Clinical effect of high-flow nasal cannula oxygen therapy combined with naloxone on severe respiratory failure in older adult patients: a randomized controlled trial.

Yaqing Zhou, Xiaoyan Shi, Zunguo Pu, Aiming Liu

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Article in American journal of translational research, 2023. 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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0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact, top 56% of its field

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

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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

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0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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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 at 2 institutions in 1 country.

Yaqing ZhouDepartment of Critical Care Medicine, Affiliated Hai'an Hospital of Nantong University Hai'an County, Nantong 226600, Jiangsu, China.

Xiaoyan ShiDepartment of Respiratory and Critical Care Medicine, Hai'an Hospital of Traditional Chinese Medicine Hai'an County, Nantong 226600, Jiangsu, China.

Zunguo PuDepartment of Critical Care Medicine, Affiliated Hai'an Hospital of Nantong University Hai'an County, Nantong 226600, Jiangsu, China.

Aiming LiuDepartment of Critical Care Medicine, Affiliated Hai'an Hospital of Nantong University Hai'an County, Nantong 226600, Jiangsu, China.

Nantong University · CNHainan Provincial Hospital of Traditional Chinese Medicine · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo analyze the clinical effect of high-flow nasal cannula (HFNC) oxygen therapy combined with naloxone on severe respiratory failure (SRF) in older adult patients.

methodsWe enrolled 96 older adult patients with SRF who were admitted to Hai'an People's Hospital between February 2019 and March 2022. The patients were divided into two groups: the control group (treated with non-invasive positive pressure ventilation combined with naloxone) and the observation group (treated with HFNC oxygen therapy combined with naloxone). The blood gas measurement, respiratory rate (RR), St. George's Respiratory Questionnaire (SGRQ) score, Clara cell secreted protein (CC16) level, tumor necrosis factor-alpha (TNF-α) level, interleukin-1 (IL-1) level, length of intensive care unit (ICU) stay, tracheal intubation rate, and 28-day mortality rate were compared between the groups.

resultsBlood gas measurement or RR did not differ significantly between the groups (

conclusionsHFNC oxygen therapy combined with naloxone in older adult patients with SRF could improve blood gas results, disease duration, tracheal intubation rate, and 28-day mortality rate. This may occur through regulation of TNF-α, IL-1, and CC16 expression.

Indexed as

Blood gas indicatorshigh-flow nasal cannulanaloxoneolder adultssevere respiratory failure

Identifiers

PMID38074811

PMCPMC10703660

OpenAlexW4389802886

What OpenQuestion holds

Textmetadata

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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.