Perioperatives Flüssigkeitsmanagement – Abschätzung des Volumenstatus

Zusammenfassung

Die individuelle Reaktion eines Patienten auf eine Volumengabe lässt sich allein anhand der traditionellen kardialen Füllungsdrücke wie dem zentralen Venendruck nur unzureichend vorhersagen. Dynamische Variable der Volumenreagibilität wie die Pulsdruckvariation und die Schlagvolumenvariation unterscheiden hier mit deutlich höherer Sensitivität und Spezifität volumenbedürftige von nicht volumenbedürftigen Patienten, insbesondere im intraoperativen Bereich. Es gibt allerdings eine Reihe von klinischen Faktoren, die die prädiktiven Eigenschaften dieser Variablen beeinflussen können, was die Definition eines allgemein gültigen Schwellenwerts erschwert. Insofern muss man zur Abschätzung einer potenziellen Vorlastreserve im klinischen Alltag die wichtigsten Störgrößen und Einflussfaktoren der dynamischen Variablen kennen.

Abstract

Cardiac filling pressures alone are not appropriate to estimate the effect of a volume challenge on the corresponding change in stroke volume. Dynamic variables of fluid responsiveness have been shown to discriminate with acceptable sensitivity and specificity between responders and non-responders to a volume challenge. However, several clinical confounders have been indentified which potentially influence the predictive power of these variables. Sound knowledge of these confounders and the acknowledgement that there is no unique threshold value for volume optimisation but a considerable „gray zone“ is necessary to fully exploit the advantages of functional haemodynamic monitoring.

Kernaussagen

• Nur bei etwa 50 % unserer kritisch kranken Patienten kommt es auf eine definierte Volumengabe hin zu einer substanziellen Verbesserung des Herzzeitvolumens auf dem Boden eines optimierten Volumenmanagements.

• Statische kardiale Füllungsdrücke wie der zentrale Venendruck sind oft nicht geeignet, verlässlich Änderungen der kardialen Vorlast anzuzeigen.

• Wird der zentrale Venendruck trotz seiner Limitationen zum Monitoring eines optimierten Volumenmangements genutzt, sollte er in Kombination mit einem kontinuierlichen Verfahren zur Herzzeitvolumenmessung interpretiert werden.

• Mit dem global enddiastolischen Volumen steht eine statisch-volumetrische Variable zur Verfügung, die bei einer Vielzahl von Patienten Änderungen der kardialen Vorlast abbilden kann.

• Dynamische Variablen der Volumenreagibilität basieren auf beatmungsinduzierten intrathorakalen Druckänderungen, die zu zyklischen Änderungen der kardialen Vorlast mit konsekutiven zyklischen Änderungen des Schlagvolumens führen.

• Mithilfe der dynamischen Variablen kann unter Berücksichtigung der bekannten Limitationen verlässlicher als mit statischen Füllungsdrücken differenziert werden zwischen Patienten, die von einer Volumengabe profitieren, und Patienten, die nicht profitieren.

• Für die Pulsdruckvariation scheint es einen sog. „Grau-Zonen-Bereich“ zu geben, der zwischen 9–13 % liegt. 25 % der Patienten zeigen Werte in diesem Bereich, 50 % dieser Patienten sind volumenreagibel.

• Für die sichere Anwendung dynamischer Variablen im pädiatrischen Bereich gibt es noch zu wenige und zu kontroverse Untersuchungen, sodass eine Empfehlung hier nicht abgegeben werden kann.

• Mit dem Pleth-Variability-Index steht eine komplett nicht invasive dynamische Variable zur Verfügung, die in ihrer Genauigkeit von einem ungestörten peripheren Perfusionsindex abhängt.

• Theoretische Überlegungen und vergleichende Untersuchungen mit statischen Vorlastparametern legen nahe, dass – unter Berücksichtigung der korrekten Indikationen und der Limitationen – mittels funktionellen hämodynamischen Monitorings ein optimiertes Volumenmanagement erreicht werden kann. Adäquat gepowerte Untersuchungen, die diesen theoretischen Vorteil anhand eines verbesserten Patientenoutcomes auch praktisch nachweisen, liegen bislang allerdings nicht vor.

Schlüsselwörter

Flüssigkeitsmanagement - Volumenreagibilität - Vorlast - Monitoring - dynamische Variablen

Keywords

Fluid management - fluid responsiveness - preload - monitoring - dynamic variables

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