Cognitive dysfunction correlates with physical impairment in frail patients with acute myocardial infarction

Abstract

Background

To the best of our knowledge, the association of physical impairment and cognitive decline has never been investigated in frail patients with acute myocardial infarction.

Aim

The aim of our study is to assess the correlation between physical and cognitive dysfunction in frail patients with ST-elevation myocardial infarction (STEMI).

Methods

We examined consecutive frail patients with first STEMI treated with primary percutaneous coronary intervention (PPCI). All patients were evaluated via Mini Mental State Examination (MMSE) and 5-m gait speed test after PPCI.

Results

A total of 871 frail patients with suspected STEMI were admitted and 301 patients successfully completed the study. We found that the gait speed significantly correlated with the MMSE score (r: 0.771; p: < 0.001). The independent effects on MMSE score were confirmed in a linear multivariate analysis.

Conclusions

Taken together, our findings indicate that an assessment of both cognitive and physical conditions should be included in the comprehensive geriatric evaluation of hospitalized older STEMI patients.

Background

Frailty is defined as the decreased ability of individuals to recover from physiological insults and often presents with the phenotype of weight loss, sarcopenia, or the lack of independence in activities of daily living [1–3]. Cognitive decline is very common in older populations, and its prevalence increases with age [3–6]. Interestingly, physical decline is typical of these subjects and physical capacity was confirmed to be predictive for major clinical outcomes [6–9]. We believe that correlating these geriatric conditions may be useful to set up the best pharmacological, clinical, and interventional approaches to reduce adverse outcomes and to improve the quality of life of these patients.

Older adults have a high risk to become frail: the frailty prevalence among patients ≥ 65 years old has been estimated to be ~ 10%; moreover, one-third of patients with acute myocardial infarction are ≥ 75 years old [10, 11]. Therefore, evaluating frailty in cardiovascular care is noteworthy to reduce mortality, comorbidities, and re-hospitalizations. ST-elevation myocardial infarction (STEMI) is one of the main causes of death and hospitalization worldwide and represents a major socio-economic burden [12, 13].

Despite these pieces of evidence and notwithstanding the emerging interest in understanding the role of geriatric conditions, the correlation between physical and cognitive impairment in frail STEMI patients remains poorly understood.

Methods

Design, setting, and participants

This is an observational study to investigate the relationship between cognitive and physical decline in a frail population of STEMI subjects. We examined consecutive frail patients with first STEMI treated with primary percutaneous coronary intervention (PPCI) between February 2008 and February 2017 at the Department of Cardiology of the Cardarelli Hospital in Naples, Italy. The diagnosis of STEMI was based on the universal definition of myocardial infarction [14]. Inclusion criteria were: correspondence between ECG findings and suspected culprit artery; a minimum visual estimate of 50% stenosis in the culprit artery; age ≥ 65 years; presentation to the hospital for PPCI in the setting of first STEMI. Exclusion criteria were: left ventricular ejection fraction less than 25%, previous myocardial infarction or previous PPCI and/or coronary by-pass grafting, or previous fibrinolytic therapy, previous diagnosis of dementia.

Frailty assessment

Physical frailty was assessed according to the Fried criteria [2]; additionally, we performed a 5-m gait speed test in all patients before discharge. This test is among the most common approaches to measure the time required to walk a short distance at a comfortable pace; an altered gait speed test has been associated with impairments in lower-extremity muscle function, as well as neurosensory and cardiopulmonary dysfunction [10].

Cognitive evaluation

Global cognitive function was assessed with the Mini-Mental State Examination (MMSE) corrected for the educational level of the patients [15]. This cognitive test, with a score that ranges from 0 to 30, covers many cognitive skills, assessing the main cognitive areas, including immediate and delayed memory (free and cued recall), language, visuo-perceptual and visuo-spatial capacities, motor planning, executive function, attention, and cognitive judgment [16–18]. MMSE scores have been shown to be influenced by demographic variables such as age and years of education [15, 19].

Statistical analyses

Data are presented as mean ± SD. We calculated the number of patients required for the study to reject the null hypothesis 95% of the time (i.e., with a one-tailed type II error rate of 0.05) with a two-tailed type I error at the 0.05 level of significance; the sample size was calculated a priori using G-POWER software, yielding a minimum of 281 patients. An evaluation of dispersion and correlation between the MMSE and the 5-m gait speed test has been performed. A multivariate regression analysis, with MMSE as dependent variable, has been applied to assess the impact of comorbidities. All calculations were performed using SPSS 26.

Results

A total of 871 frail patients with suspected STEMI were consecutively admitted to our PCI center between February 2008 and February 2017. 197 patients were excluded because PPCI was not performed, 167 patients were excluded for delays in treatment greater than 24 h, 137 patients were unwilling to provide clinical information or written informed consent, and biochemical analysis was not available for 69 subjects. Thus, 301 frail patients completed the study, as shown in the flow chart depicted in Fig. 1). Mean age, BMI, sex distribution, smoking habits, plasma cholesterol, and triglyceride levels are reported in Table 1. Comorbidities and drug therapies are reported in Table 1. Angiographic data, including the treated lesion and the stent types are summarized in Table 1, as well.

Fig. 1.

Study flow diagram

Table 1.

Clinical characteristics, angiographic, and procedural data of our population

Parameter	Values
N	301
Women	173
Mean age (years)	74 ± 7.0
BMI (kg/m2)	28.2 ± 1.6
SBP (mmHg)	128.9 ± 12.7
DBP (mmHg)	79.3 ± 7.5
Heart rate (bpm)	85.5 ± 9.5
MMSE (0–30)	21.96 ± 4.6
5-m gait speed test (m/s)	0.67 ± 0.1
TIMI Flow Grade
Grade 0, n (%)	81 (27.0)
Grade 1, n (%)	30 (10.0)
Grade 2/3, n (%)	190 (63.0)
Killip class
Class 1, n (%)	96 (33.0)
Class 2, n (%)	87 (27.0)
Class 3, n (%)	112 (38.0)
Class 4, n (%)	6 (2.0)
Comorbidities
Diabetes, n (%)	183 (61.0)
Hypertension, n (%)	222 (74.0)
Dyslipidemia, n (%)	174 (58.0)
Prior stroke, n (%)	60 (20.0)
Chronic Lung Disease, n (%)	108 (36.0)
Smoke, n (%)	129 (43.0)
Atrial fibrillation, n (%)	66 (22.0)
Heart failure (LVEF > 25%), n (%)	57 (19.0)
Osteoarthritis, n (%)	78 (26.0)
Fried criteria
Weight loss	102 (34.0)
Exhaustion	197 (65.5)
Low physical activity	103 (34.2)
Low gait speed	234 (77.6)
Low muscle strength	262 (87.0)
Active treatments
β-blockers, n (%)	199 (66.0)
ACE inhibitors, n (%)	208 (69.0)
Angiotensin receptor blockers, n (%)	96 (32.0)
Calcium inhibitors, n (%)	81 (27.0)
Statins, n (%)	168 (56.0)
Diuretics, n (%)	24 (8.0)
Insulin, n (%)	63 (21.0)
Oral antidiabetics, n (%)	111 (37.0)
Aspirin, n (%)	144 (48.0)
Laboratory analyses
Plasma glucose (mg/dl)	194.2 ± 21.8
Cholesterol (mg/dl)	201.5 ± 18.5
LDL-cholesterol (mg/dl)	130.5 ± 16.0
HDL-cholesterol (mg/dl)	38.4 ± 6.1
Triglycerides (mg/dl)	183.0 ± 18.3
Creatinine (mg/dl)	1.0 ± 0.1
cTnT (ng/l)	5.8 ± 1.6
Angiographic data
Number of diseased vessels, n (%)
1-VD	211 (70.0)
2-VD	66 (22.0)
3-VD	24 (8.0)
Lesion location, n (%)
RCA	66 (22.0)
LAD	147 (49.0)
LM	12 (4.0)
LCx	76 (25.0)
LVEF
> 50%, n (%)	190 (63.0)
41–50%, n (%)	75 (25.0)
25–40%, n (%)	36 (12.0)
Stent types
DES, n (%)	262 (87.0)
BMS, n (%)	39 (13.0)

Data are mean ± SD or n (%)

BMI body mass index; SBP systolic blood pressure; DBP diastolic blood pressure; TIMI thrombolysis in myocardial infarction; LVEF left ventricular ejection fraction; RCA right coronary artery; LM left main; LAD left anterior descending; LCx left circumflex artery; MLD minimum luminal diameter; 1-VD indicates single-vessel disease; 2-VD two-vessel disease; 3-VD three-vessel disease; BMS bare metal stent; DES drug-eluting stent

Relationships between gait speed test and MMSE score

The gait speed test significantly correlated with the MMSE score (r: 0.771; p < 0.001) (Fig. 2). The independent effects on MMSE were confirmed in a linear multivariate analysis with a regression model (Table 2); in particular, we found a significant effect of age and diabetes (p < 0.001), as well as hypertension (p: 0.023).

Fig. 2.

Dispersion and correlation between gait speed test and Mini Mental State Examination (MMSE)

Table 2.

Multivariate analysis with MMSE as dependent variable

Coefficientsa
Model		B	S.E	Beta	t	p	95% C.I. for B
							Inferior limit	Superior limit
1	(Constant)	38.109	4.043		9.425	< 0.001	30.162	46.055
	Age	− 0.228	0.031	− 0.317	− 7.345	< 0.001	− 0.288	− 0.167
	BMI	0.135	0.115	0.051	1.173	0.241	− 0.091	0.361
	Diabetes	− 2.361	0.491	− 0.214	− 4.812	< 0.001	− 3.325	− 1.397
	Hypertension	− 0.977	0.430	− 0.101	− 2.274	0.023	− 1.822	− 0.133
	Heart failure	− 0.849	0.550	− 0.087	− 1.544	0.123	− 1.930	0.232
	Osteoarthritis	− 0.980	0.647	− 0.097	− 1.516	0.130	− 2.251	0.291
	Atrial Fibrillation	0.427	0.666	0.044	0.641	0.522	− 0.883	1.737
	Stroke	− 0.419	0.500	− 0.038	− 0.838	0.402	− 1.403	0.564
	Hyperlipidemia	− 0.124	0.437	− 0.012	− 0.283	0.777	− 0.982	0.735
	Smoking	− 0.668	0.432	− 0.067	− 1.546	0.123	− 1.517	0.181

BMI body mass index; C.I. confidence interval; S.E. standard error

^aDependent variable: MMSE

Discussion

To the best of our knowledge, this is the first study to investigate and correlate cognitive and physical activity with MMSE and 5 m gait speed test. Frail subjects are known to present physical decline and may present cognitive decline [20–22]. In this scenario, with our study we sought to quantify and correlate these declines with the aforementioned tests in STEMI. We show that the performance in MMSE score was worst in patients with low score in gait speed test, as depicted in Fig. 2. Strikingly, we observed a significant correlation that was confirmed by multivariate analysis.

Our results are consistent with a previous report showing that the clinical assessment of gait speed could identify the subsets of patients at higher risk for cardiovascular events [3]. Our data strongly suggest that frail older adults with low scores in these tests should be managed and treated to reduce the risk of decline, re-hospitalization(s), and death. Thus, a simple and careful evaluation might improve the quality of life of these patients, identifying and treating high-risk subjects to reduce the risk of developing physical and/or mental decline [23]. Indeed, in full agreement with our view, previous observations have demonstrated that cardiovascular health promotion is a pivotal determinant in frail patients [24].

The findings of our study must be interpreted in light of several limitations. First, we do not have follow-up records, although we reckon the value of having data to be evaluated also at follow-up; nonetheless, we believe that observing significant differences right after acute STEMI is noteworthy, especially in a population of frail elderly subjects. Second, we used a classification of frailty that mainly assesses mere physical frailty, opposed to a multidimensional approach also involving nutritional, and psychosocial components [25]. Finally, the sample size of our group is relatively small; however, several factors support the robustness of our findings, including the fact that we had performed an a priori power analysis, based on our preliminary data, showing that the minimum estimated sample size to obtain statistically significant results was 281 patients. Nevertheless, further studies, ideally with follow-up data and larger cohorts are required to confirm our results.

Conclusions

This is the first study evaluating and correlating cognitive and physical decline in a frail population of STEMI patients ≥ 65-year-old. Our investigation can help inform whether a cognitive evaluation and a gait speed test are appropriate in frail older patients with STEMI.

Taken together, our data indicate that in the follow-up period of STEMI, after PPCI, adding a simple evaluation with MMSE and gait speed test may be useful to prevent and/or delay disability. We propose that an objective assessment of both cognitive and physical condition, should be included in the comprehensive geriatric evaluation of hospitalized older STEMI patients. Future research should explore if such assessment and subsequent intervention can actually improve the short-and long-term outcome of STEMI.