Evidence map›Paper›PMID 42519798›Full record

ArticleFrontiers in medicine2026

Prone position ventilation combined with high-flow nasal cannula oxygen therapy in patients with pulmonary infection: a retrospective study on evidence-based nursing practice.

Wenjun Lai, Jing Fei, Ye Gao, Yan He

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.

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

4 authors.

Wenjun Lai *Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital Affiliated to Tongji University, Shanghai, China.
Jing Fei *Department of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital Affiliated to Tongji University, Shanghai, China.
Ye GaoDepartment of Respiratory and Critical Care Medicine, Shanghai Pulmonary Hospital Affiliated to Tongji University, Shanghai, China.
Yan HeDepartment of Respiratory and Critical Care Medicine, Shanghai Fourth People's Hospital, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Pulmonary infections are a common and serious clinical condition, particularly affecting critically ill patients, and effective respiratory management is crucial for recovery. This study examined the clinical and nursing outcomes associated with prone position ventilation (PPV) combined with high-flow nasal cannula (HFNC) oxygen therapy in patients with pulmonary infection. Methods: We conducted a retrospective analysis of 200 patients with pulmonary infection admitted to two tertiary hospitals between January 2022 and January 2024. On the basis of the respiratory support actually received during hospitalization (non-randomized allocation), patients were assigned to an observation group ( Results: Over the first 72 h, the observation group showed greater improvements in PaO Conclusion: In this retrospective, non-randomized cohort, PPV combined with HFNC oxygen therapy was associated with better respiratory outcomes, fewer complications, shorter hospitalization and higher nurse-assessed comfort and compliance than conventional oxygen therapy. Because treatment allocation was not randomized, these associations cannot establish causality, and prospective randomized trials are needed to confirm the findings in larger cohorts.

Indexed as

evidence-based nursinghigh-flow nasal cannulaprone position ventilationpulmonary infectionretrospective study

Identifiers

PMID42519798
PMCPMC13381630

What OpenQuestion 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 OpenQuestion graph.