Category Archives: Neurology

Jerry Nolan talks cardiac arrest resuscitation at #LIVES2020

Watch the interview in the VOD section but here is a tweetorial summarising the discussion. I’ve included the key references…

Personalising Care: Machine learning from pressure waves (ICP)

Personalising Care: Machine learning from pressure waves (ICP)

Soojin Park, Associate Prof. Neurology

Division of Neurocritical Care, Columbia University, NYC, USA

Watch on demand: https://lives2020.e-lives.org/media/machine-learning-pressure-waves

Motivation

  • Acute hydrocephalus affects ~37k pts/yr in USA
  • Rx = EVD, but 1/5th develop infection ventriculitis
  • Risk of ventriculitis ↑ with duration and frequency of CSF sampling (by which diagnosis made..)

Question

Can we find a way of using physiological information contained in ICP waveform to develop a method for detecting ventriculitis, without having to sample CSF?

Park reminds us of the normal ICP waveform (exam revision déjà vu..)

And how it’s morphology changes with ↑ICP

This alteration in waveform morphology with ↑ICP has a biologically plausible mechanism in ventriculitis

 ⭐ Goal 1

Examine changes in ICP waveform morphologies prior to ventriculitis

  • Dataset = only patients WITH ventriculitis
  • Collaboration with group experienced in ICP waveform big data, however their pre-processing identified abnormal waveforms as artefactual!
  • ⚠Problem = vague definition of ventriculitis
  • Used ‘gold standard’ of limiting it to those with culture-positive CSF
  • n = 19 pts
  • ❗ Park mentions that CSF is cultured 3/w at this institution, perhaps not usual practice – CT: worth considering this in the context of their motivation

  • ⚠ EVDs left open to drainage most of the time, typical practice across other institutions, thus waveform only intermittently present when EVD clamped by nurse
  • ❓ Challenge = automating identification of waveforms (CT: I note solution was not to get desperate medical student to manually sift data in exchange for ‘research experience on their CV..)

Methods

  • Dominant pulses extracted using Morphological Clustering Analysis of ICP Pulse
  • Before / During / After ventriculitis (i.e culture-positive CSF)
  • Morphologically similar groups obtained by hierarchical k-means clustering
  • Dynamic Time Warping used as a ‘distance’ metric to correct for speed (HR), see below
  • Meta-clusters determined by clinicians, see figure B below.
  • Bi/triphasic (green)
  • Monophasic/tombstone (yellow)
  • Artefactual (red)
  • = supervised learning

Results

  • Prior to ventriculitis majority of pulses had physiological tri/biphasic appearance
  • During ventriculitis this dropped from 61.8 > 22.6%, a statistically significant change, which persisted
  • ✨ Most importantly this change occurred a full day before the ventriculitis was clinically detectable

 ⭐ Goal 2

Leverage time-varying dominant pulses of ICP from hourly EVD clamping data into a detection model of ventriculitis

  • Collaboration:
  • Columbia Vangelos College of Physicians & Surgeons
  • R Adams Cowley Shock Trauma Center, University of Maryland
  • Aims:
  • Improve performance and generalisability of model to other institutions data
  • Work in submission therefore not shown
  • Collaborators sought, see email below:

Concluding Remarks

  • Example presented for ICP but process generalisable to other waveforms, of which there are many in ICU!

‍‍My thoughts:

  • I’ve often been disappointed at how little waveform data is actually stored from ICU monitors
  • Perhaps I shouldn’t be given the general lack of high-quality ICU data (see data sharing session) and huge storage requirements
  • Most of the ‘high resolution/granular/insert other buzzword here’ EHRs I’ve come across sample at a frequency ~ 1 hz (c.f. 125-250 hZ in this study)
  • Starting point for those interested in waveform data in ICU = MIMIC-III Waveform Database
  • Be warned this is truly big data

Blog by Chris Tomlinson:

Anaesthetist & Critical Care Registrar

‍ PhD Candidate at UCL UKRI Centre for AI-enabled Healthcare

ctomlinson.net | LinkedIn | @tomlincr

Myth Busters! #LIVES2020

https://lives2020.e-lives.org/session/myth-buster-facing-myths

5 False beliefs in acute and chronic respiratory failure

Pr Alexandre DEMOULE

  1. ARDS pts should be intubated promptly
  2. Intubation can be safely delayed in ARDS patients
  3. In COPD, NIV is contra-inducated in case of coma
  4. In cancer pts, do everything not to intubate
  5. Response to prone position predicts the outcome

ARDS pts should be intubated promptly

Time to intubation has no impact on mortality

In COPD, NIV is contrainidcated in case of coma

  • NOT AT ALL, in cases of hypercapnic coma, do a NIV trial

In cancer pts, do everything not to intubate

Response to PRONE position predicts the outcome

When lactate is normal the circulation is adequate

Prof J Bakker

The ten pitfalls of lactate clearance in sepsis

Effect of a Resuscitation Strategy Targeting Peripheral Perfusion Status vs Serum Lactate Levels on 28-Day Mortality Among Patients With Septic Shock
The ANDROMEDA-SHOCK Randomized Clinical Trial

Conclusions

  • The clinical context we create from an increased lactate is: tissue hypoperfusion/hypoxia
    • This is on a macrocirculatory level
  • Lactate levels frequently remain abnormal during the first 24h of admission in survivors of septic shock
  • Mildly elevated lactate levels are associated with increases in mortality and abnormal microcirculation
  • Lactate levels need context
    • Markers of peripheral/microcirculatory perfusion
  • Lactate levels do not denote a state of perfusion

Adrenaline improves outcome after cardiac arrest?

Time to administration of epinephrine and outcome after in-hospital cardiac arrest with non-shockable rhythms: retrospective analysis of large in-hospital data registry

A Randomized Trial of Epinephrine in Out-of-Hospital Cardiac Arrest

2019 International Consensus on Cardiopulmonary Resuscitation and Emergency Cardiovascular Care Science With Treatment Recommendations

Conclusion

  • Survival to hospital admission x 3 higher
  • More survivors to discharge
  • More neurologically favourable survivors
  • More brain-injured survivors

 

False beliefs about duration of antibiotic therapy

J De Weale (twitter)

The FALSE beliefs

  1. Antibiotic duration needs to be ‘fixed’
    • No Biological rationale
    • Bacteria don’t calculate the days exposed
  2. Short courses are less effective
    • Longer courses do not protect against complications
    • BUT some infections do require longer treatment
  3. I need a biomarker to determine duration
  4. Antibiotics need to be continued until clinical symptoms have subsided
  5. An antimicrobial course should always be completed.

Summary

  • Inappropriate antimicrobial use in the ICU is unacceptably high
  • Duration important contributor
  • Management often based on incorrect assumptions
  • “7-days course” current dogma for most infections
  • Individualized therapy is the future
  • AI to refine therapy duration

Prof’s De Weale’s slideset (I like the design)

Prognostication of individual survival chances is not possible? Machine learning is the answer

Prof Mihaela van der Schaar (twitter) www.vanderschaar-lab.com

Machine learning can enable:

1) Delivering precision medicine at the patient level
2) Understanding the basis and trajectories of health and disease
3) Informing and improving clinical pathways, better utilize resources, and reduce costs
4) Transforming population health and public health policy

False beliefs in the management of fever

F Schortgen

Fever is not hyperthermia

Treating fever has never been proven to improve patient comfort

Effect of Shivering on Brain Tissue Oxygenation During Induced Normothermia in Patients With Severe Brain Injury

Antipyresis is NOT necessarily good for haemodynamic stabilistation and tissue oxygenation

 

New developments that every intensivist should know about…..

Cardiology

Prof S Price

COVID-19

2020 Acute Coronary Syndromes (ACS) in Patients Presenting without Persistent ST-Segment Elevation (Management of) Guidelines

  • Rapid rule in/rule out algorithms now recommended to use ESC 0h/1h algorithm ( or 1h/2h algorithm (second best option) if a hs-cTn test with a validated algorithm is available
  • If elective non-invasive/invasive imaging is needed after the rule-out of MI, invasive angiography is the best option in those with a very high clinical likelihood of UA. Stress testing with imaging or CCTA is best in those with low-to-modest clinical risk.
  • Rhythm monitoring for up to 24 h or to PCI (whichever comes first) is recommended for those at low risk for arrhythmias and monitoring >24h if at increased risk
  • Early routine invasive approach within 24 hours for NSTEMI based on hs-cTn measurements, GRACE score >140, dynamic/new STT changes.

Clinical application of the 4th Universal Definition of Myocardial Infarction

Temporary circulatory support for cardiogenic shock

Pulmonology

EJ Nossent

Potential therapies

Pirfenidone for idiopathic pulmonary fibrosis: analysis of pooled data from three multinational phase 3 trials

Efficacy and Safety of Nintedanib in Idiopathic Pulmonary Fibrosis

Nintedanib for Systemic Sclerosis–Associated Interstitial Lung Disease

Nintedanib in Progressive Fibrosing Interstitial Lung Diseases

Take home message

  • ILD is not one disease
  • Acute excacerbation in every type of ILD
  • The landscape is changing; finally…
  • Position antifibrotic therapy fibrotic ILD not clear yet; immunosuppressants.

From the disease lung fibrosis to criteria, towards phenotyping, towards personalized medicine.

Neurology

Prof S Koch

COVID-19

Conclusion

EID risk is increasing due to climate change and loss of biodiversity
-> we need to adress this now

Neurological manifestation of Covid-19 occur in ~ 36%

Cerebrovasculare Manifestions occur in ~ 5% of Covid-19 patients based on
–pathological coagulation or hyperinflammation
–includes younger patients or patients with typical riskfactors
–leads to more severe outcome
-> check carefully coagulation parameters and risk factors

Altered conscious state is seen in ~ 65% of Covid-19 ICU patients
–based on encephalopathy or seizures
-> EEG monitoring, MRI

Anaesthesiology

S Loer

Optimizing preoperative fluid therapy Encourage use of clear carbohydrate drinks up until 2 h prior to surgery!

  • Less catabolism
  • Less postoperative nausea and vomiting
  • Less insulin resistance
  • Less perioperative anxiety

Intraoperative fluids

Impact of intraoperative goal-directed fluid therapy on major morbidity and mortality after transthoracic oesophagectomy: a multicentre, randomised controlled trial

Perioperative goal-directed therapy: what’s the best study design to investigate its impact on patient outcome?

Anesthesia-induced immune modulation

Post-op delirium

Postoperative delirium: perioperative assessment, risk reduction, and management

Post-op pain