Abstract

Abstract Introduction Prediction of the clinical deterioration in hospitalized COVOD-19 patients is an unmet goal. Aim To assess monitoring of lung fluid status of hospitalized COVID-19 patients as a tool to predict clinical respiratory deterioration and prognosis. Methods The present study population comprised 51 patients hospitalized in our medical center with COVID-19 infection. The lung fluid status of patients was monitored by repeat measurements the lung impedance (LI). The LI technique was found to be a very effective tool for monitoring and guiding the treatment of a heart failure patients. Decreasing LI reflects lung fluid accumulation. Clinical and laboratory parameters, chest X-ray (CXR) and LI level were recorded during hospitalization. Results Of the 51 patients hospitalized for COVID-19 infection (37 men and 14 women, 55.7±12.6 years old), 46 were discharged after successful treatment (Group 1) and 5 (9.8%) died during hospitalization (Group 2). The LI kinetics during hospitalization demonstrated a different pattern between groups (Figure 1, p<0.01). In group 1 patients, a small LI decrease (−3.5±4.3%, p=0.7) during the first 4 days (median = 2.2 days, [Q1–3: 1–3.7 days]) of hospitalization was noted. Following this, LI increased progressively until discharge (+20.3±12.3%, p<0.01). Among group 2 patients, LI decreased progressively during hospitalization. Mechanical ventilation was initiated at the eighth day [median = 8, Q1–3: 4–12 days] when LI decreased by 18.2±3.8% in comparison with the admission level (p<0.01). Deaths occurred at 12.4±2.7 days (median = 12 days) after admission. Multivariate Cox regression analysis of clinical, laboratory and CXR variance has shown that the degree of LI decrease during hospitalization is the most reliable predictor of death (hazard ratio: 1.36 [1.04–1.79], p<0.04). Conclusions The combination of progressively decreasing LI after 4 days of hospitalization for COVID-19 infection and an LI decrease >15% is the most reliable predictor of death. Funding Acknowledgement Type of funding sources: None.

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