Evidence map›Paper›PMID 34425768›Full record

ArticleBMC infectious diseases2021

The development and validation of a diagnostic scoring system to differentiate pulmonary tuberculosis from non-tuberculosis pulmonary infections in HIV-infected patients with severe immune suppression.

Jing Ouyang, Jing Yuan, Yaling Chen, Yanming Zeng, Vijay Harypursat, Yanqiu Lu, Hui Chen, Yaokai Chen

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 48% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

Jing Ouyang *Clinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Jing Yuan *Clinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Yaling ChenClinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Yanming ZengClinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Vijay HarypursatClinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Yanqiu LuClinical Research Center, Chongqing Public Health Medical Center, Chongqing, China.
Hui ChenSchool of Biomedical Engineering, Capital Medical University, No. 10 Youanmenwai Road, Fengtai, Beijing, 100069, China. chenhui@ccmu.edu.cn.
Yaokai ChenClinical Research Center, Chongqing Public Health Medical Center, Chongqing, China. yaokaichen@hotmail.com.ORCID http://orcid.org/0000-0002-3229-0108
Chongqing Public Health Medical Center · CNCapital Medical University · CN

Funding

Basic Research Project of Chongqing Science & Technology Commission cstc2018jcyjAX0272Joint Medical Research Project of Chongqing Science & Technology Bureau and Chongqing Health Commission 2020GDRC010medical research project of Chongqing Municipal Health and Family Planning Committee 2016HBRC008national science and technology major project during the 13th five-year plan period 2018ZX10302104
6 · The paper itself

Abstract

backgroundIt remains challenging to differentiate tuberculosis (TB) from non-TB pulmonary infections in HIV-infected patients. Herein, we developed a scoring system aimed to rapidly determine the likelihood of TB or non-TB pathology in HIV-infected patients presenting with pulmonary infections.

methodsWe collected and collated data of hospitalized HIV-infected patients with pulmonary infections, followed by univariate and multivariate data analyses to determine risk variables that were significantly different between HIV/TB patients and HIV/non-TB patients. Subsequently, a regression coefficient was calculated for each variable, and a score was assigned to each variable in line with its regression coefficient. The sum of the scores for each variable in our scoring model was used to predict the likelihood of TB or non-TB pulmonary infection in each patient. Finally, we tested the diagnostic accuracy of the scoring system in our retrospective cohort, as well as in a prospective cohort.

resultsA total of 598 HIV-infected patients were enrolled in our retrospective cohort, among whom 288 had TB and 310 had non-TB pulmonary infections. Eight variables, including fever, highest body temperature, erythrocyte sedimentation rate (ESR), cervical lymphadenopathy, hilar and/or mediastinum lymphadenopathy, pulmonary cavitation, pleural effusion, and miliary nodules, were found to be mathematically significantly different via univariate analysis and multivariate logistic regression analysis. After regression coefficient calculation followed by score assignment, a receiver operating characteristic (ROC) curve was plotted, and the area under the curve (AUC) was calculated to be 0.902. When the total score for a patient is > 12, the sensitivity and specificity for TB prediction using our scoring system were 76.4% and 87.7% respectively in the retrospective cohort, and its diagnostic accuracy was 82.7% in the prospective cohort.

conclusionsOur results demonstrate that our proposed diagnostic scoring system could be helpful in differentiating pulmonary TB from non-TB pulmonary infections in HIV-infected patients.

Indexed as

HIV InfectionsTuberculosisTuberculosis, PulmonaryHumansProspective StudiesRetrospective StudiesDiagnosisHuman immunodeficiency virusScoring systemTuberculosis

Identifiers

PMID34425768
PMCPMC8383349
OpenAlexW3193869937

What OpenQuestion holds

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LicenceCC BY
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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.