Prestroke dementia: characteristics and clinical features in consecutive series of patients

Prestroke Cognitive Impairment: Frequency and Association With Premorbid Neuropsychiatric, Functional, and Neuroimaging Features

BACKGROUND

Some patients with stroke have prestroke cognitive impairment (pre-SCI), but its etiology is not clear. The aim of this cross-sectional study was to assess the frequency of pre-SCI and its association with premorbid neuropsychiatric, functional, and neuroimaging features.

METHODS

Patients hospitalized in stroke unit with an informant who could complete IQCODE (Informant Questionnaire for Cognitive Decline in the Elderly) were included. Pre-SCI was diagnosed if the IQCODE score was >3.3. Prestroke assessment also included NPI-Q (Neuropsychiatric Inventory Questionnaire), the basic Activities of Daily Living and Instrumental Activities of Daily Living scales, and the Clinical Dementia Rating scale. A multivariate logistic regression model was used to evaluate the association of pre-SCI with age, sex, education, arterial hypertension, atrial fibrillation, white matter lesions, cerebral microbleeds, and pathological medial temporal lobe atrophy.

RESULTS

IQCODE was available in 474 of 520 patients (91.2%; 45% women; mean age 75.5±13.3 years). Pre-SCI had a prevalence of 32.5% and was associated with prestroke NPI-Q (pre-SCI absent versus present, 1.7±2.3 versus 5.5±4.9; P<0.001), Activities of Daily Living scale (0.3±0.8 versus 1.8±1.9; P<0.001), Instrumental Activities of Daily Living scale (0.6±1.3 versus 3.8±4.0; P<0.001), and Clinical Dementia Rating scale score (0.7±1.7 versus 7.2±6.2; P<0.001). In the 271 patients with a magnetic resonance imaging available, the multivariate logistic regression showed that age (odds ratio [OR], 1.05 [95% CI, 1.62-9.73]), white matter lesions (OR, 1.26 [95% CI, 1.003-1.58]), and a pathological medial temporal lobe atrophy score (OR, 3.97 [95% CI, 1.62-9.73]) were independently associated with pre-SCI. In the 218 patients with ischemic stroke, white matter lesions (OR, 1.34 [95% CI, 1.04-1.72]) and medial temporal lobe atrophy (OR, 3.56 [95% CI, 1.38-9.19]), but not age, were associated with pre-SCI.

CONCLUSIONS

One-third of patients admitted to a stroke unit have pre-SCI that is associated with preexisting neuropsychiatric symptoms and functional performance. White matter lesions and medial temporal lobe atrophy are associated with pre-SCI, suggesting that both small vessel disease and neurodegeneration might be involved in its etiology.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early detection of dementia across a variety of healthcare settings

BACKGROUND

The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment.

OBJECTIVES

To determine the accuracy of the informant-based questionnaire IQCODE for the early detection of dementia across a variety of health care settings.

SEARCH METHODS

We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate.

SELECTION CRITERIA

We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool.

MAIN RESULTS

From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up. The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke. In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias.

AUTHORS' CONCLUSIONS

Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future detection of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.

Cognitive Impairment Before Atrial Fibrillation-Related Ischemic Events: Neuroimaging and Prognostic Associations

Background

It is likely that a proportion of poststroke cognitive impairment is sometimes attributable to unidentified prestroke decline; prestroke cognitive function is also clinically relevant because it is associated with poor functional outcomes, including death. We investigated the radiological and prognostic associations of preexisting cognitive impairment in patients with ischemic stroke or transient ischemic attack associated with atrial fibrillation.

Methods and Results

We included 1102 patients from the prospective multicenter observational CROMIS‐2 (Clinical Relevance of Microbleeds in Stroke 2) atrial fibrillation study. Preexisting cognitive impairment was identified using the 16‐item Informant Questionnaire for Cognitive Decline in the Elderly. Functional outcome was measured using the modified Rankin scale. Preexisting cognitive impairment was common (n=271; 24.6%). The presence of lacunes (odds ratio [OR], 1.50; 95% CI, 1.03–1.05; P=0.034), increasing periventricular white matter hyperintensity grade (per grade increase, OR, 1.38; 95% CI, 1.17–1.63; P<0.0001), deep white matter hyperintensity grade (per grade increase, OR, 1.26; 95% CI, 1.05–1.51; P=0.011), and medial temporal atrophy grade (per grade increase, OR, 1.61; 95% CI, 1.34–1.95; P<0.0001) were independently associated with preexisting cognitive impairment. Preexisting cognitive impairment was associated with poorer functional outcome at 24 months (mRS >2; adjusted OR, 2.43; 95% CI, 1.42–4.20; P=0.001).

Conclusions

Preexisting cognitive impairment in patients with atrial fibrillation–associated ischemic stroke or transient ischemic attack is common, and associated with imaging markers of cerebral small vessel disease and neurodegeneration, as well as with longer‐term functional outcome.

Clinical Trial Registration

URL: http://www.clinicaltrials.gov. Unique identifier: NCT02513316.

[The role of pre-stroke cognitive disorders in the formation of post-stroke cognitive impairment]

AIM

To identify pre-stroke cognitive disorders and assess their influence on the post-stroke neuropsychological status of the patient.

MATERIAL AND METHODS

The study included 103 patients in an acute state of ischemic stroke in the carotid system. Cognitive functions were assessed with MoCA and IQCODE. All patients are evaluated for the presence of vascular risk factors and their relationship to the cognitive impairment.

RESULTS AND CONCLUSION

According to the MoCA, 89 (86.4%) patients in the acute state of ischemic stroke had cognitive impairment of varying severity. Out of 103 patients, 55 (53.4%) had cognitive impairment prior to onset of stoke, mostly of mild severity. Among the main risk factors that correlated with the presence of pre-stroke cognitive impairment were age, heart rhythm disturbances and heart failure.

Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE) for the early diagnosis of dementia across a variety of healthcare settings

BACKGROUND

The Informant Questionnaire for Cognitive Decline in the Elderly (IQCODE) is a structured interview based on informant responses that is used to assess for possible dementia. IQCODE has been used for retrospective or contemporaneous assessment of cognitive decline. There is considerable interest in tests that may identify those at future risk of developing dementia. Assessing a population free of dementia for the prospective development of dementia is an approach often used in studies of dementia biomarkers. In theory, questionnaire-based assessments, such as IQCODE, could be used in a similar way, assessing for dementia that is diagnosed on a later (delayed) assessment.

OBJECTIVES

To determine the diagnostic accuracy of IQCODE in a population free from dementia for the delayed diagnosis of dementia (test accuracy with delayed verification study design).

SEARCH METHODS

We searched these sources on 16 January 2016: ALOIS (Cochrane Dementia and Cognitive Improvement Group), MEDLINE Ovid SP, Embase Ovid SP, PsycINFO Ovid SP, BIOSIS Previews on Thomson Reuters Web of Science, Web of Science Core Collection (includes Conference Proceedings Citation Index) on Thomson Reuters Web of Science, CINAHL EBSCOhost, and LILACS BIREME. We also searched sources specific to diagnostic test accuracy: MEDION (Universities of Maastricht and Leuven); DARE (Database of Abstracts of Reviews of Effects, in the Cochrane Library); HTA Database (Health Technology Assessment Database, in the Cochrane Library), and ARIF (Birmingham University). We checked reference lists of included studies and reviews, used searches of included studies in PubMed to track related articles, and contacted research groups conducting work on IQCODE for dementia diagnosis to try to find additional studies. We developed a sensitive search strategy; search terms were designed to cover key concepts using several different approaches run in parallel, and included terms relating to cognitive tests, cognitive screening, and dementia. We used standardised database subject headings, such as MeSH terms (in MEDLINE) and other standardised headings (controlled vocabulary) in other databases, as appropriate.

SELECTION CRITERIA

We selected studies that included a population free from dementia at baseline, who were assessed with the IQCODE and subsequently assessed for the development of dementia over time. The implication was that at the time of testing, the individual had a cognitive problem sufficient to result in an abnormal IQCODE score (defined by the study authors), but not yet meeting dementia diagnostic criteria.

DATA COLLECTION AND ANALYSIS

We screened all titles generated by the electronic database searches, and reviewed abstracts of all potentially relevant studies. Two assessors independently checked the full papers for eligibility and extracted data. We determined quality assessment (risk of bias and applicability) using the QUADAS-2 tool, and reported quality using the STARDdem tool.

MAIN RESULTS

From 85 papers describing IQCODE, we included three papers, representing data from 626 individuals. Of this total, 22% (N = 135/626) were excluded because of prevalent dementia. There was substantial attrition; 47% (N = 295) of the study population received reference standard assessment at first follow-up (three to six months) and 28% (N = 174) received reference standard assessment at final follow-up (one to three years). Prevalence of dementia ranged from 12% to 26% at first follow-up and 16% to 35% at final follow-up.The three studies were considered to be too heterogenous to combine, so we did not perform meta-analyses to describe summary estimates of interest. Included patients were poststroke (two papers) and hip fracture (one paper). The IQCODE was used at three thresholds of positivity (higher than 3.0, higher than 3.12 and higher than 3.3) to predict those at risk of a future diagnosis of dementia. Using a cut-off of 3.0, IQCODE had a sensitivity of 0.75 (95%CI 0.51 to 0.91) and a specificity of 0.46 (95%CI 0.34 to 0.59) at one year following stroke. Using a cut-off of 3.12, the IQCODE had a sensitivity of 0.80 (95%CI 0.44 to 0.97) and specificity of 0.53 (95C%CI 0.41 to 0.65) for the clinical diagnosis of dementia at six months after hip fracture. Using a cut-off of 3.3, the IQCODE had a sensitivity of 0.84 (95%CI 0.68 to 0.94) and a specificity of 0.87 (95%CI 0.76 to 0.94) for the clinical diagnosis of dementia at one year after stroke.In generaI, the IQCODE was sensitive for identification of those who would develop dementia, but lacked specificity. Methods for both excluding prevalent dementia at baseline and assessing for the development of dementia were varied, and had the potential to introduce bias.

AUTHORS' CONCLUSIONS

Included studies were heterogenous, recruited from specialist settings, and had potential biases. The studies identified did not allow us to make specific recommendations on the use of the IQCODE for the future diagnosis of dementia in clinical practice. The included studies highlighted the challenges of delayed verification dementia research, with issues around prevalent dementia assessment, loss to follow-up over time, and test non-completion potentially limiting the studies. Future research should recognise these issues and have explicit protocols for dealing with them.

Transoral robotic surgery (TORS) for laryngeal and hypopharyngeal cancers

Transoral robotic surgery (TORS) is increasingly used in laryngeal/hypopharyngeal cancer surgery. Ablative procedures described in these anatomical sites include: (i) supraglottic laryngectomy, (ii) total laryngectomy, (iii) glottic cordectomy, and (iv) partial pharyngectomy. TORS supraglottic laryngectomy remains the most commonly performed of these procedures. Initial oncologic and functional outcomes with these procedures are promising and comparable to other treatment options. As robotic instrumentation technology advances a rise in TORS laryngeal/hypopharyngeal surgery is anticipated.