|Year : 2020 | Volume
| Issue : 1 | Page : 33-40
Risk factors of cognitive dysfunction among patients with chronic obstructive pulmonary disease
Amgad A.M Gabr1, Mahmoud El Saeed Abd El Raoof2, Sally S Abd-Elhamed3, Ibrahim H Elbanaa2
1 Department of Psychiatry, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
2 Department of Chest Diseases, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
3 Department of Internal Medicine, Faculty of Medicine, Al-Azhar University, Cairo, Egypt
|Date of Submission||15-Oct-2019|
|Date of Decision||30-Oct-2019|
|Date of Acceptance||03-Nov-2019|
|Date of Web Publication||22-Jan-2020|
MD Psychiatry Amgad A.M Gabr
Department of Psychiatry, Faculty of Medicine, Al-Azhar University, Al Mokhaym Al Daem, Al Azhar Unversity, Nasr City, Pot Office No. 11751
Source of Support: None, Conflict of Interest: None
Background Cognitive dysfunction is one of the most common comorbidities related to chronic obstructive pulmonary disease (COPD), with ∼70% of patients developing such condition. Besides, cognitive dysfunction has been established to be a potential predictor of mortality and morbidity.
Aim This study was conducted to assess the possible causes of cognitive dysfunction among patients with COPD.
Patients and methods Patients with COPD aged more than 40 years were included in the current study. Patients were further assorted into two groups based on the assessment of cognition state using Mini Mental State Examination: patients who had COPD without cognitive dysfunction (control group) and patients who had COPD with cognitive dysfunction (case group).
Results A total of 120 participants were included in the study. Of them, 60 patients experienced COPD without cognitive dysfunction (control group) whereas 60 patients experienced COPD with cognitive dysfunction (case group). There was a statistically significant difference between both groups regarding the education level (P=0.038), intelligence quotient levels (P=0.004), duration of symptoms (P=0.042), and Modified Cumulative Illness Rating Scale (MCIRS) (P=0.001). The results of regression model showed that patient’s age (P=0.01), MCIRS (P=0.041), duration of symptoms (P=0.03), and education state (P=0.029) were statically significant predictors of Mini Mental State Examination score.
Conclusion The findings of our investigation increase the awareness that despite the controlled COPD, elderly obese patients with high MCIRS score and long duration of symptoms were more susceptible to develop cognitive dysfunction.
Keywords: causes, chronic obstructive pulmonary disease, cognitive dysfunction
|How to cite this article:|
Gabr AA, El Raoof MA, Abd-Elhamed SS, Elbanaa IH. Risk factors of cognitive dysfunction among patients with chronic obstructive pulmonary disease. Egypt J Psychiatr 2020;41:33-40
|How to cite this URL:|
Gabr AA, El Raoof MA, Abd-Elhamed SS, Elbanaa IH. Risk factors of cognitive dysfunction among patients with chronic obstructive pulmonary disease. Egypt J Psychiatr [serial online] 2020 [cited 2022 Aug 18];41:33-40. Available from: http://new.ejpsy.eg.net/text.asp?2020/41/1/33/276399
| Introduction|| |
Chronic obstructive pulmonary disease (COPD) is deemed to be a life menacing disease (Lopez-Campos et al., 2016). To date, COPD affects ∼600 million patients worldwide; thereafter, it is estimated to be the third leading cause of death and the fifth leading cause of disability by 2020 (Jemal et al., 2005; Smith and Wrobel, 2014). The burden of COPD is still mounting owing to the increased smoking rate and air pollution, principally among the elderly population (Negewo et al., 2015).
Noteworthy, COPD is a multisystem disease with numerous extrapulmonary consequences (Celli et al., 2018). In particular, COPD is characterized by pulmonary manifestations apart from progressive and irreversible airflow obstruction along with extrapulmonary manifestations such as impairment of brain function (Lopez-Torres et al., 2016). The brain is more susceptible to the systemic effects of COPD, which in turn lead to the development of abundant neurological impairment and cognitive dysfunction (Kakkera et al., 2018; Lawi et al., 2018).Cognitive dysfunction is one of the most common comorbidities related to COPD, whereby nearly 70% of patients with COPD developed such condition (Lawi et al., 2018). In addition, cognitive dysfunction has been established to be a potential predictor of mortality and morbidity among patients with COPD (Yohannes et al., 2017). Accordingly, patients showed inadequate compliance to oxygen therapy and medication, which in turn enhance considerably the risk of acute exacerbation (Bajaj et al., 2019). In addition, cognitive dysfunction had multiple repercussions on health status, patient function, and quality of life (Cleutjens et al., 2017).
Of note, COPD is often associated with many comorbidities, comprising hypertension, ischemic heart disease, lung cancer, and diabetes (Cleutjens et al., 2018). These factors coupled with the sequential hypoxia and hypercapnia might be attributed to the pathogenesis of cognitive dysfunction among patients with COPD (Dag et al., 2016). Recently, the prevalence of cognitive dysfunction is rising, particularly with the increasing awareness of such condition along with the advancement in the neurodiagnostic tools (Cleutjens et al., 2018). However, the literature is still doubtful about the detection of the possible risk factors and predictors of cognitive dysfunction among patients with COPD. To shed light on this issue, this study was conducted to assess the possible causes and predictors of such condition among patients with COPD.
| Patients and methods|| |
The present study was executed based upon the recommendations of the Ethical Research Board of the Faculty of Medicine, Al-Azhar University, Cairo, Egypt. The potential risk events and complications were illustrated obviously for the included patients, legal trustee, or their relatives before study implementation. Informed consents were obtained before study conduction. Furthermore, all clinical procedures were carried out along with the guidelines of the Declaration of Helsinki.
This is a prospective observational case–control study that was implemented at the Psychiatry and Pulmonology Departments, Sayed Galal and Al-Zahraa University Hospitals, Faculty of Medicine, Al-Azhar University, Cairo, throughout the entire period of June 2017 to January 2019.
Patients with COPD, established clinically based on Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria, and aged more than 40 years were included in the current study. Patients were further assorted into two groups based on the assessment of cognition state using Mini Mental State Examination (MMSE): patients who had COPD without cognitive dysfunction (control group) and patients who had COPD with cognitive dysfunction (case group).
Patients with COPD who experienced exacerbation attacks within 4 weeks before the study conduction were excluded. Similarly, patients with severe decompensated respiratory failure and uncontrolled coronary heart disease, diabetes, hypertension, heart failure, liver impairment, renal insufficiency, encephalitis, or epilepsy were omitted.
Patients having a history of brain tumor, head injury, previous stroke, or having a major psychiatric illness or dementia were ousted (based on the American Psychiatric Association). Eventually, patients treated by cortisone for a long period were excluded as well.
All patients were subjected to history taking to reveal the following data: age, sex, BMI, duration of symptoms, history of COPD exacerbation, and symptoms. Besides that, patients were clinically evaluated to reveal the evidence of visual and hearing impairment along with complete neurological examination.
The Modified Cumulative Illness Rating Scale
It is a method for recording all the associated comorbidities of the included participants. It assorted the diseases of 14 organ systems, whereas each organ was scored 0–4 based on the severity of affection (Miller et al., 1992).
Pulmonary function tests
Conventional spirometry was used to evaluate the pulmonary function for each participant via portable dry rolling SpiroBank spirometer (Company nSpire Health; Medics MGA USB, Oberthulba, Germany). The reference values were calculated based on the guidelines of the American Thoracic Society. Spirometry measured forced vital capacity and forced expiratory volume in 1 s (FEV1), and the ratio of these two measurements (FEV1/forced vital capacity) is then calculated.
Blood gas analysis
With the patients holding their breath, radial arterial blood was aspirated using a heparinized syringe, positioned on ice, and taken to a blood gas laboratory for analyses. Using the radiometer blood gas analyzer, arterial blood acidity (pH), partial pressure of arterial oxygen, partial pressure of arterial carbon dioxide, arterial oxygen saturation, arterial bicarbonate level, and base excess or deficit were calculated.
Mini Mental State Examination
It evaluated the overall assessment of cognitive function, as it is associated with extensive memory testing and cognitive decline among patients with COPD. Patients were given a score between 0 and 30, whereby patients scored more than 24 were considered having normal cognitive function (Incalzi et al., 1993, Incalzi et al., 1998).
Assessment of psychological well-being
Manifestations of anxiety and depression were assessed based on the hospital anxiety and depression scale (HADS). This scale is composed of a subscale, which ranged from 0 to 21 points. The patients were assorted based on their score into normal (0–7), borderline (8–10), and abnormal (11–21) levels of anxiety and depression. Subsequent to that, the Beck Depression Inventory was carried out to evaluate the depth, intensity, and severity of depression using a 21-item questionnaire. This score ranged from 0 to 63, where patient scores 0–9 represent not depressed, patient scores 10–18 and 19–29 represent mild–moderate and moderate–severe depression, respectively; and patient scores 30–63 represent severe depression (Zigmond and Snaith, 1983; Beck et al., 1961).
Using the Symptom Checklist 90 (SCL-90), the psychological system intensity for each participant was assessed (Derogotis et al., 1973).
Continuous variables were explicated in the form of mean and SD, and its confidential groups were compared using Student t test. On the contrary, categorical variables were expressed using the number and percentage, and its particular groups were compared using Pearson’s χ2 test with Fisher’s exact test. In addition, correlation analysis was conducted using Spearman’s rank correlation coefficient. The univariate linear regression model was established to reveal the possible predictors of cognitive dysfunction among patients with COPD using MMSE scale. The significance is established when P value less than 0.05. Statistical analysis was performed using SPSS software, version 23 for Windows (SPSS Inc., Chicago, Illinois, USA).
| Results|| |
Patients’ demographic characteristics
A total of 120 participants were included in the study. Based on MMSE, 60 patients experienced COPD without cognitive dysfunction (control group), whereas 60 patients experienced COPD with cognitive dysfunction (case group). The mean age of the included patients was 55.31±7.23 and 56.48±6.41 years (P=0.81) among case and control groups, respectively. There was a statistically significant difference between both groups regarding the education level (P=0.038), where 45 (65%) patients among the case group were illiterates and 31 (51.6%) patients among the control group were illiterates. In this respect, there was a statistically significant low intelligence quotient level (P=0.004) among the case group, with a mean of 73.98±6.45, in contrast to the control group, with a mean of 91.77±4.87. Furthermore, the patients among the case group showed statistically significant (P=0.042) long duration of symptoms (18.61±4.29 years), relative to the patients among the control group (13.7±3.5 years). Subsequent to that, there was a statistically significant (P=0.001) high Modified Cumulative Illness Rating Scale (MCIRS) among the case group when compared with the control group, with a mean of 26.79±3.87 and 19.51±2.31, respectively ([Table 1] and [Figure 1] and [Figure 2]).
|Figure 1 Bar chart displaying the pattern of education (illiterate) among the studied group.|
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|Figure 2 Error bar chart displaying the duration of symptoms among the studied group.|
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Based on pulmonary function tests, there was no statistically significant difference between the case and the control groups regarding the levels of FEV1 (P=0.059), partial pressure of arterial oxygen (P=0.73), and partial pressure of arterial carbon dioxide (P=0.905). Similarly, there was no statistically significant difference between both groups regarding the number of patients received oxygen therapy (P=0.86) ([Table 1] and [Figure 3]).
|Figure 3 Error bar chart displaying the mean MCIRS among the studied group. MCIRS, Modified Cumulative Illness Rating Scale.|
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Patients’ psychological assessment
The mean levels of MMSE scores differed substantially (P=0.002) between the case and the control groups, with a mean of 19.203±3.41 and 27.3±3.1, respectively. On the contrary, there was no statistically significant difference between both groups regarding HADS depression score (P=0.8), HADS anxiety score (P=0.61), Beck Depression Inventory score (P=0.79), SCL-90 anxiety score (P=0.804), SCL-90 agoraphobia score (P=0.58), and SCL-90 depression score (P=0.091) ([Table 2] and [Figure 4]).
|Figure 4 Error bar chart displaying the mean MMSE scores among the studied group. MMSE, Mini Mental State Examination.|
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Risk factors of cognitive dysfunction among patients with chronic obstructive pulmonary disease
Correlation analysis showed that there was a significant negative correlation between MMSE score and the age of the patients (r=−0.4, P=0.039), BMI (r=−0.37, P=0.02), MCIRS (−0.61, P=0.001), and duration of symptoms (r=−0.54, P=0.04). Subsequently, there was a significant positive correlation between MMSE score and the number of literates (r=0.81, P<0.001), and intelligence quotient levels (r=0.45, P=0.046) ([Table 3]).
|Table 3 Correlation between patients’ demographics and Mini Mental State Examination score|
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The results of regression model displayed that patients’ age (P=0.01), MCIRS (P=0.041), duration of symptoms (P=0.03), and education state (P=0.029) were statically significant predictors of MMSE score ([Table 4]).
|Table 4 Univariate linear regression model to predict cognitive dysfunction based on Mini Mental State Examination score|
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| Discussion|| |
COPD is a progressive multicomponent disease that altered noticeably several functions of multiple organs besides its significant effect on lung and heart (Dal Negro et al., 2015). The presence of significant cognitive dysfunction was found to be related to the severity of the disease; however, some studies showed that cognitive deterioration may occur even among patients with controlled COPD (Metwally et al., 2017).
Finding the possible risk factors of cognitive deterioration among patients with stable COPD is a doubtful question in the literature. This is because the inadequate number of studies had abundant limitations. Herein, the evidence abbreviated in our investigation brings to light that even if patients with COPD did not experience significant deterioration of their pulmonary function tests, they may develop cognitive dysfunction. Thereafter, patients with COPD should be subjected to comprehensive follow-up protocol comprehending cognitive assessment as a part of the respiratory assessment.
These results might be attributed to the associated persistent hypoxemia, which directly causes neural damage. In detail, the brain has the highest oxygen demand in the body; therefore, it is highly sensitive to ischemia (Lee et al., 2000). If the oxygen supply is inadequate to fulfill the metabolic demands of the brain, this can lead to a lack of cerebral neurons (Lawi et al., 2018). In addition, it also affects oxygen-dependent enzymes, which are extremely pivotal in the synthesis of different neurotransmitters likewise acetylcholine. Besides, elevated carbon dioxide tension along with hypercapnia plays a major role in the development of cognitive dysfunction (López-Torres et al., 2016).
For patients with stable COPD state, the underlying cause of cognitive impairment may be related to neurophysiological consequences such as continuous decline of prefrontal cortex circulation (Dal Negro et al., 2014). In this respect, Shim et al. (2001), notified that cerebral metabolism was noticeably affected, whereas the pattern of derangement was considerably high based on the magnetic resonance spectroscopy among controlled patients with COPD. Subsequently, a study by Metwally et al. 2017 (Kozora et al., 1999) showed that there was a significant impairment of cognitive dysfunction, based on MMSE scale, among patients with COPD despite the absence of respiratory failure.
The results of our study showed that elderly obese patients with high MCIRS score coupled with a long duration of symptoms were more vulnerable to develop cognitive dysfunction. This result might be attributed to the increase in the oxidative stress and inflammation process coupled with the decline of physical activity can express the process of aging, which in turn enhance considerably the neurodegenerative changes (Thakur et al., 2018). In compliance with our results, Dag et al. (2016), reported that there was a significant difference between patients who developed cognitive dysfunction and those who did not develop regarding the age (P=0.001), education level (P=0.04), and MCIRS (P=0.01), which were also predictors of cognitive performance among patients with COPD.
Despite the evidence retrieved in our study, this study had some limitations, such as lack of randomization along with short-follow up period, which hinder the capability to detect long-term consequences of cognitive dysfunction and may hinder the feasibility of our study.
| Conclusion|| |
The findings of our investigation increase the awareness that despite the controlled COPD, elderly obese patients with high MCIRS score and long duration of symptoms were more susceptible to develop cognitive dysfunction. Thereafter, cognitive evaluation should be a part of the routine respiratory assessment.
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Conflicts of interest
There are no conflicts of interest.
| References|| |
Bajaj MK, Burrage DR, Tappouni A, Dodd AW, Paul W (2019). COPD patients hospitalized with exacerbations have greater cognitive impairment than patients hospitalized with decompensated heart failure. Clin Interv Aging 14:1–8.
Beck AT, Ward CH, Mendelson M, Mock J, Erbaugh J (1961). An inventory for measuring depression. Arch Gen Psychiatry 4:561–571.
Celli BR, Locantore N, Tal-Singer R, Riley J, Miller B, Vestbo J et al.
(2018). Emphysema and extrapulmonary tissue loss in COPD: a multi-organ loss of tissue phenotype. Eur Resp J 17:21–46.
Cleutjens F, Spruit MA, Ponds R, Vanfleteren LEGW, Franssen FME, Dijkstra JB et al.
(2017). The impact of cognitive impairment on efficacy of pulmonary rehabilitation in patients with COPD. J Am Med Directors Ass 18:420–426.
Cleutjens F, Spruit MA, Ponds R, Vanfleteren LEGW, Franssen FME, Gijsen C et al.
(2018) Cognitive impairment and clinical characteristics in patients with chronic obstructive pulmonary disease. Chronic Resp Dis 15:91-102.
Dag E, Bulcun E, Turkel Y, Aydanur E, Mehmet E (2016). Factors influencing cognitive function in subjects with COPD. Respir Care 61:1044–1050.
Dal Negro RW, Bonadiman L, Tognella S, Bricolo FP, Turco P (2014). Extent and prevalence of cognitive dysfunction in chronic obstructive pulmonary disease, chronic non-obstructive bronchitis, and in asymptomatic smokers, compared to normal reference values. Int J Chronic Obstructive Pulm Dis 9:675–683.
Dal Negro RW, Bonadiman L, Tognella S, Bricolo FP, Turco P (2015). Cognitive dysfunction in severe chronic obstructive pulmonary disease (COPD) with or without Long-Term Oxygen Therapy (LTOT). Multidiscip Respir Med 10:17.
Derogotis L, Lipman R, Coy L (1973). An outpatient psychiatric rating scale-preliminary report. Psychopharmacol Bull 9:13–27.
Incalzi RA, Gemma A, Marra C, Muzzolon R, Capparella O, Carbonin P (1993). Chronic obstructive pulmonary disease. An original model of cognitive decline. Am Rev Resp Dis 148:418–424.
Incalzi RA, Chiappini F, Fuso L, Torrice MP, Gemma A, Pistelli R (1998). Predicting cognitive decline in patients with hypoxaemic COPD. Respir Med 92:527–533.
Jemal A, Ward E, Hao Y, Jemal A, Ward E, Hao Y, Thun M (2005). Trends in the leading causes of death in the United States, 1970-2002. JAMA 294:1255–1259.
Kakkera K, Padala KP, Kodali M, Kakkera K, Padala KP, Kodali M, Padala PR (2018). Association of chronic obstructive pulmonary disease with mild cognitive impairment and dementia. Curr Opin Pulm Med 24:173–178.
Kozora E, Filley CM, Julian LJ, Kozora E, Filley CM, Julian LJ, Cullum CM (1999). Cognitive functioning in patients with chronic obstructive pulmonary disease in mild hypoxemia compared with patients with mild Alzheimer disease and normal controls. Neuropsychiatry Neuropsychol Behav Neurol 12:178–183.
Lawi D, Berra G, Janssens JP, Soccal PM, Adler D (2018). COPD and cognitive impairment. Rev Med Suisse 14:2066–2069.
Lee J-M, Grabb MC, Zipfel GJ, Choi DW (2000). Brain tissue responses to ischemia. J Clin Investig 106:723–731.
Lopez-Campos JL, Tan W, Soriano JB (2016). Global burden of COPD. Respirology 21:14–23.
Lopez-Torres I, Valenza MC, Torres-Sanchez I, Cabrera-Martos, Rodriguez-Torres J, Moreno-Ramírez MP (2016). Changes in cognitive status in COPD patients across clinical stages. COPD 13:327–332.
Metwally M, Khedr E, El-Shinnawy O, Hassan Alaa EL-din Th, Shaddad AM (2017). Evaluation of cognitive function in COPD: a role of P-300 event-related potentials. Chest 152:A792–A792.
Miller MD, Paradis CF, Houck PR, Mazumdar S, Stack JA, Rifai AH et al.
(1992). Rating chronic medical illness burden in geropsychiatric practice and research: application of the Cumulative Illness Rating Scale. Psychiatry Res 41:237–248.
Negewo NA, Gibson PG, McDonald VM (2015). COPD and its comorbidities: impact, measurement and mechanisms. Respirology 20:1160–1171.
Shim TS, Lee JH, Kim SY, Lim TH, Kim SJ, Kim DS, Kim WD (2001). Cerebral metabolic abnormalities in COPD patients detected by localized proton magnetic resonance spectroscopy. Chest 120:1506–1513.
Smith MC, Wrobel JP (2014). Epidemiology and clinical impact of major comorbidities in patients with COPD. Int J Chronic Obstruct Pulmon Dis 9:871–888.
Thakur ER, Sansgiry S, Petersen NJ, Stanley M, Kunik ME, Naik AD, Cully JA (2018). Cognitive and perceptual factors, not disease severity, are linked with anxiety in COPD: results from a cross-sectional study. Int J Behav Med 25:74–84.
Yohannes AM, Chen W, Moga AM, Leroi I, Connolly MJ (2017). Cognitive impairment in chronic obstructive pulmonary disease and chronic heart failure: a systematic review and meta-analysis of observational studies. J Am Med Directors Ass 18:451.e1–451.e11.
Zigmond AS, Snaith RP (1983). The hospital anxiety and depression scale. Acta Psychiatr Scand 67:361–370.
[Figure 1], [Figure 2], [Figure 3], [Figure 4]
[Table 1], [Table 2], [Table 3], [Table 4]