INS NYC 2024 Program

Poster	Poster Session 08 Program Schedule 02/16/2024 01:45 pm - 03:00 pm Room: Shubert Complex (Posters 1-60) Poster Session 08: Cognition \| Cognitive Reserve Variables Final Abstract #45 Cognitive Function in Older Adults with Congenital Heart Disease: Results of a National Centre Study Elise Liljekvist, Department of Cardiology, Skåne University Hospital, Lund University, Lund, Sweden Åsa Hammar, Clinical Sciences, Lund University, Office for Psychiatry and Habilitation, Psychiatry Research Skåne, Region Skåne, Lund, Sweden Åsa Hammar, Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway Linda Ternrud, Department of Cardiology, Skåne University Hospital, Lund University, Clinical Sciences, Lund University, Lund, Sweden Joanna Hlebowicz, Department of Cardiology, Skåne University Hospital, Lund University, Clinical Sciences, Lund University, Lund, Sweden Category: Medical/Neurological Disorders/Other (Adult) Keyword 1: congenital disorders Keyword 2: cognitive functioning Keyword 3: executive functions Objective: The life expectancy of congenital heart disease (CHD) patients is rising, leading to an ageing population. Recent studies show that there is higher morbidity, healthcare use and mortality among older CHD patients and that this may be associated with cognitive impairment. However, knowledge about cognitive function and which particular test we should use in the clinical daily practice in older CHD patients is currently limited. This study aimed to describe cognitive dysfunction in older adults with moderate to complexity CHD and investigate the relationship with patients self-reported out-come and cognitive function. Participants and Methods: We included 47 patients aged ≥ 40 years (median age: 55 years [40-70 years], 37% were women, 83% had moderate disease and 17% had complex CHD). Cognitive function was evaluated using a battery of neuropsychological tests including the Montreal Cognitive Assessment (MoCA), Symbol Digit Modalities Test (SDMT), Trail-Making Test (TMT1-5, D-KEFS), Verbal Fluency Test (VF1, D-KEFS), Color-Word Interference Test (CWIT1-4, D-KEFS), Brief Visuospatial Memory Test (BVMT-R), Dysexecutive questionnaire (DEX, BADS). Outcomes were compared with normative data and patients were classified into robust, impaired or not. Z-scores were computed for tests included in the neuropsychological battery. The cut-off performed z-score (-0.6 – -1.3)(-1.3 – -2.0)( ≤ − 2), was approximately the 24^th percentile. Fatigue was assessed by the Multidimensional Fatigue Inventory (MFI-20). Spearman’s correlations were used to determine the relationship between MoCA and different cognitive tests. Results: Based on the MoCA, 37% had cognitive impairment in this total sample. Using the SDMT, processing speed was measured, and showed that 37% had cognitive impairment. TMT1 was used to measure processing speed and attention and showed that 17% had cognitive impairment. CWIT1 was used to measure processing speed and attention and showed that 52% had cognitive impairment. Using the TMT3 to measure executive function, 22% were found to have cognitive impairment. The TMT4 showed that 48% had cognitive impairment. With the VF1-test, 41% were found to have cognitive impairment of executive function. Using the BVMT-total to measure episodic memory, learning and recognition memory, 48% of the sample were found to have cognitive impairment. Using the BVMT-delay, 37% were found to have cognitive impairment. With the BVMT2, 44% were found to have cognitive impairment, BVMT3, 39% were found to have cognitive impairment. In our study 91% of the patients reported mild to very severe mental and general fatigue. Correlations were observed between MoCA and SDMT (r=0.356, p=0.017), TMT1 (r=0.501, p<0.001), TMT3 (r=0.379, p=0.011), TMT4 (r=0.378, p=0.011), VF1 (r=0.438, p=0.003), CWIT1 (r=0.408, p=0.007), BVMT2 (r=0.363, p=0.014), BVMT3 (r=0.436, p=0.003), BVMT-total (r=0.295, p=0.049) and BVMT-delay (r=0.475, p<0.001). Correlations were observed between MFI-20/general fatigue and DEX (r=0.302, p=0.037). The correlation doesn’t indicate that MFI-20/general fatigue, can describe cognitive dysfunction regarding self-reported executive function. Based on the DEX, only 4% in this sample reported mild to severe cognitive executive impairment. Conclusions: This study describes a relative high prevalence of cognitive dysfunction in older adults with moderate to complex CHD, which suggests that the MoCA test may be suitable to use as screening instrument in daily practice. However, this study indicates that it is not self-reported cognitive impairments and executive functions that describe this population.

Poster

02/16/2024
01:45 pm - 03:00 pm
Room: Shubert Complex (Posters 1-60)

Poster Session 08: Cognition | Cognitive Reserve Variables

Final Abstract #45

Cognitive Function in Older Adults with Congenital Heart Disease: Results of a National Centre Study

Elise Liljekvist, Department of Cardiology, Skåne University Hospital, Lund University, Lund, Sweden
Åsa Hammar, Clinical Sciences, Lund University, Office for Psychiatry and Habilitation, Psychiatry Research Skåne, Region Skåne, Lund, Sweden
Åsa Hammar, Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
Linda Ternrud, Department of Cardiology, Skåne University Hospital, Lund University, Clinical Sciences, Lund University, Lund, Sweden
Joanna Hlebowicz, Department of Cardiology, Skåne University Hospital, Lund University, Clinical Sciences, Lund University, Lund, Sweden

Category: Medical/Neurological Disorders/Other (Adult)

Keyword 1: congenital disorders
Keyword 2: cognitive functioning
Keyword 3: executive functions

Objective:

The life expectancy of congenital heart disease (CHD) patients is rising, leading to an ageing population. Recent studies show that there is higher morbidity, healthcare use and mortality among older CHD patients and that this may be associated with cognitive impairment. However, knowledge about cognitive function and which particular test we should use in the clinical daily practice in older CHD patients is currently limited.

This study aimed to describe cognitive dysfunction in older adults with moderate to complexity CHD and investigate the relationship with patients self-reported out-come and cognitive function.

Participants and Methods:

We included 47 patients aged ≥ 40 years (median age: 55 years [40-70 years], 37% were women, 83% had moderate disease and 17% had complex CHD).

Cognitive function was evaluated using a battery of neuropsychological tests including the Montreal Cognitive Assessment (MoCA), Symbol Digit Modalities Test (SDMT), Trail-Making Test (TMT1-5, D-KEFS), Verbal Fluency Test (VF1, D-KEFS), Color-Word Interference Test (CWIT1-4, D-KEFS), Brief Visuospatial Memory Test (BVMT-R), Dysexecutive questionnaire (DEX, BADS). Outcomes were compared with normative data and patients were classified into robust, impaired or not. Z-scores were computed for tests included in the neuropsychological battery. The cut-off performed z-score (-0.6 – -1.3)(-1.3 – -2.0)( ≤ − 2), was approximately the 24^th percentile. Fatigue was assessed by the Multidimensional Fatigue Inventory (MFI-20).

Spearman’s correlations were used to determine the relationship between MoCA and different cognitive tests.

Results:

Based on the MoCA, 37% had cognitive impairment in this total sample. Using the SDMT, processing speed was measured, and showed that 37% had cognitive impairment. TMT1 was used to measure processing speed and attention and showed that 17% had cognitive impairment. CWIT1 was used to measure processing speed and attention and showed that 52% had cognitive impairment.

Using the TMT3 to measure executive function, 22% were found to have cognitive impairment. The TMT4 showed that 48% had cognitive impairment. With the VF1-test, 41% were found to have cognitive impairment of executive function.

Using the BVMT-total to measure episodic memory, learning and recognition memory, 48% of the sample were found to have cognitive impairment. Using the BVMT-delay, 37% were found to have cognitive impairment. With the BVMT2, 44% were found to have cognitive impairment, BVMT3, 39% were found to have cognitive impairment. In our study 91% of the patients reported mild to very severe mental and general fatigue.

Correlations were observed between MoCA and SDMT (r=0.356, p=0.017), TMT1 (r=0.501, p<0.001), TMT3 (r=0.379, p=0.011), TMT4 (r=0.378, p=0.011), VF1 (r=0.438, p=0.003), CWIT1 (r=0.408, p=0.007), BVMT2 (r=0.363, p=0.014), BVMT3 (r=0.436, p=0.003), BVMT-total (r=0.295, p=0.049) and BVMT-delay (r=0.475, p<0.001).

Correlations were observed between MFI-20/general fatigue and DEX (r=0.302, p=0.037). The correlation doesn’t indicate that MFI-20/general fatigue, can describe cognitive dysfunction regarding self-reported executive function. Based on the DEX, only 4% in this sample reported mild to severe cognitive executive impairment.

Conclusions:

This study describes a relative high prevalence of cognitive dysfunction in older adults with moderate to complex CHD, which suggests that the MoCA test may be suitable to use as screening instrument in daily practice. However, this study indicates that it is not self-reported cognitive impairments and executive functions that describe this population.