Kitonsa Peter J, Kikaire Bernard, Wambi Peter, Nalutaaya Annet, Nakafeero Jascent, Nanyonga Gertrude, Kiconco Emma, Atwiine Deus, Castro Robert, Oumo Ernest A, Aanyu Hellen T, Mudiope Mary N, Mupere Ezekiel, Sekadde Moorine P, Mohanty Swomitra, Cattamanchi Adithya, Wobudeya Eric, Jaganath Devan
Uganda Tuberculosis Implementation Research Consortium (U-TIRC), Walimu, Kampala, Uganda.
Department of Pediatrics and Child Health, College of Health Sciences, Makerere University, Kampala, Uganda.
PLOS Glob Public Health. 2025 Apr 7;5(4):e0004026. doi: 10.1371/journal.pgph.0004026. eCollection 2025.
Diagnosing childhood pulmonary tuberculosis (TB) is a challenge. This led the Uganda National Tuberculosis and Leprosy Program (NTLP) to develop a clinical treatment decision algorithm (TDA) for children. However, there is limited data on its accuracy, and how it compares to new World Health Organization (WHO) TB TDAs for children. This study aimed to evaluate and compare the accuracy of the 2017 Uganda NTLP diagnostic algorithm with the 2022 WHO TDAs for TB among children. We analyzed four years of clinical data from children <15 years old in Kampala, Uganda. Children were classified as per National Institutes of Health (NIH) consensus definitions (Confirmed, Unconfirmed or Unlikely TB). We applied the 2017 Uganda NTLP and 2022 WHO algorithms (A with chest x-ray [CXR], B without CXR) to make a decision to treat for TB or not, and calculated the sensitivity, specificity and predictive values in reference to Confirmed vs. Unlikely TB, as well as a microbiological and composite reference standard. Of the 699 children included in this analysis, 64% (451/699) were under 5 years, 53% (373/669) were male, 12% (85/699) were Xpert Ultra positive, 11% (74/669) were HIV positive and 6% had severe acute malnutrition (SAM). The Uganda NTLP algorithm had a sensitivity of 97.9% (95% CI: 96.4-99.4) and specificity of 25.9% (95% CI: 21.2-30.7). If CXR was considered unavailable, sensitivity was 97.9% (95% CI: 96.4-99.4) and specificity 28.1% (95% CI: 23.2-33.0). In comparison, WHO TDAs had similar sensitivity to the Uganda NTLP, but algorithm A was more specific (32.2%, 95% CI: 26.9-37.5) and algorithm B was less specific (15.4%, 95% CI: 11.3-19.5). The WHO TDAs had better specificity than the NTLP algorithm with CXR, and worse specificity without CXR. Further optimization of the algorithms is needed to improve specificity and reduce over-treatment of TB in children.
诊断儿童肺结核是一项挑战。这促使乌干达国家结核病和麻风病防治项目（NTLP）为儿童制定了一种临床治疗决策算法（TDA）。然而，关于其准确性以及与世界卫生组织（WHO）新的儿童结核病TDA相比的数据有限。本研究旨在评估并比较2017年乌干达NTLP诊断算法与2022年WHO儿童结核病TDA的准确性。我们分析了乌干达坎帕拉15岁以下儿童的四年临床数据。儿童按照美国国立卫生研究院（NIH）的共识定义进行分类（确诊、未确诊或疑似结核病）。我们应用2017年乌干达NTLP算法和2022年WHO算法（A有胸部X光[CXR]，B无CXR）来决定是否进行结核病治疗，并参照确诊与疑似结核病以及微生物学和综合参考标准计算敏感性、特异性和预测值。在纳入本次分析的699名儿童中，64%（451/699）年龄在5岁以下，53%（373/669）为男性，12%（85/699）Xpert Ultra检测呈阳性，11%（74/669）HIV检测呈阳性，6%患有重度急性营养不良（SAM）。乌干达NTLP算法的敏感性为97.9%（95%CI：96.4 - 99.4），特异性为25.9%（95%CI：21.2 - 30.7）。如果认为无法进行CXR检查，敏感性为97.9%（95%CI：96.4 - 99.4），特异性为28.1%（95%CI：23.2 - 33.0）。相比之下，WHO TDA与乌干达NTLP的敏感性相似，但算法A更具特异性（32.2%，95%CI：26.9 - 37.5），算法B特异性较低（15.4%，95%CI：11.3 - 19.5）。WHO TDA在有CXR时比NTLP算法具有更好的特异性，在无CXR时特异性更差。需要对算法进行进一步优化以提高特异性并减少儿童结核病的过度治疗。
