andras buki m.d., ph.d.,d.sc. department of neurosurgery,...
TRANSCRIPT
AZ ÉLETTUDOMÁNYI- KLINIKAI FELSŐOKTATÁS GYAKORLATORIENTÁLT ÉS HALLGATÓBARÁT
KORSZERŰSÍTÉSE A VIDÉKI KÉPZŐHELYEK NEMZETKÖZI VERSENYKÉPESSÉGÉNEK ERŐSÍTÉSÉRE
TÁMOP-4.1.1.C-13/1/KONV-2014-0001
Andras Buki M.D., Ph.D.,D.Sc.Department of Neurosurgery, Medical Faculty of Pecs University, Pecs, Hungary, H-7624
Clinical Evaluation and Prognosis
of Traumatic Brain Injury
• Clinical evaluation is still the most important independent predictor of outcome
• Focused neurological examination
• Other prognostic factors
Focused neurological
examination
Post-resuscitation GCS
• Systolic blood pressure is over 90mmHg
• SatO2 is over 90%
• Mind the conditions with unreliable pulse
oxymetry reading!
Standardisation of pain stimuli
Best response of best arm
Courtesy of Prof. Andrew Maas
59/451 (13%) non surgical cases:
mistakenly severe
Courtesy of Prof. Andrew Maas
Trade-off
Clinical observation
Deep sedation for
ICP control
Ventilation, etc.
Sedation and myorelaxants for
airways and ventilation
Courtesy of Prof. Andrew Maas
PRIMARY BRAIN INJURY
SECONDARY BRAIN INJURY
ASSOCIATED CNS INJURYassociated C-spine (CO-II) injurytandem injury
ASSOCIATED INJURYmultiple/polytraumaassociated multiorgan injury/failure (MOF)
General classification
Advanced Trauma Life Support®-ATLS ®
The gold standard upon
radiological evaluation …• (Forget skull Xrays!!!!!!!!!!!!!!!!!!!!!!!!)
• …is CT
15
• NOOOO SKULL X RAYSSS!!!
Outcome prediction: why do we bother with?
• support early clinical decision-making
• inform the relatives
• facilitate comparison of outcomes (patient series, results over time)
• audit of care
• provide endpoint and facilitate the selection of target population in RCTs
Building Blocks for prognosisCharacteristics of the individual
Admission Clinical Course Early Endpoints
Outcome
Biological constitution- genotype
________________Demographic factors- age- race
________________Socioeconomic status and education
________________Medical History
Injury details
- type (closed, penetrating etc.)- cause
_________________Clinical severity
- intracranial (GCS/pupils)
- extracranial(AIS/ISS)
_________________Second insults
- systemic (hypoxia, hypotension, hypothermia)
- intracranial (neuroworsening, seizures)
_________________CT characteristics
_________________Biomarkers/lab values
Biological response to injury- metabolomics
_______________Change in adm.parameters- clin. severity- change in CT
- biomarkers, lab values
_______________‘New’ predictorsSecond insult
Clinical Monitoring (ICP, brain tissue PO2, evoked potentials)
Early mortality(day 14)
_______________Neuroworsening
_______________ICP control
_______________Neuro-imaging
Mortality
______________GOS (E)
______________HRQoL
______________Neuro-imaging
______________Neuro-psychological assessment
Factors contributing to outcome -AGE
• studies identified age as the strongest independent predictive factor
• Cut off for survival: 50y
• Cut off for good outcome 30y
Factors contributing to outcome -GCS
• clinical utility of the GCS is limited by the application of therapeutic guidelines based on sedation
Saatman KE, Duhaime AC, Bullock R, Maas AI, Valadka A, Manley GT; Workshop Scientific Team and Advisory Panel Members. Classification of traumatic brain injury for targeted therapies. J Neurotrauma. 2008;25(7):719-38.
The gold standard upon
radiological evaluation …• (Forget skull Xrays!!!!!!!!!!!!!!!!!!!!!!!!)
• …is CT
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Marshall CT classification
Category Definition
Diffuse Injury I./No visible pathology/
No visible pathology seen on CT scan
Diffuse Injury II. Cisterns are present with midline shift 0-5 mm
and/or:
lesion densities present
no high- or mixed-density lesion > 25 cc may
include bone fragments and foreign bodies
Diffuse Injury III./Swelling/
Cisterns compressed or absent with midline shift
0-5 mm, no high- or mixed-density lesion > 25 cc
Diffuse Injury IV./Shift/
Midline shift > 5 mm, no high- or mixed-density
lesion > 25 cc
Evacuated mass lesion Any lesion surgically evacuated
Nonevacuated mass lesion High- or mixed-density lesion > 25 cc, not
surgically evacuated
Based on: J Neurosurg. 1991 Nov;75(5S):S14 – S20
Rotterdam CT Score Basal cysterns
• Normal 0
• Compressed 1
• Absent 2
Midline shift
• No shift or shift ≤ 5mm 0
• Shift > 5mm 1
Epidural mass lesion
• Present 0
• Absent 1
Intraventricular blood or tSAH
• Absent 0
• Present 1
• Add plus 1 to make the grading numerically consistent with the grading ofthe motor score of the GCS and with the Marshall CT classification.
• Based on: Maas et al.: Neurosurgery 57:1173-1182, 2005
Factors contributing to outcome –CT, MR
• CT misses diffuse lesions,
• predictive value of diffuse lesions identified on CT is relatively low
• MR: problems with:– Availability
– Cost efficiency
• The significance of MRI-only lesions is not
yet established
Factors contributing to outcome – Monitoring
• Multiparametric ICU monitoring primarily reflects
secondary insults;
• initial results do not necessarily harbour
predicitve value
• Conflicting data on the significance of Pbr02-
monitoring
Classic models of risk prediction at critical care
IMPACT (International Mission for Prognosis
And Clinical Trial Design)
Outcome calculator
• core prognostic model: based on three
clinical predictors: age, motor component
of Glasgow coma score (GCS), and
pupillary reactivity
• extended model: core + secondary insults
and CT characteristics
• laboratory model: also includes
haemoglobin and glucose
CRASH
• Corticosteroid Randomisation After
Significant Head Injury trial
MRC CRASH Trial Collaborators, Perel P, Arango M,
Clayton T, Edwards P, et al. (2008) Predicting outcome
after traumatic brain injury: Practical prognostic models
based on large cohort of international patients. BMJ 336:
425-429.
0%
20%
40%
60%
80%
100%
0% 20% 40% 60% 80% 100%
probability of unfavorable outcome, IMPACT CORE model
observ
ed m
ort
alit
y
Probability of unfavorable outcome: IMPACT-calculator
• Concerns: – Statistics: decision tree analysis vs.
Logistic regression analysis– Content: limitations due to initial data-
collection: • Lack of :
– data on coagulopathy– Rotterdam score– detailed data on surgery– some physiological parameters
• Work is needed to establish the accuracy of these models prospectively in patients not enrolled in clinical trials.
What measures should help?
• Coagulopathy
• Rotterdam score
• Biomarkers
2,289
0,930 0,850 0,946
6.955*
2,173
0,01,02,03,04,05,06,07,08,0
OR
Patients with SDH above 60
4,1051.160* 0,788 0,435
55.513*
23.846*
0,05,0
10,015,020,025,030,035,040,045,050,055,060,0
OR
Patients with SDH below 60
BIOMARKERS
0,171 0,188
0,2640,289
0,3100,355
0,429 0,428
0,501
0
0,1
0,2
0,3
0,4
0,5
0,6R2
Take home message…
• Outcome prediction is important:– Continuous validation and revision of
institutional protocols
• Outcome calculators provide useful information, but fine tuning by expert opinion is important–and vica versa.
• Outcome calculators should take into consideration additional issues primarily biomarkers
Thank You!