Who Is Classified as Untestable on Brief Cognitive Screens in an Acute Stroke Setting?

Elliott, Emma; Drozdowska, Bogna; Taylor‐Rowan, Martin; Shaw, Robert C.; Cuthbertson, Gillian; Quinn, Terence J.

doi:10.3390/diagnostics9030095

Cited by 19 publications

(23 citation statements)

References 35 publications

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“…This clinical practice, data-based study showed that 44% of the patients did not undergo cognitive screening during their stay in ASUs. The proportion of unscreened patients is higher than those reported by other studies, where approximately 17% of the patients did not undergo cognitive screening 10 , 25 . The divergence between the results of the present and previous studies may be related to the study design.…”

Section: Discussioncontrasting

confidence: 69%

“…In our study, the registry datasets generated from clinical practice were used. Thus, a more representative picture of clinical practice could be described compared with that in other studies where data collection was conducted with pre-specified inclusion and exclusion criteria 10 , 25 . Therefore, the results might be representative of other stroke units.…”

Section: Discussionmentioning

confidence: 99%

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Barriers to cognitive screening in acute stroke units

Abzhandadze

Buvarp

Lundgren‐Nilsson

et al. 2021

Sci Rep

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Cognitive impairment is common after stroke. However, not all patients with stroke undergo cognitive screening, despite recommendations. The aim of this retrospective, explorative study was to examine the barriers to cognitive screening in acute stroke units. Data were retrieved from two Swedish Stroke registries. The outcome variable was cognitive screening during the stay at acute stroke units. Forty-three candidate explanatory variables were considered for analysis, encompassing sociodemographic factors and stroke-related outcomes during the stay at acute stroke units. The Least Absolute Shrinkage and Selection Operator and decision-tree methods were used. Of the 1120 patients (56% male, mean age: 72 years, 50% with mild stroke), 44% did not undergo cognitive screening. Walking 10 m post-stroke was the most important attribute for decisions regarding cognitive screening. The classification accuracy, sensitivity, and specificity of the model were 70% (95% CI 63–75%), 71% (63–78%), and 67% (55–77%), respectively. Patient-related parameters that influenced cognitive screening with a valid and reliable screening instrument in acute stroke units included new stroke during the hospitalisation, aphasia at admission, mobility problems, impaired verbal output skills, and planned discharge to another care facility. The barriers to cognitive screening were both patient- and organisation-related, suggesting the need for patient-tailored cognitive screening tools as well as the implementation and systematic adherence to guidelines.

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Section: Discussioncontrasting

confidence: 69%

Section: Discussionmentioning

confidence: 99%

Barriers to cognitive screening in acute stroke units

Abzhandadze

Buvarp

Lundgren‐Nilsson

et al. 2021

Sci Rep

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“…[42]. The specific tasks included in this measure have been described in a previous publication [43].…”

Section: Mediatorsmentioning

confidence: 99%

Cardiovascular risk factors indirectly affect acute post-stroke cognition through stroke severity and prior cognitive impairment: a moderated mediation analysis

et al. 2020

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Background: Cognitive impairment is an important consequence of stroke and transient ischaemic attack, but its determinants are not fully understood. Simple univariable or multivariable models have not shown clinical utility for predicting cognitive impairment. Cardiovascular risk factors may influence cognition through multiple, direct, and indirect pathways, including effects on prior cognition and stroke severity. Understanding these complex relationships may help clinical teams plan intervention and follow-up strategies. Methods: We analysed clinical and demographic data from consecutive patients admitted to an acute stroke ward. Cognitive assessment comprised Abbreviated Mental Test and mini-Montreal Cognitive Assessment. We constructed bias-corrected confidence intervals to test indirect effects of cardiovascular risk factors (hypertension, vascular disease, atrial fibrillation, diabetes mellitus, previous stroke) on cognitive function, mediated through stroke severity and history of dementia, and we assessed moderation effects due to comorbidity. Results: From 594 eligible patients, we included 587 in the final analysis (age range 26-100; 45% female). Our model explained R 2 = 62.10% of variance in cognitive test scores. We found evidence for an indirect effect of previous stroke that was associated with increased risk of prevalent dementia and in turn predicted poorer cognitive score (estimate = − 0.39; 95% bias-corrected CI, − 0.75 to − 0.13; p = 0.02). Atrial fibrillation was associated with greater stroke severity and in turn with a poorer cognitive score (estimate = − 0.27; 95% bias-corrected CI, − 0.49 to − 0.05; p = 0.02). Conversely, previous TIA predicted decreased stroke severity and, through that, lesser cognitive impairment (estimate = 0.38; 95% bias-corrected CI, 0.08 to 0.75; p = 0.02). Through an association with reduced stroke severity, vascular disease was associated with lesser cognitive impairment, conditional on presence of hypertension and absence of diabetes mellitus (estimate = 0.36; 95% bias-corrected CI, 0.03 to 0.68; p = 0.02), although the modelled interaction effects did not reach statistical significance.

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“…Common themes from our PROBAST ratings highlight some of the challenges inherent to stroke prognostic research. Stroke-related impairments limiting completion of certain assessments, 28 deaths and losses to follow-up can all contribute to missing data and biased study samples. Another challenge relates to incorporation bias, where the assessment of the outcome of interest requires knowledge of factors that inform the prognostic tool.…”

Section: Discussionmentioning

confidence: 99%

Prognostic rules for predicting cognitive syndromes following stroke: A systematic review

Drozdowska

McGill

McKay

et al. 2021

European Stroke Journal

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Purpose Stroke survivors are at high risk of developing cognitive syndromes, such as delirium and dementia. Accurate prediction of future cognitive outcomes may aid timely diagnosis, intervention planning, and stratification in clinical trials. We aimed to identify, describe and appraise existing multivariable prognostic rules for prediction of post-stroke cognitive status. Method We systematically searched four electronic databases from inception to November 2019 for publications describing a method to estimate individual probability of developing a cognitive syndrome following stroke. We extracted data from selected studies using a pre-specified proforma and applied the Prediction model Risk Of Bias Assessment Tool (PROBAST) for critical appraisal. Findings Of 17,390 titles, we included 10 studies (3143 participants), presenting the development of 11 prognostic rules – 7 for post-stroke cognitive impairment and 4 for delirium. Most commonly incorporated predictors were: demographics, imaging findings, stroke type and symptom severity. Among studies assessing predictive discrimination, the area under the receiver operating characteristic (AUROC) in apparent validation ranged from 0.80 to 0.91. The overall risk of bias for each study was high. Only one prognostic rule had been externally validated. Discussion/conclusion: Research into the prognosis of cognitive outcomes following stroke is an expanding field, still at its early stages. Recommending use of specific prognostic rules is limited by the high risk of bias in all identified studies, and lack of supporting evidence from external validation. To ensure the quality of future research, investigators should adhere to current, endorsed best practice guidelines for conduct of prediction model studies.

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Who Is Classified as Untestable on Brief Cognitive Screens in an Acute Stroke Setting?

Cited by 19 publications

References 35 publications

Barriers to cognitive screening in acute stroke units

Barriers to cognitive screening in acute stroke units

Cardiovascular risk factors indirectly affect acute post-stroke cognition through stroke severity and prior cognitive impairment: a moderated mediation analysis

Prognostic rules for predicting cognitive syndromes following stroke: A systematic review

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