Evidence map›Paper›PMID 42535149›Full record

ArticleChina CDC weekly2024

Patient Delay in the Diagnosis of Pulmonary Tuberculosis in the Elderly - China, 2015-2023.

Yushu Liu, Mingkuan Fan, Yuhong Li, Jiaojie Kang, Ybryim A, Tianxin Yan, Jun Cheng, Hui Zhang

Abstract read
In one paragraph

Article in China CDC weekly, 2024. 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
–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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. 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

8 authors.

Yushu LiuNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Mingkuan FanMedical College of Xiangyang Polytechnic, Xiangyang City, Hubei Province, China.
Yuhong LiNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Jiaojie KangNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Ybryim ANational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Tianxin YanNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Jun ChengNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.
Hui ZhangNational Center for Tuberculosis Control and Prevention, ChineseCenter for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

What is already known about this topic?: Patient delay in seeking medical care for pulmonary tuberculosis (PTB), especially among elderly individuals with weakened immune systems and mild symptoms, not only slows their recovery but also increases the risk of tuberculosis spread because cases are not identified promptly. What is added by this report?: In China, patient delays experienced by elderly PTB patients showed a modest decrease from 2015 to 2023. Notably, longer patient delays were observed among agricultural workers and those identified through passive case-finding methods. Furthermore, the patient delay in the western regions was longer than in the eastern and central regions. What are the implications for public health practice?: The study underscores the imperative of accessible healthcare for the elderly to minimize patient delay in pulmonary tuberculosis diagnosis and treatment.

Indexed as

elderlypatient delaytuberculosis

Identifiers

PMID42535149
PMCPMC13423184

What OpenQuestion holds

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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.