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PROFITS A CLINICAL INFRASTRUCTURE FOR
STRUCTURAL AND MULTI- NETWORK
ASSESSMENT OF DETERMINANTS & MODULATORS OF FUNCTIONAL
OUTCOME AFTER STROKE
LeidenDelft
Rotterdam
Amsterdam
Twente
Nijmegen
• A longitudinal observational cohort (n=160).
• 0-26 weeks post- stroke
• Evolving in a clinical infrastructure
• Of standardized prognosis, monitoring and outcomeassessment of motor recovery post- stroke
PROFITS in short (1)
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• A longitudinal observational cohort (n=160).
• 0-26 weeks post- stroke
• Evolving in a clinical infrastructure
• Of standardized prognosis, monitoring and outcomeassessment of motor recovery post- stroke
PROFITS in short (1)
• Connect between acute phase and rehab phase.
– Effects of interventions in the acute phase ?
– Effects of interventions in the rehab phase ?
– Prediction rules for planning of rehab.
• As a basis for network care.
– Transport of information in the chain
• Integrating clinical care with research- development
Why PROFITS ?
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Acu
te c
are
ACUTE PHASECHRONIC
PHASE
SUB
ACUTE
Prediction
Optimisation
Home
Acute
Rehab phase
Chronic phase
Strokeunit
Rehabcenter
Acute phase
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• Modified ranking scale:
– 0 = goed
– 6= dood.
• Barthel Index
• NIHSS score
MrClean, primary outcome
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STRONG TECHNOLOGICAL PUSH
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Left/right 2 1
Dominant side affected 19 15
476
Figure 3 Change in FMA-UE as compared to baseline during the course of study - a comparison between 477
conventional (control) and robotic therapy groups (ARMin); Error bars are standard deviations. 478
479
Table 3 F-ratios,significance levels, estimated marginal means, and confidence intervals for primary and 480
secondary outcomes. CI: confidence interval; FMA-UE: Fugl-Meyer Assessment (upper extremity motor 481
function); WMFT: Wolf Motor Function Test: MAL-QOM: Motor Activity Log, quality of movement; SIS = Stroke 482
Impact Scale, mAS = modified Ashworth Scale; GAS = Goal Attainment Scale. 483
group effect
F-ratio p value estimated marginal means CI
FMA-UE 4·2 ·041 0·78 0·03 to 1.53
WMFT time 1·4 ·173 2·02 -0·90 to 4·93
WMFT function 1·6 ·212 -0·37 -0·10 to 0·021
SIS total 3·6 ·059 1·42 -0·05 to 2·91
SIS physical domain 0·8 ·387 0·76 -0·96 to 2·47
BUT ADDED VALUE NOT YET PROVEN…
Kwakkel et al. 2008, Klamroth-Marganska et al. 2014, Kwakkel & Meskers, Lancet Neurology 2015.
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• Proper selection of patients?
• Proper timing of assessment?
• Target disease specific mechanisms?
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Left/right 2 1
Dominant side affected 19 15
476
Figure 3 Change in FMA-UE as compared to baseline during the course of study - a comparison between 477
conventional (control) and robotic therapy groups (ARMin); Error bars are standard deviations. 478
479
Table 3 F-ratios,significance levels, estimated marginal means, and confidence intervals for primary and 480
secondary outcomes. CI: confidence interval; FMA-UE: Fugl-Meyer Assessment (upper extremity motor 481
function); WMFT: Wolf Motor Function Test: MAL-QOM: Motor Activity Log, quality of movement; SIS = Stroke 482
Impact Scale, mAS = modified Ashworth Scale; GAS = Goal Attainment Scale. 483
group effect
F-ratio p value estimated marginal means CI
FMA-UE 4·2 ·041 0·78 0·03 to 1.53
WMFT time 1·4 ·173 2·02 -0·90 to 4·93
WMFT function 1·6 ·212 -0·37 -0·10 to 0·021
SIS total 3·6 ·059 1·42 -0·05 to 2·91
SIS physical domain 0·8 ·387 0·76 -0·96 to 2·47
]
INDIVIDUAL RECOVERY PATTERNS
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In first ever ischemic MCA- strokeDeterministic patterns of upper limb functionalrecovery in time (Kwakkel et al. Lancet 1999, Kwakkel et al. Stroke,
2006).P
robability for
achie
vin
g
dexte
rity
aft
er
MC
A s
troke
0
10
20
30
40
50
60
70
80
90
100
1 2 3 4 5 6 7 8 9 10
weeks
0
10
20
30
40
50
60
70
80
90
100
<72h 5d 1 2 3 4 5 6 7 8 9 10
Weeks post stroke
Good prognosis
Poor prognosis
Nijland et al, Stroke. 2010;41:745-50 Stinear et al, Lancet Neurol 2010; Dec;9(12):1228-32.De EPOS cohortstudie
SAFE-model
<72 hours
Probability (%) ARAT ≥ 10 points at 6 months post stroke (N=188)
FUNCTIONAL OUTCOME CAN BE PREDICTED
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Stroke: the 70% recovery rule
Winters et al. 2015 NNR
Kwakkel et al. NNR 2016
Explicit-stroke
S
NS
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Restitution (spontaneous) Substitution
+Neurological
recovery
‘activities’
Kwakkel et al, Rest. Neurology & Neuroscience 2004;22:281-299
Buma et al, Rest Neurol Neuroscience 2013; 31(6):707-722)
Compensational
behavior
?
• Can we improve current prediction models of functionalrecovery post stroke in terms of restitution andcompensation?
– Do they hold in patients other than first ever MCA stroke? (recurrent stroke, bleeds, co-morbidity)?
– Can we identify the non- fitters?– Can we improve individual predictability?
PROFITS Research questions
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Acute Phase Rehab. phase
PredictionFunctional outcome
CLINICAL INFRASTRUCTURE
Chronic phase
Acute Phase Chronic phase
PredictionFunctional outcome
• Phenotype
• Clinimetry
• EEG
CLINICAL INFRASTRUCTURE
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Acute Phase Chronic phase
PredictionFunctional outcome
• Phenotype
• Clinimetry
• EEG
CLINICAL INFRASTRUCTURE
]
Acu
te c
are
HIGH PRECISION PROFILING COHORT
FUNCTIONALOUTCOME
PREDICTION
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+ +
References+
· Berkheimer+et+al.,+NEJM+2015;+372:11=20.+
· Nijland+et+al,+Stroke.+2010;+41:745=50;+
· Kwakkel+et+al.,+Neurorehabil+Neural+Repair+2016;+Jan+7.+
· Kwakkel+&+Meskers,+Lancet+Neurol.+2014;+13:132=3+
· Kwakkel+et+al.+Lancet+1999.+
· Kwakkel+et+al.+Stroke+2006.+
· Prabhakaran+et+al.,+Neurorehabil+Neural+Repair+2008;+22:64=71.+
· Stinear+et+al,+Lancet+Neurol+2010;+9:1228=32.+
· Winters+et+al.+Stroke+2016.+++Measurement+schemes.++I.+PROFITS+CORE.++
+++
II.+PROFITS=+FULL+++
+
+
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Clinimetrie- NIHSS- Fugl meyer- Trunk control- FAC- MI- Timed Balance Test- Barthel- MOCA
Uitkomst- Fugl Meyer BE- Fugl Meyer OE
- ARAT- 10 meter looptest
Type patient- Leeftijd/geslacht- Type stroken- Trombolyse?- Comorbiditeit- Risicofactoren- Complicaties
ACUTE FASE-PREDICTIE
FOLLOW-UP/HERSTEL
Clinimetrie- NIHSS- Fugl meyer- Trunk control- FAC- MI- Timed Balance Test- Barthel- MOCA
Uitkomst- Fugl Meyer BE- Fugl Meyer OE
- ARAT- 10 meter looptest
Type patient- Leeftijd/geslacht- Type stroken- Trombolyse?- Comorbiditeit- Risicofactoren- Complicaties
ACUTE FASE-PREDICTIE
FOLLOW-UP/HERSTEL
Restitutie
Compensatie
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Rehabcenter
Strokeunit
Nursinghome
Strokeunit
Nursinghome
Rehabcenter
Home
“Brain Van”
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Project support
Local assessment
Effo
rt
Time
Acute Phase Chronic phase
PredictionFunctional outcome
WEB BASED ICT SOLUTION
Web-baseddatabase
INDIVIDUALIZEDPREDCTION MODELS
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PROFITS APPROACH
Routine outcome measurements: Win-Win for clinical care and research
PROFITS SHOULD CREATE VALUE FOR
Treatment of individual patients
At the level of a organization/hospital
For research and development
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Create data on health care outcomes
AIMS AND STARTING POINTS
PROFITS
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HOW CAN IT HELP RESEARCH?
Research and development
Cohort studies, for example to develop clinical prediction models
Using practice variation for comparative effectiveness
Add-on studies:
Diagnostic and clinimetric
Randomized controlled trials
Etcetera
Rehabcenter
Strokeunit
Nursinghome
Strokeunit
Nursinghome
Rehabcenter
Home
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ICT INFRASTRUCTURE
EXISTING GEMSTRACKER APPLICATION
Dupuytren surgeryN=±2200
Thumb base OA n=±2000
Carpal tunnel syndromn=±4000
2011-present:
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EXISTING GEMSTRACKER APPLICATION
Combination of:
Patient-reported outcome
measures (PROMS)
Clinical reported outcome
measures (CROMS)
EXAMPLE USE CASE
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Example use case 2
GEMSTRACKER DATABASE
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STAPSGEWIJS
Klinimetrie coreset is gedefinieerd
Training van assessoren
Dataverzameling in PROFITS onderzoekcohort
Dataverzameling in reguliere zorg
Clinimetrie is standaardzorg
Clinimetrie over zorgketen
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Project support
Local assessment
Effo
rt
Time
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A. Andringa MScDr. C.G.M. Meskers MDDr. E.E.H. Van WegenProf dr. G. Kwakkel
Prof dr F.C.T van der Helm
Dr. R.W. SellesDr. J.B.J. Bussmann
Prof dr. G. Ribbers MDDr. J. Slaman
Dr. L. Aerden MD
MEER WETEN OF MEE DOEN?
Neem contact op met: Carel Meskers, Ruud Selles of Carel Meskers
Wij helpen graag met verdure afstemming intern op jullie afdeling, oamet de neurologen
