Estimation of Asynchrony Events with Negative Elastance in Spontaneously Breathing Mechanically Ventilated Patients in ICU

Abstract

Most mathematical models were developed to guide clinicians in managing patients who are mechanically ventilated (MV) in intensive care unit (ICU). However, asynchrony events (AE) could occur when a patient's breathing is not synchronized with the MV support, which is caused by spontaneously breathing (SB) effort or mismatch of inspiratory and expiratory timings of ventilator support even though the patients are fully sedated. One of the real metrics that can detect AEs in MV patients is through time varying elastance estimation. Previous studies found that SB patients developed a negative elastance as a result of the SB effort put forth by these patients. Hence, this study aims to estimate the AEs of MV patients by adding negative elastance (AUC Edrs_negative) in the model. Data were obtained from nine mechanically ventilated respiratory failure patients from the International Islamic University Malaysia (IIUM) Hospital. Asynchrony index (AInew) represents a total estimation of AEs and the negative elastance in MV patients. Patients’ data were classified by ventilation mode, and AInew was computed for each of the patients and compared with the previous methods in calculating the AI. The results show that the new modelbased technique in estimating the value of AInew has produced a higher value as compared to previous measurements of AIori as expected. Hence, this new measurement of AI has successfully shown that by adding AEs and AUC Edrs negative together, this model is more sensitive and precisely measures the AI especially during the synchronized intermittent mandatory ventilation (SIMV) mode. Thus, the estimation of AEs with negative elastance may aid clinicians in selecting the appropriate MV ventilation mode and allow for precise respiratory mechanics monitoring, especially in SB patients.