To the Editor,
We would like to thank Drs. Ece Salihoglu and Ziya Salihoglu for their interest in our article.2
While not directly addressed in the paper, the CURE clinical study data used in this paper considers patient gas concentration alongside both ventilator pressure and volume. The four CURE pilot trial patients had FiO2 set to 40, 40, 55 and 65 with PaO2 measurements of 71, 84, 60 and 101 mmHg, respectively. The McREM trial data used for validation did not provide specific oxygenation results.3 However, each patient’s initial P/F ratio is provided in Table 1 of the paper, and indicates FiO2 varied in typical ranges.3
The model presented in our paper was designed for use in an upcoming clinical trial that aims to optimise mechanical ventilation care.1,4 The trial uses two steps to optimise oxygenation. Step 1 optimises alveolar recruitment by titrating PEEP to the point of minimum elastance. The model thus safely maximises oxygenation via mechanics without adjusting FiO2. Step 2 uses this foundation to titrate FiO2 to achieve patient SpO2 levels within 92-95%. This process minimises the risk of excessively high oxygen levels, so the broad range of patients with respiratory failure can be optimally treated dependent on their specific condition and response to ventilation.
Thank you again for your time and interest.
Morton, S., Y. Chiew, C. Pretty, E. Moltchanova, C. Scarrott, D. Redmond, G. Shaw, and J. Chase. Effective sample size estimation for a mechanical ventilation trial through Monte-Carlo simulation: length of mechanical ventilation and ventilator free days. Math. Biosci. 284:21–31, 2017.
Morton, S. E., J. L. Knopp, J. G. Chase, K. Möller, P. Docherty, G. M. Shaw, and M. Tawhai. Predictive virtual patient modelling of mechanical ventilation: impact of recruitment function. Ann. Biomed. Eng. 47:1626–1641, 2019.
Stahl, C. A., K. Möller, S. Schumann, R. Kuhlen, M. Sydow, C. Putensen, and J. Guttmann. Dynamic versus static respiratory mechanics in acute lung injury and acute respiratory distress syndrome. Crit. Care Med. 34:2090–2098, 2006.
Szlavecz, A., Y. S. Chiew, D. Redmond, A. Beatson, D. Glassenbury, S. Corbett, V. Major, C. Pretty, G. M. Shaw, and B. Benyo. The Clinical Utilisation of Respiratory Elastance Software (CURE Soft): a bedside software for real-time respiratory mechanics monitoring and mechanical ventilation management. Biomed. Eng. Online 13:140, 2014.
Funding was provided by NZ Tertiary Education Commission (TEC) fund MedTech CoRE (Grant No. E6391), NZ National Science Challenge 7, Science for Technology and Innovation (Grant No. E6525), Engineering Technology-based Innovation in Medicine (eTIME) consortium grant (eTIME 318943) and EU FP7 International Research Staff Exchange Scheme (IRSES) grant (#PIRSES-GA-2012-318943).
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Associate Editor Stefan M. Duma oversaw the review of this article.
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Morton, S.E., Knopp, J.L., Chase, J.G. et al. Authors’ Response to Drs. Ece Salihoglu and Ziya Salihoglu’s Letter to the Editor. Ann Biomed Eng 48, 2–3 (2020). https://doi.org/10.1007/s10439-019-02339-5