2/ The goal of monitoring is
1⃣to detecting small and early changes
2⃣so that therapies can help patients.
For successful monitoring, the measurements must be precise and acquired rapidly and effortlessly. Neither #EchoFirst nor #POCUS fulfil these criteria.
3/ Eyeballing is rapid, effortless, and OK for diagnosing LV dysfunction.
But eyeballing is NOT precise because it categorises LV function.
Changes in LVEF from 45 to 30% are important, yet still in the same category ➡️ undetectable by categorical assessment.
4/ The monitored measurements must be quantitative to be precise.
Manual measurements in #EchoFirst are quantitative, but human variability still render them imprecise.
📜
Imprecision causes 2⃣ problems during monitoring. rdcu.be/dw7fT
5/ Problem1⃣: Busy doctors may be fooled by imprecision.
Its easy to misinterpret random changes as real and react to this randomness with interventions. Of course, the patient has no chance of benefitting from those interventions, and can only be harmed.
6/ Problem2⃣: When we use imprecise tools like #POCUS, we need much larger changes to be confident that the observed changes are real. Changes of that magnitude tend to be clinically obvious. Also, they tend to occur late. Either way, the point of monitoring is lost.
7/ Precision is always improved by averaging several measurements. Unfortunately, this requires more tedious measurements and is seldomly done in real life. #AutoMAPSE can easily take several measurements of LV function and improve the precision needed for effective monitoring.
8/ Monitoring must be effortless, and #POCUS/#Echofirst is not. Manual measurements takes too much effort. This effort is better spent on important decision-making.
9/ #AutoMAPSE alleviates the effort in quantifying LV function by using AI. #AutoMAPSE also reduces the effort in image acquisition by using #TEE.
📜
This even allows for continuous, hands-free imaging: rdcu.be/dw7fT
10/ Finally, LV function must also be quantified rapidly.
Measurements by #EchoFirst or #POCUS are too slow for #ICU, where changes in LV function can occur very fast. #AutoMAPSE helps by providing instantaneous measurements.
📜rdcu.be/dw7fT
11/ Effective monitoring of LV function requires precise, rapid and effortless measurements. Current practices fails to achieve this in #CriticalCare.
Our paper show that #autoMAPSE can rapidly quantify LV function and fill this need. #MAPSE
📜 rdcu.be/dw7fT
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🧵1/
A very interesting RCT by @MirjanaCihoric & @BangFoss in @BJSurgery show the importance of dexamethasone (DXM) in acute abdominal surgery! DXM ⬇️inflammation,⬇️vasodilation,⬇️pressor dependency, and improves fluid balance and even 90-day ☠️ doi.org/10.1093/bjs/zn…
2/ DXM shows positive effects on various secondary endpoints with different levels of significance. Also, less fatigue, pain, immobilization and better peak exp flow.
3/ Interestingly, there were no more infections in the DXM-group; in fact, there were fewer infections of various subtypes, though statistically insignificant. However, DXM had more hyperglycemia.
1/ 🧵Can the pulmonary artery catheter (PAC) guide massive transfusion?
Key ideas:
1⃣Continuous SvO2 may be useful for optimizing O2-delivery.
2⃣Continuous SvO2 & CO aids in detecting distributive shock physiology.
#FOAMed #MedTwitter #CritCare #ICU
2/ 1⃣Optimizing DO2
The goal of transfusion is to improve O2-delivery. SvO2 is an excellent measure O2-delivery. PAC allows continuous SvO2 monitoring.
3/ 1⃣Optimizing DO2
🩸SvO2 > 65% during bleeding suggests a need for transfusion.
🩸SvO2 > 65% suggests that resuscitation is adequate, avoiding unnessecary transfusions and potentially preventing transfusion-associated complications.
2/
1⃣st report of TEE was in 1980, using M-mode from TGSAX during cardiac surgery. The rationale for this was: "Currently used monitoring techniques such as measurements of pressure and cardiac output provide an incomplete picture of LV function..." doi.org/10.1016/0002-9…
3/ A serious limitation is that all measurements required manual image acquisition and measurements.
Imagine using Korotkoff sounds for "monitoring" BP; manual methods requires too much time and attention to effectively serve as monitoring and guide patient management⏱️🧠
1/ 🎯Bland-Altman analysis is the common way to evaluate AI in #EchoFirst. However, BA analyses can be tricky to interpret. 🧵On the paradox of BA analysis for AI in #EchoFirst with examples from our studies on #AutoMAPSE 📜
#Foamed #Cardiotwitter rdcu.be/dH8aR
2/ BA analysis is an important approach used for comparing 2⃣measuement methods for measuring the same unit, like #MAPSE (mm) and #AutoMAPSE (mm). ‼️Correlation (r) is inappropriate yet commonly used because it is seductive. Read the reasoning in their📜: doi.org/10.1016/S0140-…
3/ The output in BA analysis is 1⃣bias &2⃣limits of agreement (LOA). Bias is the avg difference across all paired measurements of manual MAPSE and autoMAPSE. LOA=+/- 2SD of the bias in the study. The bias and LOA is presented in a BA plot from 📜: rdcu.be/dH0mY
🧵1/ #AutoMAPSE had high feasibility for estimating MAPSE from ≥1⃣wall. Many worry that #MAPSE is limited by RWMA, such as acute MI - however, evidence suggests that regional MAPSE reflects global LV function.
2/ Several studies have shown that in AMI, MAPSE is ⬇️even in walls remote to MI. This was confirmed experimentally by Berg et al, in an experiment occluding the LAD in pigs and measuring #MAPSE by #WhyCMR.
First paper:
Berg et al: doi.org/10.1080/140174… doi.org/10.1152/japplp…
3/ ⬇️MAPSE in remote walls is explained through the distribution of afterload. For a specific region to shorten, that region must overcome the opposing afterload imposed by its neighboring region, which is shortening in the opposite direction.
🧵We have now refined AutoMAPSE.!
🔓
⬆️New paper on #autoMAPSE showing that the newest version achieves an optimal balance between feasibility, analysis speed, and agreement.
A🧵on the clinical importance of these findings
#echofirst #CardioTwitter #POCUS doi.org/10.1016/j.ultr…
1/ Our design involved measurements from 🔟beats per #EchoFirst recording. This is very different from the usual practice of measuring 1-3 beats. What are the advantages?
2/ Measuring 1-3 beats in #Echofirst involves huge physiological variability. How?
❤️🫁 interactions can cause serious beat-to-beat variations in any echo measurement. Often overlooked, these changes may be misinterpreted as real. Acting on wrong info ⬆️the risk of harm.