Evidence map›Paper›PMID 41204279›Full record

ArticleBMC pulmonary medicine2025

Pulmonary alveolar proteinosis that improved after a COVID-19 infection: a case report.

Chunyu Xu, Li Gao, Xi Wang, Zhanwei Hu, Chengli Que

Abstract readCase Reports
In one paragraph

Article in BMC pulmonary medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

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

5 authors.

Chunyu XuDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China.
Li GaoDepartment of Medical Imaging, Peking University First Hospital, Beijing, 100034, China.
Xi WangDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China.
Zhanwei HuDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China.
Chengli QueDepartment of Respiratory and Critical Care Medicine, Peking University First Hospital, Beijing, 100034, China. quechengli@bjmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pulmonary alveolar proteinosis (PAP) is a rare disease caused by the accumulation of abnormal surfactant in the alveoli, leading to impaired gas exchange. A 54-year-old woman presented with intermittent wheezing who developed increasing infiltrates gradually on chest CT, was diagnosed with PAP in our department in December 2017. She then underwent granulocyte-macrophage colony-stimulating factor (GM-CSF) inhalation therapy for three months without improvement. Regular follow-up imaging and pulmonary function tests suggested disease progression. However, the patient declined whole-lung lavage (WLL) due to her unrestricted daily activities. Two months after a coronavirus disease 2019 (COVID-19) infection in February 2023, the patient’s chest CT became clear, accompanied by improved pulmonary function. Repeated HRCT of the chest in March 2024 confirmed no signs of recurrence, nor in pulmonary function tests. In this case, COVID-19 infection may have contributed to the improvement of this patient’s PAP, raising the hypothesis of an immunomodulatory effect.

Indexed as

COVID-19Granulocyte-Macrophage Colony-Stimulating FactorPulmonary Alveolar ProteinosisFemaleHumansMiddle AgedPandemicsRespiratory Function TestsSARS-CoV-2Tomography, X-Ray ComputedGranulocyte-Macrophage Colony-Stimulating FactorCoronavirus disease 2019 (COVID-19)Granulocyte-macrophage colony-stimulating factor (GM-CSF)MacrophagePulmonary alveolar proteinosis (PAP)

Identifiers

PMID41204279
PMCPMC12595731

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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.