Evidence map›Paper›PMID 39010097›Full record

ArticleRespiratory research2024

Effect of noninvasive ventilation on mortality and clinical outcomes among patients with severe hypoxemic COVID-19 pneumonia after high-flow nasal oxygen failure: a multicenter retrospective French cohort with propensity score analysis.

Antoine Goury, Zeyneb Houlla, Mathieu Jozwiak, Tomas Urbina, Matthieu Turpin, Alexandra Lavalard, Driss Laghlam, Sebastian Voicu, Jeremy Rosman, Claire Coutureau and 1 more

Abstract readMulticenter Study
In one paragraph

Article in Respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed, 1 pooled it
–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

1 citing paper in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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

11 authors.

Antoine GouryUnité de Médecine Intensive et Réanimation Polyvalente, CHU Reims, Reims, F-51100, France. agoury@chu-reims.fr.
Zeyneb HoullaUnité de Médecine Intensive et Réanimation Polyvalente, CHU Reims, Reims, F-51100, France.
Mathieu JozwiakService de Médecine Intensive Réanimation, Centre Hospitalier Universitaire de Nice, Hôpital l'Archet 1, Nice, France.
Tomas UrbinaService de Médecine Intensive Réanimation, Hôpital Saint-Antoine, Assistance Publique Hôpitaux de Paris, Paris, France.
Matthieu TurpinService de Médecine Intensive Réanimation, Hôpital Tenon, Assistance Publique Hôpitaux de Paris, Paris, France.
Alexandra LavalardUnité de Réanimation Polyvalente, Centre Hospitalier de Troyes, Troyes, France.
Driss LaghlamService de Médecine Intensive et Réanimation, Hôpital Cochin, Assistance Publique Hôpitaux de Paris, Paris, France.
Sebastian VoicuRéanimation Médicale et Toxicologique, Hôpital Lariboisière, Assistance Publique Hôpitaux de Paris, Paris, France.
Jeremy RosmanUnité de Soins Intensifs et Réanimation, Groupe Hospitalier de Territoire Nord-Ardennes, Charleville-Mézières, France.
Claire CoutureauUniversité de Reims Champagne-Ardenne, VieFra, Reims, F-51100, France.
Bruno MourvillierUnité de Médecine Intensive et Réanimation Polyvalente, CHU Reims, Reims, F-51100, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWe assessed the effect of noninvasive ventilation (NIV) on mortality and length of stay after high flow nasal oxygenation (HFNO) failure among patients with severe hypoxemic COVID-19 pneumonia.

methodsIn this multicenter, retrospective study, we enrolled COVID-19 patients admitted in intensive care unit (ICU) for severe COVID-19 pneumonia with a HFNO failure from December 2020 to January 2022. The primary outcome was to compare the 90-day mortality between patients who required a straight intubation after HFNO failure and patients who received NIV after HFNO failure. Secondary outcomes included ICU and hospital length of stay. A propensity score analysis was performed to control for confounding factors between groups. Exploratory outcomes included a subgroup analysis for 90-day mortality.

resultsWe included 461 patients with HFNO failure in the analysis, 233 patients in the straight intubation group and 228 in the NIV group. The 90-day mortality did not significantly differ between groups, 58/228 (25.4%) int the NIV group compared with 59/233 (25.3%) in the straight intubation group, with an adjusted hazard ratio (HR) after propensity score weighting of 0.82 [95%CI, 0.50-1.35] (p = 0.434). ICU length of stay was significantly shorter in the NIV group compared to the straight intubation group, 10.0 days [IQR, 7.0-19.8] versus 18.0 days [IQR,11.0-31.0] with a propensity score weighted HR of 1.77 [95%CI, 1.29-2.43] (p < 0.001). A subgroup analysis showed a significant increase in mortality rate for intubated patients in the NIV group with 56/122 (45.9%), compared to 59/233 (25.3%) for patients in the straight intubation group (p < 0.001).

conclusionsIn severely hypoxemic COVID-19 patients, no significant differences were observed on 90-day mortality between patients receiving straight intubation and those receiving NIV after HFNO failure. NIV strategy was associated with a significant reduction in ICU length of stay, despite an increase in mortality in the subgroup of patients finally intubated.

Indexed as

COVID-19Noninvasive VentilationOxygen Inhalation TherapyPropensity ScoreAgedAged, 80 and overCohort StudiesFemaleFranceHospital MortalityHumansHypoxiaIntensive Care UnitsLength of StayMaleMiddle AgedAcute respiratory distress syndromeAcute respiratory failureCOVID-19High flow oxygen therapyIntubationMortalityNoninvasive ventilationOutcomes

Identifiers

PMID39010097
PMCPMC11251296

What OpenQuestion holds

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LicenceCC BY
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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.