Evidence map›Paper›PMID 40654577›Full record

Observational studyFrontiers in cellular and infection microbiology2025

Atelectasis predicts poor prognosis in pediatric macrolides-unresponsive

Jie Cheng, Ya Liu, Guangli Zhang, Yuanyuan Li, Xiaoyin Tian, Liping Tan, Zhengxiu Luo

Abstract readObservational Study
In one paragraph

Observational study in Frontiers in cellular and infection microbiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Prediction of atelectasis inFrontiers in pediatrics · 2026
    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

7 authors.

Jie ChengDepartment of Emergency, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.
Ya LiuDepartment of Pediatrics, Chongqing Youyoubaobei Women and Children's Hospital, Chongqing, China.
Guangli ZhangDepartment of Respiratory Medicine, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.
Yuanyuan LiDepartment of Respiratory Medicine, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.
Xiaoyin TianDepartment of Respiratory Medicine, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.
Liping TanDepartment of Emergency, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.
Zhengxiu LuoDepartment of Respiratory Medicine, National Clinical Research Center for Child Health and Disorders, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing Key Laboratory of Child Rare Diseases in Infection and Immunity, Intelligent Application of Big Data in Pediatrics Engineering Research Center of Chongqing Education Commission of China, Children's Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: We aimed to investigate prognostic indicators for pediatric macrolides-unresponsive Methods: This was a retrospective observational cohort study conducted at the Children's Hospital of Chongqing Medical University. Children with macrolide-resistant mutations (A2063/2064G) diagnosed as MUMPP who received only anti- Results: This study retrospectively included 82 children with MUMPP, and all received only azithromycin for anti-MP treatment. The incidence of pulmonary consolidation, pleural effusion, and atelectasis was 80.49% (66/82), 34.15% (28/82), and 24.39% (20/82), respectively. 29.27% (24/82) of patients diagnosed with RMPP, and 14.63% (12/82) of patients diagnosed with bronchiolitis obliterans (BO) or bronchiectasis diagnosed within one year after discharge. Logistic analysis showed that atelectasis was independently associated with short-term (RMPP) and long-term (BO or bronchiectasis) adverse prognosis (odds ratio [OR] 4.02, 95% confidence interval [CI] 1.03-16.00, P = 0.043; OR 5.62, 95% CI 1.04-32.80, P = 0.045; respectively). Conclusion: Atelectasis predicts a poor prognosis for children with A2063/2064G MUMPP. The occurrence of atelectasis may indicate an increased risk of failure of current azithromycin treatment. Combined with the results of drug-resistant mutations, it is recommended to strengthen disease monitoring and individualized intervention evaluation.

Indexed as

Anti-Bacterial AgentsAzithromycinDrug Resistance, BacterialMacrolidesMycoplasma pneumoniaePneumonia, MycoplasmaPulmonary AtelectasisChildChild, PreschoolFemaleHumansInfantMaleMutationPrognosisRetrospective StudiesAnti-Bacterial AgentsAzithromycinMacrolidesA2063/2064G mutationatelectasisazithromycinchildrenMycoplasma pneumoniae pneumonia

Identifiers

PMID40654577
PMCPMC12245878

What Socratic 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 Socratic graph.