Abstract
IntroductionThe insufficient understanding and misdiagnosis of clinically diagnosed pulmonary tuberculosis (PTB) without an aetiological evidence is a major problem in the diagnosis of tuberculosis (TB). This study aims to confirm the value of Long non-coding RNA (lncRNA) n344917 in the diagnosis of PTB and construct a rapid, accurate, and universal prediction model.MethodsA total of 536 patients were prospectively and consecutively recruited, including clinically diagnosed PTB, PTB with an aetiological evidence and non-TB disease controls, who were admitted to West China hospital from Dec 2014 to Dec 2017. The expression levels of lncRNA n344917 of all patients were analyzed using reverse transcriptase quantitative real-time PCR. Then, the laboratory findings, electronic health record (EHR) information and expression levels of n344917 were used to construct a prediction model through the Least Absolute Shrinkage and Selection Operator algorithm and multivariate logistic regression.ResultsThe factors of n344917, age, CT calcification, cough, TBIGRA, low-grade fever and weight loss were included in the prediction model. It had good discrimination (area under the curve = 0.88, cutoff = 0.657, sensitivity = 88.98%, specificity = 86.43%, positive predictive value = 85.61%, and negative predictive value = 89.63%), consistency and clinical availability. It also showed a good replicability in the validation cohort. Finally, it was encapsulated as an open-source and free web-based application for clinical use and is available online at https://ziruinptb.shinyapps.io/shiny/.ConclusionCombining the novel potential molecular biomarker n344917, laboratory and EHR variables, this web-based prediction model could serve as a user-friendly, accurate platform to improve the clinical diagnosis of PTB.
Highlights
The insufficient understanding and misdiagnosis of clinically diagnosed pulmonary tuberculosis (PTB) without an aetiological evidence is a major problem in the diagnosis of tuberculosis (TB)
Two ways are used for PTB detection: detection of Mycobacterium tuberculosis (MTB) itself or specific biomarkers of the host immune response (Lyu et al, 2021)
Acid-fast bacilli (AFB) in sputum smear microscopy and the cultivation of MTB complex bacteria are still the gold standard, but they suffer from low sensitivity and consume considerable time (Kohlmorgen et al, 2017; Yang et al, 2020)
Summary
The insufficient understanding and misdiagnosis of clinically diagnosed pulmonary tuberculosis (PTB) without an aetiological evidence is a major problem in the diagnosis of tuberculosis (TB). Rapid and accurate diagnosis of PTB is a crucial element in the World Health Organization (WHO)’s End TB Strategy (Uplekar et al, 2015). The detection of MTB DNA using Gene Xpert or polymerase chain reaction (PCR) can improve the sensitivity and provide quicker results than cultivation to a certain extent, nearly half of PTB patients were clinically diagnosed by PTB only by manifestations, radiographic imaging and laboratory examination without an aetiological evidence, especially in lowand middle-income countries with constrained resources and a high PTB prevalence (Alavi-Naini et al, 2012; Gao, 2018; Ahmad et al, 2019)
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