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Predictive values of the DANish cognitive screen for cardiac arrest survivors (DANcSCA) - A digital cognitive
Anders Wieghorst1, Britt Borregaard2, Ann-Dorthe Zwisler3
1REHPA, The Danish Knowledge Centre for Rehabilitation and Palliative Care, Odense University Hospital, Nyborg, Denmark; Department of Clinical Research University of Southern Denmark, Vestergade 17, 5800 Nyborg, Denmark; Department of Psychology, University of Southern Denmark, Campusvej 55, 5230 Odense M, Denmark; "OPEN, Open Patient data Explorative Network, Odense University Hospital, Region of Southern Denmark" J. B. Winsløws Vej 21, 3rd floor, 5000 Odense C, Denmark.
Background:
Persistent cognitive deficits affect up to 50 % of out-of-hospital cardiac arrest (OHCA) survivors. Despite this prevalence, no consensus exists on the optimal tool for identifying deficits. This study assessed the predictive validity of the digital DANcSCA by comparing its classification of OHCA survivors into risk classes-green (low), yellow (moderate), and red (high)-against a neuropsychological test battery as the reference standard.
Methods:
The prospective, multicentre DANcSCA validation study was conducted at Danish hospitals and the Knowledge Centre for Rehabilitation and Palliative Care. Adult OHCA survivors were included. The reference standard comprised four neuropsychological tests: Rey Auditory Verbal Learning Test, Symbol Digit Modalities Test, Trail Making Test, and Verbal Fluency. The DANcSCA index test used subtests from the Cambridge Neuropsychological Test Automated Battery. Cognitive assessments occurred six to eight weeks post-arrest or during rehabilitation three months to three years post-arrest. ROC curves were constructed for binary classifications of green versus non-green and red versus non-red. Thresholds were set by fixing sensitivity at 0.90 for the green/non-green ROC and specificity at 0.90 for the red/non-red ROC.
Results:
Among 175 participants, the DANcSCA classified 23 % as green, 59 % as yellow, and 18 % as red, with 9 % false positives and 5 % false negatives. The ROC curve for distinguishing green from non-green had an AUC of 0.77, and for distinguishing red from non-red an AUC of 0.89.
Conclusion:
The digital DANcSCA appears suitable for cognitive screening following OHCA, although the modest AUC for green/non-green and potential overfitting warrant validation in new samples.
