Predictive value of baseline cognitive functioning on health-related quality of life in individuals with coronary artery disease: a 5-year longitudinal study

Abstract

Aims

Emerging studies suggest an association exists between coronary artery disease (CAD) and the development of neurodegenerative diseases, with CAD acting as a precursor. Our study aimed to investigate the relationship between baseline measures of cognitive functioning and long-term health-related quality of life (HRQoL) in individuals with CAD with specification to Type D personality traits and sex.

Methods and results

This prospective observational cohort study consisted of 864 participants (mean age 58 SD = 9 years, 74.0% men) with CAD after acute coronary syndrome. Baseline characteristics included comprehensive cognitive testing, measures of sociodemographic and clinical factors, and psychological assessment scales, such as Type D personality scale and the Hospital Anxiety and Depression scale. The Minnesota Living with Heart Failure Questionnaire assessed participants’ HRQoL, conducted through phone interviews at baseline, every 6 months for up to 2 years, and after 5 years. Cognitive functioning correlated with HRQoL at all time intervals over the 5-year follow-up. Regarding sex and Type D personality, significant differences emerged in associations between impaired cognitive functioning at baseline and HRQoL measured over the period of 5 years. Men participants with characteristics of Type D personality were especially vulnerable to impaired cognitive functioning affecting the 5-year quality of life.

Conclusion

Men with CAD who obtained scores indicating characteristics of Type D personality were significantly more likely to have lower baseline cognitive functions and long-term HRQoL outcomes. This information could inform healthcare practitioners to screen for personality characteristics and closely follow-up those at a greater risk.

Coronary artery disease, Health-related quality of life, Type D personality, Cognition

Implications for practice

• Analysis of cognitive functioning soon after a cardiac event in a rehabilitation setting may provide an important value in predicting health-related quality of life (HRQoL) up to 5 years.

• Assessment of Type D personality is recommended as a routine practice in a rehabilitation setting as this measure is useful in identifying coronary artery disease (CAD) population subgroups vulnerable to cognitive impairment and decreased long-term quality of life.

• Neuropsychological evaluation in a CAD rehabilitation setting should particularly target men who obtained scores indicating characteristics of Type D personality as they are particularly vulnerable for lower baseline cognitive functions and worse long-term HRQoL outcome.

Introduction

Cardiovascular diseases (CVDs) are a recognized risk factor for cognitive impairment, and the term ‘vascular cognitive impairment’ is often used to indicate cognitive decline related to cardiovascular factors.¹ Several studies confirmed that individuals with coronary artery disease (CAD) and heart failure (HF) most often demonstrate deficits in executive functioning, global cognition, complex psychomotor speed, and verbal memory.² Reduced cognitive functioning is known to negatively impact many aspects of individual functioning, including the psychological, social and occupational spheres.³ Recent literature has suggested that the decline of cognitive functions in individuals with CAD is related to significant deterioration of health-related quality of life (HRQoL).⁴

Contemporary scholars agree that subjective HRQoL is a multidimensional construct, involving an individual feeling of general well-being in the areas of ‘physical and psychosocial functioning.’^5,6 In the last 10 years, HRQoL has become an important tool for assessing functional recovery in individuals with CAD. Longitudinal studies are needed to deepen the understanding of functional outcomes of individuals with CAD by investigating a set of cognitive, clinical, and personality predictors and their impact on HRQoL.⁷

Type D personality traits are well-researched psychological risk factors of adverse CAD outcomes, associated with an elevated risk of cardiac events and mortality.⁸ Indeed, research has shown that Type D personality traits contribute in a significant manner to cognitive function and HRQoL of patients with CAD.^4,9,10 Recent literature indicates that the presence of Type D personality traits—consisting of negative affectivity and social inhibition features—in individuals with CAD and HF undergoing rehabilitation is significantly associated with impaired HRQoL and worse global cognitive functioning.^4,9 These findings support that a complex set of personality variables affect functional recovery, warranting a deeper understanding of interrelationships between Type D personality traits, cognitive functions, and HRQoL.

Another essential aspect in the previous relationship is sex differences. For example, an extensive study (N = 7479) by Haring et al.¹¹ involving postmenopausal women with CVD showed increased risk of cognitive decline in this group. Recently, a systematic review by Narvaez Linares et al.¹² found that women with CAD, like myocardial infarction (MI) and angina pectoris (AP), experience cognitive deficits following a CAD event. Nevertheless, women are usually less likely to have Type D personality¹³, and their coping strategies for HRQoL improvement might differ from men.¹⁴

Thus, this study is the first known investigation to examine the relationship between baseline measures of cognitive functioning and 5-year HRQoL in individuals with CAD, while taking into consideration Type D personality traits and sex. Considering past research, we hypothesize that individuals with CAD with Type D characteristics compared to participants without these characteristics will obtain significantly lower results on cognitive tests. We also hypothesize that there will be sex differences in baseline cognitive function measures in individuals with CAD. Finally, a third hypothesis states that cognitive functions measured at baseline will be associated with reduced baseline HRQoL, and that this association will last over the 5-year follow-up period. However, we believe that sex and Type D personality traits could potentially mitigate this relationship.

Methods

Study participants

From 2014 to 2018, we invited 950 individuals with CAD to participate in this study. Our exclusion criteria included: (i) cognitive impairment assessed by a cognitive screener [Mini-Mental State Examination (MMSE) score < 19] or a marked disability to communicate (n = 36); (ii) severe comorbidities including unstable cardiovascular status at baseline or chronic kidney failure (n = 35); and (iii) refusal to participate (n = 15). Thus, the final sample consisted of N = 864 individuals with CAD [74.0% men (n_m = 639) and 26.0% women (n_w = 225)] with a mean age of 58 ± 9 years. Only HRQoL data were gathered longitudinally and participant responses varied accordingly: after 6 months [n = 698, 80.8% (n_m = 521, n_w = 177)], 12 months [n = 777, 89.9% (n_m = 578, n_w = 199)], 18 months [n = 833, 96.4% (n_m = 614, n_w = 219)], 24 months [n = 826, 95.6% (n_m = 608, n_w = 218)], and 5 years [n = 693, 80.2% (n_m = 500, n_w = 193)] (Figure 1).

Figure 1

Participant flow chart.

Study procedure

Within 7 days after treatment for either MI or unstable AP, individuals attending an inpatient cardiac rehabilitation programme at the hospital Palangos Klinika were invited to participate in the study. On admission to the study, an experienced cardiologist (J.Br.) evaluated participants’ level of cardiac dysfunction using echocardiography. Within 3 days, participants provided baseline measures of sociodemographic, psychological, and cognitive factors and clinical data, including CAD risk factors. We gathered their contact information to implement the HRQoL follow-up assessments over a period of 5 years. Each participant gave informed consent before participation. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki. The Kaunas Regional Biomedical Research Ethics Committee approved the study protocol (Protocol No. BE-2-21; P1-38/2007; P2-38/2007).

Sociodemographic and clinical characteristics

Sociodemographic information collected included sex, age, and education. (Throughout the article, we use the terms ‘men’ and ‘women’. However, we are referring to the concept of ‘sex’ which is biological sex at birth, rather than ‘gender’ which is an individual’s socially constructed gender role and gender expression.) The degree of functional disability was based on the New York Heart Association (NYHA) functional I–IV classification system and was rated together with left ventricular function. We retrieved the history of acute MI, unstable AP, and hypertension, as well as information on body mass index (BMI), smoking history, and medication use from existing medical records.

Measures

Mini-Mental State Examination, MMSE

The MMSE¹⁵ served to screen the global cognitive functioning of individuals with CAD. MMSE’s cognitive function areas include attention, immediate and delayed recall, orientation, visual-constructive abilities, and language. Scores of the MMSE test may vary from 0 to 30. Scores from 25 to 30 indicate no cognitive impairment, scores below 25 represent a mild form of cognitive impairment, and scores below 20 indicate the possibility of severe cognitive impairment. In this study, we used the Lithuanian version of the MMSE.¹⁶

Digit Span Test, DST

The Digit Span Test (DST) was used to measure participants’ auditory working memory.¹⁷ The test is divided into two parts: (i) participants are required to repeat numbers using the same numerical order that was previously presented to them; and (ii) participants have to repeat digits in reversed order. The results of the DST represent two possible cognitive outcomes with scores ranging from 0 to 14. Higher scores on the first part represent better cognitive functioning in the auditory attention domain, while higher scores in the second part represent better auditory working memory.

Digit Symbol Test, DSST

The Digit Symbol Test (DSST)¹⁷ examines an individual’s psychomotor ability, speed, and visual–motor coordination. In this test, participants must quickly assign the correct symbol to a random digit based on the code provided on a separate table. Scores of the test range from 0 to 93.

Trail Making Test—Part A and B, TMT-A; TMT-B

The main cognitive functions measured with the Trail Making Test (TMT)¹⁸ include perceptual speed, executive control, and task switching. Time competition is essential for these tasks; the faster, the better. In the TMT-A version, the participant must connect randomly displayed numbers in numerical order. In the TMT-B version, the participant must connect both letters and numbers alternately in sequential (alphabetical and numeric) order. Participants are corrected if an error is identified (e.g. set-loss). The total time measured in seconds to complete TMT-A and TMT-B versions reflects the perceptual speed and task switching, respectively. The executive control measure is derived by subtracting the time to complete TMT-A from the time to complete TMT-B, whereby a lower score represents better executive control.

Minnesota Living with Heart Failure Questionnaire, MLHFQ

The Minnesota Living with Heart Failure Questionnaire (MLHFQ) is a 21-question instrument designed to measure the HRQoL of individuals with HF.¹⁹ While this questionnaire was initially designed for individuals with HF, several studies have used it with individuals with CAD finding relatively little difference in sensitivity to CAD-related HRQoL between the generic indexes and MLHFQ^20,21. Answers on a six-point Likert scale range from 0 to 5, with a total score range from 0 to 105. Higher scores represent a greater influence of HF on HRQoL. The internal reliability of the MLHFQ in this study was: Total HRQoL Cronbach’s α = 0.912; Physical HRQoL Cronbach’s α = 0.882; and Emotional HRQoL Cronbach’s α = 0.827.

Type D personality scale, DS14

We used the Type D personality scale (DS14) to assess Type D personality characteristics in our sample. The questionnaire has two factors—each containing seven questions answered using a five-point Likert scale and measuring negative affectivity and social inhibition.²² The total score on each subscale ranges from zero to 28. If both subscales have scores ≥10, there is an indication of Type D personality traits. The internal reliability of DS14 for our sample was: Cronbach’s α = 0.804.

Hospital Anxiety and Depression Scale, HADS

The Hospital Anxiety and Depression Scale (HADS) is a 14-item self-assessment tool often used for anxiety (HADS-A) and depression (HADS-D) symptoms evaluation.²³ Each question is rated on a four-point Likert scale. The sum scores of the HADS-A and the HADS-D subscales range from zero to 21. Higher scores represent higher levels of anxiety and depression symptoms. The internal reliability of our sample was: HADS-A Cronbach’s α = 0.832; HADS-D Cronbach’s α = 0.743.

Multidimensional Fatigue Inventory-20, MFI-20

To measure Reduced Motivation in our sample, we used a subscale from the Multidimensional Fatigue Inventory-20 (MFI-20).^24,25 Participants rated four questions on a five-point Likert scale ranging from 1 to 5. The total score on the MFI-20 motivation subscale ranges from 4 to 20. The higher the score, the more motivated a person is to initiate an activity. The reliability of the MFI-20 scale for our sample is acceptable (Cronbach’s α = 0.555).

Statistical analysis

We used the SPSS statistical package for Windows version 17.0 (SPSS Inc., Chicago, IL, USA) to conduct the statistical analyses. We first calculated the means and frequencies for sociodemographic, clinical risk factor characteristics, mental distress, fatigue, cognitive function, and HRQoL scores. Then a t-test for independent samples and χ² criteria for categorical variables were used to compare means and frequencies.

The relationships between cognitive functioning and HRQoL, both during cardiac rehabilitation and during the 5-year follow-up, were determined using Pearson correlation analysis. With Bonferroni adjustment, we corrected multiple comparisons where eight independent variables predicted HRQoL scores (adjusted P-value was determined by dividing 0.05 alpha level by eight). Thus, we included into the multivariable linear regression models variables statistically significant at the level of P <0.006 in the Pearson correlation analysis.

We used multivariable linear regression analyses to determine if cognitive functioning remained associated with HRQoL. When testing for associations, we also aimed to adjust our results with sociodemographic, clinical, and psychological risk factors such as: (i) age; (ii) education; (iii) NYHA functional class; (iv) left ventricular ejection fraction; (v) hypertension; (vi) smoking; (vii) BMI; (viii) medication use; (ix) anxiety and depression symptoms; and (x) reduced motivation. Stringent control for the previously established cognitive function and quality of life risk factors enabled us to identify a unique relationship between the cognitive function measures and quality of life. We performed two separate multivariable linear regression analyses for those with and without Type D personality characteristics.

With a given sample size allowing R² for a 2% change, we achieved power ranging from 0.950 to 0.953.

Results

Baseline information of sociodemographic characteristics in our study participants is presented in Table 1, separated according to sex and presence of Type D personality traits. In brief, 641 (74.0%) participants were men, the mean age was 58 ± 9. In total, 676 (78.0%) of the participants had II NYHA functional class and the remaining 135 (16.0%) participants were within the III NYHA functional class. In total, 695 (80.0%) of participants had hypertension, while 98 (11.0%) had left ventricular ejection fraction ≤40%. Overall, 107 (12.0%) participants had moderate to severe depressive symptoms (HADS-D score ≥ 8), while 291 (34.0%) had markedly expressed anxiety symptoms (HADS-A score ≥ 8).

Table 1

Baseline characteristics of study participants, comparing the sub-groups with and without Type D personality traits

Characteristics	Total group (N = 864)	Men (n = 639)	Women (n = 225)	P-value	Non-D type (n = 580)	D type (n = 284)	P-value
Age (years), mean ± SD	58 ± 9	57 ± 9	61 ± 8	<0.001	57.8 ± 9.1	58.4 ± 8.8	0.316
Sex, n (%)
Male	639 (74.0)				455 (78.4)	184 (64.8)	<0.001
Education, n (%)				0.941			0.001
Up to 8 years	77 (8.9)	58 (9.1)	19 (8.4)		49 (8.4)	28 (9.9)
High school	427 (49.4)	314 (49.1)	113 (50.2)		264 (45.5)	163 (57.4)
College/university degree	360 (41.7)	267 (41.8)	93 (41.3)		267 (46.0)	93 (32.7)
NYHA functional class, n (%)				<0.001			0.039
I	54 (6.3)	49 (7.7)	5 (2.2)		36 (6.2)	18 (6.3)
II	675 (78.1)	508 (79.5)	167 (74.2)		466 (80.3)	209 (73.6)
III	135 (15.6)	82 (12.8)	53 (23.6)		78 (13.4)	57 (20.1)
Left ventricular ejection fraction, mean ± SD	50.97 ± 8.61	50.67 ± 8.57	51.83 ± 8.68	0.082	50.72 ± 8.44	51.49 ± 8.95	0.220
≤40	98 (11.3)	73 (12.2)	25 (11.8)		65 (11.9)	33 (12.5)
41–49	286 (29.5)	186 (31.0)	47 (22.3)		163 (29.9)	70 (26.4)
>50	480 (59.2)	341 (56.8)	139 (65.9)		318 (58.2)	162 (61.1)
Arterial hypertension, n (%)				0.378			0.344
Yes	693 (80.2)	508 (79.5)	158 (82.2)		460 (79.3)	233 (82.0)
No	171 (19.8)	131 (20.5)	40 (17.8)		120 (20.7)	51 (18.0)
History of smoking, n (%)	364 (42.1)	335 (52.4)	29 (12.9)	<0.001	249 (42.9)	115 (40.5)	0.495
Obesity (BMI > 30 kg/m2), n (%)	400 (46.3)	276 (43.2)	124 (55.1)	0.002	266 (45.9)	134 (47.2)	0.715
Current medication use, n (%)
Beta-blockers	771 (89.2)	574 (89.8)	197 (87.6)	0.344	518 (89.3)	253 (89.1)	0.920
Statins	813 (94.1)	600 (93.9)	213 (94.7)	0.673	540 (93.1)	273 (96.1)	0.077
Benzodiazepine	138 (16.0)	83 (13.0)	55 (24.4)	<0.001	76 (13.1)	62 (21.8)	0.001
Depression as measured by HADS-D ≥ 8, n (%)	107 (12.4)	59 (9.2)	48 (21.3)	<0.001	29 (5.0)	78 (27.5)	<0.001
Anxiety as measured by HADS-A ≥ 8, n (%)	291 (33.7)	166 (26.0)	125 (55.6)	<0.001	124 (21.4)	167 (58.8)	<0.001
D type	284 (32.9)	184 (28.8)	100 (44.4)	<0.001
Multidimensional Fatigue Inventory, mean ± SD
Reduced motivation	10 ± 3	10 ± 3	12 ± 4	<0.001	9.5 ± 3.3	11.4 ± 3.4	<0.001
Mini-Mental State Examination, mean ± SD	28 ± 2	28 ± 2	28 ± 2	0.764	27.8 ± 1.8	27.4 ± 2.0	0.001
Digit Span Test, mean ± SD
Forward recall of digits	6 ± 2	6 ± 2	6 ± 2	0.781	6.1 ± 2.2	5.9 ± 2.0	0.191
Backward recall of digits	5 ± 2	5 ± 2	5 ± 2	0.920	5.4 ± 1.7	5.1 ± 1.7	0.078
Digit Symbol Test, mean ± SD
Raw score	33 ± 10	32 ± 10	33 ± 11	0.184	33.1 ± 10.4	31.6 ± 10.3	0.041
Digit Symbol Test time (s)	195 ± 67	195 ± 64	192 ± 75	0.608	190.6 ± 64.1	202.5 ± 72.8	0.020
Trail Making Test, mean ± SD
Test A Time (s)	44 ± 21	43 ± 20	49 ± 23	<0.001	43.3 ± 20.9	46.8 ± 20.9	0.021
Test B Time (s)	110 ± 51	107 ± 50	118 ± 54	0.025	105.8 ± 52.2	117.1 ± 48.9	0.008
B-A Test Time (s)	68 ± 42	67 ± 40	72 ± 44	0.170	65.6 ± 41.5	73.5 ± 41.3	0.027

BMI, body mass index; HADS-A, anxiety subscale of the Hospital Anxiety and Depression Scale; HADS-D, depression subscale of the Hospital Anxiety and Depression Scale; NYHA, New York Heart Association functional class.

In line with the first hypothesis, participants with CAD and Type D personality traits demonstrated significantly lower general cognitive functioning (Total MMSE score, P < 0.001), slower psychomotor speed (DSST score, P < 0.05), less effective visual search (TMT A, P < 0.05), worse mental flexibility (TMT B, P < 0.01), and executive control (TMT B-A, P < 0.05).

Our second hypothesis was partially confirmed, as there were no sex differences on all cognitive tests, except the TMT-A (P < 0.001). There was also a tendency for women to take more time to complete TMT-B test (P > 0.03).

We found significant differences in characteristics of participants with Type D personality vs. non-Type D personality, and men vs. women. We performed supplementary analysis: men with and without Type D personality, and women with and without Type D personality characteristics.

Supplementary material online summarizes associations between baseline cognitive function and HRQoL over the 5-year period. As expected, the correlations between cognitive function and HRQoL differed according to sex and Type D personality traits. In the group of men with Type D personality traits, performance in several cognitive areas including psychomotor performance, perceptual speed, task switching, executive control, and global cognitive functioning significantly correlated with HRQoL over the 5-year period (r’s ranged from 0.231 to 0.359; P’s < 0.006). In the men’s group without Type D personality traits, the HRQoL Emotional subscale scores were only negatively associated with global cognitive functioning at the 6-month follow-up assessment (r = −0.174, P = 0.001).

In women with Type D personality traits, the general HRQoL score (24 months) was associated with psychomotor performance (r = −0.302, P = 0.003). There was a trend of association between physical HRQoL score (60 months) and psychomotor performance (r = –0.287, P = 0.0058). In women without Type D personality characteristics, baseline emotional HRQoL scores correlated with psychomotor performance (r = –0.296, P = 0.001) and DSST completion time (r = 0.254, P = 0.004).

Table 2 summarizes the multivariable regression analysis adjusted for CAD and cognitive function risk factors. As for correlational analysis, results were stratified by Type D personality traits and sex. In men with Type D personality, physical HRQoL (12 months) remained associated with executive control [B = 0.059, 95% confidence interval, CI (B) = (0.021; 0.096), P = 0.002]. Associations also remained between physical HRQoL (18 months) and perceptual speed [B = 0.087, 95% CI (B) = (0.004; 0.170), P = 0.040], task switching [B = 0.054, 95% CI (B) = (0.021; 0.087), P = 0.001], and executive control [B = 0.050, 95% CI (B) = (0.013; 0.086), P = 0.008]. The 5-year physical HRQoL (60 months) remained associated with baseline cognitive measures of DSST completion time [B = 0.034, 95% CI (B) = (0.005; 0.062), P = 0.021], perceptual speed [B = 0.106, 95% CI (B) = (0.018; 0.194), P = 0.018], and task switching [B = 0.058, 95% CI (B) = (0.021; 0.094), P = 0.003]. The 5-year (60 months) general and emotional HRQoL scores remained significantly correlated with global cognitive functioning scores (β = –0.266, P = 0.002; β = –0.259, P = 0.003). For non-type D personality men, the baseline emotional HRQoL remained associated with baseline global cognitive functioning [B = −0.558, 95% CI (B) = (−0.922; −0.194), P = 0.003].

Table 2

Multivariable regression analysis of baseline cognitive function with HRQoL over a 5-year period

Group	Assessment time-points in months	Minnesota HRQoL	Digit Span Test		Digit Symbol Test		Trail Making Test			Mini-Mental State Examination
			Forward recall of digits	Backward recall of digits	Raw score	Test completion time	Test A	Test B	B-A test
Men
Non D type	6	Emotional	—	—	—	—	—	—	—	B = −0.299 P = 0.005 95% CI (B) = (−0.506; −0.093)
D type	12	Physical	—	—	—	—	—	—	B = 0.059 P = 0.002 95% CI (B) = (0.021; 0.096)	—
	18	Total	—	—	—	—	—	B = 0.078 P = 0.013 95% CI (B) = (0.017; 0.140)	—	—
		Physical	—	—	—	—	B = 0.087 P = 0.040 95% CI (B) = (0.004; 0.170)	B = 0.054 P = 0.001 95% CI (B) = (0.021; 0.087)	B = 0.050 P = 0.008 95% CI (B) = (0.013; 0.086)	—
	60	Total	—	—	—	—	—	—	—	B = −1.990 P = 0.002 95% CI (B) = (−3.222; −0.758)
		Physical	—	—	—	B = 0.034 P = 0.021 95% CI (B) = (0.005; 0.062)	B = 0.106 P = 0.018 95% CI (B) = (0.018; 0.194)	B = 0.058 P = 0.003 95% CI (B) = (0.021; 0.094)	—	—
		Emotional	—	—	—	—	—	—	—	B = −0.558 P = 0.003 95% CI (B) = (−0.922;−0.194)
Women
Non D type	Baseline	Emotional	—	—	—	B = 0.019 P = 0.040 95% CI (B) = (0.001; 0.038)	—	—	—	—
D type	24	Total	—	—	B = −0.410 P = 0.014 95% CI (B) = (−0.735; −0.086)	—	—	—	—	—
	60	Physical	—	—	B = −0.193 P = 0.065 95% CI (B) = (−0.399; 0.013)	—	—	—	—	—

Adjusted for age, education [up to 8 years (1); college (2); university (3)], NYHA functional class [I-II class (1); III class (2)], left ventricular ejection fraction [≤40% (1); >40% (2)], hypertension [non-present (0); present (1)], smoking [yes (0), no (1)], obesity as measured by body mass index [≤30 kg/m² (1); >30 kg/m² (2)], beta-blockers use [yes (0), no (1)], statins use [yes (0), no (1)], benzodiazepine use [yes (0), no (1)], anxiety and depression scores as measured by HADS, reduced motivation as measured by Multidimensional Fatigue Inventory-20.

Total, physical, and emotional HRQoL was assessed at baseline, every 6 months for 2 years and after 5 years.

HRQoL, heath-related quality of life; MMSE, Mini-Mental State Examination.

In women with Type D personality characteristics, the general HRQoL score (24 months) remained associated with psychomotor performance [B = −0.410, 95% CI (B) = (−0.735; −0.086), P = 0.014]. A trend remained for an association between physical HRQoL score (60 months) and psychomotor performance [B = −0.193, 95% CI (B) = (−0.399; 0.013), P = 0.065]. In women without Type D personality traits, baseline emotional HRQoL scores remained associated with DSST completion time [B = 0.019, 95% CI (B) = (0.001; 0.038), P = 0.040].

Discussion

This study aimed to examine associations between cognitive function and HRQoL and determine whether Type D personality interferes with this association in individuals with CAD over a 5-year period. As hypothesized, the main findings of this study support cognitive functioning playing a critical role in long-term HRQoL. Notably, Type D personality traits were associated with reduced cognitive performance in participants with CAD. We also observed sex differences in baseline cognitive function in individuals with CAD. Moreover, cognitive functioning was positively correlated with HRQoL at all time intervals over the 5-year follow-up, especially for men participants with Type D personality traits. The association between cognitive functioning and HRQoL represents an important novel finding. To our knowledge, there are no studies that have investigated this relationship using Type D personality traits and sex as possible variables playing a role in functional recovery in individuals with CAD.

Our results are consistent with studies supporting Type D personality traits being a significant predictor of poor functional status and decreased motivation²⁶ in individuals with CAD. While Williams et al.²⁷ reported Type D personality traits to be associated with poor quality of life in the general population, similar relationships have been found in individuals with CAD.²⁸ Incidentally, decreased performance in specific cognitive function, namely planning, have been reported in individuals with CAD and Type D personality traits.²⁹ Together with the aforementioned findings, our observations support the negative impact of Type D personality traits on different cognitive function domains including worsened global cognitive functioning, information processing speed, task switching, and executive control.

Sex differences in cognitive function measures were not as apparent as those associated with Type D personality traits. However, we found men’s performances to be slightly higher in perceptual speed tasks compared to those observed in women. Women also tended to take more time to complete the TMT-B task than men, particularly affecting their scores in task switching. Since TMT-B requires paying attention to two sets of stimuli simultaneously (set-shifting), a tendency to take more time to complete TMT-B may be expected.³⁰ Our study also revealed women differing from men in discrete aspects related to their clinical and sociodemographic profiles. Particularly, women were older than men at the time of the assessment; this finding concords with women experiencing their first cardiac event on average 8–10 years following menopause onset.³¹ Analyses also indicated that a higher proportion of men reported a history of smoking, a behaviour known to influence different factors (e.g. hypertension, higher occurrence of MI), and result in worse cognitive functioning. Finally, women were frequently prescribed Benzodiazepine medication. Considering a possible contribution of these factors to cognitive recovery, we chose to evaluate cognitive function and HRQoL results using sex and Type D personality as filters of performance assessments.

To our knowledge, this study is the first to examine the contribution of personality traits and sex influencing cognitive functioning and long-term HRQoL. Our results strongly support Type D personality traits as an influential factor in CAD recovery, associated with increased likelihood of baseline cognitive decline and enduring negative impact on HRQoL, particularly for men. The heightened vulnerability to CAD-induced cognitive impairments noted in these individuals’ warrants specialized or targeted clinical intervention. Although the present study did not explore the underlying mechanisms, negative impact on cerebral blood supply related to increased vulnerability to systemic vascular dysfunction in individuals with CAD and Type D personality could affect cognitive function. This proposition is consistent with the psychological distress that characterizes individuals with Type D personality and reported impaired endothelial function following CAD.³²

Our findings support that measuring cognitive functioning soon after a cardiac event in a rehabilitation setting may have an essential value in predicting HRQoL for up to 5 years. Furthermore, our findings indicate that assessment of Type D personality traits might be helpful to identify CAD population subgroups, surveillance of which might provide further insights into the role of personality status in regulating cognitive function. Hence, interventions targeting improvement in HRQoL require more extensive psychological assessments of individuals with CAD, including an evaluation for Type D personality traits.

Strengths and limitations

A large sample size, longitudinal design, and the use of well-validated instruments (e.g. our main outcome measure MLHFQ had excellent reliability scores) are the major strengths of our study. The findings of this study provide important information about the long-term effects of baseline cognitive functioning on HRQoL in relatively young individuals with CAD. Nevertheless, in recent years, clinicians have seen an increase of CAD in younger adults, particularly in women^33,34. Therefore, despite having a younger cohort of individuals, this is in line with the latest research trends. Furthermore, our study employed objective measures of cognitive function, supporting the previously reported association between HRQoL and subjective (perceived) cognitive functioning.^3,35

Despite the consistent results, our study has limitations. We only measured cognitive functioning at baseline, so we could not infer whether cognitive decline between 6th months and 5 years might have continued to influence HRQoL. Participant recruitment from a single cardiac rehabilitation centre could have subjected our results to selection bias. Although our study controlled for major confounding factors, the exact mechanisms underlying established relationships remain to be determined. Several other CAD risk factors not collected in this study, such as diabetes mellitus status, might have influenced results. Future studies should explore the possible role of mediating factors that may affect the associations between cognitive impairment and HRQoL in both men and women with and without Type D personality traits.

Furthermore, other possible personality traits common in individuals with CAD might be shown to link worsened cognitive functioning with impaired functional status. We recognize that underlying mechanisms were not explored in this study and commend further investigation to address physiological factors. Finally, there is a great need for replication in more diverse clinical samples, notably with more women participants.

Conclusions

Our study examined the effect of Type D personality traits on associations between cognitive function and long-term HRQoL. Cognitive functioning of those with Type D personality traits is significantly associated with reduced HRQoL during a 5-year follow-up period. Assessment of baseline cognitive functioning and Type D personality in individuals with CAD might be of value to predict 5-year HRQoL.

Supplementary material

Supplementary material is available at European Journal of Cardiovascular Nursing online.

Acknowledgements

The authors are grateful to members of the European College of Neuropsychopharmacology (ECNP) Obsessive Compulsive and Related Disorders Research Network (OCRN) and Anxiety Disorders Network (ADRN). Their comments have shaped this manuscript in its development. The ECNP OCRN and ADRN are components of the ECNP-Network Initiative (ECNP-NI) and receives financial support from the ECNP, to support its academic activities.

Funding

This project was funded by the European Social Fund under the No 09.3.3-LMT-K-712-19-0127 ‘Development of Competences of Scientists, other Researchers and Students through Practical Research Activities’ measure. H.P.’s research work is supported by a Discovery grant from the Natural Sciences and Engineering Research Council (NSERC) of Canada (RG203596-13). A doctoral sholarship from the Fonds de recherche du Québec - Nature et technologies (FRQNT) supported N.F.N.L.'s collaboration.

Conflict of interest: J.G.-S. works as a consultant at FACITtrans. N.A.F. reports grants or contracts from COST Action, NIHR; Royalties from oxford university press; honorarium for delivering educational lectures from the ICD-11 training committee; Support for attending meetings and/or travel from the British Association for Psychopharmacology, European College for Neuropsychopharmacology; International College for Neuropsychopharmacology, Royal College of Psychiatrists; Advisory work for the MHRA; Board member, Orchard (UK consumer charity); Secretary, International college of OC spectrum disorders (UK reg charity); Honorarium for editorial duties, from Elsevier. J.B. has served as a consultant at Cogstate, Ltd. The remaining authors declare no conflict of interest.

Data availability

The data underlying this article will be shared on reasonable request to the corresponding author.