Comparison of optimization parametrizations for regional lung compliance estimation using personalized pulmonary poromechanical modeling.

Interstitial lung diseases, such as idiopathic pulmonary fibrosis (IPF) or post-COVID-19 pulmonary fibrosis, are progressive and severe diseases characterized by an irreversible scarring of interstitial tissues that affects lung function. Despite many efforts, these diseases remain poorly understood and poorly treated. In this paper, we propose an automated method for the estimation of personalized regional lung compliances based on a poromechanical model of the lung. The model is personalized by integrating routine clinical imaging data - namely computed tomography images taken at two breathing levels in order to reproduce the breathing kinematic-notably through an inverse problem with fully personalized boundary conditions that is solved to estimate patient-specific regional lung compliances. A new parametrization of the inverse problem is introduced in this paper, based on the combined estimation of a personalized breathing pressure in addition to material parameters, improving the robustness and consistency of estimation results. The method is applied to three IPF patients and one post-COVID-19 patient. This personalized model could help better understand the role of mechanics in pulmonary remodeling due to fibrosis; moreover, patient-specific regional lung compliances could be used as an objective and quantitative biomarker for improved diagnosis and treatment follow up for various interstitial lung diseases.

Recommended Approaches to Minimize Aerosol Dispersion of SARS-CoV-2 During Noninvasive Ventilatory Support Can Cause Ventilator Performance Deterioration: A Benchmark Comparative Study.

BACKGROUND: SARS-CoV-2 aerosolization during noninvasive positive-pressure ventilation may endanger health care professionals. Various circuit setups have been described to reduce virus aerosolization. However, these setups may alter ventilator performance. RESEARCH QUESTION: What are the consequences of the various suggested circuit setups on ventilator efficacy during CPAP and noninvasive ventilation (NIV)? STUDY DESIGN AND METHODS: Eight circuit setups were evaluated on a bench test model that consisted of a three-dimensional printed head and an artificial lung. Setups included a dual-limb circuit with an oronasal mask, a dual-limb circuit with a helmet interface, a single-limb circuit with a passive exhalation valve, three single-limb circuits with custom-made additional leaks, and two single-limb circuits with active exhalation valves. All setups were evaluated during NIV and CPAP. The following variables were recorded: the inspiratory flow preceding triggering of the ventilator, the inspiratory effort required to trigger the ventilator, the triggering delay, the maximal inspiratory pressure delivered by the ventilator, the tidal volume generated to the artificial lung, the total work of breathing, and the pressure-time product needed to trigger the ventilator. RESULTS: With NIV, the type of circuit setup had a significant impact on inspiratory flow preceding triggering of the ventilator (P < .0001), the inspiratory effort required to trigger the ventilator (P < .0001), the triggering delay (P < .0001), the maximal inspiratory pressure (P < .0001), the tidal volume (P = .0008), the work of breathing (P < .0001), and the pressure-time product needed to trigger the ventilator (P < .0001). Similar differences and consequences were seen with CPAP as well as with the addition of bacterial filters. Best performance was achieved with a dual-limb circuit with an oronasal mask. Worst performance was achieved with a dual-limb circuit with a helmet interface. INTERPRETATION: Ventilator performance is significantly impacted by the circuit setup. A dual-limb circuit with oronasal mask should be used preferentially.

The Affinity of Hemoglobin for Oxygen Is Not Altered During COVID-19.

Background: A computational proteomic analysis suggested that SARS-CoV-2 might bind to hemoglobin (Hb). The authors hypothesized that this phenomenon could result in a decreased oxygen (O2) binding and lead to hemolytic anemia as well. The aim of this work was to investigate whether the affinity of Hb for O2 was altered during COVID-19. Methods: In this retrospective, observational, single-center study, the blood gas analyses of 100 COVID-19 patients were compared to those of 100 non-COVID-19 patients. Fifty-five patients with carboxyhemoglobin (HbCO) ≥8% and 30 with sickle cell disease (SCD) were also included ("positive controls" with abnormal Hb affinity). P50 was corrected for body temperature, pH, and PCO2. Results: Patients did not differ statistically for age or sex ratio in COVID-19 and non-COVID-19 groups. Median P50 at baseline was 26 mmHg [25.2-26.8] vs. 25.9 mmHg [24-27.3], respectively (p = 0.42). As expected, P50 was 22.5 mmHg [21.6-23.8] in the high HbCO group and 29.3 mmHg [27-31.5] in the SCD group (p < 0.0001). Whatever the disease severity, samples from COVID-19 to non-COVID-19 groups were distributed on the standard O2-Hb dissociation curve. When considering the time-course of P50 between days 1 and 18 in both groups, no significant difference was observed. Median Hb concentration at baseline was 14 g.dl-1 [12.6-15.2] in the COVID-19 group vs. 13.2 g.dl-1 [11.4-14.7] in the non-COVID-19 group (p = 0.006). Among the 24 COVID-19 patients displaying anemia, none of them exhibited obvious biological hemolysis. Conclusion: There was no biological argument to support the hypothesis that SARS-CoV-2 could alter O2 binding to Hb.

Environmental contamination related to SARS-CoV-2 in ICU patients.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is a primary global concern, and data are lacking concerning risk of novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) environmental contamination. OBJECTIVE: To identify risk factors for SARS-CoV-2 environmental contamination in COVID-19 patients admitted to the intensive care unit (ICU). METHODS: A prospective single centre 1-day study was carried out in an ICU. Four surfaces (the ventilator control screen, the control buttons of the syringe pump, the bed rails and the computer table located >1 m away from the patient) were systematically swabbed at least 8 h after any cleaning process. We analysed clinical, microbiological and radiological data to identify risk factors for SARS-CoV-2 environmental contamination. RESULTS: 40% of ICU patients were found to contaminate their environment. No particular trend emerged regarding the type of surface contaminated. Modality of oxygen support (high-flow nasal cannula oxygenation, invasive mechanical ventilation, standard oxygen mask) was not associated with the risk of environmental contamination. Univariate analysis showed that lymphopenia <0.7×109·L-1 was associated with environmental contamination. CONCLUSION: Despite small sample size, our study generated surprising results. Modality of oxygen support is not associated with risk of environmental contamination. Further studies are needed.