Clinical validation of a computerized algorithm to determine mean systemic filling pressure.

Autor: Meijs LPB; Department of Intensive Care, Catharina Hospital, Eindhoven, The Netherlands. cardiology.intensivecare@gmail.com.; Department of Cardiology, Catharina Hospital, Eindhoven, The Netherlands. cardiology.intensivecare@gmail.com., van Houte J; Department of Intensive Care, Catharina Hospital, Eindhoven, The Netherlands.; Department of Anesthesiology, Catharina Hospital, Eindhoven, The Netherlands., Conjaerts BCM; Department of Anesthesiology, Maastricht University Medical Center, Maastricht, The Netherlands., Bindels AJGH; Department of Intensive Care, Catharina Hospital, Eindhoven, The Netherlands., Bouwman A; Department of Anesthesiology, Catharina Hospital, Eindhoven, The Netherlands., Houterman S; Department of Research and Education, Catharina Hospital, Eindhoven, The Netherlands., Bakker J; Department of Intensive Care, Erasmus MC University Medical Centre, Rotterdam, The Netherlands.; Division of Pulmonary, Allergy, and Critical Care Medicine, Columbia University Medical Center, New York, NY, USA.; Department of Pulmonary and Critical Care, New York University, New York, NY, USA.; Department of Intensive Care, Pontificia Universidad Católica de Chile, Santiago, Chile.
Jazyk: angličtina
Zdroj: Journal of clinical monitoring and computing [J Clin Monit Comput] 2022 Feb; Vol. 36 (1), pp. 191-198. Date of Electronic Publication: 2021 Mar 31.
DOI: 10.1007/s10877-020-00636-2
Abstrakt: Mean systemic filling pressure (Pms) is a promising parameter in determining intravascular fluid status. Pms derived from venous return curves during inspiratory holds with incremental airway pressures (Pms-Insp) estimates Pms reliably but is labor-intensive. A computerized algorithm to calculate Pms (Pmsa) at the bedside has been proposed. In previous studies Pmsa and Pms-Insp correlated well but with considerable bias. This observational study was performed to validate Pmsa with Pms-Insp in cardiac surgery patients. Cardiac output, right atrial pressure and mean arterial pressure were prospectively recorded to calculate Pmsa using a bedside monitor. Pms-Insp was calculated offline after performing inspiratory holds. Intraclass-correlation coefficient (ICC) and assessment of agreement were used to compare Pmsa with Pms-Insp. Bias, coefficient of variance (COV), precision and limits of agreement (LOA) were calculated. Proportional bias was assessed with linear regression. A high degree of inter-method reliability was found between Pmsa and Pms-Insp (ICC 0.89; 95%CI 0.72-0.96, p = 0.01) in 18 patients. Pmsa and Pms-Insp differed not significantly (11.9 mmHg, IQR 9.8-13.4 vs. 12.7 mmHg, IQR 10.5-14.4, p = 0.38). Bias was -0.502 ± 1.90 mmHg (p = 0.277). COV was 4% with LOA -4.22 - 3.22 mmHg without proportional bias. Conversion coefficient Pmsa ➔ Pms-Insp was 0.94. This assessment of agreement demonstrates that the measures Pms-Insp and the computerized Pmsa-algorithm are interchangeable (bias -0.502 ± 1.90 mmHg with conversion coefficient 0.94). The choice of Pmsa is straightforward, it is non-interventional and available continuously at the bedside in contrast to Pms-Insp which is interventional and calculated off-line. Further studies should be performed to determine the place of Pmsa in the circulatory management of critically ill patients. ( www.clinicaltrials.gov ; TRN NCT04202432, release date 16-12-2019; retrospectively registered).Clinical Trial Registration www.ClinicalTrials.gov , TRN: NCT04202432, initial release date 16-12-2019 (retrospectively registered).
(© 2021. The Author(s).)
Databáze: MEDLINE
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