/clinids/12.supplement_s870.

  PMID: 2270410 BACKGROUND

• Pneumonia Etiology Research for Child Health (PERCH) Study Group. Causes of severe pneumonia requiring hospital admission in children without HIV infection from Africa and Asia: the PERCH multi-country case-control study. Lancet. 2019 Aug 31;394(10200):757-779. doi: 10.1016/S0140-6736(19)30721-4. Epub 2019 Jun 27.

  PMID: 31257127 BACKGROUND

• Ginsburg AS, Mvalo T, Nkwopara E, McCollum ED, Ndamala CB, Schmicker R, Phiri A, Lufesi N, Izadnegahdar R, May S. Placebo vs Amoxicillin for Nonsevere Fast-Breathing Pneumonia in Malawian Children Aged 2 to 59 Months: A Double-blind, Randomized Clinical Noninferiority Trial. JAMA Pediatr. 2019 Jan 1;173(1):21-28. doi: 10.1001/jamapediatrics.2018.3407.

  PMID: 30419120 BACKGROUND

• Jehan F, Nisar I, Kerai S, Balouch B, Brown N, Rahman N, Rizvi A, Shafiq Y, Zaidi AKM. Randomized Trial of Amoxicillin for Pneumonia in Pakistan. N Engl J Med. 2020 Jul 2;383(1):24-34. doi: 10.1056/NEJMoa1911998.

  PMID: 32609980 BACKGROUND

• Allwell-Brown G, Hussain-Alkhateeb L, Sewe MO, Kitutu FE, Stromdahl S, Martensson A, Johansson EW. Determinants of trends in reported antibiotic use among sick children under five years of age across low-income and middle-income countries in 2005-17: A systematic analysis of user characteristics based on 132 national surveys from 73 countries. Int J Infect Dis. 2021 Jul;108:473-482. doi: 10.1016/j.ijid.2021.05.058. Epub 2021 May 28.

  PMID: 34058373 BACKGROUND

• Allwell-Brown G, Hussain-Alkhateeb L, Kitutu FE, Stromdahl S, Martensson A, Johansson EW. Trends in reported antibiotic use among children under 5 years of age with fever, diarrhoea, or cough with fast or difficult breathing across low-income and middle-income countries in 2005-17: a systematic analysis of 132 national surveys from 73 countries. Lancet Glob Health. 2020 Jun;8(6):e799-e807. doi: 10.1016/S2214-109X(20)30079-6.

  PMID: 32446345 BACKGROUND

• McCollum ED, Park DE, Watson NL, Buck WC, Bunthi C, Devendra A, Ebruke BE, Elhilali M, Emmanouilidou D, Garcia-Prats AJ, Githinji L, Hossain L, Madhi SA, Moore DP, Mulindwa J, Olson D, Awori JO, Vandepitte WP, Verwey C, West JE, Knoll MD, O'Brien KL, Feikin DR, Hammitt LL. Listening panel agreement and characteristics of lung sounds digitally recorded from children aged 1-59 months enrolled in the Pneumonia Etiology Research for Child Health (PERCH) case-control study. BMJ Open Respir Res. 2017 Jun 30;4(1):e000193. doi: 10.1136/bmjresp-2017-000193. eCollection 2017.

  PMID: 28883927 BACKGROUND

• Gurung A, Scrafford CG, Tielsch JM, Levine OS, Checkley W. Computerized lung sound analysis as diagnostic aid for the detection of abnormal lung sounds: a systematic review and meta-analysis. Respir Med. 2011 Sep;105(9):1396-403. doi: 10.1016/j.rmed.2011.05.007. Epub 2011 Jun 14.

  PMID: 21676606 BACKGROUND

• Bjornstad E, Preidis GA, Lufesi N, Olson D, Kamthunzi P, Hosseinipour MC, McCollum ED. Determining the quality of IMCI pneumonia care in Malawian children. Paediatr Int Child Health. 2014 Feb;34(1):29-36. doi: 10.1179/2046905513Y.0000000070. Epub 2013 Dec 6.

  PMID: 24091151 BACKGROUND

• United Nations General Assembly. Political declaration of the high-level meeting of the General Assembly on antimicrobial resistance (A/RES/71/3). 2016. https://undocs.org/A/RES/71/3

  BACKGROUND

• World Health Organization. Global action plan on antimicrobial resistance. Geneva: WHO; 2015. https://www.who.int/publications/i/item/9789241509763

  BACKGROUND

• Ahmed S, Nair H, Cunningham S, Baqui AH, McCollum ED. Evaluation of machine learning to detect adventitious lung sounds using digital auscultation to aid childhood pneumonia diagnosis. ISPPD-12; 2022 Jun 19-23; Toronto, Canada.

  BACKGROUND

• Hoekstra NE, Chagomerana MB, Smith ZH, Kala A, McLane I, Verwey C, Olson D, Buck WC, Mulindwa J, Gaudio A, Kapoor S, Schuh HB, Chiume M, Fitzgerald E, Elhilali M, Mvalo T, Hosseinipour M, McCollum ED. Performance of an artificial intelligence algorithm for interpreting lung sounds from children hospitalised with pneumonia in Malawi. J Glob Health. 2025 Sep 19;15:04264. doi: 10.7189/jogh.15.04264.

  PMID: 40968644 BACKGROUND

• McCollum ED, Park DE, Watson NL, Fancourt NSS, Focht C, Baggett HC, Brooks WA, Howie SRC, Kotloff KL, Levine OS, Madhi SA, Murdoch DR, Scott JAG, Thea DM, Awori JO, Chipeta J, Chuananon S, DeLuca AN, Driscoll AJ, Ebruke BE, Elhilali M, Emmanouilidou D, Githua LP, Higdon MM, Hossain L, Jahan Y, Karron RA, Kyalo J, Moore DP, Mulindwa JM, Naorat S, Prosperi C, Verwey C, West JE, Knoll MD, O'Brien KL, Feikin DR, Hammitt LL. Digital auscultation in PERCH: Associations with chest radiography and pneumonia mortality in children. Pediatr Pulmonol. 2020 Nov;55(11):3197-3208. doi: 10.1002/ppul.25046. Epub 2020 Sep 11.

  PMID: 32852888 BACKGROUND

• Kala A, Husain A, McCollum ED, Elhilali M. An objective measure of signal quality for pediatric lung auscultations. Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:772-775. doi: 10.1109/EMBC44109.2020.9176539.

  PMID: 33018100 BACKGROUND

• Graceffo S, Husain A, Ahmed S, McCollum ED, Elhilali M. Validation of Auscultation Technologies using Objective and Clinical Comparisons. Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:992-997. doi: 10.1109/EMBC44109.2020.9176456.

  PMID: 33018152 BACKGROUND

• Ahmed S, McCollum ED, Nair H, Cunningham S, Baqui AH. Community use of digital auscultation to improve diagnosis of childhood pneumonia in low-resource settings. Eur Respir J 2020;56(Suppl 64):4350.

  BACKGROUND

• Emmanouilidou D, McCollum ED, Park DE, Elhilali M. Adaptive Noise Suppression of Pediatric Lung Auscultations With Real Applications to Noisy Clinical Settings in Developing Countries. IEEE Trans Biomed Eng. 2015 Sep;62(9):2279-88. doi: 10.1109/TBME.2015.2422698. Epub 2015 Apr 13.

  PMID: 25879837 BACKGROUND

• McLane I, Emmanouilidou D, West JE, Elhilali M. Design and Comparative Performance of a Robust Lung Auscultation System for Noisy Clinical Settings. IEEE J Biomed Health Inform. 2021 Jul;25(7):2583-2594. doi: 10.1109/JBHI.2021.3056916. Epub 2021 Jul 27.

  PMID: 33534721 BACKGROUND

• West JE, McLane I, Emmanouilidou D, et al. Introducing feelix, a digital stethoscope incorporating active noise control and automatic detection of lung sound abnormalities. J Acoust Soc Am 2019;145(3):1923.

  BACKGROUND

• Park DE, Watson NL, Focht C, Feikin D, Hammitt LL, Brooks WA, Howie SRC, Kotloff KL, Levine OS, Madhi SA, Murdoch DR, O'Brien KL, Scott JAG, Thea DM, Amorninthapichet T, Awori J, Bunthi C, Ebruke B, Elhilali M, Higdon M, Hossain L, Jahan Y, Moore DP, Mulindwa J, Mwananyanda L, Naorat S, Prosperi C, Thamthitiwat S, Verwey C, Jablonski KA, Power MC, Young HA, Deloria Knoll M, McCollum ED. Digitally recorded and remotely classified lung auscultation compared with conventional stethoscope classifications among children aged 1-59 months enrolled in the Pneumonia Etiology Research for Child Health (PERCH) case-control study. BMJ Open Respir Res. 2022 May;9(1):e001144. doi: 10.1136/bmjresp-2021-001144.

  PMID: 35577452 BACKGROUND

• Joarder T, Tune SNBK, Islam AA, et al. End-user acceptability of a prototype digital stethoscope to diagnose childhood pneumonia - a qualitative exploration from Sylhet, Bangladesh. BMC Digit Health 2023;1.

  BACKGROUND

• Grzywalski T, Piecuch M, Szajek M, Breborowicz A, Hafke-Dys H, Kocinski J, Pastusiak A, Belluzzo R. Practical implementation of artificial intelligence algorithms in pulmonary auscultation examination. Eur J Pediatr. 2019 Jun;178(6):883-890. doi: 10.1007/s00431-019-03363-2. Epub 2019 Mar 29.

  PMID: 30927097 BACKGROUND

• Mazurek H, Emeryk A, Janeczek K, Derom E, Kuznar-Kaminska B, Grzywalski T, Biniakowski A, Szarzynski K, Pastusiak A, Kaminiarczyk-Pyzalka D, Botteldooren D, Hafke-Dys H, Kocinski J. AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations. J Cyst Fibros. 2025 Mar;24(2):390-397. doi: 10.1016/j.jcf.2025.02.011. Epub 2025 Feb 18.

  PMID: 39971691 BACKGROUND

• Emeryk A, Derom E, Janeczek K, Kuznar-Kaminska B, Zelent A, Lukaszyk M, Grzywalski T, Pastusiak A, Biniakowski A, Szarzynski K, Botteldooren D, Kocinski J, Hafke-Dys H. Home Monitoring of Asthma Exacerbations in Children and Adults With Use of an AI-Aided Stethoscope. Ann Fam Med. 2023 Nov-Dec;21(6):517-525. doi: 10.1370/afm.3039.

  PMID: 38012028 BACKGROUND

• Emmanouilidou D, McCollum ED, Park DE, Elhilali M. Computerized Lung Sound Screening for Pediatric Auscultation in Noisy Field Environments. IEEE Trans Biomed Eng. 2018 Jul;65(7):1564-1574. doi: 10.1109/TBME.2017.2717280. Epub 2017 Jun 19.

  PMID: 28641244 BACKGROUND

• Ahmed S, Mitra DK, Nair H, Cunningham S, Khan AM, Islam AA, McLane IM, Chowdhury NH, Begum N, Shahidullah M, Islam MS, Norrie J, Campbell H, Sheikh A, Baqui AH, McCollum ED. Digital auscultation as a novel childhood pneumonia diagnostic tool for community clinics in Sylhet, Bangladesh: protocol for a cross-sectional study. BMJ Open. 2022 Feb 9;12(2):e059630. doi: 10.1136/bmjopen-2021-059630.

  PMID: 35140164 BACKGROUND

• EMPIC Study Group. Innovative, enhanced community management of non-hypoxaemic chest-indrawing pneumonia in 2-59-month-old children: a cluster-randomised trial in Africa and Asia. BMJ Glob Health. 2022 Jan;7(1):e006405. doi: 10.1136/bmjgh-2021-006405.

  PMID: 34987033 BACKGROUND

• Enhanced Management of Pneumonia in Community (EMPIC) Study Group. Community case management of chest indrawing pneumonia in children aged 2 to 59 months by community health workers: study protocol for a multi-country cluster randomized open label non-inferiority trial. Int J Clin Trials. 2020 Apr-Jun;7(2):131-141. doi: 10.18203/2349-3259.ijct20201719.

  PMID: 32832583 BACKGROUND

• Damschroder LJ, Aron DC, Keith RE, Kirsh SR, Alexander JA, Lowery JC. Fostering implementation of health services research findings into practice: a consolidated framework for advancing implementation science. Implement Sci. 2009 Aug 7;4:50. doi: 10.1186/1748-5908-4-50.

  PMID: 19664226 BACKGROUND

MeSH Terms

Conditions

Pneumonia; Tuberculosis, Pulmonary; Respiratory Tract Infections; Bronchiolitis; Respiratory Sounds

Condition Hierarchy (Ancestors)

Infections; Lung Diseases; Respiratory Tract Diseases; Tuberculosis; Mycobacterium Infections; Actinomycetales Infections; Gram-Positive Bacterial Infections; Bacterial Infections; Bacterial Infections and Mycoses; Bronchitis; Bronchial Diseases; Lung Diseases, Obstructive; Signs and Symptoms, Respiratory; Signs and Symptoms; Pathological Conditions, Signs and Symptoms

Study Officials

• Eric McCollum, MD, MPH

  Johns Hopkins University

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Eric D McCollum, MD,MPH

CONTACT

410-955-2035; emccoll3@jhmi.edu

Sunaina Kapoor, MD,MPH

CONTACT

410-955-2035; skapoor@jhmi.edu

Study Design

• Study Type: interventional
• Phase: phase 4
• Allocation: RANDOMIZED
• Masking: QUADRUPLE
• Who Masked: PARTICIPANT, CARE PROVIDER, INVESTIGATOR, OUTCOMES ASSESSOR
• Masking Details: The trial is masked both to randomization-arm allocation and to the digital stethoscope's real-time AI classification outputs. Caregivers/participants and the routine clinic health care workers who make all clinical management decisions are masked to study-arm allocation. Study clinicians and research staff performing the digital recordings and assessments are masked to the device's AI outputs, which are permanently disabled in the field interface, and the independent physician reference panel that adjudicates the reference diagnosis is masked to study arm, AI outputs, and participant identifiers. Only the study statistician, who holds the randomization schedule, has access to allocation. Blinding integrity is maintained by using separate personnel for enrollment, assessment, and follow-up and by a weekly blinding-compliance checklist verified by the principal investigator.
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Model Details: Randomized, individually allocated, parallel-group diagnostic accuracy study. Eligible children aged 2-59 months are randomized 1:1 to standard IMCI assessment or to IMCI enhanced by the StethoMe AI-enabled digital stethoscope, with stratification by age group (\<1 year and ≥1 year) using a computer-generated sequence implemented in REDCap with allocation concealment. An independent, blinded physician reference panel provides the reference-standard pneumonia diagnosis. Three cross-sectional device-validation sub-studies (AI Diagnostics digital stethoscope, Perin Health Patch, and ChARM) are nested within subsets of enrolled participants and do not constitute additional randomized arms.

Study Record Dates

• First Submitted: June 1, 2026
• First Posted: June 8, 2026
• Study Start (Estimated): July 20, 2026
• Primary Completion (Estimated): January 31, 2028
• Study Completion (Estimated): June 30, 2028
• Last Updated: June 9, 2026

Record last verified: 2026-06

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP, ICF, ANALYTIC CODE
• Time Frame: Data will become available beginning 12 months after publication of the primary results and will remain available for at least 5 years thereafter (or for the retention period of the hosting repository).
• Access Criteria: Requests should be directed to the principal investigator. Requesting researchers must submit a written proposal with a scientifically sound objective and analysis plan, which will be reviewed by the study investigators and sponsor. Approved requestors must sign a data use/access agreement governing confidentiality, permitted uses, and prohibition of re-identification before any data are released; data use must be consistent with the participants' informed consent and the approving ethics committees.