Abstract

Objective

The aim of this study was to determine the influence of left ventricular dysfunction type on the pattern of neuropsychological dysfunctions among heart failure (HF) subjects.

Method

A sub-analysis of the data of subjects recruited in a cross-sectional survey of cognitive dysfunction among Nigerians with HF was performed. Cognitive performance on the Community Screening Interview for Dementia (CSI'D), Word List Learning Delayed Recall (WLLDR), Boston Naming Test (BNT), and Modified Token Test (MTT) were compared between heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Clinical and echocardiographic correlation analysis with cognitive performance was performed.

Results

Subjects with HFpEF were impaired on the WLLDR (71.4% vs. 34.6%, p = .026). The group with HFpEF scored lower on the language domain (definition subscale) of CSI'D (p = .036), and WLLDR (p = .005). The performance on the MTT (p = .185) and BNT (p = .923) were comparable between the two groups. An inverse relationship was found between pulse pressure and delay recall (r = −.565 p = .003) among the cohort with HFpEF whereas body mass index, BMI (r = −.737, p = .023) and tricuspid valve E/A ratio, TVEA (r = −.650, p = .042) showed an inverse relationship with the total CSI'D score in the cohort with HFrEF.

Conclusions

Cognitive dysfunction is largely similar between the two groups. Delay recall is however poorer among subjects with HFpEF. Regular cognitive screening is advocated among HF subjects to prevent non-adherence with therapeutic options.

Introduction

Heart failure (HF) is becoming a pandemic worldwide. This is due in part to the increasing burden of its risk factors and the availability of better treatment modalities for many precursors of HF (Yancy et al., 2013). Global measures of left ventricular function such as ejection fraction have been shown to be powerful predictors of cardiovascular and all cause outcomes in many studies (Borlaug & Redfield, 2011; Burkhoff, 2012; Karaye & Sani, 2008). Two hypertrophy phenotypes have been identified in the clinical spectrum of HF leading to the classification of HF into systolic HF (or heart failure with reduced ejection fraction, HFrEF) and diastolic HF (heart failure with preserved ejection fraction, HFpEF) (Komajda & Ruschitzka, 2016)

Even though it is not clear where the dividing line is between the two distinct phenotypic types of HF, considerable differences exist between subjects with the two types. Some differing pathophysiologic mechanism, treatment differences, natural histories and outcome have been reported in the two types of HF (Karaye & Akintunde, 2013; Karaye & Sani, 2008; Komajda & Ruschitzka, 2016; Dokainish et al., 2016). In Africans, similar characteristics of the two phenotypes of HF have been described (Karaye & Akintunde, 2013). Hypertension is still the major documented risk for HF in Africa (Damasceno et al., 2012; Dokainish et al., 2016). HF is associated with many comorbid factors among Africans including renal dysfunction, obstructive sleep apnea, anemia, poor quality of life and neuropsychological dysfunction (Adebayo et al., 2016; Akintunde, Kareem, Bakare, & Audu, 2014; Ola et al., 2006).

While the underlying pathophysiological mechanisms of the two HF phenotypes are still being unraveled, extant literatures suggest that the type of cardiac dysfunction affects cognition in different ways. The findings of Bratzke-Bauer, Pozehl, Paul, and Johnson (2013) showed that individuals with HFrEF had worse immediate and delay recall, in addition to worse attention and language functions, compared to counterparts with HFpEF, as measured by Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) (Bauer et al., 2012). Using the mini-mental state examination, cognitive dysfunction has been associated with high serum level of brain natriuretic peptide (BNP) among cardiovascular disease subjects with left ventricular diastolic dysfunction (Suwa & Ito, 2009), In hypertensive subjects not in HF too, the risk of cognitive dysfunction was found to be higher among subjects with cardiac hypertrophy independent of other cardiovascular correlates (Hayakawa et al., 2012).

It has been demonstrated that native African HF subjects were more cognitively impaired than age-, gender- and level of education-matched control individuals (Adebayo et al., 2016). In that survey, the 1 year prevalence of cognitive dysfunction was 90%, suggesting that cognitive dysfunction is highly prevalent among native Nigerian Africans with HF (Adebayo et al., 2016). However, the influence of left ventricular dysfunction pattern on cognitive dysfunction was not explored. On the premises of reduced ejection fraction and associated reduced cerebral blood flow (CBF) (Bauer, Johnson, & Pozehl, 2011), it is assumed that left ventricular dysfunction type will influence neuropsychological performance because HFrEF has been the substrate of subjects at particularly increased risk for cognitive dysfunction (Bratzke-Bauer et al., 2013). In this context, we postulated that the pattern of neurocognitive function will differ between the two HF phenotypes. This study therefore sought to determine the effect of left ventricular dysfunction type on the pattern of neuropsychological dysfunctions among HF subjects.

Materials and Methods

Subjects

In this cross-sectional study, patients with HF were recruited from the medical ward and the cardiology outpatient clinics of the Ladoke Akintola University of Technology (LAUTECH) Teaching Hospital, Ogbomoşo, south-western Nigeria between February 1, 2013 and January 31, 2014. Inclusion criteria consisted of a diagnosis of HF, age above 18 years and willingness to participate in the study. Exclusion criteria were history of stroke, epilepsy, previous head trauma, Parkinsonism or any other neurological/psychiatric disorders, visual or auditory impairment, concurrent renal or hepatic impairment and acute HF. Admitted patients were evaluated after they were out of failure. Sixty patients with HF met the recruitment criteria. In this analysis however, we excluded nine patients who did not have full echocardiographic parameters and 11 patients who could not be matched for age and educational status with another pair of different HF phenotype. Forty HF subjects were eventually included in this analysis. The institutional review board of the LAUTECH teaching hospital, Ogbomoşo, approved the study. Written informed consent was obtained from all the subjects.

Demography and Clinical Data

Consecutive patients who met the recruitment criteria were interviewed on the day of their clinic visit or at echocardiography. A questionnaire containing sections for demography, clinical and neuropsychological evaluation was administered to all subjects. The demographic data included age, sex, level of education, occupation and marital status. HF-related variables such as age at diagnosis, duration of illness, number of hospital admissions, and etiology of HF as well as New York Heart Association (NYHA) stage were recorded. History of concurrent medical comorbid condition was documented and comorbidity score was calculated using the Charlson Comorbidity Index (an index of comorbidity that includes age) (Charlson, Pompei, Ales, & MacKenzie, 1987; Charlson, Szatrowski, Peterson, & Gold, 1994). In addition, detailed cardiovascular and neurological examinations were carried out on all subjects. Dry Body weight (to the nearest 0.1 kg) and height (to the nearest 0.1 cm) were measured with subject standing erect on bare foot and their eyes directed straight ahead. Body mass index (BMI) was calculated as weight (kg)/height (m)2. Waist circumference (WC) was measured at a point midway between the coastal margin and the anterior superior iliac spine whereas the hip circumference (HC) was measured at the level of the greater trochanter of the femur. Waist Hip ratio (WHR) was derived from the above measurements. Sitting blood pressure was recorded before each interview using Omron digital blood pressure monitor. Three consecutive readings were taken and the average of the last two readings recorded. Two-dimensional echocardiography was performed to measure the LVEF using General Electric Ultrasound Machine (LOGIQPro6) with 3.5 MHz probe.

Neuropsychological Test Battery

The Community Screening Interview for Dementia (CSI'D) was used to assess global cognitive functioning. The Word List Learning Delayed Recall (WLLDR) and the memory domain of the CSI'D was used to assess memory. The Boston Naming Test (BNT) was used to test for confrontational naming and language function whereas executive and visuo-spatial function were assessed using the Modified Indiana University Token Test (Modified Token Test; MTT). The details of the psychometric properties of these instruments, among Nigerian Africans, have recently been described (Adebayo et al., 2016). For the CSI'D, a score 2 standard deviation below the mean scores of control was regarded as cognitively impaired. The cut-off points for BNT, MTT, and WLLDR were determined in like manner.

Statistical Analysis

Main analyses

In analyzing the data, categorical data were presented as frequencies and proportions. Chi-square test was used to analyze the difference in frequencies between the categorical variables. Numerical data were summarized as means and standard deviation when normally distributed and median with inter-quartile range when skewed. The difference between means was tested using the student's t-test. The effect size for group differences in neuropsychological test scores was calculated using Cohen's d. Pearson correlation coefficient was used to test association between HF-related numerical variables and the scores on neuropsychological batteries.

Secondary analyses

To investigate the predictors of global cognitive impairment (measured by total CSI'D score) in the cohort of subjects with HFrEF, stepwise multivariate linear regression analysis was performed with BMI and TVEA as covariates. The independent variables for the model were those that showed significant association with CSI'D on correlation analysis.

All statistical analyses were performed using SPSS version 20.0 (SPSS, Chicago, IL, USA). A p-value < .05 was considered to be statistically significant.

Results

Demography, Clinical and Echocardiographic Characteristics

Table 1 summarizes the demographic and clinical characteristics of the subjects. Forty subjects were included in the analysis. The study group consisted 26 with HFpEF and 14 with HFrEF. The mean age of the cohort with HFpEFwas higher although this was statistically insignificant (p = .082). The participants with HFrEF were predominantly in NYHA stage III/IV (71.4% vs. 34.6%, p = .026) whereas the participants with HFpEF were more obese (p = .027). The two groups were comparable on years of education (p = .366), duration of illness (.751), Charlson comorbidities index (p = .276), systolic BP (p = .106), diastolic BP (p = .624), mean arterial blood pressure, MABP (p = .243) and pulse pressure (p = .161).

Table 1.

Demographic and clinical characteristics of the subjects by heart failure phenotypes; mean (SD)

 Heart failure phenotype t p 95% CI 
HFrEF (n = 14)
Mean (SD
HFpEF (n = 26)
Mean (SD
Age 57.57 (14.88) 65.11 (11.43) 1.793 0.082 0.991 to 16.078 
Years of education 9.42 (6.95) 7.15 (7.78) 0.914 0.366 7.312 to 2.762 
Disease duration (years) 3.36 (4.53) 3.58 (4.48) 0.147 0.751 2.800 to 3.239 
Charlson commodity index 3.21 (1.63) 3.73 (1.28) 1.106 0.276 0.432 to 1.461 
Age at onset (years) 54.21 (15.84) 61.92 (11.70) 1.752 0.088 1.187 to 16.608 
Systolic BP (mmHg) 130.71 (22.15) 144.72 (26.79) 1.661 0.105 −3.079 to 31. 078 
Diastolic BP (mmHg) 84.21 (21.57) 86.92 (12.75) 0.494 0.624 −8.392 to 13.801 
MABP (mmHg) 99.71 (18.40) 106.19 (15.14) 1.186 0.243 4.591 to 17.534 
Pulse pressure (mmHg) 46.50 (24.70) 57.80 (23.09) 1.430 0.161 4.710 to 27.307 
BMI (kg/m221.88 (5.64) 26.87 (5.53) 2.297 0.027* 0.611 to 9.372 
 n(%) n (%) χ2 p-Value  
Gender – Women (%) 3 (21.43) 12 (46.15) 2.374 .123 0.732 to 13.948 
NYHA III/IV (%) 10 (71.43) 9 (34.62) 4.945 .026* 1.021 to 2.869 
 Heart failure phenotype t p 95% CI 
HFrEF (n = 14)
Mean (SD
HFpEF (n = 26)
Mean (SD
Age 57.57 (14.88) 65.11 (11.43) 1.793 0.082 0.991 to 16.078 
Years of education 9.42 (6.95) 7.15 (7.78) 0.914 0.366 7.312 to 2.762 
Disease duration (years) 3.36 (4.53) 3.58 (4.48) 0.147 0.751 2.800 to 3.239 
Charlson commodity index 3.21 (1.63) 3.73 (1.28) 1.106 0.276 0.432 to 1.461 
Age at onset (years) 54.21 (15.84) 61.92 (11.70) 1.752 0.088 1.187 to 16.608 
Systolic BP (mmHg) 130.71 (22.15) 144.72 (26.79) 1.661 0.105 −3.079 to 31. 078 
Diastolic BP (mmHg) 84.21 (21.57) 86.92 (12.75) 0.494 0.624 −8.392 to 13.801 
MABP (mmHg) 99.71 (18.40) 106.19 (15.14) 1.186 0.243 4.591 to 17.534 
Pulse pressure (mmHg) 46.50 (24.70) 57.80 (23.09) 1.430 0.161 4.710 to 27.307 
BMI (kg/m221.88 (5.64) 26.87 (5.53) 2.297 0.027* 0.611 to 9.372 
 n(%) n (%) χ2 p-Value  
Gender – Women (%) 3 (21.43) 12 (46.15) 2.374 .123 0.732 to 13.948 
NYHA III/IV (%) 10 (71.43) 9 (34.62) 4.945 .026* 1.021 to 2.869 

Note: MABP, mean arterial blood pressure; BMI, body mass index; NYHA, New York Heart Association; *, statistically significant value.

Table 2 shows the echocardiographic parameters of the participants. Those with HFpEF had lower left ventricular internal dimension in diastole (LVDD, p < .001), left ventricular internal dimension in systole (LVSD, p = .037), mitral early filling velocity/atrial filling velocity (E/A) ratio (MEA, p = .003) and tricuspid E/A ratio (TVEA, p = .007) whereas the participants with HFrEF had significantly lower fractional shortenings (p = .034), peak aortic systolic velocity (PASV, 0.028) and mitral valve deceleration time (MDT, p = .007).

Table 2.

Echocardiographic parameters of the subjects according to heart failure phenotype and performance on WLLDR: mean (SD)

Echocardiography parameters Heart failure phenotype p-Value Cohen's d Impaired WLLDR p-Value Cohen's d 
HFrEF (n = 14)
Mean (SD
HFpEF (n = 26)
Mean (SD
HFrEF (n = 4)
Mean (SD
HFpEF (n = 17)
Mean (SD
LVDD 59.15 (4.58) 46.42 (8.54) <0.001* 1.858 58.96 (4.77) 45.67 (10.72) 0.002* 1.602 
LVSD 45.93 (8.54) 37.85 (12.41) 0.037* 0.759 44.52 (4.71) 38.27 (14.23) 0.244* 0.589 
FS 18.91 (4.62) 26.18 (11.78) 0.034* 0.813 19.19 (4.67) 26.19 (6.75) 0.023* 1.206 
EF 37.54 (8.53) 47.00 (17.84) 0.069 0.677 37.81 (8.78) 43.52 (15.47) 0.330 0.454 
IVST 11.35 (2.71) 12.76 (3.43) 0.186 0.456 12.02 (2.93) 11.57 (4.93) 0.811 0.111 
PWTd 10.97 (2.92) 11.3 (3.67) 0.775 0.099 11.66 (3.01) 10.81 (4.49) 0.633 0.222 
RVD 32.71 (5.57) 29.82 (6.27) 0.180 0.487 29.93 (3.93) 32.00 (5.61) 0.409 0.427 
AOD 31.86 (3.08) 30.48 (3.32) 0.198 0.431 32.26 (3.00) 31.93 (3.54) 0.830 0.101 
ACS 18.29 (3.25) 16.93 (3.37) 0.226 0.411 18.77 (3.25) 17.38 (1.72) 0.295 0.535 
LAD 45.52 (6.61) 42.17 (7.44) 0.160 0.476 43.87 (7.02) 43.38 (9.59) 0.901 0.058 
TAPSE 16.60 (2.9) 17.60 (4.57) 0.601 0.261 15.92 (3.02) 15.20 (4.72) 0.781 0.182 
PASV 0.77 (0.17) 0.98 (0.31) 0.028* 0.839 0.74 (0.18) 0.87 (0.25) 0.229 0.597 
PPG 2.56 (1.06) 4.18 (2.90) 0.051 0.742 2.33 (1.11) 3.35 (2.28) 0.243 0.569 
MEV 0.93 (0.24) 0.95 (1.94) 0.956 0.015 0.96 (0.26) 0.66 (0.32) 0.035* 1.029 
MAV 0.59 (0.16) 0.97 (0.82) 0.157 0.643 0.65 (0.15) 0.88 (0.37) 0.161 0.815 
MEA 1.59 (0.27) 0.93 (0.62) 0.003* 1.380 1.52 (0.27) 0.89 (0.56) 0.021* 1.433 
MDT 144.07 (61.88) 232.98 (103.40) 0.007* 1.043 142.40 (66.98) 223.92 (128.54) 0.096 0.795 
AVPAFV 1.13 (0.21) 1.20 (0.54) 0.622 0.171 1.11 (0.21) 1.04 (0.49) 0.705 0.186 
AVAPG 5.00 (1.78) 6.97 (6.11) 0.247 0.438 4.80 (1.42) .5.32 (5.17) 0.756 0.137 
TVEV 0.64 (0.21) 0.56 (0.19) 0.292 0.399 0.63 (0.20) 0.59 (0.14) 0.665 0.232 
TVAV 0.52 (0.19) 0.60 (0.23) 0.306 0.379 0.49 (0.18) 0.54 (0.28) 0.688 0.212 
TVEA 1.31 (0.39) 0.90 (0.37) 0.007* 1.079 1.32 (0.36) 0.83 (0.41) 0.036* 1.270 
Echocardiography parameters Heart failure phenotype p-Value Cohen's d Impaired WLLDR p-Value Cohen's d 
HFrEF (n = 14)
Mean (SD
HFpEF (n = 26)
Mean (SD
HFrEF (n = 4)
Mean (SD
HFpEF (n = 17)
Mean (SD
LVDD 59.15 (4.58) 46.42 (8.54) <0.001* 1.858 58.96 (4.77) 45.67 (10.72) 0.002* 1.602 
LVSD 45.93 (8.54) 37.85 (12.41) 0.037* 0.759 44.52 (4.71) 38.27 (14.23) 0.244* 0.589 
FS 18.91 (4.62) 26.18 (11.78) 0.034* 0.813 19.19 (4.67) 26.19 (6.75) 0.023* 1.206 
EF 37.54 (8.53) 47.00 (17.84) 0.069 0.677 37.81 (8.78) 43.52 (15.47) 0.330 0.454 
IVST 11.35 (2.71) 12.76 (3.43) 0.186 0.456 12.02 (2.93) 11.57 (4.93) 0.811 0.111 
PWTd 10.97 (2.92) 11.3 (3.67) 0.775 0.099 11.66 (3.01) 10.81 (4.49) 0.633 0.222 
RVD 32.71 (5.57) 29.82 (6.27) 0.180 0.487 29.93 (3.93) 32.00 (5.61) 0.409 0.427 
AOD 31.86 (3.08) 30.48 (3.32) 0.198 0.431 32.26 (3.00) 31.93 (3.54) 0.830 0.101 
ACS 18.29 (3.25) 16.93 (3.37) 0.226 0.411 18.77 (3.25) 17.38 (1.72) 0.295 0.535 
LAD 45.52 (6.61) 42.17 (7.44) 0.160 0.476 43.87 (7.02) 43.38 (9.59) 0.901 0.058 
TAPSE 16.60 (2.9) 17.60 (4.57) 0.601 0.261 15.92 (3.02) 15.20 (4.72) 0.781 0.182 
PASV 0.77 (0.17) 0.98 (0.31) 0.028* 0.839 0.74 (0.18) 0.87 (0.25) 0.229 0.597 
PPG 2.56 (1.06) 4.18 (2.90) 0.051 0.742 2.33 (1.11) 3.35 (2.28) 0.243 0.569 
MEV 0.93 (0.24) 0.95 (1.94) 0.956 0.015 0.96 (0.26) 0.66 (0.32) 0.035* 1.029 
MAV 0.59 (0.16) 0.97 (0.82) 0.157 0.643 0.65 (0.15) 0.88 (0.37) 0.161 0.815 
MEA 1.59 (0.27) 0.93 (0.62) 0.003* 1.380 1.52 (0.27) 0.89 (0.56) 0.021* 1.433 
MDT 144.07 (61.88) 232.98 (103.40) 0.007* 1.043 142.40 (66.98) 223.92 (128.54) 0.096 0.795 
AVPAFV 1.13 (0.21) 1.20 (0.54) 0.622 0.171 1.11 (0.21) 1.04 (0.49) 0.705 0.186 
AVAPG 5.00 (1.78) 6.97 (6.11) 0.247 0.438 4.80 (1.42) .5.32 (5.17) 0.756 0.137 
TVEV 0.64 (0.21) 0.56 (0.19) 0.292 0.399 0.63 (0.20) 0.59 (0.14) 0.665 0.232 
TVAV 0.52 (0.19) 0.60 (0.23) 0.306 0.379 0.49 (0.18) 0.54 (0.28) 0.688 0.212 
TVEA 1.31 (0.39) 0.90 (0.37) 0.007* 1.079 1.32 (0.36) 0.83 (0.41) 0.036* 1.270 

Note: LVDD, left ventricular internal dimension in diastole; LVSD, left ventricular internal dimension in systole; FS, fractional shortening; EF, ejection fraction; IVST, interventricular septal thickness in diastole; PWTd, posterior wall thickness in systole; RVD, right ventricular dimension; AOD, aortic root dimension; ACS, aortic cusp separation; LAD, left atrial dimension; TAPSE, tricuspid annular pulmonary systolic excursion; PASV, peak aortic systolic velocity; PPG, peak pulmonary gradient; MEV, mitral E wave velocity; MAV, mitral A wave velocity; MEA, mitral E/A ratio; MDT, mitral valve deceleration time; AVPAFV, average peak aortic flow velocity; AVAPG, average aortic pressure gradient; TVEV, tricuspid E wave velocity; TVAV, tricuspid A wave velocity; TVEA, tricuspid E/A ratio; WLLDR, word list learning delayed recall; *, significant value.

Neuropsychology Test Scores

The performance on neuropsychological test by the groups is presented in Table 3. There was no statistically significant difference in the total CSI'D score between the groups although, the participants with HFpEF had lower total CSI'D score. When subscales of the CSI'D were considered, the groups with HFpEF scored lower than the HFrEF group on the definition domain of the language subscale (p = .036). The participants with HFpEF also performed significantly lower on the word list learning recall (p = .005). The performance on the MTT (p = .185) and BNT (p = .923).were comparable between the groups.

Table 3.

Mean scores on neuropsychological tests between patients with different heart failure phenotypes

Neuropsychological tests Heart failure phenotype t-test p-Value 95% CI Cohen's d 
HFrEF (n = 14) Mean (SDHFpEF (n = 26) Mean (SD
CSID 45.71 (4.84) 42.48 (7.56) 1.441 0.157 7.748 to 1.292 0.509 
 Attention & calculation 5.64 (1.65) 5.76 (2.49) 0.158 0.875 1.587 to 1.369 0.057 
 Orientation (time) 4.5 (0.85) 4.03 (0.79) 1.780 0.082 0.059 to 0.988 0.573 
 Orientation (place) 4.71 (0.61) 4.34 (0.90) 1.388 0.172 0.166 to 0.912 0.478 
 Language (naming) 7.00 (0.67) 7.03 (0.91) 0.126 0.900 0.589 to 0.519 0.038 
 Language (definition) 6.21 (1.80) 5.31 (1.38) 2.159 0.036* 0.071 to 2.084 0.561 
 Language (fluency) 1.21 (0.80) 1.31 (0.66) 0.421 0.679 0.562 to 0.371 0.136 
 Memory (registration) 2.71 (0.99) 2.48 (0.98) 0.719 0.416 0.418 to 0.883 0.233 
 Memory (immediate recall) 2.57 (0.85) 2.13 (0.95) 1.146 0.258 0.253 to 0.902 0.488 
 Memory (semantic memory) 6.57 (1.60) 5.75 (2.19) 1.231 0.225 0.524 to 2.137 0.428 
 Memory (short story test) 4.57 (1.55) 4.48 (1.76) 0.160 0.874 1.031 to 1.201 0.054 
Modified Token Test 19.78 (3.57) 17.58 (5.56) 1.348 0.185 5.492 to 1.087 0.471 
Boston Naming Test 11.28 (2.36) 11.37 (3.20) 0.097 0.923 1.850 to 2.037 0.032 
WLLDR 2.57 (0.76) 1.73 (1.04) 3.005 0.011* 1.531 to 0.301 0.922 
Neuropsychological tests Heart failure phenotype t-test p-Value 95% CI Cohen's d 
HFrEF (n = 14) Mean (SDHFpEF (n = 26) Mean (SD
CSID 45.71 (4.84) 42.48 (7.56) 1.441 0.157 7.748 to 1.292 0.509 
 Attention & calculation 5.64 (1.65) 5.76 (2.49) 0.158 0.875 1.587 to 1.369 0.057 
 Orientation (time) 4.5 (0.85) 4.03 (0.79) 1.780 0.082 0.059 to 0.988 0.573 
 Orientation (place) 4.71 (0.61) 4.34 (0.90) 1.388 0.172 0.166 to 0.912 0.478 
 Language (naming) 7.00 (0.67) 7.03 (0.91) 0.126 0.900 0.589 to 0.519 0.038 
 Language (definition) 6.21 (1.80) 5.31 (1.38) 2.159 0.036* 0.071 to 2.084 0.561 
 Language (fluency) 1.21 (0.80) 1.31 (0.66) 0.421 0.679 0.562 to 0.371 0.136 
 Memory (registration) 2.71 (0.99) 2.48 (0.98) 0.719 0.416 0.418 to 0.883 0.233 
 Memory (immediate recall) 2.57 (0.85) 2.13 (0.95) 1.146 0.258 0.253 to 0.902 0.488 
 Memory (semantic memory) 6.57 (1.60) 5.75 (2.19) 1.231 0.225 0.524 to 2.137 0.428 
 Memory (short story test) 4.57 (1.55) 4.48 (1.76) 0.160 0.874 1.031 to 1.201 0.054 
Modified Token Test 19.78 (3.57) 17.58 (5.56) 1.348 0.185 5.492 to 1.087 0.471 
Boston Naming Test 11.28 (2.36) 11.37 (3.20) 0.097 0.923 1.850 to 2.037 0.032 
WLLDR 2.57 (0.76) 1.73 (1.04) 3.005 0.011* 1.531 to 0.301 0.922 

Note: CSI'D, community screening interview for dementia; HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; WLLDR, word list learning delay recall; *, statistically significant value.

Considering the cut-off for impairment on the neuropsychological tests (as previously determined) (Adebayo et al., 2016), a significant proportion of participants with HFpEF were impaired on the WLLDR (65.4% vs. 28.6%, p = 0.026). Although larger proportion of the participants with HFpEF were impaired on CSID (84.6% vs. 71.4%), MTT (69.3% vs. 51.7%) and BNT (53.8% vs. 51.7%), the differences were insignificant. Table 4 summarizes the proportion of individuals in each group who scored in the impaired range on the total CSI'D, BNT, MTT and WLLDR. To explore inherent cardiac differences between participants with impaired WLLDR (because this is the significantly different cognitive domain between the groups), we compared the echocardiographic parameters of groups with impaired scores on WLLDR based on the type of left ventricular dysfunction (Table 2). The LVDD (p = .002), MEV (p = .035), MEA (p = .021) and TVEA (p = .036) were significantly lower among the cohorts with HFpEF whereas those with HFrEF had significantly lower fractional shortening (p = .023).

Table 4.

Prevalence of subjects who had impaired scores on the neuropsychological tests

Neuropsychological tests Heart failure phenotype χ2 df p-Value 95% CI 
HFrEF, n = 14 (%) HFpEF, n = 26 (%) 
CSI'D 10 (71.42) 22 (84.62) 0.989 0.320 0.094 to 2.195 
Modified Token Test 8 (57.14) 18 (69.23) 0.584 0.445 0.154 to 2.279 
Boston Naming Test 8 (57.14) 14 (53.84) 0.399 0.842 0.309 to 4.234 
WLLDR 4 (28.57) 17 (65.38) 4.945 0.026* 0.052 to 0.870 
Neuropsychological tests Heart failure phenotype χ2 df p-Value 95% CI 
HFrEF, n = 14 (%) HFpEF, n = 26 (%) 
CSI'D 10 (71.42) 22 (84.62) 0.989 0.320 0.094 to 2.195 
Modified Token Test 8 (57.14) 18 (69.23) 0.584 0.445 0.154 to 2.279 
Boston Naming Test 8 (57.14) 14 (53.84) 0.399 0.842 0.309 to 4.234 
WLLDR 4 (28.57) 17 (65.38) 4.945 0.026* 0.052 to 0.870 

Note: CSID, community screening interview for dementia; WLLDR, world list learning delay recall; HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; df, degree of freedom; *, statistically significant value.

Correlates and Predictor of Impaired Neuropsychological Test

Pearson correlation coefficient was conducted to investigate the correlates of the overall CSI'D and WLLDR. The clinical and echocardiographic variables that differed significantly between the groups were identified as cofounding variables and included in the correlation analysis while controlling for the effect of age, comorbidity and education. Pulse pressure and mean arterial blood pressure were also included in the model because they have been shown to affect the cognitive performance. The correlation analysis revealed an inverse correlation between pulse pressure and delay recall (r = .565, p = .003) among the cohort with HFpEF whereas BMI (r = .737, p = .023) and TVEA (r = .650, p = .042) showed an inverse relationship with the total CSI'D score in the cohort with HFrEF. Table 5 shows the correlation of clinical and echocardiographic variables with cognitive performance.

Table 5.

Correlates of CSI'D and WLLDR scores among subjects with the two heart failure phenotypes

 Age Duration Education Comorbidity BMI MABP Pulse-p LVDD LVSD LVEF FS MEV MEA TVEA 
WLLDR in HFpEF (n = 24)               
r 0.081 0.377 0.158 0.146 0.152 2.238 0.565 0.064 0.050 0.046 0.188 −.118 −.036 −.048 
p-Value 0.693 0.057 0.440 0.476 0.459 0.251 0.003* 0.755 0.853 0.823 0.415 0.565 0.867 0.842 
WLLDR in HFrEF (n = 16)               
r −.318 0.250 0.301 −.483 −.604 0.079 0.210 −.006 −.273 −.072 −.032 0.297 −.250 −0.154 
p-Value 0.267 0.388 0.295 0.080 0.085 0.788 0.471 0.985 0.367 0.807 0.913 0.302 0.486 0.670 
CSI'D in HFpEF (n = 24)               
r −.296 0.120 0.249 −.302 0.215 0.127 −.243 0.057 0.046 0.071 0.057 0.152 −.299 0.232 
p-Value 0.142 0.559 0.220 0.133 0.292 0.546 0.242 0.783 0.867 0.731 0.806 0.460 0.155 0.326 
CSI'D in HFrEF (n = 16)               
r 0.229 0.114 −.177 0.426 −.737 −.202 0.076 0.073 0.067 −.086 −.119 −.247 −.134 −.650 
p-Value 0.430 0.699 0.544 0.129 0.023* 0.489 0.797 0.803 0.829 0.771 0.686 0.395 0.711 0.042* 
 Age Duration Education Comorbidity BMI MABP Pulse-p LVDD LVSD LVEF FS MEV MEA TVEA 
WLLDR in HFpEF (n = 24)               
r 0.081 0.377 0.158 0.146 0.152 2.238 0.565 0.064 0.050 0.046 0.188 −.118 −.036 −.048 
p-Value 0.693 0.057 0.440 0.476 0.459 0.251 0.003* 0.755 0.853 0.823 0.415 0.565 0.867 0.842 
WLLDR in HFrEF (n = 16)               
r −.318 0.250 0.301 −.483 −.604 0.079 0.210 −.006 −.273 −.072 −.032 0.297 −.250 −0.154 
p-Value 0.267 0.388 0.295 0.080 0.085 0.788 0.471 0.985 0.367 0.807 0.913 0.302 0.486 0.670 
CSI'D in HFpEF (n = 24)               
r −.296 0.120 0.249 −.302 0.215 0.127 −.243 0.057 0.046 0.071 0.057 0.152 −.299 0.232 
p-Value 0.142 0.559 0.220 0.133 0.292 0.546 0.242 0.783 0.867 0.731 0.806 0.460 0.155 0.326 
CSI'D in HFrEF (n = 16)               
r 0.229 0.114 −.177 0.426 −.737 −.202 0.076 0.073 0.067 −.086 −.119 −.247 −.134 −.650 
p-Value 0.430 0.699 0.544 0.129 0.023* 0.489 0.797 0.803 0.829 0.771 0.686 0.395 0.711 0.042* 

Note: BMI, body mass index; MABP, mean arterial blood pressure; LVDD, left ventricular diastolic diameter; LVSD, left ventricular systolic diameter; LVEF, left ventricular ejection fraction; FS, fractional shortening; MEV, mitral E wave velocity; MAV, mitral A wave velocity; MEA, mitral E/A ratio; TVEA, tricuspid E/A ratio; CSI'D, community screening interview for dementia; WLLDR, word list learning delay recall; r, correlation coefficient; *, significant value.

To investigate the predictors of global cognitive impairment (measured by total CSI'D score) in the cohort of subjects with HFrEF, stepwise multivariate linear regression analysis was performed with BMI and TVEA as covariates. In this model, the effect of BMI was washed off (β = −0.082, p = 0.807) whereas TVEA retained a significant inverse regression with total CSI'D (β = −0.880, p = 0.009, 95% CI = 22.34 to 5.25).

Discussion

While the controversy is still on-going about whether HFpEF and HFrEF represent separate HF phenotypes or two independent points on the disease continuum (Bronzwaer & Paulus, 2009), HF continues to exert its deleterious effects on the physical, emotional and neuropsychological wellbeing of the subjects. In the presence of cognitive dysfunction in HF subjects, compliance with beneficial therapeutic interventions, decision making, as well as the performance of HF self-care, including dietary discretion, becomes a herculean task. The cumulative effect of the aforementioned factors is the huge morbidity and mortality associated with HF.

Essentially, the results of this study indicate that HF subjects with different types of left ventricular dysfunction (HFrEF and HFpEF) demonstrated almost comparable profiles of performance on neuropsychological tests. Although there were varied results in the different cognitive domains of CSI'D; with a significantly lower score on the definition subscale of the language domain among the participants with HFpEF, the groups did not differ on the overall CSI'D score. However, the test of delay recall (as measured by WLLDR) revealed a significantly lower score among the cohort with HFpEF.

Memory appears to be the consistently impaired domain among the cohort with HFpEF. Although the differences were insignificant, participants with HFpEF had lower scores on test of registration, immediate recall, semantic memory and short story test. About two-third of the cohort with HFpEF had statistically significant impaired delay recall. Our finding is contrary to the report by Bratzke-Bauer and colleagues (2013); who found that memory score was significantly lower on indices of immediate and delay memory (measured by RBANS) among individuals with HFrEF. On the test of immediate recall, there was no significant difference in the performance of the two groups. This finding of ours, however, mirrors that of other authors (Deshields et al., 1996; Grubb et al., 2000; Putzke et al., 2000). These studies showed that immediate memory scores were similar between HF subjects and comparison group, thereby suggesting that immediate memory may be preserved in HF subjects. In the light of the foregoing, it appears that data encoding and retrieval at short interval (immediate memory) may not be the problem in HF subjects but delayed memory storage and/or subsequent retrieval of data (delay memory) might be, especially among HFpEF.

Reduced cerebral perfusion has been the hub of the cognitive dysfunction in HF (Leto & Feola, 2014). Certainly, this theory has been corroborated by neuroimaging and neurovascular findings (Alves et al., 2005; Gruhn et al., 2001). Therefore, it is no surprise that HFrEF has been the substrate of subjects at particularly increased risk for cognitive dysfunction because it has been demonstrated that cardiac output, is inversely associated with subcortical white matter hyper intensities (Jefferson et al., 2007). The findings of cognitive dysfunction in HFpEF however, lend support to the multifactorial aetiopathogenesis (other than the simple reduction in cardiac output) of cognitive dysfunction in HF subjects. Apart from cardiac output, CBF depends on other variables such as blood pressure, and cerebral autoregulatory mechanism. Impairment of these variables might perturb CBF leading to the neuro-anatomic and neuropsychological changes in HF (Bauer et al., 2011).

We do not know for certain, the reason(s) for the difference in the delay recall between the HF types. Existing literatures have established that delay recall is associated with, and best predicted by hippocampal volume among patients at risk for Alzheimer's disease and those with mild cognitive impairment (Bonner-Jackson, Mahmoud, Miller, & Banks, 2015; de Toledo-Morrell et al., 2000). In the same vein, a test of delay recall performance (Russell's Adaptation of the Visual Reproduction Test; VRT) and hippocampal volume estimation has been found to show high diagnostic value for early Alzheimer's disease (Laakso, Hallikainen, Hänninen, Partanen, & Soininen, 2000). In the light of the foregoing, we would like to speculate that a difference in hippocampal volume exist between the two HF phenotypes, and could have accounted for the observed difference in the performance of delay memory test in this study. Although, this hypothesis needs to be tested, empirical evidence is provided by the dissimilarities in the mean BMI between the two groups (The mean BMI of the HFpEF group was in the overweight range, whereas that of the HFrEF group was normal). It has been shown, that overweight and obesity are inversely related to hippocampal atrophy among community dwelling non-demented individuals (Cherbuin, Sargent-Cox, Fraser, Sachdev, & Anstey, 2015), as well as among patients with Alzheimer's disease (Ho et al., 2011). It is therefore likely, that the group with higher BMI (HFpEF group) would have a lower hippocampal volume and by extension, have a lesser score on the measure of delay recall. This hypothesis is even more plausible when one considers that increased BMI is associated with worse left ventricular diastolic dysfunction independent of left ventricular mass and associated risk factors (Russo et al., 2011).

The correlation analysis showed different factor associated with neuropsychological impairment among the two groups. Pulse pressure showed an inverse correlation with delay recall among HFpEF subjects whereas BMI and TVEA showed an inverse correlation with the global cognitive function among HFrEF subjects. Abnormal pulse pressure has been associated with several cardiovascular events such as recurrent events after myocardial infarction in subjects with impaired left ventricular function (Mitchell et al., 1997). In addition, lower pulse pressure in combination with lower blood pressure and lower CBF increase the risk for cortical atrophy (Muller et al., 2010). In an earlier report, pulse pressure was found to relate to cognitive function in an inverse, graded manner independent of other clinical covariates (Adebayo et al., 2016). It is therefore pertinent to keep pulse pressure within acceptable range in HF subjects to prevent untoward events that may worsen cognitive performance. Tricuspid valve E/A ratio -TVEA, a measure of right ventricular dysfunction predicts poor global cognitive function in subjects with HFrEF. This suggest that right ventricular dysfunction may be as important (if not more important) as left ventricular dysfunction in determining cognitive performance in HF subjects. This hypothesis however, needs further testing on a larger population of HF subjects.

This current study is limited by its modest sample size, its cross-sectional design and the fact that multiple comparisons were not accounted for. We did not also correct for fatigue, sleep abnormalities as well as depressive symptoms which could have impaired performance of the participants on neuropsychological tests. The strength of our study however, lies in the fact that the two groups of HF patients were well matched for sex, age and educational status. We also evaluated clinical and echocardiographic correlates of cognitive performance. Correcting these specific clinical correlates may enhance cognitive performance among the cohorts of HF subjects. Large, longitudinal survey to determine the trajectory and modifiers of cognitive performance among Africans with HF is needed.

Conclusion

Cognitive dysfunction is largely similar between the two groups. Delay recall is however the main issue among subjects who have HFpEF. Maintenance of optimal pulse pressure, as well as regular cognitive screening and surveillance are advocated in HF subjects. These measures can enhance early recognition and prevent worsening of HF symptoms which can ensue from forgetfulness in observing HF self-care.

Funding

None.

Conflict of Interest

None declared.

Acknowledgments

None.

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