|Year : 2015 | Volume
| Issue : 1 | Page : 14-20
Cognitive decline in different delirium subtypes and the associated change in the biomarker S100B serum level
Nabil R Mohamed1, Lamiaa G El Hamrawy1, Ayman K Abdel-Hamid2, Afaf Z Ragab1, Mohamed S Abdel-Shafy1
1 Neuro-Psychiatry Department, Faculty of Medicine, Menoufiya University, Menoufiya, Egypt
2 Biochemistry Department, Faculty of Medicine, Menoufiya University, Menoufiya, Egypt
|Date of Web Publication||23-Mar-2015|
Afaf Z Ragab
Lecturer of Psychiatry, Psychiatry Department, Faculty of Medicine, Menoufiya University, Shebin El-Kom, Menoufiya
Source of Support: None, Conflict of Interest: None
This study was designed to assess the cognitive decline in different delirium subtypes and the change in the level of serum S100B, with determination of the outcome of delirium.
Delirium involves a wide range of cognitive disturbances across its different subtypes. The serum S100B level is high in delirious patients and plays a role in the process of learning and memory. The outcome of delirium differs according to delirium subtypes.
Participants and methods
This study enrolled 35 delirious patients (group A) and two control groups. Group B comprised 10 patients with disease but without delirium. Group C comprised 10 normal healthy individuals. All participants were subjected to the Delirium Symptom Interview scale, the Cognitive Test for Delirium, the Delirium Motor Subtype Scale, and the Trail Making Test parts A and B, and the level of serum S100B was measured. About 17 delirious patients were followed up after 1 month to assess the cognitive decline and the mortality rate.
The level of cognitive dysfunction in delirious patients was significantly higher than that in the two control groups (group B and group C). The level of cognitive dysfunction was not significantly different among the four delirium subtypes. Attention impairment occurred in 96% of the patients, and the less affected cognitive domain was comprehension, which occurred in 77% of the patients. The level of serum S100B was significantly higher in delirious patients compared with the two control groups, but it was not significantly different among the delirium subtypes. After 1 month, the hypoactive subtype was associated with more cognitive dysfunction and a high mortality rate.
Cognitive decline occurs in delirious patients, but this decline was not significantly different among the delirium subtypes. The most affected cognitive domain was attention and the least affected one was comprehension. Delirium was associated with a high level of serum S100B, but this level was not significantly different among the delirium subtypes. The hypoactive subtype was associated with a poor outcome.
Keywords: cognitive decline, delirium subtypes, serum S100B
|How to cite this article:|
Mohamed NR, El Hamrawy LG, Abdel-Hamid AK, Ragab AZ, Abdel-Shafy MS. Cognitive decline in different delirium subtypes and the associated change in the biomarker S100B serum level. Egypt J Psychiatr 2015;36:14-20
|How to cite this URL:|
Mohamed NR, El Hamrawy LG, Abdel-Hamid AK, Ragab AZ, Abdel-Shafy MS. Cognitive decline in different delirium subtypes and the associated change in the biomarker S100B serum level. Egypt J Psychiatr [serial online] 2015 [cited 2021 Jan 21];36:14-20. Available from: http://new.ejpsy.eg.net/text.asp?2015/36/1/14/153772
| Introduction|| |
Delirium is an acute neuropsychiatric disorder characterized by impaired attention, disturbed consciousness, and disorganized thinking (Brown et al., 2011).
It is a clinical syndrome that is related to several adverse outcomes, including a longer mean length of hospital stay, a poor functional status, need for institutional care, and an increase in mortality rate (Hend et al., 2014).
Delirium has an acute onset, developing within hours to days, and tends to fluctuate during the course of the day. Inability to focus, sustain, and shift attention is accompanied by other cognitive symptoms (e.g. disorientation, episodic memory dysfunction) and/or perceptual disturbances (misinterpretations, illusions, or hallucinations) (Silverstein et al., 2007).
Cognitive impairment is one of the core diagnostic features of delirium (Lins et al., 2005). Disturbed attention has become a cardinal feature of the diagnostic criteria for delirium since years (Meagher and Leonard, 2008). Other associated features include disturbances in the sleep-wake cycle and the activity level, affective disturbances (mood lability, anger, sadness, and euphoria), and thought disorders (disorganized thinking and delusions) (Silverstein et al., 2007).
There are three subtypes of delirium, namely hyperactive, hypoactive, and mixed presentations of delirium. Hyperactive patients are restless, agitated, and hyperalert and often show hallucinations and delusions, but hypoactive delirious patients appear lethargic and drowsy, and sometimes they appear to be sedated, respond slowly to questions, and hardly move spontaneously (Lipowski, 1990).
The suggested pathophysiological mechanisms of delirium are mostly hypothetical, but lately there is growing interest in the role of the neuroinflammatory system (Maclullich et al., 2008).
S100B can be measured in the cerebrospinal fluid or the serum of blood with readily available immunoassay kits; a normal S100B level reliably predicts the absence of significant central nervous system injury (Bloomfield et al., 2007).
| Participants and methods|| |
A Thirty-five educated patients who experienced delirium due to neoplasm (extracranial), traumatic brain injury, and patients who undergone hip replacement surgery were enrolled in the this study. All patients were selected from inpatients of medical and surgical wards and the ICU setting in Menoufiya University Hospitals between June 2013 and June 2014. Two control groups were selected: group B comprised 10 patients with the same diseases, but without delirium; and group C comprised 10 healthy individuals with an age range from 18 to 40 years. A written informed consent was obtained from all patients and/or caregivers before participation in the study. It contained the name of the study and its aims. It also included a detailed description of the procedure. The participants or caregivers were informed that they had the right to withdraw from the study at any time without justification. The study was approved by the local ethical committee of the hospital.
We excluded patients with pre-existing cognitive impairment as noted by history, investigations, or their relatives, patients with an acute confusional state due to substance abuse, patients with severe hearing and visual disability, and patients who refused to assign the consent.
About 17 delirious patients (48.6%) were followed up at 1 month for the degree of recovery from delirium and cognitive functions, which were assessed by the delirium severity scales and cognitive tests. About 18 patients (51.4%) dropped out during the follow-up because they were lost to follow-up or due to refusal of the patients or their caregivers to complete the study.
All patients were subjected to the questionnaire, which included patients' demographics, mode of onset of the illness, history of disease and disease-related symptoms, current medications, clinical findings, and laboratory investigations. Patients fulfilled the criteria for the diagnosis of delirium according to the Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV-TR), the Delirium Symptom Interview (DSI) for the screening of symptoms and the severity of delirium, the Cognitive Test For Delirium (CTD), the Delirium Motor Subtype Scale, and the Trail Making Test parts A and B (TMT-A, B) to test psychomotor activity and attention.
The level of S100B was measured in the serum of venous blood samples that were drawn in the morning after the delirium inclusion criteria were assessed in the 55 participants of the study.
Principle of the test: The S100 ELISA is a two-site, one-step, enzyme-linked immunosorbent assay. In the assay, calibrators, controls, and unknown samples react simultaneously with two solid-phase capture antibodies and a detector antibody conjugated with horseradish peroxidase during the incubation in the microtiter wells. After a washing step, a tetramethylbenzidine chromogen is added and the reaction is allowed to proceed for 15 min. The enzyme reaction is stopped by adding a stop solution, and the absorbance is measured at 450 nm.
The collected data were tabulated and analyzed by SPSS (Statistical Package for Social Science software) statistical package version 22 (SPSS, 2014). Quantitative data were expressed as mean and SD (X SD). Qualitative data were expressed as the number and percentage. Spearman's correlation (r) was used to detect the association between quantitative variables. Logistic regression analysis was used to calculate the effect of risk factors as independent odds ratios with the effect of other confounders removed. The results of the study were considered significant when the P-value was less than 0.05 and highly significant when the P-value was less than 0.001.
| Results|| |
A highly significant difference was detected between the delirium group (group A) and the diseased patients without delirium group (group B) in the scores of the DSI, the CTD, TMT-A, B, and the level of serum S100B as shown in [Figure 1].
|Figure 1: The mean value shows a highly signifi cant difference between delirium patients, diseased patients without delirium, and normal healthy individuals regarding different scales and levels of serum S100B.|
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A highly significant difference was found between the delirium group (group A) and the normal healthy group (group C) in the scores of the DSI, the CTD, TMT-A, B, and the level of serum S100B as shown in [Figure 1].
There was no significant difference between the diseased patients without delirium group (group B) and the normal healthy group (group C) in the scores of the DSI, the CTD, TMT-A, B, and the level of serum S100B as shown in [Figure 1].
There was no significant difference in the scores of the DSI, the CTD, TMT-A, B, and the level of serum S100B in the different delirium subtypes as shown in [Table 1].
|Table 1 Comparison between delirium subtypes regarding different scales and levels of serum S100B|
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There was a significant difference across the four delirium subtypes in the outcome at 1 month as shown in [Table 2].
|Table 2 Comparison between delirium subtypes regarding the outcome at 1 month|
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A highly significant correlation was detected between the initial DSI score and scores of the CTD, and TMT-A, B as shown in [Table 3].
|Table 3 Spearman's correlation between the score of the initial Delirium Symptom Interview and other scales|
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A significant difference was detected between scores of the DSI, the CTD, and TMT-A, B before and at 1 month as shown in [Figure 2].
|Figure 2: The Wilcoxon test showed a signifi cant difference before and at 1 month for delirium patients regarding scores of the Delirium Symptom Interview, the Cognitive Test for Delirium, and the Trail|
Making Test parts A, B.
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Scores of the DSI, the CTD, the TMT-A, the TMT-B, and finally the level of serum S100B are independent risk factors for delirium occurrence as shown in [Table 4].
|Table 4 Multivariate logistic regression analysis of the risk factors for delirium|
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Neoplasm (extracranial) was the only risk factor for the hypoactive subtype and traumatic brain injury was the only risk factor for the hyperactive subtype as shown in [Table 5].
|Table 5 Multivariate logistic regression analysis of risk factors for hypoactive and hyperactive subtypes|
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| Discussion|| |
In the current study, the level of cognitive dysfunction in delirious patients was significantly higher than that in the control groups, but there was an insignificant difference between diseased patients without delirium and normal individuals in their cognitive functions. This was in agreement with Christensen et al. (1994); Hart et al. (1996); Simon et al. (2006); Lowery et al. (2008); Brown et al. (2009); O'Keefe and Gosney (2009), who found a widespread pattern of cognitive impairment in their studies on delirium, leading some researchers to suggest that these patients have global deficits in cognitive functions rather than patients without delirium (i.e. dementia) or normal individuals. In contrast Brown and Boyle (2002), who conducted a study on cognitive assessment in 37 postoperative delirious patients aged 60-87 years, found that different cognitive domains may not be equally affected in delirium. Patients with delirium showed significant deficits on tests of fluid cognition, which involve the active processing of mental representations such as attention, concentration, and vigilance, but no change occurred in the crystallized cognition such as well-learnt word pronunciation knowledge and memory. These results were parallel to recent findings in Alzheimer's dementia and suggest that despite extensive deficits of fluid cognitive processing, crystallized cognition is preserved in delirium.
In the present study, the level of serum S100B was significantly higher in delirious patients than the two control groups. This was supported by Van Munster et al. (2010), who found that the S100B level was significantly higher during delirium than in non-delirium. In contrast, Aly et al. (2014) found that the S100B level was higher in delirium cases than in controls, but the difference was not significant, and they reported that there was no significant difference in S100B level between the different subtypes of delirium.
In the present study, the level of cognitive dysfunction was not significantly different among the four delirium subtypes, but the highest level of cognitive dysfunction was found in the mixed subtype, followed by the hyperactive, and then the hypoactive subtypes, and better cognitive functions was in no subtype group. This was consistent with Leonard et al. (2011), who found that cognitive functioning was not significantly different among the motor subtypes for any neuropsychological domain, with the mixed group often having the worst overall level of impairment, and the no subtype group was the least affected group. This was in contrary to Meagher et al. (2000), who found that overall score of cognitive functions differed significantly among delirium subtypes, with the highest score in the hyperactive subtype, the lowest one in the hypoactive subtype, and intermediate score in the mixed subtype. This was explained by Meagher et al. (2000), who found that the hyperactive subtype had a longer duration of recognized delirium than the other subtypes. Hyperactive patients are recognized and referred earlier because these patients rarely go unnoticed or are misdiagnosed, and finally, this discrepancy may be related to psychotropic medications (benzodiazepine and anticholinergic) that were associated with the hyperactive presentation of delirium. In the present study, the level of serum S100B was not significantly different among the four subtype groups. This was in agreement with Van Munster et al. (2010), who found that delirium subtypes and the S100B level were not significantly correlated.
In contrast to our results, Undιn et al. (2004) found that the highest level of serum S100B occured in the hyperactive subtype was the result of traumatic brain injury. This might be explained in our study by the fact that S100B values were measured in the peripheral blood and may not necessarily correspond to values in the brain. Under normal conditions, the serum S100B content is lower than that in the cerebrospinal fluid. Second, this might be due to the small numbers of the different subtypes.
In the current study, impairment of switching attention was significantly different between delirious patients and the control groups, but was insignificantly different among the four delirium subtypes, with more impaired switching of attention and psychomotor speed in the mixed subtype, followed by the hypoactive subtype, and then in the no subtype group, and the impairment was less in the hyperactive subtype. This was in agreement with Sylvie (2004), who assessed seven different tests of attention between delirious and nondelirious patients who undergone postoperative hip replacement surgery and found that the task of switching attention was impaired in delirious patients, and there was no significant difference between delirious and nondelirious patients in the other aspects of attention such as sustaining, sharing, or suppressing attention.
This was in contrast to O'Keefe and Gosney (2009), who reported that delirious individuals performed more poorly than nondelirious patients in tests measuring sustained and selective attention as compared with switching attention, but these differences in results may be because these patients had a more severe level of delirium compared with our patients, 56.5% of whom had a mild form of delirium.
In the present study, full recovery from delirium was 66.7% in the no subtype group, followed by 33.3% in the hyperactive group, and no patients in the mixed or the hypoactive groups achieved full recovery. This was in agreement with Leonard et al. (2011), who found that the no subtype group had less severe delirium and had better recovery than the other subtypes. This was in contrast to Camus et al. (2000), who found no significant difference in the outcome profile between clinical subtypes. Full recovery occurred more in the hyperactive group (48.4%), followed by the mixed subtype (29.2%), and then the hypoactive subtype (22%), and full recovery occurred in fewer patients in the no subtype group (0.4%).
This was in agreement with Olofsson et al. (2009), who found that the best outcome occurred in the hyperactive subtype.
In the present study, there was a significant improvement in the delirium severity, with better cognitive functions and attention at 1 month of follow-up. This was supported by Mattoo et al. (2010), who found that in most cases of delirium, reversibility of symptoms occurred within 10-12 days. This was in contrast to Wacker et al. (2006), who found that 1 month was not a sufficient time for the complete resolution of symptoms, and cognitive symptoms lasting for many years harbinger a risk for dementia. This variation in the present study was due to the fact that 54.3% of our patients had a mild degree of delirium, and our patients were young with intact premorbid cognitive functions and no comorbid physical illness or drug effect, which delay recovery from delirium or cognitive dysfunction.
In the present study, logistic regression analysis of risk factors for delirium revealed that the high level of serum S100B, the high score of DSI, the severity of cognitive impairment, the level of impairment of attention, the psychomotor speed, and the level of impairment of sustaining and switching attention increase the risk for delirium. This means that new-onset delirium has multiple risk factors. Our results were supported by Van Munster et al. (2010), who reported that cortisol, interleukin-6, and S100B may play a role in the pathogenesis of delirium, but the level of S100B is the strongest independent marker for delirium. In contrast, Peterson et al. (2006) studied 112 delirious patients for delirium risk factors and found that old age and pre-existing cognitive impairment are the only independent risk factors for delirium. Our results could be explained by the nature of our sample, which consisted of young patients without pre-existing cognitive impairment or effect of drugs.
In the present study, the logistic regression analysis of risk factors for the hypoactive subtype showed that mainly neoplasm was the only risk factor, but this was not significantly different. This was in agreement with Morita et al. (2001), who found that delirium motor subtypes related to the etiology and delirium in palliative care is predominantly the hypoactive subtype. In contrast, Camus et al. (2000) studied delirium in 183 geriatric patients and found that no difference in the etiology or the outcome between different delirium subtypes. This was explained by the motor activity profile: hypoactivity or hyperactivity is shaped by the underlying cause of delirium: for example, patients experience a direct stimulation of the brain cells, that is, intoxication or substance withdrawal of stimulants, traumatic brain injury, or stroke are more likely to exhibit autonomic disturbances that are linked to hyperactive behaviors, whereas those with sedative-hypnotic or opiate intoxication or delirium in the context of neoplasm or organ failure are likely to present with reduced activity and arousal of the hypoactive subtype (Meagher et al. , 2000; Peterson et al., 2006).
In the present study, the logistic regression model of risk factors for the hyperactive subtype showed that mainly traumatic brain injury was the only risk factor because the odd ratio was greater than 1, but this was not significantly different. This was in agreement with Olofsson et al. (2009), who found that sepsis, medications, and traumatic brain injury were common in the hyperactive subtype as against metabolic causes and hypoxia in hypoactive patients.
In contrary to our study, Camus et al. (2000) found that no difference in the etiology or the outcome between different delirium subtypes. This could be explained by the fact that our patients had no comorbidity or were young, which can affect the motor profile as confirmed by Meagher et al. (2000); Peterson et al. (2006) claimed that the relative hyperactive subtype is associated with a range of factors including less frailty, less severity of physical illness, no comorbid dementia, and young age through the interaction of inflammatory mechanisms with neurotransmission, and proinflammatory cytokines result in reduced cholinergic activity, which in turn is linked to relative hyperactivity.
| Conclusion|| |
- Widespread patterns of cognitive decline occur in different delirium subtypes.
- The level of serum S100B was significantly different between delirious patients and control groups, but not significantly different across the four delirium subtypes.
- The aspect of attention that is mostly affected is switching attention.
- The hypoactive subtype had the worst outcome after 1 month of delirium, with the highest mortality rate, poor recovery, and less cognitive function improvement.
- The degree of cognitive impairment, a high score of DSI, and the level of serum S100B were independent risk factors for delirium.
- Further researches and longitudinal studies need to be conducted on the relationship between the occurrence of delirium and the occurrence of other neurocognitive disorders, that is, is delirium a risk factor for dementia?
- The definition of delirium should be changed from acute onset and transient reversible course to acute onset and long-term sequelae.
- It is essential to identify patients at risk of delirium so that time-directed and effective intervention can identify and reduce incident delirium with subsequent improvement in the outcome.
- Follow-up with serum S100B as a biomarker for diagnosis and prognosis, and as a therapeutic factor in delirium.
| Acknowledgements|| |
Conflicts of interest
There are no conflicts of interest.
| References|| |
Aly W, Samia AR, Salma MS, Samah AB (2014). S100B and delirium in the geriatric acute care setting. Adv Age Res 1:1-5.
Bloomfield SM, McKinney J, Smith L, Brisman J (2007). Reliability of S100B in predicting severity of central nervous system injury. Neurocrit Care 6:121-138.
Brown TM, Boyle MF (2002). Delirium. BMJ 325:644-647.
Brown LJ, McGrory S, McLaren L, Starr JM, Deary IJ, Maclullich AM (2009). Cognitive visual perceptual deficits in patients with delirium. J Neurol Neurosurg Psychiatry 80:594-599.
Brown LJ, Ferner HS, Robertson J, Mills NL, Pessotto R, Deary IJ, MacLullichAM ( 2011). Differential effects of delirium on fluid and crystallized cognitive abilities. Arch Gerontol Geriatr 52:153-158.
Camus V, Gonthier R, Dubos G, Schwed P, Simeone I (2000). Etiologic and outcome profiles in hypoactive and hyperactive subtypes of delirium. J Geriatr Psychiatry Neurol 13:38-42.
Christensen KJ, Bettin KM, Jilk KM, Weldon DT, Mach JR (1994). Neuropsychological tests for monitoring delirium severity. Geri Psych 4:69-76.
Hart RP, Levenson JL, Sessler CN, Best AM, Schwartz SM, Rutherford LE (1996). Validation of a cognitive test for delirium in medical ICU patients. Psychosomatics 37:533-546.
Hend FM, Yasser EF, Rania MA, Mohamed HB ( 2014). Does delirium predict mortality among hospitalized non demented elderly? 3 months follow up study. Life Sci J 11:51-57.
Leonard M, Donnelly S, Conroy M, Trzepacz P, Meagher DJ (2011). Phenomenological and neuropsychological profile across motor variants of delirium in a palliative-care unit. J Neuropsychiatry Clin Neurosci 23:180-188.
Lins H, Wallesch CW, Wunderlich MT (2005). Sequential analyses of neurobiochemical markers of cerebral damage in cerebrospinal fluid and serum in CNS infections. Acta Neurol Scand 112:303-308.
Lipowski Z (1990). Delirium: acute confusional state. Psychosomatics 37:45-49.
Lowery DP, Wesnes K, Brewster N, Ballard C (2008). Quantifying the association between computerised measures of attention and confusion assessment method defined delirium: a prospective study of older orthopaedic surgical patients, free of dementia. Int J Geriatr Psychiatry 23:1253-1260.
Maclullich AM, Ferguson KJ, Miller T, de Rooij SE, Cunningham C (2008). Unravelling the pathophysiology of delirium: a focus on the role of aberrant stress responses. J Psychosom Res 65:229-238.
Mattoo SK, Grover S, Gupta N (2010). Delirium in general practice. Indian J Med Res 131:387-398.
Meagher D, Leonard M (2008). The active management of delirium: improving detection and treatment. Adv Psych 14:292-297.
Meagher DJ, O'Hanlon D, O'Mahony E, Casey PR, Trzepacz PT (2000). Relationship between symptoms and motoric subtype of delirium. J Neuropsychiatry Clin Neurosci 12:51-56.
Morita T, Tei Y, Tsunoda J, Inoue S, Chihara S (2001). Underlying pathologies and their associations with clinical features in terminal delirium of cancer patients. J Pain Symptom Manage 22:997-1006.
O'Keefe S, Gosney M (2009). Assessing attentiveness in older hospital patients: global assessment versus test of attention. J Am Geri Soc 45:470-473.
Olofsson SM, Weitzner MA, Valentine AD, Baile WF, Meyers CA (2009). A retrospective study of the psychiatric management and outcome of delirium in the cancer patient. Sup Care Can 4:351-357.
Peterson JF, Pun BT, Dittus RS, Thomason JW, Jackson JC, Shintani AK, Ely EW (2006). Delirium and its motoric subtypes: a study of 614 critically ill patients. J Am Geriatr Soc 54:479-484.
Silverstein JH, Timberger M, Reich DL, Uysal S (2007). Central nervous system dysfunction after noncardiac surgery and anesthesia in the elderly. Anesthesiology 106:622-628.
Simon SE, Bergmann MA, Jones RN, Murphy KM, Orav EJ, Marcantonio ER (2006). Reliability of a structured assessment for nonclinicians to detect delirium among new admissions to postacute care. J Am Med Dir Assoc 7:412-415.
SPSS (2014). Statistical package for social science computer software. Ver.22.
London, UK:SPSS Company.
Sylvie RP (2004). The attentional deficits associated with post-operative delirium in the elderly. Mol Cell Biol 23:4870-4881.
Undén J, Christensson B, Bellner J, Alling C, Romner B (2004). Serum S100B levels in patients with cerebral and extracerebral infectious disease. Scand J Infect Dis 36:10-13.
Van Munster BC, Bisschop PH, Zwinderman AH, Korevaar JC, Endert E, Wiersinga WJ, et al. (2010). Cortisol, interleukins and S100B in delirium in the elderly. Brain Cogn 74:18-23.
Wacker P, Nunes PV, Cabrita H, Forlenza OV (2006). Post-operative delirium is associated with poor cognitive outcome and dementia. Dement Geriatr Cogn Disord 21:221-227.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]