Use of a Single Ventilator to Support Multiple Patients: Modeling Tidal Volume Response to Heterogeneous Lung Mechanics

  1. Vitaly O. Kheyfets
  2. Steven Lammers
  3. Jennifer Wagner
  4. Karsten Bartels
  5. Bradford Smith

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Abstract

The COVID-19 pandemic is creating ventilator shortages in many countries that is sparking a conversation about placing multiple people on a single ventilator. However, on March 26 th the American College of Chest Physicians (CHEST), along with other leading medical organizations, released a joint statement warning clinicians that attempting this technique could lead to poor outcomes and high mortality. Nevertheless, several hospitals around the United States and abroad are turning to this technique out of desperation (e.g. New York), but little data exists to guide their approach. The overall objective of this study is to utilize a computational model of mechanically ventilated lungs to assess how patient-specific lung mechanics and ventilator settings impact lung tidal volume (Vt).

Methods

We developed a single compartment computational model of four patients connected to a shared ventilator and validated it against a similar experimental study. We used this model to evaluate how patient-specific lung compliance (C) and resistance (R) would impact Vt under 5 ventilator settings of pre-set PIP, PEEP, and I:E ratio (suggested by Farkas, J.D. MD as an approach by hospitals to manage multiple patients on a single ventilator).

Results

Our computational model predicts Vt within 10% of experimental measurements. Using this model to perform a parametric study, we provide proof-of-concept for an algorithm to better match patients in different hypothetical scenarios of a single ventilator shared by more than one patient.

Conclusions

Assigning patients to pre-set ventilators based on their lung mechanics could be used to overcome some of the legitimate concerns of placing multiple patients on a single ventilator. We emphasize that our results are currently based on a computational model that has not been validated against any pre-clinical/clinical data. Therefore, clinicians considering this approach should not look to our study as an exact estimate of predicted patient tidal volumes.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.07.20056671: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    Our simulations may provide guidance to refining this protocol and further insights into some of these concerns (insight into those concerns provided by our simulations are provided in italics): We also propose two additional factors that must be considered when placing multiple patients on a single ventilator: Limitations: The serious clinical limitations of utilizing a single ventilator for 4 patients has been extensively outlined in previous clinical and experimental studies 2,4,7,8. Therefore, this manuscript will focus on the present limitations of our study. Our overall objective is to provide a proof-of-concept graphic reference (see Fig. 3) for choosing the proper ventilator (or ventilator settings) using a computational model for a hypothetical patient with known lung compliance (C) and resistance (R), to achieve a desired Vt. In some clinics, acquiring patient-specific R and C values may not be possible. Furthermore, even in cases where patient specific R and C values are available, these values are likely to vary in a patient as his/her conditions improves or deteriorates. Therefore, it would have to be continuously re-evaluated based on clinical recommendations. Some centers routinely change from supine to prone positioning during ventilation, which could drastically change the patient’s R and C values. In fact, recent studies with an admittedly small sample size have shown anecdotal data that alternating body positioning improved recruitability in COVID-19 patien...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

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  2. Version published to 10.1101/2020.04.07.20056671v1 on medRxiv