Association between respiratory distress time and invasive mechanical ventilation in COVID-19 patients: A multicentre regional cohort study.

AIM: To determine whether the duration of respiratory distress symptoms in severe COVID-19 pneumonia affects the need for invasive mechanical ventilation and clinical outcomes. MATERIALS AND METHODS: An observational multicentre cohort study of patients hospitalised in five COVID-19-designated ICUs of the University Hospitals of Emilia-Romagna Region. Patients included were adults with pneumonia due to SARS-CoV-2 with PaO2/FiO2 ratio <300 mmHg, respiratory distress symptoms, and need for mechanical ventilation (invasive or non-invasive). Exclusion criteria were an uncertain time of respiratory distress, end-of-life decision, and mechanical respiratory support before hospital admission. MEASUREMENTS AND MAIN RESULTS: We analysed 171 patients stratified into tertiles according to respiratory distress duration (distress time, DT) before application of mechanical ventilation support. The rate of patients requiring invasive mechanical ventilation was significantly different (p < 0.001) among the tertiles: 17/57 patients in the shortest duration, 29/57 in the intermediate duration, and 40/57 in the longest duration. The respiratory distress time significantly increased the risk of invasive ventilation in the univariate analysis (OR 5.5 [CI 2.48-12.35], p = 0.003). Multivariable regression analysis confirmed this association (OR 10.7 [CI 2.89-39.41], p < 0.001). Clinical outcomes (mortality and hospital stay) did not show significant differences between DT tertiles. DISCUSSION: Albeit preliminary and retrospective, our data raised the hypothesis that the duration of respiratory distress symptoms may play a role in COVID-19 patients' need for invasive mechanical ventilation. Furthermore, our observations suggested that specific strategies may be directed towards identifying and managing early symptoms of respiratory distress, regardless of the levels of hypoxemia and the severity of the dyspnoea itself.

Monitoring lung impedance changes during long-term ventilator-induced lung injury ventilation using electrical impedance tomography.

OBJECTIVE: The target of this methodological evaluation was the feasibility of long-term monitoring of changes in lung conditions by time-difference electrical impedance tomography (tdEIT). In contrast to ventilation monitoring by tdEIT, the monitoring of end-expiratory (EELIC) or end-inspiratory (EILIC) lung impedance change always requires a reference measurement. APPROACH: To determine the stability of the used Pulmovista 500® EIT system, as a prerequisite it was initially secured on a resistive phantom for 50 h. By comparing the slopes of EELIC for the whole lung area up to 48 h from 36 pigs ventilated at six positive end-expiratory pressure (PEEP) levels from 0 to 18 cmH2O we found a good agreement (range of r 2 = 0.93-1.0) between absolute EIT (aEIT) and tdEIT values. This justified the usage of tdEIT with its superior local resolution compared to aEIT for long-term determination of EELIC. MAIN RESULTS: The EELIC was between -0.07 Ωm day-1 at PEEP 4 and -1.04 Ωm day-1 at PEEP 18 cmH2O. The complex local time pattern for EELIC was roughly quantified by the new parameter, centre of end-expiratory change (CoEEC), in equivalence to the established centre of ventilation (CoV). The ventrally located mean of the CoV was fairly constant in the range of 42%-46% of thorax diameter; however, on the contrary, the CoEEC shifted from about 40% to about 75% in the dorsal direction for PEEP levels of 14 and 18 cmH2O. SIGNIFICANCE: The observed shifts started earlier for higher PEEP levels. Changes of EELI could be precisely monitored over a period of 48 h by tdEIT on pigs.

Ventilator-related causes of lung injury: the mechanical power.

PURPOSE: We hypothesized that the ventilator-related causes of lung injury may be unified in a single variable: the mechanical power. We assessed whether the mechanical power measured by the pressure-volume loops can be computed from its components: tidal volume (TV)/driving pressure (∆P aw), flow, positive end-expiratory pressure (PEEP), and respiratory rate (RR). If so, the relative contributions of each variable to the mechanical power can be estimated. METHODS: We computed the mechanical power by multiplying each component of the equation of motion by the variation of volume and RR: [Formula: see text]where ∆V is the tidal volume, ELrs is the elastance of the respiratory system, I:E is the inspiratory-to-expiratory time ratio, and R aw is the airway resistance. In 30 patients with normal lungs and in 50 ARDS patients, mechanical power was computed via the power equation and measured from the dynamic pressure-volume curve at 5 and 15 cmH2O PEEP and 6, 8, 10, and 12 ml/kg TV. We then computed the effects of the individual component variables on the mechanical power. RESULTS: Computed and measured mechanical powers were similar at 5 and 15 cmH2O PEEP both in normal subjects and in ARDS patients (slopes = 0.96, 1.06, 1.01, 1.12 respectively, R (2) > 0.96 and p < 0.0001 for all). The mechanical power increases exponentially with TV, ∆P aw, and flow (exponent = 2) as well as with RR (exponent = 1.4) and linearly with PEEP. CONCLUSIONS: The mechanical power equation may help estimate the contribution of the different ventilator-related causes of lung injury and of their variations. The equation can be easily implemented in every ventilator's software.