Evidence map›Paper›PMID 40278779›Full record

ArticleTropical medicine and infectious disease2025

Treatment-Decision Algorithm of Child TB: Evaluation of WHO Algorithm and Development of Indonesia Algorithm.

Rina Triasih, Finny Fitry Yani, Diah Asri Wulandari, Betty Weri Yolanda Nababan, Muhammad Buston Ardiyamustaqim, Fransiska Meyanti, Sang Ayu Kompiyang Indriyani, Tiffany Tiara Pakasi, Ery Olivianto

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Article in Tropical medicine and infectious disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Rina TriasihDepartment of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
Finny Fitry YaniDepartment of Child Health, Faculty of Medicine, Universitas Andalas, Padang 25175, Indonesia.
Diah Asri WulandariDepartment of Child Health, Faculty of Medicine, Universitas Padjajaran, Bandung 40161, Indonesia.
Betty Weri Yolanda NababanCentre for Tropical Medicine, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
Muhammad Buston ArdiyamustaqimDepartment of Child Health, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada/Dr. Sardjito Hospital, Yogyakarta 55281, Indonesia.
Fransiska MeyantiCV Data Narya Amerta Semesta, Jakarta 13330, Indonesia.
Sang Ayu Kompiyang IndriyaniDepartment of Child Health, Faculty of Medicine, University of Mataram, Mataram 83115, Indonesia.ORCID 0000-0002-9779-5908
Tiffany Tiara PakasiNational Tuberculosis Program, Ministry of Health, Jakarta 12950, Indonesia.
Ery OliviantoDepartment of Child Health, Faculty of Medicine, Universitas Brawijaya, Malang 65145, Indonesia.ORCID 0000-0002-2532-3143

Funding

World Health Organization - Indonesia 203028579
6 · The paper itself

Abstract

Clinical algorithms for child tuberculosis (TB) are a valuable guide for healthcare workers to initiate treatment. We evaluated the agreement of pediatric TB diagnosis using the current Indonesia diagnostic algorithms with the 2022 WHO treatment decision algorithm and developed a new Indonesia algorithm for child TB based upon our findings and expert opinion. We conducted a retrospective study at 10 hospitals in Indonesia, involving children (0-10 years), who were evaluated for TB diagnosis in 2022. A panel of child TB experts used participants' records to make a diagnosis using the 2022 WHO algorithm and the 2016 Indonesian algorithm. We assessed agreement between the diagnosis made by the attending doctor and those determined by the expert panel. A new Indonesia guideline was developed based on the findings and consensus of various stakeholders. Of 523 eligible children, 371 (70.9%) were diagnosed with TB by the attending doctors, 295 (56.4%) by the WHO algorithm, and 246 (47%) by the Indonesia algorithm. The Cohen's Kappa of TB diagnosis was: attending doctor vs. WHO algorithm (0.27), attending doctor vs. Indonesia algorithm (0.45), and WHO algorithm vs. Indonesia algorithm (0.42). A review of both algorithms revealed challenges for implementation. An algorithmic approach for child TB diagnosis may not be universally applicable or implementable due to variable access to diagnostic tests and the wide variety of clinical presentations.

Indexed as

algorithmpediatrictreatment decisiontuberculosis

Identifiers

PMID40278779
PMCPMC12031215

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