The Pv-aCO2 gap is an easily obtained measure that serves as a marker of impaired cardiac output/tissue perfusion, yet seemingly few of us use it in practice
A short 🧵 on ΔCO2, its potential benefits & some pitfalls
The Pv-aCO2 gradient (ΔCO2) is simply the partial pressure of CO2 in venous blood (mixed or central venous) - the partial pressure of CO2 in arterial blood.
Normal values are ≤ 6mmHg (0.8kPa)
Values > 6mmHg suggest a low CO or impaired microvascular tissue perfusion
ΔCO2 is primarily determined by total CO2 production (VCO2), cardiac output (CO) and the complex relationship between pCO2 and total blood CO2 content (CCO2).
It can be conceptualised mathematically using the Fick equation
PCO2 is related to CCO2 by the CO2 dissociation curve, a curvilinear relationship that can be described by:
PCO2 = k x CCO2 (where k is the dissociation coefficient)
Over physiological ranges they maintain a relatively linear relationship, as shown below:
We can modify the Fick equation, swapping CCO2 for pCO2, to show how ΔCO2 is inversely related to CO & why it’s a good surrogate of CO.
This has been demonstrated in multiple trials especially during hypovolaemic, cardiogenic & obstructive shock.
[PMID: 15803301, 9635647]
In sepsis the relationship becomes less clear, as microcirculatory dysfunction can lead to tissue CO2 accumulation & an elevated ΔCO2 gap despite a high CO.
Here ⬆️ ΔCO2 can be a helpful sign of poor tissue perfusion despite reassuringly high CO/ScvO2
- ⬆️ ΔCO2 only reflects tissue dysoxia if caused by a ‘stagnant’ mechanism, and can be normal in anaemic/hypoxic/cytopathic dysoxia
- Extremes of pH/Temp/pO2 will shift the CO2 dissociation curve altering the pCO2/CCO2 relationship
Take-away message:
🔸 ΔCO2 is an easily obtained, reliable indicator of tissue perfusion & can be a useful data point in the evaluation/management of patients with shock
*proposed diagnostic algorithm by Ltaief et al. PMID: 34461974
Hope the 🧵 may’ve been of interest & if you’ve any thoughts, corrections or questions please comment. I’d love to hear how/if you incorporate it into clinical practice & if you find it beneficial!
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In medicine we worship at the altar of SBP. In ICU the MAP reigns supreme. But too often the poor old DBP is an afterthought, & it’s crying out for our attention.
A short 🧵 on the clinical utility of the ugly duckling of blood pressures, the Diastolic Blood Pressure 🎉
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It makes sense to consider first what determines DBP?
At end systole, aortic pressure begins to exponentially decay as the ejected SV/pressure wave propagates down the arterial tree. Uninterrupted, it will continue to drop until the mean circulatory filling pressure is reached
The rate of the decay is known as the time constant (τ) - a concept we’re familiar with from respiratory physiology.
Just like in the lungs, it’s the product of arterial compliance (C) x arterial resistance (R)
Doc 1: There’s a big swing on their A-line, shall I give more fluids?
Doc 2: Well given that they’re spontaneously breathing, there’s no real evidence to support PPV here 🤷♂️
- A recently overheard conversation, prompting this 🧵 on PPV in the spontaneously breathing patient.
The ∆ between systolic & diastolic pressures is the pulse pressure (PP) & it is determined by the compliance of the aorta and the ventricular stroke volume (SV).
Whilst aortic compliance reduces with age, beat-to-beat changes in PP occur predominately due to changes in SV.
When asking if a pt is fluid responsive (FR), we’re asking if ⬆️ preload will ⬆️ SV. Observing a ∆PP with a ∆preload can help us try to answer this.
Pulse pressure variation (PPV) is the diff. between the max/min PP (as a % of the mean), occurring over a respiratory cycle.