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Risk Factors for Noninvasive Ventilation Failure in Critically Ill Subjects With Confirmed Influenza Infection

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  • Risk Factors for Noninvasive Ventilation Failure in Critically Ill Subjects With Confirmed Influenza Infection

    Respir Care. 2017 Jul 11. pii: respcare.05481. doi: 10.4187/respcare.05481. [Epub ahead of print]
    Risk Factors for Noninvasive Ventilation Failure in Critically Ill Subjects With Confirmed Influenza Infection.

    Rodr?guez A1, Ferri C2, Martin-Loeches I3, D?az E4, Masclans JR5, Gordo F6, Sole-Viol?n J7, Bod? M2, Avil?s-Jurado FX8, Trefler S2, Magret M2, Moreno G2, Reyes LF9, Marin-Corral J, Yebenes JC10, Esteban A11, Anzueto A9, Aliberti S12, Restrepo MI9.
    Author information

    Abstract

    BACKGROUND:

    Despite wide use of noninvasive ventilation (NIV) in several clinical settings, the beneficial effects of NIV in patients with hypoxemic acute respiratory failure (ARF) due to influenza infection remain controversial. The aim of this study was to identify the profile of patients with risk factors for NIV failure using chi-square automatic interaction detection (CHAID) analysis and to determine whether NIV failure is associated with ICU mortality.
    METHODS:

    This work was a secondary analysis from prospective and observational multi-center analysis in critically ill subjects admitted to the ICU with ARF due to influenza infection requiring mechanical ventilation. Three groups of subjects were compared: (1) subjects who received NIV immediately after ICU admission for ARF and then failed (NIV failure group); (2) subjects who received NIV immediately after ICU admission for ARF and then succeeded (NIV success group); and (3) subjects who received invasive mechanical ventilation immediately after ICU admission for ARF (invasive mechanical ventilation group). Profiles of subjects with risk factors for NIV failure were obtained using CHAID analysis.
    RESULTS:

    Of 1,898 subjects, 806 underwent NIV, and 56.8% of them failed. Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, infiltrates in chest radiograph, and ICU mortality (38.4% vs 6.3%) were higher (P < .001) in the NIV failure than in the NIV success group. SOFA score was the variable most associated with NIV failure, and 2 cutoffs were determined. Subjects with SOFA ≥ 5 had a higher risk of NIV failure (odds ratio = 3.3, 95% CI 2.4-4.5). ICU mortality was higher in subjects with NIV failure (38.4%) compared with invasive mechanical ventilation subjects (31.3%, P = .018), and NIV failure was associated with increased ICU mortality (odds ratio = 11.4, 95% CI 6.5-20.1).
    CONCLUSIONS:

    An automatic and non-subjective algorithm based on CHAID decision-tree analysis can help to define the profile of patients with different risks of NIV failure, which might be a promising tool to assist in clinical decision making to avoid the possible complications associated with NIV failure.
    Copyright ? 2017 by Daedalus Enterprises.


    KEYWORDS:

    CHAID analysis; influenza infection; noninvasive ventilation; prognosis

    PMID: 28698265 DOI: 10.4187/respcare.05481
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