ABSTRACT
BACKGROUND: The N3 wave is a vestibular evoked neurogenic potential detected in some patients with profound sensorineural hearing loss (PSNHL) during brainstem auditory evoked potential (BAEP) analysis. In 1998, Kato et al. mentioned two electropositive waves preceding N3, which we named p1-p2, but no further description was given. OBJECTIVE: We sought to demonstrate the reproducibility of these waves and hypothesize on their anatomic origin. METHODS: We used two cohorts of patients with PSNHL. The first cohort comprised 10 patients with N3, allowing us to establish a new test with adequate electrophysiological conditions headed to detect p1-p2 waves (PN3EP). The second cohort consisted of two groups: group A comprised 10 patients in whom N3 was not detected; and group B comprised 20 patients presenting N3. PN3EP was performed in both groups, of which 50% had cervical myogenic vestibular evoked potentials (cVEMPs). RESULTS: Only group B presented p1-p2. The PN3EP facilitated the identification of p1-p2 over BAEP analysis, and their presence correlated well with cVEMPs. CONCLUSIONS: P1-p2 may be covered due to inadequate BAEP setting conditions, and could be generated in the distal neural path that generates the N3 wave.
Subject(s)
Evoked Potentials, Auditory, Brain Stem , Hearing Loss, Sensorineural/physiopathology , Vestibular Evoked Myogenic Potentials , Acoustic Stimulation , Adolescent , Adult , Child , Child, Preschool , Female , Hearing Tests , Humans , Infant , Male , Middle Aged , Reproducibility of Results , Young AdultABSTRACT
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.
Subject(s)
Influenza, Human/complications , Noninvasive Ventilation/mortality , Respiratory Insufficiency/therapy , APACHE , Adult , Aged , Chi-Square Distribution , Critical Illness/mortality , Female , Hospital Mortality , Humans , Influenza, Human/mortality , Intensive Care Units/statistics & numerical data , Male , Middle Aged , Noninvasive Ventilation/methods , Organ Dysfunction Scores , Prospective Studies , Respiration, Artificial/methods , Respiration, Artificial/mortality , Respiratory Insufficiency/mortality , Respiratory Insufficiency/virology , Risk Factors , Treatment FailureABSTRACT
OBJECTIVES: To define which variables upon ICU admission could be related to the presence of coinfection using CHAID (Chi-squared Automatic Interaction Detection) analysis. METHODS: A secondary analysis from a prospective, multicentre, observational study (2009-2014) in ICU patients with confirmed A(H1N1)pdm09 infection. We assessed the potential of biomarkers and clinical variables upon admission to the ICU for coinfection diagnosis using CHAID analysis. Performance of cut-off points obtained was determined on the basis of the binominal distributions of the true (+) and true (-) results. RESULTS: Of the 972 patients included, 196 (20.3%) had coinfection. Procalcitonin (PCT; ng/mL 2.4 vs. 0.5, p < 0.001), but not C-reactive protein (CRP; mg/dL 25 vs. 38.5; p = 0.62) was higher in patients with coinfection. In CHAID analyses, PCT was the most important variable for coinfection. PCT <0.29 ng/mL showed high sensitivity (Se = 88.2%), low Sp (33.2%) and high negative predictive value (NPV = 91.9%). The absence of shock improved classification capacity. Thus, for PCT <0.29 ng/mL, the Se was 84%, the Sp 43% and an NPV of 94% with a post-test probability of coinfection of only 6%. CONCLUSION: PCT has a high negative predictive value (94%) and lower PCT levels seems to be a good tool for excluding coinfection, particularly for patients without shock.
