Background: Health-related quality of life (HRQoL) impairment is often reported among COVID-19 ICU survivors, and little is known about their long-term outcomes. We evaluated the HRQoL trajectories between 3 months and 1 year after ICU discharge, the factors influencing these trajectories and the presence of clusters of HRQoL profiles in a population of COVID-19 patients who underwent invasive mechanical ventilation (IMV). Moreover, pathophysiological correlations of residual dyspnea were tested. Methods: We followed up 178 survivors from 16 Italian ICUs up to one year after ICU discharge. HRQoL was investigated through the 15D instrument. Available pulmonary function tests (PFTs) and chest CT scans at 1 year were also collected. A linear mixed-effects model was adopted to identify factors associated with different HRQoL trajectories and a two-step cluster analysis was performed to identify HRQoL clusters. Results: We found that HRQoL increased during the study period, especially for the significant increase of the physical dimensions, while the mental dimensions and dyspnea remained substantially unchanged. Four main 15D profiles were identified: full recovery (47.2%), bad recovery (5.1%) and two partial recovery clusters with mostly physical (9.6%) or mental (38.2%) dimensions affected. Gender, duration of IMV and number of comorbidities significantly influenced HRQoL trajectories. Persistent dyspnea was reported in 58.4% of patients, and weakly, but significantly, correlated with both DLCO and length of IMV. Conclusions: HRQoL impairment is frequent 1 year after ICU discharge, and the lowest recovery is found in the mental dimensions. Persistent dyspnea is often reported and weakly correlated with PFTs alterations. Trial registration: NCT04411459. 15D score 3 months -mean ± SD 0.857 ± 0.133 0.927 ± 0.061 0.800 ± 0.135 0.853 ± 0.114 0.637 ± 0.204 < 0.001 15D score 1 year -mean ± SD 0.880 ± 0.115 0.964 ± 0.033 0.820 ± 0.068 0.866 ± 0.088 0.572 ± 0.112 < 0.001 Mobility -mean ± SD 0.876 ± 0.207 0.963 ± 0.104 0.828 ± 0.191 0.901 ± 0.166 0.375 ± 0.298 < 0.001 Vision -mean ± SD 0.953 ± 0.119 0.992 ± 0.040 0.942 ± 0.108 0.949 ± 0.094 0.681 ± 0.280 < 0.001 Hearing -mean ± SD 0.968 ± 0.098 1.000 ± 0.000 1.000 ± 0.000 0.745 ± 0.135 0.857 ± 0.192 < 0.001 Breathing -mean ± SD 0.746 ± 0.238 0.879 ± 0.154 0.620 ± 0.227 0.753 ± 0.223 0.438 ± 0.238 < 0.001 Sleeping -mean ± SD 0.838 ± 0.238 0.940 ± 0.135 0.716 ± 0.274 0.929 ± 0.142 0.632 ± 0.312 < 0.001 Eating -mean ± SD 0.979 ± 0.102 1.000 ± 0.000 1 .000 ± 0.000 1.000 ± 0.000 0.587 ± 0.221 < 0.001 Speech -mean ± SD 0.980 ± 0.090 0.996 ± 0.032 0.996 ± 0.036 0.948 ± 0.117 0.777 ± 0.276 < 0.001 Excretion -mean ± SD 0.974 ± 0.110 1.000 ± 0.000 1.000 ± 0.000 0.872 ± 0.191 0.720 ± 0.292

Up to fifteen percent of patients with novel pandemic coronavirus disease have acute respiratory failure (ARF). Ratio between arterial partial pressure of oxygen (PaO2) and fraction of inspired oxygen (FiO2), P/F, is currently used as a marker of ARF severity in Covid-19. P/F does not reflect the respiratory efforts made by patients to maintain arterial blood oxygenation, such as tachypnea and hyperpnea, leading to hypocapnia. Standard PaO2, the value of PaO2 adjusted for arterial partial pressure of carbon dioxide (PaCO2) of the subject, better reflects the pathophysiology of hypoxemic ARF. We hypothesized that the ratio between standard PaO2 over FiO2 (STP/F) better predicts Covid-19 ARF severity compared to P/F. Methods: Aim of this pilot prospectic observational study was to observe differences between STP/F and P/F in predicting outcome failure, defined as need of invasive mechanical ventilation and/or deaths in Covid-19 ARF. Accuracy was calculated using Receiver Operating Characteristics (ROC) analysis and areas under the ROC curve (AUROC) were compared. Results: 349 consecutive subjects admitted to our respiratory wards due to Covid-19 ARF were enrolled. STP/F was accurate to predict mortality and superior to P/F with, respectively, AUROC 0.710 versus 0.688, p = 0.012. Both STP/F and PF were accurate to predict outcome failure (AUROC respectively of 0.747 and 0.742, p = 0.590).

No abstract