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Erschienen in: Journal of Clinical Monitoring and Computing 4/2021

28.01.2021 | Editorial

Blood pressure stability: a road to better outcomes

verfasst von: Kamal Maheshwari

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 4/2021

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Excerpt

Maintaining hemodynamic stability is emphasized as an important goal during anesthesia training. Stable blood pressure exemplified by the “railroad track” blood pressure recordings in anesthesia chart is equated with high quality anesthesia delivery. However, the relationship between blood pressure stability during surgery and the postoperative outcome is unclear. For example, we know that low blood pressure during surgery [1] and in critically ill patients [2] is associated with worse outcomes, thus should be avoided. But the defintion of blood pressure stability is unclear. Patients with stable blood pressure can be identified if they have low blood pressure variability measured by; standard deviation, coefficient of variation, average real variability, or generalized average real variability. Nevertheless, in this issue, Yoon et al. [3] calculated blood pressure stability using performance measurement of MAP (mean arterial pressure) using median performance error (MDPE) and median absolute performance error (MDAPE), and wobble, using preoperative blood pressure as a reference value. MDPE is a measure of bias, in this case how far the intraoperative blood pressure deviated from baseline blood pressure. MDAPE is a measure of accuracy, in this case closeness of the measured intraoperative blood pressure to the baseline.  Infact, wobble is a measure of MAP varibaility independant of baseline pressure. The use of performance measurement is interesting, which otherwise is commonly used in pharmacokinetic studies to measure difference in predicted and actual concentration. …
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Metadaten
Titel
Blood pressure stability: a road to better outcomes
verfasst von
Kamal Maheshwari
Publikationsdatum
28.01.2021
Verlag
Springer Netherlands
Erschienen in
Journal of Clinical Monitoring and Computing / Ausgabe 4/2021
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-021-00659-3

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