Central venous pressure swing outperforms diaphragm ultrasound as a measure of inspiratory effort during pressure support ventilation in COVID-19 patients

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Abstract

Purpose: The COVID-19-related shortage of ICU beds magnified the need of tools to properly titrate the ventilator assistance. We investigated whether bedside-available indices such as the ultrasonographic changes in diaphragm thickening ratio (TR) and the tidal swing in central venous pressure (ΔCVP) are reliable estimates of inspiratory effort, assessed as the tidal swing in esophageal pressure (ΔPes). Methods: Prospective, observational clinical investigation in the intensive care unit of a tertiary care Hospital. Fourteen critically-ill patients were enrolled (age 64 ± 7 years, BMI 29 ± 4 kg/m2), after 6 [3; 9] days from onset of assisted ventilation. A three-level pressure support trial was performed, at 10 (PS10), 5 (PS5) and 0 cmH2O (PS0). In each step, the esophageal and central venous pressure tidal swing were recorded, as well as diaphragm ultrasound. Results: The reduction of pressure support was associated with an increased respiratory rate and a reduced tidal volume, while minute ventilation was unchanged. ΔPes significantly increased with reducing support (5 [3; 8] vs. 8 [14; 13] vs. 12 [6; 16] cmH2O, p < 0.0001), as did the diaphragm TR (9.2 ± 6.1 vs. 17.6 ± 7.2 vs. 28.0 ± 10.0%, p < 0.0001) and the ΔCVP (4 [3; 7] vs. 8 [5; 9] vs. 10 [7; 11] cmH2O, p < 0.0001). ΔCVP was significantly associated with ΔPes (R2 = 0.810, p < 0.001), as was diaphragm TR, albeit with a lower coefficient of determination (R2 = 0.399, p < 0.001). Conclusions: In patients with COVID-19-associated respiratory failure undergoing assisted mechanical ventilation, ΔCVP is a better estimate of inspiratory effort than diaphragm ultrasound.

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Lassola, S., Miori, S., Sanna, A., Cucino, A., Magnoni, S., & Umbrello, M. (2022). Central venous pressure swing outperforms diaphragm ultrasound as a measure of inspiratory effort during pressure support ventilation in COVID-19 patients. Journal of Clinical Monitoring and Computing, 36(2), 461–471. https://doi.org/10.1007/s10877-021-00674-4

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