ArticleBMC emergency medicine2025
Clinical factors associated with the use of NIV in the pre-hospital setting in adult patients treated for acute COPD exacerbation: a single-center retrospective cohort study.
Article in BMC emergency 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.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundNon-invasive ventilation (NIV) is a cornerstone in the management of acute chronic obstructive pulmonary disease (COPD) exacerbations with respiratory failure. While extensively studied in hospital settings, limited data exist on its use in the pre-hospital setting and clinical factors influencing its application. This study aimed to identify predictors of NIV use in the pre-hospital setting and to assess its association with patient-centered outcomes.
methodsThis single-center retrospective cohort study analyzed data from a pre-hospital emergency medical service registry in Geneva, Switzerland. Adult patients with a presumptive diagnosis of acute COPD exacerbation were included, spanning a control period (2007-2010, before NIV implementation) and an intervention period (2013-2017, after NIV implementation). For the primary analysis, multivariable logistic regression was used to identify predictors of NIV use during the intervention period. For the secondary analysis, coarsened exact matching balanced patients treated with NIV during the intervention period with those from the control period, followed by conditional regression analyses to assess patient-centered outcomes.
resultsAmong 270 included patients, 84 (46%) received NIV during the intervention period. Age ≥ 70 years (aOR 2.49, 95% CI 1.11, 5.76), female sex (aOR 2.48, 95% CI 1.13, 5.60), and systolic blood pressure (SBP) ≥ 140 mmHg (aOR 2.75, 95% CI 1.19, 6.62) were independent predictors associated with receiving NIV in the pre-hospital setting. In the matched cohort, pre-hospital NIV use was significantly associated with increased ICU admission rates, but was not associated with transport time, emergency department length of stay, hospital length of stay, or 28-day mortality. Sensitivity analyses demonstrated consistent results across different modeling approaches.
conclusionsAge ≥ 70 years, female sex, and SBP ≥ 140 mmHg were independent predictors associated with receiving NIV in the pre-hospital management of acute COPD exacerbation. The association between NIV use and increased ICU admissions may reflect its application in more severely ill patients. Pre-hospital NIV was not associated with short- or long-term outcomes beyond ICU admission. These findings underscore the need for prospective studies to clarify the role of pre-hospital NIV in patient outcomes.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.