Evidence map›Paper›PMID 37809964›Full record

ArticleHeliyon2023

Clinical features of HIV positive talaromycosis marneffei patients and development of a risk prediction model.

Jiemei Cen, Jie Huang, Wen Zeng, Mianluan Pan, Ye Qiu, Jianquan Zhang

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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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

12 citing papers in PubMed.

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  5. Infection and drug resistance · 2026
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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

6 authors.

Jiemei CenDepartment of Respiratory Medicine, the Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China.
Jie HuangGuangxi Nanning Fourth People's Hospital, Department of Tuberculosis Ward, Nanning, Guangxi, China.
Wen ZengDepartment of Respiratory Medicine, the Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China.
Mianluan PanDepartment of Respiratory Medicine, the Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China.
Ye QiuDepartment of Respiratory Medicine, the Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China.
Jianquan ZhangDepartment of Respiratory Medicine, the Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518033, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Aims: The purpose of this study was to establish and verify a nomogram to predict the prognosis of patients with human immunodeficiency virus (HIV)-related talaromycosis marneffei and evaluate the prognosis. Methods: We examined the acquired immune deficiency syndrome (AIDS) patients hospitalized in the Fourth People's Hospital of Nanning from 2018 to 2020 with an aetiological diagnosis of Talaromyces marneffei infection. Logistic regression analysis was used to identify the independent risk factors for relapse or death of the prognosis of Talaromyces marneffei infection. According to the regression coefficient, the corresponding nomograph prediction model was drawn. Results: A total of 400 patients were included, including 321 males and 79 females. Recurrence or death occurred in 70 cases (17.5%). The area under the receiver operator characteristic curve (ROC) of the established model was 0.716 with good discrimination, calibration, and clinical effectiveness. The risks of age between 45 and 60 years old and <40 years old were successively higher than that of >60 years old, and the risks of G test <50 pg/ml and >100 pg/ml were higher than that of 50-100 pg/ml. Respiratory failure, decreased albumin and elevated total bilirubin are risk factors for relapse or death in HIV patients infected with Talaromyces marneffei. Conclusion: This model can accurately predict the prognosis of HIV complicated with Talaromyces marneffei infection.

Indexed as

HIVNomogramPrediction modelPrognosisTalaromycosis marneffei

Identifiers

PMID37809964
PMCPMC10559804

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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.