Evidence map›Paper›PMID 39435459›Full record

ArticleInfection and drug resistance2024

Diagnostic Efficiency of the Blood-Based Cepheid 3-Gene Host Response Test and Urine-Based Lipoarabinomannan for Active Tuberculosis Case Detection at a General Hospital in China.

Zhongkang Ji, Sheng Bi, Bin Lu, Lin Zheng, Xiuyuan Jin, Shujuan Huang, Liangxiu Jiang, Yuping Wang, Cheng Ding, Kaijin Xu

Abstract read
In one paragraph

Article in Infection and drug resistance, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
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  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Zhongkang Ji *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Sheng Bi *State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Bin LuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Lin ZhengState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Xiuyuan JinState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Shujuan HuangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Liangxiu JiangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Yuping WangState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Cheng DingState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.
Kaijin XuState Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the diagnostic performance of the blood-based Cepheid 3-gene Host Response test (MTB-HR), urine-based Lipoarabinomannan (LAM), and a combination of MTB-HR and LAM (MTB-HR & LAM) for detecting active tuberculosis (ATB). Methods: All participants were recruited from the First Affiliated Hospital, Zhejiang University School of Medicine, between June 8, 2023 and September 13, 2023. Subsequently, the participants were classified into the ATB group or non-active tuberculosis (non-ATB) group based on microbiological evidence. MTB-HR and LAM tests were performed using fingerstick blood and urine samples from each participant, respectively. The diagnostic performance of the tests was evaluated based on the sensitivity, specificity, Youden index, and Kappa value. Pairwise comparisons of the areas under the receiver operating characteristic curves (AUROCs) between different tests were conducted using nonparametric methods. Results: A total of 297 participants were included. The MTB-HR test demonstrated diagnostic efficacy with a sensitivity of 77.37% (95% CI: 70.37-84.38) and a specificity of 85.63% (95% CI: 80.19-91.06). The LAM test demonstrated a high specificity of 97.50% (95% CI: 95.08-99.92), albeit with a lower sensitivity of 54.74% (95% CI: 46.41-63.082). The sensitivity and specificity of the MTB-HR & LAM were 83.21% (95% CI: 76.95-89.47) and 83.13% (95% CI: 77.32-88.93), respectively. Only MTB-HR & LAM exhibited higher values of area under the receiver operating characteristic curve than the LAM test (MTB-HR & LAM vs LAM: 0.83 vs 0.76, P=0.0031). Conclusion: In this study, although both non-sputum-based triage MTB-HR and LAM do not meet the WHO diagnostic target currently, they show possible values for triage and diagnosis in ATB. Compared to single MTB-HR or LAM test, the combined MTB-HR & LAM does not demonstrate advantages.

Indexed as

active tuberculosisAUROCdiagnosticLipoarabinomannanthree-gene host response

Identifiers

PMID39435459
PMCPMC11492898

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.