Identifying dementia using medical data linkage in a longitudinal cohort study: Lothian Birth Cohort 1936.

BACKGROUND: The Lothian Birth Cohort 1936 (LBC1936) is a longitudinal study of ageing with well-characterised assessments, but until now, it has relied on self-report or proxies for dementia such as cognitive tests. Our aims were twofold: a) to describe a framework for identifying dementia in a cohort study. b) to report the age-specific incidence and prevalence of all-cause dementia and dementia subtypes in 865 individuals in the LBC1936. METHODS: Electronic Health Records (EHR) of all participants were reviewed, and relevant information was extracted to form case vignettes for everyone with any record of cognitive dysfunction. The EHR data sources include hospital and clinic letters, general practitioner and hospital referrals, prescribed medications, imaging and laboratory results. Death certificate data were obtained separately. Clinician assessments were performed when there was concern about a participant's cognition. A diagnosis of probable dementia, possible dementia, or no dementia was agreed upon by a consensus diagnostic review board, comprised of a multidisciplinary team of clinical dementia experts who reviewed case vignettes and clinician assessment letters. For those with probable dementia, a subtype was also determined, where possible. We compared the agreement between our newly ascertained dementia diagnoses with the existing self-reported dementia diagnoses. RESULTS: Self-reported dementia diagnoses were positive in only 17.8% of ascertained dementia diagnoses. The EHR review identified 163/865 (18.8%) individuals as having cognitive dysfunction. At the consensus diagnostic review board, 118/163 were diagnosed with probable all-cause dementia, a prevalence of 13.6%. Age-specific dementia prevalence increased with age from 0.8% (65-74.9 years) to 9.93% (85-89.9 years). Prevalence rates for women were higher in nearly all age groups. The most common subtype was dementia due to Alzheimer disease (49.2%), followed by mixed Alzheimer and cerebrovascular disease (17.0%), dementia of unknown or unspecified cause (16.1%), and dementia due to vascular disease (8.5%). CONCLUSIONS: We present a robust systematic framework and guide for other cohort teams wanting to ascertain dementia diagnoses. The newly ascertained dementia diagnosis provides vital data for further analyses of LBC1936 to allow exploration of lifecourse predictors of dementia.

Feasibility of Atrial Fibrillation Screening With Mobile Health Technologies at Pharmacies.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia. Thus, the aim of our study was to evaluate the smartphone-based electrocardiogram (ECG) recordings aimed at AF screening at Polish pharmacies. METHODS: Prospective AF screening among patients aged ≥65 years was conducted at 10 pharmacies using Kardia Mobile with a dedicated application (Kardia app). Prior AF was a study exclusion criterion. CHA2DS2-VASc score (congestive heart failure, hypertension, age, diabetes mellitus, previous stroke/transient ischemic attack, female sex, and vascular disease) has been collected from every patient. A single-lead ECG has been acquired by the placement of fingers from each hand on the pads. Kardia app diagnosis has been evaluated by the cardiologist. RESULTS: A total of 525 ECGs were performed. Kardia app diagnosis was provided in 490 cases. In 437 (89.18%) cases, it was "normal" rhythm, in 17 (3.47%) recordings "possible AF," in 23 (4.69%) ECGs "unreadable," and in 13 (2.65%) "unclassified". After the cardiologist reevaluation, the new AF was identified in 7 (1.33%) patients. Sensitivity and specificity of Kardia app in detecting AF was 100% (95% confidence interval [CI]: 71.5%-100%) and 98.7% (95% CI: 97.3%-99.5%), respectively. The positive predictive value was 64.7% (95% CI: 38.3%-85.7%) and the negative predictive value was 100% (95% CI: 99.2%-100%). CHA2DS2-VASc score was 2.14 ± 0.69 for those with new AF and 3.33 ± 1.26 in the non-AF group. CONCLUSION: Kardia app is capable of fast screening and detecting AF with high sensitivity and specificity. The possible diagnosis of AF deserves additional cardiological evaluation. The results obtained in patients with low CHA2DS2-VASc score and "silent" AF confirm the importance of routine AF screening. Cardiovascular screening with the use of mobile health technology is feasible at pharmacies.