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Individualized goal directed perioperative care - the way to go!

Molnár Z - Front Med (Lausanne) (2015)

View Article: PubMed Central - PubMed

Affiliation: Department of Anaesthesiology and Intensive Therapy, Faculty of Medicine, University of Szeged , Szeged , Hungary.

ABSTRACT

There is increasing evidence that interventions based on multimodal monitoring of physiological and biochemical processes in the high-risk patients, let it be in the perioperative or critical care setting, may improve outcome. Advanced knowledge accompanied and reinforced by technical developments of continuous real time monitoring of organ function and molecular mechanisms give firm ground for utilizing them as a “goal directed individualized” approach, which may replace “figure-driven” protocolized care in the future.

No MeSH data available.


Related in: MedlinePlus

Assessing fluid responsiveness with stroke volume variation (SVV) in patients with different Frank–Starling curves. The upper curve (——) represents the Frank–Starling curve of a patient with normal heart, the lower curve (– – –) a patient with chronic heart failure. Intermittent positive pressure ventilation (IPPV) causes a similar changes in ventricular preload (A–B) in both cases. However, in the patient who is on the flat part on the Frank–Starling curve IPPV causes small stroke volume variation (SVV1), hence this patient would not respond for fluid administration with an increase in stroke volume. On the contrary, in the other case, the patient is on the steep part of the curve have large changes in stroke volume (SVV2), indicating fluid responsiveness.
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Figure 1: Assessing fluid responsiveness with stroke volume variation (SVV) in patients with different Frank–Starling curves. The upper curve (——) represents the Frank–Starling curve of a patient with normal heart, the lower curve (– – –) a patient with chronic heart failure. Intermittent positive pressure ventilation (IPPV) causes a similar changes in ventricular preload (A–B) in both cases. However, in the patient who is on the flat part on the Frank–Starling curve IPPV causes small stroke volume variation (SVV1), hence this patient would not respond for fluid administration with an increase in stroke volume. On the contrary, in the other case, the patient is on the steep part of the curve have large changes in stroke volume (SVV2), indicating fluid responsiveness.

Mentions: According to the survey by Cannesson et al., dynamic indices such as SVV, pulse pressure variation (PPV) are only applied in 6–25% during anesthesia for high-risk surgery (2). Heart–lung interactions during forced expiration against closed glottis, which was first described by Antonio Mario Valsalva almost 300 years ago, form the principle of SVV/PPV phenomena. Intermittent positive pressure ventilation can be regarded as a series of Valsalva-maneuvers: large enough tidal volumes of ~8 mL/kg of ideal bodyweight (17), will cause decreased venous return, hence a drop in stroke volume, which can be detected by SVV/PPV. If the circulation is well filled the variation is small, while on the contrary, increased variation means hypovolemia (Figure 1). It is also important to acknowledge that patients have different types of Frank–Starling curves. This is why set figures of “static” preload indices, such as CVP, cannot indicate fluid responsiveness, also demonstrated in Figure 1 (18). Indeed, the variation in PPV induced by mechanical ventilation has been shown to be a very accurate predictor of fluid responsiveness, with an optimal threshold value around 12% (19). However, PPV/SVV based approaches have some limitations: it requires controlled ventilation with tidal volumes above the “protective” 6 mL/kg tidal volumes, and in the case of spontaneous breathing or breathing efforts and cardiac arrhythmias values cannot be relied on.


Individualized goal directed perioperative care - the way to go!

Molnár Z - Front Med (Lausanne) (2015)

Assessing fluid responsiveness with stroke volume variation (SVV) in patients with different Frank–Starling curves. The upper curve (——) represents the Frank–Starling curve of a patient with normal heart, the lower curve (– – –) a patient with chronic heart failure. Intermittent positive pressure ventilation (IPPV) causes a similar changes in ventricular preload (A–B) in both cases. However, in the patient who is on the flat part on the Frank–Starling curve IPPV causes small stroke volume variation (SVV1), hence this patient would not respond for fluid administration with an increase in stroke volume. On the contrary, in the other case, the patient is on the steep part of the curve have large changes in stroke volume (SVV2), indicating fluid responsiveness.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4389568&req=5

Figure 1: Assessing fluid responsiveness with stroke volume variation (SVV) in patients with different Frank–Starling curves. The upper curve (——) represents the Frank–Starling curve of a patient with normal heart, the lower curve (– – –) a patient with chronic heart failure. Intermittent positive pressure ventilation (IPPV) causes a similar changes in ventricular preload (A–B) in both cases. However, in the patient who is on the flat part on the Frank–Starling curve IPPV causes small stroke volume variation (SVV1), hence this patient would not respond for fluid administration with an increase in stroke volume. On the contrary, in the other case, the patient is on the steep part of the curve have large changes in stroke volume (SVV2), indicating fluid responsiveness.
Mentions: According to the survey by Cannesson et al., dynamic indices such as SVV, pulse pressure variation (PPV) are only applied in 6–25% during anesthesia for high-risk surgery (2). Heart–lung interactions during forced expiration against closed glottis, which was first described by Antonio Mario Valsalva almost 300 years ago, form the principle of SVV/PPV phenomena. Intermittent positive pressure ventilation can be regarded as a series of Valsalva-maneuvers: large enough tidal volumes of ~8 mL/kg of ideal bodyweight (17), will cause decreased venous return, hence a drop in stroke volume, which can be detected by SVV/PPV. If the circulation is well filled the variation is small, while on the contrary, increased variation means hypovolemia (Figure 1). It is also important to acknowledge that patients have different types of Frank–Starling curves. This is why set figures of “static” preload indices, such as CVP, cannot indicate fluid responsiveness, also demonstrated in Figure 1 (18). Indeed, the variation in PPV induced by mechanical ventilation has been shown to be a very accurate predictor of fluid responsiveness, with an optimal threshold value around 12% (19). However, PPV/SVV based approaches have some limitations: it requires controlled ventilation with tidal volumes above the “protective” 6 mL/kg tidal volumes, and in the case of spontaneous breathing or breathing efforts and cardiac arrhythmias values cannot be relied on.

View Article: PubMed Central - PubMed

Affiliation: Department of Anaesthesiology and Intensive Therapy, Faculty of Medicine, University of Szeged , Szeged , Hungary.

ABSTRACT

There is increasing evidence that interventions based on multimodal monitoring of physiological and biochemical processes in the high-risk patients, let it be in the perioperative or critical care setting, may improve outcome. Advanced knowledge accompanied and reinforced by technical developments of continuous real time monitoring of organ function and molecular mechanisms give firm ground for utilizing them as a “goal directed individualized” approach, which may replace “figure-driven” protocolized care in the future.

No MeSH data available.


Related in: MedlinePlus