Klinimetrie bij het stellen van de functionele prognose na een CVA:

hulp of last?

Dr. G. Kwakkel

Identify patient’s problem

Define a meaningful question

Determine the prognosis

Select most appropriate therapy

Evaluate efficacy

Doel van het (klinisch) meten

om te onderscheiden (diagnostiseren en/of klassificeren)

Kirshner & Guyatt, J. Chron. Dis 1985; 38: 27

om te voorspellen

om (verandering) te evalueren

home at 6 months ?

outcome of ADL ?

needs further help ?

clinical decision making

pa

tie

nts

fu

ture

home at 6 months?

outcome of ADL ?

needs further help?

pattern recognition

hypothetico-deductive reasoning?

problem solving ?

intuition ?

pa

tie

nts

fu

ture

determinantOutcome of

what?

(1) Prediction of what?

Health Condition Health Condition ((disorder/diseasedisorder/disease))

Interaction of ConceptsInteraction of ConceptsICF 2001ICF 2001

Environmental Environmental FactorsFactors

Personal Personal FactorsFactors

Body Body function&structure function&structure

(Impairment(Impairment))

ActivitiesActivities(Limitation)(Limitation)

ParticipationParticipation(Restriction)(Restriction)

? ?

Neuro-physiology

Neuroradiology

Clinical neurology

Neuro-psychology

Demographic factors

determinant

Functional outcome (e.g., dexterity, walking ability, (I)ADL-independency

Which construct (at level of activity) do we exactly like to predict?

Basic ADLArm-

handvaardigheid

Barthel Index ARAT

?

Loopvaardigheid

Functional Ambulation Categories

Construct validity of BI (N=89)

0

0,2

0,4

0,6

0,8

1

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

FAC

weeks

Correlation coefficient (rs)

Construct validity of BI (N=89)

0

0,2

0,4

0,6

0,8

1

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

FACARA

weeks

Correlation coefficient (rs)

Neuro-physiology

Neuroradiology

Clinical neurology

Neuro-psychology

Demographic factors

determinantFunctional outcome of basic ADLs

(2) Which determinants are valid?

I . Key methodological criteria for prognostic research

internal validity reliable and valid measurements inception cohort appropriate end-points of observation control of patient drop-out

statistical validity control for statistical significance adequate estimation of sample-size control for multicollinearity

Kwakkel et al, Age & Ageing 1996;25:479-489

Factor x2

Factor x1

Outcome Y(explained variance)

r y.x2

r y.x1

r x1.x2

Predictive value of volume of stroke according to MRI scan for outcome of ADL-independency at 6 months post stroke

Schiemanck et al, Stroke. 2006;37:1050-1054

Copyright ©2006 American Heart AssociationSchiemanck, S. K. et al. Stroke 2006;37:1050-1054

Receiver operating curves of model 1 (clinical) and model 2 (clinical imaging) (N=75)

Model 1 (AUC=0.83) = age and IBI

Model 2 (AUC =0.87) = Model 1 + volume MRI

Schiemanck et al, Stroke. 2006;37:1050-1054.

II. Key methodological criteria for prognostic research

external validity specification of inclusion and exclusion criteria description of additional treatment effects during period of

observation cross-validation of the prediction model

Kwakkel et al, Age & Ageing 1996;25:479-489

Internal validity

78

Statistical validity

external validity

13 (8)

0

Valid predictors for ADL (and walking ability)

admission ADL (i.e., assessment specific) urinary (in)continence age* previous stroke (and other disabling co-morbidity) consciousness at onset severity of paresis sitting balance orientation in time and place level of social support inattention depression

Possible negative predictors for ADL

homonymous hemianopia conjugate deviation of the eyes fatigue dyspraxia dysphasia ??

Variables not related to outcome of ADL

gender ethnic origin side of stroke

Kwakkel et al., Age & Ageing, 1996: 25:479-489

Individual recovery patterns of Barthel Index (n=13)

0

2

4

6

8

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16

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20

22

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weeks

BI-score

weeks

Mean recovery pattern of Barthel Index

0

10

20

30

40

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60

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90

100

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weeks

Barthelindex

prediction

outcome

Regression model statistics for outcome of BI

Intercept Initial BI Sitting balance Soc. Support age *

Model Nh Pooled

R-square

0.51 0.61 0.64 0.67

0.52 0.57

Eigenvalue 4.291 0.363 0.226 0.110 0.023

0.106 0.120

CI 1.0 3.44 4.36 6.24 13.66

5.71 5.34

Final regression model for outcome of Barthel Index at 6 months post stroke

BI = 42.29 + (0.51 * IBI) + (20.93 * SB) + (10.35 * SS)

BI= (Initial) Barthel Index (ranging from 0-100)

SB=initial sitting balance (yes/no on the TCT)

SS= Social Support (yes/no: having a partner able to support)

Increment in explained variance for outcome of BI score (N=102)

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26weeks

model retesting

Explained variance (%)

Effects of initial BI on outcome at 6 months post stroke (N=89)

0123456789

1011121314151617181920

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weeks

Barthelindex

Adjusted R2=0.50 (Initial BI)

0

20

40

60

80

100

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weeks

Barthel In

dex

stairs

bowel

grooming

bladder

feeding

transfer

toilet use

mobility

dressingbathing

Coefficient of Scalability: 0.72 (week 26) < CS <0.85 (week3)

Rest. Neurology & Neuroscience 2004;22: 281-299

Copyright ©2006 American Heart Association

van Hartingsveld, F. et al. Stroke 2006;37:162-166

Logit item step difficulties ({beta}I) of the Rasch homogeneous 8-item Barthel scale

Van Hartingsveld et al, Stroke. 2006;37:162-166.

Logit item step difficulties (I) of the Rasch homogeneous 8-item Barthel scale (N=559).

1.4

1.21.0

0.80.6

0.40.2

0-0.2

-0.4-0.6

-0.8-1.0

-1.2-1.4 feeding

transfer step 1

groom

dress step 1

toilet

mobility step 2

dress step 2

stairs

bathing

easy

difficult

Take home message:

• Barthel Index gemeten in de eerste 2 weken na een CVA is een robuuste determinant voor het uiteindelijk te verwachten herstel op de BI na 6 maanden.

• Een klinimetrische testuitslag krijgt pas een prognostische

(meer)waarde wanneer men deze relateert aan het moment waarop het CVA heeft plaatsgevonden.

• Functionele prognostiek is pas mogelijk wanneer men eveneens kennis heeft over de psychometrische eigenschappen van gebruikte meetinstrumenten.

Mijn dank voor uw aandacht!

Clinical assessments increase the transparency in making client-related decisions within a team of professionals working together as a stroke team.

Advantage of clinimetrics (2):

Increment in explained variance for outcome of BI, FAC and ARA score (N=102)

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1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weeks

explained variance of model

consensus in clinimetrics:What do we measure systematically?How do we measure systematically?Who is measuring what?When do we measure the stroke patient?

Steps to follow for getting relation coordination

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1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

weken

% h

ers

tel

Hospital Rehabilitation centre

Home/ Nursing house

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weken

% h

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Hospital Rehabilitation centre

Home/ Nursing house

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weken

% h

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‘learning from making functional prognosis’

Hospital Rehabilitation centre

Home/ Nursing house

Clinimetrics (ICF 2001)

pathology impairment disability handicap

OCSP

Stroke type

Number of strokes

Epilepsy

HSP, GHS

SHS

MI-score

FM-motor score

Ashworth Scale

Thumb-Finding Test

Letter cancellation task, line-bisection task

MMSE

Scan. Stroke Scale

Trunk Control Test

Berg-Balance Scale

Timed-Balance test

Timed-Get-up & Go-Test

FAC, 10-meter walking test

ARA, Frenchay Arm

Barthel Index

FAI, EADL

SIP-68

NHP-part 1

Post-stroke Depression

Carer Strain Index

Satisfaction Questionnaires

activities participation

Construct validiteit van de BI (N=89)

0

0,2

0,4

0,6

0,8

1

1 2 3 4 5 6 7 8 9 10 12 14 16 18 20 26

ARA

weeks

Pearson correlation coefficients with Barthel Index

Clinimetrics

objectivity

communication

relia

bility validity

hiera

rchy

responsiveness

CONSENSUS

From perspective of a health care professional:

Assessment contribute to set realistic and therapeutically attainable treatment goals (i.e., improves objectivity).

Advantage of clinimetrics:

From perspective of a (stroke) team:

Clinical assessments increase the transparency in making client-related decisions within a team of professionals working together as a stroke team (i.e., improves communication).

Multidisciplinary Multidisciplinary guidelines for guidelines for

stroke financed by stroke financed by the Dutch Heart the Dutch Heart

FoundationFoundation

Stroke Stroke GuidelinesGuidelines

http://www.kngf.nl/

Praktijkrichtlijn

Samenvattingskaart

Deskundigheidsbevorderingspakket

Verantwoording en toelichting

Samenvattingskaart

Conclusion

Not only differences in heterogeneity in stroke patients are responsible for lack of accuracy in predicting functional outcome, but also the methodological shortcomings in published prognostic research

Kwakkel et al., Age & Ageing, 1996: 25:479-489