Anatomic stenosis evaluation on coronary CT angiography (CCTA) lacks specificity in indicating the functional significance of a stenosis. Recent developments in CT techniques (including dual-layer spectral detector CT [SDCT] and static stress CT perfusion [CTP]) and image analyses (including fractional flow reserve [FFR] derived from CCTA images [FFRCT] and deep learning analysis [DL]) are potential strategies to increase the specificity of CCTA by combining both anatomical and functional information in one investigation. The aim of the current study is to assess the diagnostic performance of (combinations of) SDCT, CTP, FFRCT and DL for the identification of functionally significant coronary artery stenosis.
Seventy-five patients aged 18 years and older with stable angina and known coronary artery disease and scheduled to undergo clinically indicated invasive FFR will be enrolled. All subjects will undergo the following SDCT scans: coronary calcium scoring, static stress CTP, rest CCTA and if indicated (history of myocardial infarction) a delayed enhancement acquisition. Invasive FFR of ≤0.80, measured within 30 days after the SDCT scans, will be used as reference to indicate a functionally significant stenosis. The primary study endpoint is the diagnostic performance of SDCT (including CTP) for the identification of functionally significant coronary artery stenosis. Secondary study endpoint is the diagnostic performance of SDCT, CTP, FFRCT and DL separately and combined for the identification of functionally significant coronary artery stenosis.
Ethical approval was obtained. All subjects will provide written informed consent. Study findings will be disseminated through peer-reviewed conference presentations and journal publications.
To assess changes in depressive symptoms and health-related quality of life (HRQOL) after screening for cognitive impairment in people with type 2 diabetes.
A prospective cohort study, part of the Cognitive Impairment in Diabetes (Cog-ID) study.
Participants were screened for cognitive impairment in primary care. People suspected of cognitive impairment (screen positives) received a standardised evaluation at a memory clinic.
Participants ≥70 years with type 2 diabetes were included in Cog-ID between August 2012 and September 2014, the current study includes 179 patients; 39 screen positives with cognitive impairment, 56 screen positives without cognitive impairment and 84 participants not suspected of cognitive impairment during screening (screen negatives).
Depressive symptoms and HRQOL assessed with the Center for Epidemiologic Studies Depression Scale (CES-D), 36-Item Short-Form Health Survey, European Quality of Life-5 Dimensions questionnaire and the EuroQol Visual Analogue Scale. Outcomes were assessed before the screening, and 6 and 24 months after screening. An analysis of covariance model was fitted to assess differences in score changes among people diagnosed with cognitive impairment, screen negatives and screen positives without cognitive impairment using a factor group and baseline score as a covariate.
Of all participants, 60.3% was male, mean age was 76.3±5.0 years, mean diabetes duration 13.0±8.5 years. At screening, participants diagnosed with cognitive impairment had significantly more depressive symptoms and a worse HRQOL than screen negatives. Scores of both groups remained stable over time. Screen positives without cognitive impairment scored between the other two groups at screening, but their depressive symptoms decreased significantly during follow-up (mean CES-D: –3.1 after 6 and –2.1 after 24 months); their HRQOL also tended to improve.
Depressive symptoms are common in older people with type 2 diabetes. Screening for and a subsequent diagnosis of cognitive impairment will not increase depressive symptoms.