Evidence map›Paper›PMID 33816355›Full record

ArticleFrontiers in cellular and infection microbiology2021

Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting.

Jing Peng, Juan Song, Feng Wang, Peng Zuo, Yanjun Lu, Weiyong Liu, Lei Tian, Zhongju Chen, Yaowu Zhu, Xiong Wang and 8 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in cellular and infection microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.4field-weighted citation impact, top 37% of its field
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

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Use of big data on the social determinants of TB to find the "missing millions".The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease · 2022
    Article
  7. Combination of HLA-DR onFrontiers in immunology · 2021
    Article
  8. Article
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

18 authors at 4 institutions in 2 countries.

Jing PengDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Juan SongDepartment of Gastroenterology & Endocrinology, Wuhan No. 9 Hospital, Wuhan, China.
Feng WangDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Peng ZuoDepartment of Respiratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yanjun LuDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Weiyong LiuDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Lei TianDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Zhongju ChenDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yaowu ZhuDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiong WangDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Na ShenDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xu WangDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Shiji WuDepartment of Gastroenterology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Qin YuDepartment of Gastroenterology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Bruce A VallanceDepartment of Pediatrics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada.
Kevan JacobsonDepartment of Pediatrics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada.
Ziyong SunDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Hong Bing YuDepartment of Pediatrics, BC Children's Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada.
Huazhong University of Science and Technology · CNTongji Hospital · CNUniversity of British Columbia · CAWuhan No.9 Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting. Methods: 28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT. Results: Sputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB Conclusions: Concurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOT

Indexed as

Mycobacterium tuberculosisTuberculosis, PulmonaryAdultAlgorithmsBig DataChinaHumansLeukocytes, MononuclearRetrospective StudiesSensitivity and SpecificitySputumdiagnostic algorithmreal-world studysmear microscopyT-SPOT.TBXpert MTB/RIF

Identifiers

PMID33816355
PMCPMC8012509
OpenAlexW3137999755

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.