Values depends on the pt but if Poes is -15 then patient effort is very high. And for THOSE WITHOUT Poes, if you have a CVP and CVP values or waveform dips significantly during inspiration then you know that the patient effort is ++++ and intra thoracic pressure swing +++
It’s insane we have a live model (happily reading a book) whilst having a oesophageal catheter inserted ! And also a explanted lung model.
Definitely need training + empowerment of critical care nurses to gain confidence in inserting and using Poes. Like anything in intensive care , great bedside nurse is an absolute must.
Hamilton (Left )portable acting as a patient effort. Big Hamilton (Right) has Poes to measure that effort. 🤯 #LIVES2022#ventilation@ESICM
Nutrivent. 4ml balloon + NG tube
Essentially theory : pleura pressure is positive. Which causes Alveoli to collapse - we put PEEP to counteract and prevent that collapse. By measuring Ppleural via Poes you could put the same PEEP to counter and thus prevent collapse of alveoli. P(lung) = P(airway) - P(oes).
Finally. Note end inspiration is not at the peak of P oes tracing.
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@Lennie333@ESICM this is because otherwise we will need large "n" and long time for trials.
e.g., anti-hypertensives - you dont want to test one drug at one dose. you want to test a range of doses and a range of duration.
third-thing : we struggle to find a end-point especially in critical care
@Lennie333@ESICM huge effort doing RCT but we use "mortality" yes/no as a very binary endpoint. For patient, length of stay, quality of life after d/c important end points beyond survival.
in RCT, we cant learn whilst the trials are still running. in classic RCT.
NEXT:Interfacing ICU data Nicolas Bennet
- Nicolas was very pleased to hear Chris Sauer(earlier speaker) advocating use of 2 -data set at least @ESICM#criticalcare#ai#ml#icudatasets
@ESICM Merit of publicly available ICU databases
- no randomzined evidence exists for most clinical situations
-data and pt level insights incredibly useful.
-local epidemiology and treatment difers
-real world data sets help deliver optimal treatment policies. #DataScience#LIVES2022
@ESICM 1st publicly available dataset MIMIC-3 in 2016,
Beth Israel Deaconess Medical Centre, Boston,MA
>70,000 icu stays, 2008 to 2019
now also includes chest x-rays, emergency room data
- large, community developed Github repo. #DataScience
This problem is mainly for ML engineers who may not have talked to domain expert or clinicians / end users.
Pitfall 1 : sampling bias
"whos included in the analysis"
"who in your EHR"?
- e.g., - COVID prediction dataset where missing all blood tests were removed, but this missingess has a meaning. Thus not generalisable.
e.g., yesterday I mentioned about females < 6% of sample popn
Extra-corporeal therapies in Resp Failure @CarolynCalfee
- Phenotypes in ARDS
Many phenotypes in ARDS: severity of ARDS, aetiology,
- physiologic
- does any of this response to differently to ECMO? #LIVES2022 #ventilation #extracorpreal@ESICM
@CarolynCalfee@ESICM Severe ARDS phenotypes EOLIA using P/F ratio
- within 1st 7 days
- within this, which pt benefits most.
Meta-analysis on ECMO patients
- multiple subgroups but none of them statistically significant
- only key difference is No of organ failure . >2 ecmo less likely to work