Poster presentation | Open | Published:
Rapid shallow breathing index – a key predictor for noninvasive ventilation
Critical Carevolume 11, Article number: P169 (2007)
The rapid shallow breathing index (RSBI) is the ratio determined by the frequency (f) divided by the tidal volume (VT). An RSBI <105 has been widely accepted by healthcare professionals as a criteria for weaning to extubation and has been integrated into most mechanical ventilation weaning protocols. We hypothesized that the converse of using the RSBI for weaning might be useful in predicting the need for noninvasive ventilation. Advancements in technology have made it easier to accurately attain bedside RSBI measurements. The purpose of this study was to ascertain a threshold value of RSBI that could predict the need for noninvasive ventilation (NIV) in patients presenting with acute respiratory distress to the critical care area (Cat 1) in the emergency department.
This was a blinded, observational cohort trial that was approved by the Henry Ford Hospital Institutional Review Board. Henry Ford Hospital is an urban, tertiary institution in Detroit, Michigan with an emergency department census of 95,000 patient visits per year. Inclusion criteria: patients > 18 years of age triaged to Cat 1 with acute respiratory distress and for whom the decision to intubate, use NIV or discharge the patient had not been decided. Exclusion criteria: immediate intubation, NIV, or discharge from Cat 1. Baseline demographics and vital signs were collected prior to the initiation of the trial (Figure 1). The CO2SMO Plus! with the ETCO2/flow sensor was used for obtaining bedside measurements. Patients would breathe through the ETCO2/flow sensor for 60 seconds with nose clips.
The threshold value for RSBI that discriminated best between no NIV and the need for NIV was determined in 61 patients. Thirty-five patients who did not require ventilatory support had a mean RSBI of 105, and 26 patients with NIV had a mean RSBI of 222 (P = 0.0001). A receiver-operating-characteristic curve was constructed based upon the dataset in increments of 10 for the RSBI (Figure 2). An RSBI > 120 yielded a sensitivity of 0.81 and a specificity of 0.74 for determining the need for NIV. A likelihood ratio positive (LR+) of 3.14 further illustrates the formidable predictive value of the 120 RSBI.
A RSBI of 120 or greater, as reflected by f/VT ratio, may be a predictor of when NIV support should be considered. Further prospective randomized studies are needed to validate the value of 120.