A review of hospital based ventilator malfunctions reported to the FDA in 2021

Ventilator care is synonymous with Intensive care. These devices are electromechanical and as such can fail. Most failures are without patient incident, injury, and harm. The FDA requires manufacturers who learn of malfunction, injury or death while operating their product to report to the agency via the Manufacturer and User Facility Device Experience database. I reviewed 500 recent events reported to the FDA and found an increasing trend from 2020 to 2021 in hospital ventilator malfunction reports. Examination of these reports is critical to assuring quality ventilator care. The author concluded that intensive training on the device characteristics and feature and a more rigorous examination of ventilator performance between patients may assist in reducing device malfunctions. Keywords: Mechanical ventilation, Ventilator malfunction, FDA

Scoring System to Evaluate the Performance of ICU Ventilators in the Pandemic of COVID-19: A Lung Model Study

Ventilators in the intensive care units (ICU) are life-support devices that help physicians to gain additional time to cure the patients. The aim of the study was to establish a scoring system to evaluate the ventilator performance in the context of COVID-19. The scoring system was established by weighting the ventilator performance on five different aspects: the stability of pressurization, response to leaks alteration, performance of reaction, volume delivery, and accuracy in oxygen delivery. The weighting factors were determined with analytic hierarchy process (AHP). Survey was sent out to 66 clinical and mechanical experts. The scoring system was built based on 54 valid replies. A total of 12 commercially available ICU ventilators providing non-invasive ventilation were evaluated using the novel scoring system. A total of eight ICU ventilators with non-invasive ventilation mode and four dedicated non-invasive ventilators were tested according to the scoring system. Four COVID-19 phenotypes were simulated using the ASL5000 lung simulator, namely (1) increased airway resistance (IR) (10 cm H2O/L/s), (2) low compliance (LC) (compliance of 20 ml/cmH2O), (3) low compliance plus increased respiratory effort (LCIE) (respiratory rate of 40 and inspiratory effort of 10 cmH2O), (4) high compliance (HC) (compliance of 50 ml/cmH2O). All of the ventilators were set to three combinations of pressure support and positive end-expiratory pressure levels. The data were collected at baseline and at three customized leak levels. Significant inaccuracies and variations in performance between different non-invasive ventilators were observed, especially in the aspect of leaks alteration, oxygen and volume delivery. Some ventilators have stable performance in different simulated phenotypes whereas the others have over 10% scoring differences. It is feasible to use the proposed scoring system to evaluate the ventilator performance. In the COVID-19 pandemic, clinicians should be aware of possible strengths and weaknesses of ventilators.

Patient-Ventilator Interaction Testing Using the Electro- mechanical Lung Simulator xPULM™during V/A-C and PSV Ventilation Mode

During mechanical ventilation, a disparity between flow, pressure or volume demands of the patient and the assistance delivered by the mechanical ventilator often occurs. Asynchrony effect and ventilator performance are frequently studied from ICU datasets or using commercially available lung simulators and test lungs. This paper introduces an alternative approach of simulating and evaluating patient-ventilator interactions with high fidelity using the electro-mechanical lung simulator xPULM™ under selected conditions. The xPULM™ approximates respiratory activities of a patient during alternating phases of spontaneous breathing and apnoea intervals while connected to a mechanical ventilator. Focusing on different triggering events, volume assist-controlled (V/A-C) and pressure support ventilation (PSV) modes were chosen to test patient-ventilator interactions. In V/A-C mode a double-triggering was detected every third breathing cycle leading to an asynchrony index of 16.67%, being classified as severe. This asynchrony causes a major increase of Peak Inspiratory Pressure PIP = 12.80 ± 1.39 cmH2O and Peak Expiratory Flow PEF = -18.33 ± 1.13 L/min when compared to synchronous phases of the breathing simulation. Additionally, events of premature cycling were observed during PSV mode. In this mode, the peak delivered volume during simulated spontaneous breathing phases almost doubles compared to apnoea phases. The presented approach demonstrates the possibility of simulating and evaluating disparities in fundamental ventilation characteristics caused by double-triggering and premature cycling under V/A-C and PSV ventilation modes. Various dynamic clinical situations can be approximated and could help to identify undesired patient-ventilation interactions in the future. Rapidly manufactured ventilator systems could also be tested using this approach.

Accuracy of the dynamic signal analysis approach in respiratory mechanics during noninvasive pressure support ventilation: a bench study

Objective To evaluate the accuracy of respiratory mechanics using dynamic signal analysis during noninvasive pressure support ventilation (PSV). Methods A Respironics V60 ventilator was connected to an active lung simulator to model normal, restrictive, obstructive, and mixed obstructive and restrictive profiles. The PSV was adjusted to maintain tidal volumes (VT) that achieved 5.0, 7.0, and 10.0 mL/kg body weight, and the positive end-expiration pressure (PEEP) was set to 5 cmH2O. Ventilator performance was evaluated by measuring the flow, airway pressure, and volume. The system compliance (Crs) and airway resistance (inspiratory and expiratory resistance, Rinsp and Rexp, respectively) were calculated. Results Under active breathing conditions, the Crs was overestimated in the normal and restrictive models, and it decreased with an increasing pressure support (PS) level. The Rinsp calculated error was approximately 10% at 10.0 mL/kg of VT, and similar results were obtained for the calculated Rexp at 7.0 mL/kg of VT. Conclusion Using dynamic signal analysis, appropriate tidal volume was beneficial for Rrs, especially for estimating Rexp during assisted ventilation. The Crs measurement was also relatively accurate in obstructive conditions.

NIV Is not Adequate for High Intensity Endurance Exercise in COPD

Noninvasive ventilation (NIV) during exercise has been suggested to sustain higher training intensity but the type of NIV interface, patient-ventilator asynchronies (PVA) or technological limitation of the ventilator may interfere with exercise. We assessed whether these parameters affect endurance exercise capacity in severe COPD patients. In total, 21 patients with severe COPD not eligible to home NIV performed three constant workload tests. The first test was carried out on spontaneous breathing (SB) and the following ones with NIV and a nasal or oronasal mask in a randomized order. PVA and indicators of ventilator performance were assessed through a comprehensive analysis of the flow pressure tracing raw data from the ventilator. The time limit was significantly reduced with both masks (406 s (197–666), 240 s (131–385) and 189 s (115–545), p < 0.01 for tests in SB, with oronasal and nasal mask, respectively). There were few PVA with an oronasal mask (median: 3.4% (1.7–5.2)) but the ventilator reached its maximal generating capacity (median flowmax: 208.0 L/s (189.5–224.8) while inspiratory pressure dropped throughout exercise (from 10.1 (9.4–11.4) to 8.8 cmH2O (8.6–10.8), p < 0.01). PVA were more frequent with nasal mask (median: 12.8% (3.2–31.6), p < 0.01). Particularly, the proportion of patients with ineffective efforts > 10% was significantly higher with nasal interface (0% versus 33.3%, p < 0.01). NIV did not effectively improve endurance capacity in COPD patients not acclimated to home NIV. This was due to a technological limitation of the ventilator for the oronasal mask and the consequence either of an insufficient pressure support or a technological limitation for the nasal mask.

Bench investigation of the accuracy of the dynamic approach in respiratory mechanics during noninvasive ventilation with different pressure support levels

Background: Under the dynamic conditions of non-invasive mechanical ventilation, respiratory system mechanics parameters, including compliance (Crs) and airway resistance (Rrs), are affected by systemic and ventilator parameters. We evaluated the accuracy of respiratory mechanics in the dynamic approach in different lung disease models during pressure support ventilation (PSV).Methods: A Respironics V60 ventilator was connected to an active lung simulator for modeling four profiles of respiratory mechanics: normal, restrictive, obstructive and mixed obstructive/restrictive. PSV and positive end-expiration pressure (PEEP) were 2-25 cmH2O and 5 cmH2O, respectively. Measurements were performed with an air leak of 25-28 L/min. Ventilator performance and patient-ventilator asynchrony were evaluated by measuring flow, airway pressure, and volume. Crs and inspiratory/expiratory resistance (Rinsp/Rexp) were calculated by dynamic approach. Results: Crs was overestimated with pressure support (PS) at 5 cmH2O. Peak inspiratory/expiratory flow (PIF/PEF) and tidal volume (VT) was increased with PS level, while calculated Crs was decreased. At PS 10-15 cmH2O, the difference between calculated and preset Crs was ≤20% in higher resistance models (obstructive and mixed). In normal resistance conditions (restrictive and normal), the calculated Crs was always larger than the preset value significantly regardless of PS. Underestimations of Rinsp and Rexp were observed at PS 5-10 cmH2O. The calculation error might be controlled within 10% when PS above 15 cmH2O in higher resistance models. Conclusion: Higher gas flow is beneficial for Rrs estimation by using dynamic approach, whereas the calculation of Crs is always overestimated in normal resistance conditions.