ABSOLUTELY FUCKING USELESS!
Nothing on how to get cognition back to normal. Predictions do nothing to get survivors recovered. If your doctor predicts non recovery, ask for specific objective analysis and keep asking until the stroke president is notified of incompetence.
Strategic infarct locations for post-stroke cognitive impairment: a pooled analysis of individual patient data from 12 acute ischaemic stroke cohorts
- et al.
Summary
Background
Post-stroke cognitive impairment (PSCI) occurs in approximately half of people in
the first year after stroke. Infarct location is a potential determinant of PSCI,
but a comprehensive map of strategic infarct locations predictive of PSCI is unavailable.
We aimed to identify infarct locations most strongly predictive of PSCI after acute
ischaemic stroke and use this information to develop a prediction model.
Methods
In this large-scale multicohort lesion-symptom mapping study, we pooled and harmonised
individual patient data from 12 cohorts through the Meta-analyses on Strategic Lesion
Locations for Vascular Cognitive Impairment using Lesion-Symptom Mapping (Meta VCI
Map) consortium. The identified cohorts (as of Jan 1, 2019) comprised patients with
acute symptomatic infarcts on CT or MRI (with available infarct segmentations) and
a cognitive assessment up to 15 months after acute ischaemic stroke onset. PSCI was
defined as performance lower than the fifth percentile of local normative data, on
at least one cognitive domain on a multidomain neuropsychological assessment or on
the Montreal Cognitive Assessment. Voxel-based lesion-symptom mapping (VLSM) was used
to calculate voxel-wise odds ratios (ORs) for PSCI that were mapped onto a three-dimensional
brain template to visualise PSCI risk per location. For the prediction model of PSCI
risk, a location impact score on a 5-point scale was derived from the VLSM results
on the basis of the mean voxel-wise coefficient (ln[OR]) within each patient's infarct.
We did combined internal–external validation by leave-one-cohort-out cross-validation
for all 12 cohorts using logistic regression. Predictive performance of a univariable
model with only the location impact score was compared with a multivariable model
with addition of other clinical PSCI predictors (age, sex, education, time interval
between stroke onset and cognitive assessment, history of stroke, and total infarct
volume). Testing of visual ratings was done by three clinicians, and accuracy, inter-rater
reliability, and intra-rater reliability were assessed with Cohen's weighted kappa.
Findings
In our sample of 2950 patients (mean age 66·8 years [SD 11·6]; 1157 [39·2%] women),
1286 (43·6%) had PSCI. We achieved high lesion coverage of the brain in our analyses
(86·9%). Infarcts in the left frontotemporal lobes, left thalamus, and right parietal
lobe were strongly associated with PSCI (after false discovery rate correction, q<0·01;
voxel-wise ORs >20). On cross-validation, the location impact score showed good correspondence,
based on visual assessment of goodness of fit, between predicted and observed risk
of PSCI across cohorts after adjusting for cohort-specific PSCI occurrence. Cross-validations
showed that the location impact score by itself had similar performance to the combined
model with other PSCI predictors, while allowing for easy visual assessment. Therefore
the univariable model with only the location impact score was selected as the final
model. Correspondence between visual ratings and actual location impact score (Cohen's
weighted kappa: range 0·88–0·92), inter-rater agreement (0·85–0·87), and intra-rater
agreement (for a single rater, 0·95) were all high.
Interpretation
To the best of our knowledge, this study provides the first comprehensive map of strategic
infarct locations associated with risk of PSCI. A location impact score was derived
from this map that robustly predicted PSCI across cohorts. Furthermore, we developed
a quick and reliable visual rating scale that might in the future be applied by clinicians
to identify individual patients at risk of PSCI.
Funding
The Netherlands Organisation for Health Research and Development.
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