Background Surges of COVID-19 infections have led to insufficient supply of mechanical ventilators (MV), resulting in rationing of MV care. In-parallel, co-mechanical ventilation (Co-MV) of multiple patients is a potential solution. However, due to lack of testing, there is currently no means to match ventilation requirements or patients, with no guidelines to date. In this research, we have developed a model-based method for patient matching for pressure control mode MV. Methods The model-based method uses a single-compartment lung model (SCM) to simulate the resultant tidal volume of patient pairs at a set ventilation setting. If both patients meet specified safe ventilation criteria under similar ventilation settings, the actual mechanical ventilator settings for Co-MV are determined via simulation using a double-compartment lung model (DCM). This method allows clinicians to analyse Co-MV in silico, before clinical implementation. Results The proposed method demonstrates successful patient matching and MV setting in a model-based simulation as well as good discrimination to avoid mismatched patient pairs. The pairing process is based on model-based, patient-specific respiratory mechanics identified from measured data to provide useful information for guiding care. Specifically, the matching is performed via estimation of MV delivered tidal volume (mL/kg) based on patient-specific respiratory mechanics. This information can provide insights for the clinicians to evaluate the subsequent effects of Co-MV. In addition, it was also found that Co-MV patients with highly restrictive respiratory mechanics and obese patients must be performed with extra care. Conclusion This approach allows clinicians to analyse patient matching in a virtual environment without patient risk. The approach is tested in simulation, but the results justify the necessary clinical validation in human trials. Supplementary Information The online version contains supplementary material available at 10.1186/s12938-022-00983-y.
【저자키워드】 Decision support, Parallel ventilation, Co-ventilation, Model-based method, 【초록키워드】 Ventilation, lung, risk, in silico, COVID-19 infection, implementation, Research, Patient, mechanical ventilator, information, Care, patients, trials, Safe, criteria, Respiratory mechanics, Volume, supplementary material, clinician, Effect, approach, Result, resulting, tested, performed, lack, evaluate, subsequent, addition, obese patient, 【제목키워드】 Ventilation, Patient,