Evidence map›Paper›PMID 42027822›Full record

ArticleFrontiers in medicine2026

Doxycycline treatment for drug-resistant

Ruijuan Ren, Yuping Xu, Xinyan Cui, Mengsheng Zhang, Xiangtao Wu, Tuanjie Wang, Xue Liu, Shujun Li

Abstract read
In one paragraph

Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Ruijuan RenChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Yuping XuChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Xinyan CuiChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Mengsheng ZhangChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Xiangtao WuChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Tuanjie WangChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Xue LiuChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.
Shujun LiChildren's Intensive Care Unit of the First Affiliated Hospital of Xinxiang Medical College, Xinxiang, Henan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Mycoplasma pneumoniae pneumonia (MPP) in children is a common respiratory infection, with rising concerns over macrolide-resistant strains. The aim of this study is to establish an effective diagnostic prediction model for refractory MPP (RMPP) and evaluate doxycycline as an alternative treatment for macrolide-unresponsive MPP (MUMPP). Methods: 106 children with RMPP receiving doxycycline and 73 children with MUMPP treated with azithromycin were retrospectively analyzed. For all patients, the detection of MP-DNA in BALF, alongside clinical criteria, served to confirm active MP infection and infer phenotypic macrolide unresponsiveness/resistance. Univariate and multivariate logistic regression analyses were then used to identify clinically available risk factors for the development of RMPP among these patients with MP pneumonia. Results: The doxycycline group had significantly shorter fever duration, fewer lavage procedures, reduced steroid use, and shorter hospital stays compared to the azithromycin group ( Conclusion: In children with MUMPP, doxycycline treatment is associated with superior clinical outcomes compared to azithromycin. A nomogram incorporating readily available clinical factors can effectively identify patients at risk of developing RMPP, supporting early intervention.

Indexed as

diagramdoxycyclinemycoplasmarefractory pneumoniaresistant

Identifiers

PMID42027822
PMCPMC13101431

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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.