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Record W2947544207 · doi:10.1186/s13054-019-2425-6

Influenza and associated co-infections in critically ill immunosuppressed patients

2019· article· en· W2947544207 on OpenAlexaff
Ignacio Martín‐Loeches, Virginie Lemiale, Pierce Geoghegan, Aisling McMahon, Peter Pickkers, Márcio Soares, Anders Perner, Tine Sylvest Meyhoff, Ramin Brandt Bukan, Jordi Rello, Philippe R. Bauer, Andry van de Louw, Fabio Silvio Taccone, Jorge I. Salluh, Pleun Hemelaar, Peter Schellongowski, Kateřina Rusínová, Nicolas Terzi, Sangeeta Mehta, Massimo Antonelli, Achille Kouatchet, Pål Klepstad, Miia Valkonen, Precious Pearl Landburg, Andreas Barratt‐Due, Fabrice Bruneel, Frédéric Pène, Victoria Metaxa, Virginie Souppart, Gastón Burghi, Christophe Girault, Ulysses V. A. Silva, Luca Montini, François Barbier, Lene B. Nielsen, Benjamin Gaborit, Djamel Mokart, Sylvie Chevret, Élie Azoulay

Bibliographic record

VenueCritical Care · 2019
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsSinai Health SystemUniversity of Toronto
FundersHealth Research Board
KeywordsMedicineCritically illIntensive care medicineCritical illnessEmergency medicine

Abstract

fetched live from OpenAlex

BACKGROUND: It is unclear whether influenza infection and associated co-infection are associated with patient-important outcomes in critically ill immunocompromised patients with acute respiratory failure. METHODS: Preplanned secondary analysis of EFRAIM, a prospective cohort study of 68 hospitals in 16 countries. We included 1611 patients aged 18 years or older with non-AIDS-related immunocompromise, who were admitted to the ICU with acute hypoxemic respiratory failure. The main exposure of interest was influenza infection status. The primary outcome of interest was all-cause hospital mortality, and secondary outcomes ICU length of stay (LOS) and 90-day mortality. RESULTS: Influenza infection status was categorized into four groups: patients with influenza alone (n = 95, 5.8%), patients with influenza plus pulmonary co-infection (n = 58, 3.6%), patients with non-influenza pulmonary infection (n = 820, 50.9%), and patients without pulmonary infection (n = 638, 39.6%). Influenza infection status was associated with a requirement for intubation and with LOS in ICU (P < 0.001). Patients with influenza plus co-infection had the highest rates of intubation and longest ICU LOS. On crude analysis, influenza infection status was associated with ICU mortality (P < 0.001) but not hospital mortality (P = 0.09). Patients with influenza plus co-infection and patients with non-influenza infection alone had similar ICU mortality (41% and 37% respectively) that was higher than patients with influenza alone or those without infection (33% and 26% respectively). A propensity score-matched analysis did not show a difference in hospital mortality attributable to influenza infection (OR = 1.01, 95%CI 0.90-1.13, P = 0.85). Age, severity scores, ARDS, and performance status were all associated with ICU, hospital, and 90-day mortality. CONCLUSIONS: Category of infectious etiology of respiratory failure (influenza, non-influenza, influenza plus co-infection, and non-infectious) was associated with ICU but not hospital mortality. In a propensity score-matched analysis, influenza infection was not associated with the primary outcome of hospital mortality. Overall, influenza infection alone may not be an independent risk factor for hospital mortality in immunosuppressed patients.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.014
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.409
Teacher spread0.359 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations48
Published2019
Admission routes1
Has abstractyes

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