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EditorialEditorials

RSBI and NIV: Who is Failing: Patient or Machine?

Lisa F Wolfe
Respiratory Care October 2012, 57 (10) 1685-1686; DOI: https://doi.org/10.4187/respcare.02137
Lisa F Wolfe
Division of Pulmonary and Critical Care Medicine Northwestern University Feinberg School of Medicine Chicago, Illinois
MD
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Noninvasive ventilation (NIV) for treatment of both acute hypoxemic and hypercapnic respiratory failure is now widely utilized; however, it is also widely acknowledged that this therapy is not always a success, and the many studies that have evaluated this technology have found conflicting results.1 In this issue of Respiratory Care, Berg et al2 report an original study investigating possible factors that predict which patients are likely to fail NIV in an acute care setting. Previous studies have evaluated factors such as patient diagnosis or laboratory abnormalities. The paper by Berg et al is unique, because the study design allowed for all patients regardless of diagnosis to be evaluated in one group, provided that they require acute care for NIV support. This is advantageous, given the rapidity with which acute care decisions are made, often precluding time to make accurate diagnosis before initiating therapy. Given this reality, a more universal standard could, hypothetically, be the use of vital signs. Respiratory rate has been used in the past, and in many studies a reduction in respiratory rate has been found to be effective in predicting success of NIV. This has not been a robust finding, as the results have varied from study to study.3

Expanding upon the previous reports that examined respiratory rate only, the current report utilizes the rapid shallow breathing index (RSBI), and finds this to be a more robust predictor of future NIV success. The initial report of the RSBI intended the variable to be used in the setting of patients who are undergoing a spontaneous breathing trial as a discrete event, when determining the likelihood of success with discontinuation of mechanical ventilation.4 Berg et al adapted the measurement of RSBI to patients who are on NIV. The measurement (RSBI), when assessed spontaneously, assesses the patients' ability to keep up with their ventilatory load. The exercise helps to highlight the fundamental issue in respiratory failure and ventilatory support: that being the need to balance the respiratory load placed on the system with the system's ability to generate an effective work force to meet the need. When there is an inability to meet that work force requirement, respiratory failure will ensue.

When the RSBI is measured in an assisted fashion (aRSBI), this assisted value does not reflect the patient's inherent stability in work load balance, but, rather, the capacity for the combined efforts of the patient and the NIV device to meet the work load present at the time. It is logical to conclude, as the authors do, that the aRSBI is an effective tool to assess the stability of this combined system. The persistent high value in aRSBI (> 105) represents an ineffective ventilator support that is unable to meet the needs of the patient. In conclusion, the authors suggest an apparent need to consider an escalation to invasive mechanical ventilation as the aRSBI increases beyond 105, in order to reduce poor outcomes.

This assumption may not be the only relevant conclusion to these findings. When studies of NIV in acute care have included an esophageal pressure transducer, estimates of work of breathing (WOB) could be made. In these investigations, maximum pressure support was associated with a reduction in WOB, and patient support with NIV is more successful.5 New data suggest that RSBI may track with WOB,6 and, given this, the study by Berg et al leads to the next obvious question. Is it possible that the aRSBI could be used to inform care teams about the adequacy of therapy, encouraging optimization of NIV rather than abandonment?

When considering this question, it may be instructive to bear in mind that there has not been a universal standard between trials, in regard to how and when to escalate support. Some report a fixed target for pressure support, while others set a target of exhaled tidal volume (ie, 6 mL/kg ideal body weight) and, lastly, others recommend adjustment to reduce symptoms by augmenting pressure support until dyspnea complaints resolve. More in-depth settings such as trigger, cycle, backup rate, or inspiratory time are not addressed at all.7 It is likely that, if our ultimate goal is to use NIV to better address work load balance, we will need trials that not only use better surrogate markers of this balance (such as aRSBI), but that also allow for better study designs that include plans to better deal with NIV setting parameter options.

Lastly, it is possible that we can extend this concept of aRSBI and ask an alternative question. The Berg study hypothesized that when aRSBI was obtained, a point could be calculated at which NIV was likely to fail as a therapy because of an inability to meet work load balance. But what if the hypothesis investigated the opposite, that there is a point at which aRSBI could determine when WOB has been completely supported by NIV, a WOB that would approach zero? This would possibly allow us to support care providers by giving them the confidence that they have reached appropriate settings to allow for full diaphragm rest and recovery in the setting of acute illness (Figure ).8

Figure.
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Figure.

In this diagram the term “work” refers to the force generated by the respiratory muscles and “load” refers to the ventilatory requirements of the patient. Starting at the top and moving clockwise, this figure demonstrates the work versus load imbalance of respiratory failure, and the ability to use both a spontaneous and an assisted rapid shallow breathing index (RSBI) when assessing system stability, fatigue, and balance.

In summary, aRSBI appears to be an interesting and effective tool to assess the effectiveness of NIV in the setting of acute respiratory failure. More importantly, this study is a model highlighting what may potentially be a bigger role for aRSBI as a method to gain insight into our patients' overall respiratory work load balance.

Footnotes

  • Correspondence: Lisa F Wolfe MD, Division of Pulmonary and Critical Care Medicine, Northwestern University Feinberg School of Medicine, 675 North Saint Claire Street, 18-250, Chicago IL 60611. E-mail: lwolfe{at}northwestern.edu.
  • The author has disclosed a relationship with ResMed.

  • See the Original Study on Page 1548

  • Copyright © 2012 by Daedalus Enterprises Inc.

References

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    . Noninvasive ventilation for patients presenting with acute respiratory failure: the randomized controlled trials. Respir Care 2009;54(1):116–126.
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    . The rapid shallow breathing index as a predictor of failure of noninvasive ventilation for patients with acute respiratory failure. Respir Care 2012;57(10):1548–1554.
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    1. Lightowler JV,
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    . Predicting the outcome from NIV for acute exacerbations of COPD. Thorax 2000;55(10):815–816.
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    . Measurement of minute ventilation in ventilator-dependent patients: need for standardization. Crit Care Med 1991;19(1):49–53.
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    1. Kallet RH,
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    . The physiologic effects of noninvasive ventilation. Respir Care 2009;54(1):102–115.
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    1. Banner MJ,
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    . Noninvasive work of breathing improves prediction of post-extubation outcome. Intensive Care Med 38(2):248–255.
  7. 7.↵
    1. Garpestad E,
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    . Noninvasive ventilation for critical care. Chest 2007;132(2):711–720.
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Respiratory Care: 57 (10)
Respiratory Care
Vol. 57, Issue 10
1 Oct 2012
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RSBI and NIV: Who is Failing: Patient or Machine?
Lisa F Wolfe
Respiratory Care Oct 2012, 57 (10) 1685-1686; DOI: 10.4187/respcare.02137

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RSBI and NIV: Who is Failing: Patient or Machine?
Lisa F Wolfe
Respiratory Care Oct 2012, 57 (10) 1685-1686; DOI: 10.4187/respcare.02137
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