Studies on delirium and associated cognitive and functional decline in older surgical patients
Beishuizen, Sara
DOI:
10.33612/diss.135861414
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Publication date: 2020
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Beishuizen, S. (2020). Studies on delirium and associated cognitive and functional decline in older surgical patients: The time is now to improve perioperative care and outcomes. University of Groningen.
https://doi.org/10.33612/diss.135861414
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Chapter 3
Unraveling the relationship between delirium, brain
damage and subsequent cognitive decline in a cohort of
individuals undergoing surgery for hip fracture
Sara J. Beishuizen Rikie M. Scholtens Barbara C. van Munster Sophia E. de Rooij
ABSTRACT
Objectives: Delirium is associated with subsequent increased risk of dementia. This may reflect actual brain damage that arises during a delirious episode. Several studies suggest that the S100 calcium-binding protein B (S100B), a marker of brain damage, is elevated during delirium. We aim to assess the association between serum S100B levels, delirium and subsequent cognitive decline.
Design, Setting, Participants, Measurements: We conducted a sub study of a multi-center randomized controlled trial, including patients aged 65 years and older who were admitted for hip fracture surgery. During hospitalization, presence of delirium was assessed daily. S100B was assayed in repeated serum samples. Twelve months post-discharge cognitive decline and death rate were evaluated.
Results: We analyzed 995 samples of 385 patients, aged 65-102 years old. Premorbid cognitive impairment was present in 226 (58.7%) patients and 127 (33.0%) patients experienced peri-operative delirium. Multivariable analysis showed that older age, surgery, and presence of infection, but not of delirium, were associated with increased S100B levels. Among patients with peri-operative delirium, 58.6% experienced cognitive decline or death, and only age was a risk factor. In total, 36.5% of patients without peri-operative delirium experienced cognitive decline or death in the following year, and higher S100B, premorbid cognitive impairment and higher age were risk factors.
Conclusion: In a cohort of older hip fracture patients, we found no association between serum S100B levels and occurrence of delirium. S100B was associated with cognitive decline or death in the first year after hip fracture only in the patients without peri-operative delirium. This suggests that a minimal cognitive reserve is necessary to produce increased serum S100B levels. S100B seems to be of limited value as a biomarker of brain damage in delirium.
BACKGROUND
Delirium is a neuropsychiatric syndrome that is encountered by up to 60% of elderly hospitalized patients.1 Although the syndrome itself is considered reversible, it is independently associated
with important negative outcomes like increased risk of institutionalization, dementia and death.2
The pathophysiology of delirium is poorly understood. The higher incidence of dementia after delirium has led to the hypothesis that some patients might suffer from irreversible brain damage during a delirium episode. A possible marker of cerebral damage is the S100 calcium-binding protein B (S100B) that is mainly expressed by astrocytes and to a lesser extent by chondrocytes, adipocytes, melanocytes, skeletal myofibers and myoblasts.3 At nanomolar concentrations,
S100B exerts trophic effects on neuronal tissue, but at micromolar concentrations its effects become toxic by stimulating the expression of proinflammatory cytokines and inducing apoptosis.4 S100B levels in serum can increase either because of enhanced production in brain
tissue and subsequent passage through the blood brain barrier (BBB), or by enhanced production by extra neuronal tissue.5 S100B is currently used as a biomarker of brain damage in patients
with mild traumatic brain injury (TBI), as in this context normal serum levels can safely exclude significant intracranial complications.6
The value of S100B as a disease marker in delirium is not yet established. Elevated serum levels were found in delirious patients after hip fracture 7,8, after cardiac surgery 9, after abdominal
surgery 10 and in medical 11 and ICU-patients 12. Other authors could not demonstrate this
association in medical, ICU- and outpatients.13-15 The association between elevated S100B levels
and subsequent development of cognitive decline has not received much attention from researchers yet. However, this is a highly relevant topic as it might provide the link between delirium and its associated poor outcomes.
Our primary aim was to test whether different serum levels of S100B can be observed in patients with delirium compared to patients without delirium. Secondly we wanted to assess the association between S100B levels and long term cognitive outcome, in order to evaluate the value of S100B as a biomarker of brain damage in older patients at risk for delirium.
METHODS
Study design
We performed a sub study of a multi-center double blind randomized controlled trial that was conducted between November 2008 and May 2013 in the Netherlands. The trial, of which the protocol and results have been published previously 16,17 investigated whether prophylactic
in-hospital use of melatonin could prevent delirium after hip surgery, which could not be demonstrated. In the present sub study, the data on S100B levels, delirium and cognitive functioning are analyzed. The study was undertaken in compliance with the Helsinki Declaration and Good Clinical Practice Guidelines and approved by the Medical Ethics Committee of the Academic Medical Centre. From all patients, or a legal representative in case of a cognitive impairment, written informed consent was obtained. The trail was registered with the Dutch Clinical Trial Registry (NTR1576).
Setting and subjects
The study population consisted of patients aged 65 years or older, who were consecutively admitted for any kind of hip fracture surgery on one of the three study locations, and of whom at least one serum S100B sample was obtained during admission. The study locations were the surgical, orthopedic and trauma surgery ward of the Academic Medical Centre in Amsterdam, a 1000-bed university teaching hospital, and both locations of the Tergooi Hospitals in Hilversum and Blaricum, a 633-bed regional teaching hospital. Exclusion criteria were transfer from another hospital to the trial location, anticipated postoperative stay on intensive care or coronary care unit, and inability to speak Dutch. An experienced team of geriatric nurses conducted a follow-up visit 12 months after hospital discharge.
Clinical assessments
All patients aged 65 years or older with hip fracture were screened for eligibility and asked to participate within 24 hours of admission. At admission, we recorded demographic data, medical history and medication use. Number and severity of comorbidities was scored with the Charlson Comorbidity Index.18 We assessed functional status with the 15-item Katz Index of Activities of
Daily Living (Katz-ADL), based on the situation two weeks prior to admission.19 The
caregiver. Functional impairment was calculated as the sum of all activities with impairment. Occurrence of any type of peri-operative infection was recorded.
Cognitive assessments
The presence of delirium during admission was assessed daily, using the criteria from the
Diagnostic and Statistical Manual of Mental Disorders, IV edition (DMS-IV-R),20 by an
experienced team of geriatric nurses and geriatricians. To assess global cognitive functioning, the Mini Mental State Examination (MMSE), a validated 30-point questionnaire21, was performed on
admission, at discharge and 12 months post-discharge. The Informant Questionnaire on Cognitive Decline Short Form (IQCODE-sf) was completed by the primary caregiver on admission by comparing the situation two weeks before admission with 10 years earlier.22 At 12
months post-discharge, this questionnaire was repeated, by comparing the current situation with 10 years earlier. We defined premorbid cognitive impairment as a score of 3.4 or higher on the IQCODE-sf or a record of formally diagnosed dementia in the medical history.22 For the analysis
of the association between S100B levels during admission and subsequent cognitive decline, we introduced the combined outcome variable ‘cognitive decline or death’ during follow-up. The combined outcome variable was chosen because death can be regarded as the ultimate cognitive decline and rapid deterioration of cognitive functions is often observed in the months prior to death.23 Cognitive decline was defined as an increase in IQCODE-sf score of ≥ 1 standard
deviation (SD) (which was 0.79 in our population) between admission and 12 months post discharge and/or a decrease in MMSE score of ≥ 3 points between the highest score measured during admission and 12 months follow-up. The cut-off value of 1 SD increase in IQCODE-sf score was chosen because there is no general consensus on cut-off values for measuring decline with this questionnaire, and deterioration with 1 SD is generally considered a clinically meaningful decline in cognitive functioning. We based the cut-off value of ≥ 3 points decline in MMSE score on work of previous authors who found this value to be robust against test-retest variations and longitudinal changes in cognitively stable patients.24
S100B measurements
A maximum of four serum samples per patient was collected during hospital admission under similar conditions during weekdays. Serum was obtained by centrifugation for 15 minutes at 1780 g at 4 °C and then stored in aliquots at -80 °C. S100B levels were measured on the Modular Analytics E170 analyzer (Roche Diagnostics, Mannheim, Germany) using the
electrochemiluminescence immunoassay (ECLIA) technique. Levels below the detection limit of 0.020 µg/L were set at half the value.
Statistical analysis
Statistical Package for the Social Sciences (SPSS) version 22.0 was used for data analysis. Baseline differences between patients with and without delirium were assessed with T-test, Chi square test or Mann-Whitney U test. To assess the association between delirium and the repeated S100B measurements, we performed a linear mixed model with S100B level as outcome variable. To fulfill the assumption of normality, the natural logarithm of the S100B values (LnS100B) was calculated. We categorized serum samples according to the ‘delirious state’ on the day the serum sample was obtained: ‘before delirium’, ‘during delirium’ and ‘after delirium’ in delirious patients, and ‘never’ in non-delirious patients. Patient number was taken as a random affect, time and delirious state as fixed effects, and age, premorbid cognitive impairment, surgery and post-operative infection as covariates. We selected the best fitting model based on the Akaike’s Information Criterion and by inspection of the distribution of the residuals.
Next, we performed a logistic regression using generalized estimating equations with the combined outcome variable cognitive decline/death as dependent variable and the repeated LnS100B measurements as independent variable. Age, baseline functional status, premorbid cognitive impairment, delirium and peri-operative infection were added as covariates to the model. In a backward selection, variables with a p-value above 0.05 were discarded from the logistic model. Additionally, an analysis stratified for delirium was performed.
RESULTS
Patient recruitment and baseline data
A total of 850 patients was assessed for eligibility. Three hundred fifteen patients declined to participate, 115 did not meet inclusion criteria and of 35 patients no serum samples could be obtained. This resulted in 385 patients, providing 995 serum samples, who were eligible to participate in the analysis of the association between delirium and S100B levels. For the analysis of cognitive decline 55 patients with insufficient data on follow-up cognitive tests were
excluded. Three hundred and thirty patients who both survived and had cognitive tests at 12 months post discharge (n=217) or died (n=113) within this period were included. (Figure 1) The baseline characteristics of the 385 included patients are described in table 1, subdivided by delirium status. Patients with peri-operative delirium (127/385, 33%) were older, had more comorbidities, higher levels of functional impairment and were less often living at home. Premorbid cognitive impairment was present in 103/127 (81.1%) patients with delirium, compared to 129/258 (50.0%) patients without delirium (p<0.001). Post-operative S100B levels did not differ between delirious (median 0.09 µg/L, inter quartile range (IQR) 0.06-0.14 µg/L) and non-delirious patients (median 0.09 µg/L, IQR 0.06-0.13 µg/L, p=0.395).
Figure 1. Enrollment and follow up of patients
Assessed for eligibility
n=850
Excluded n=465
- did not meet inclusion criteria n=115 - declined to participate n= 315 - no serum sample obtained n=35 Participated in
delirium-S100B analysis
n=385
Excluded n=55
- declined further participation n= 34 - lost to follow up n= 10 - incapable n= 11 Participated in S100B-cognitive outcome analysis n=330
Table 1. Baseline characteristics of included patients
Variable Delirium (n=127) No delirium (n=258) p-value
Mean age (SD) 86.7 (6.5) 82.6 (7.8) <0.001
Sex, male (%) 41 (32.3) 70 (27.1) 0.34
Living at home (%) 55 (43.3) 181 (70.2) <0.001
IQCODE-sf (IQR) 4.6 (3.6, 5.0) 3.5 (3.0, 4.6) <0.001
Premorbid cognitive impairment (%) 103 (81.1) 129 (50.0) <0.001
CCI, median (IQR) 2 (1, 2) 1 (0, 2) 0.01
Katz ADL, median (IQR) 8 (5, 13) 4 (1, 9) <0.001
missing data 6 6
MMSE admission, median (IQR) 17 (10.0, 22.8) 25.1 (21.1, 28.0) <0.001
missing data 32 38 S100B mcg/L, median (IQR)* missing data 0.09 (0.06, 0,14) 4 0.09 (0.06, 0.13) 1 0.39 SD= standard deviation, IQCODE-sf= Informant Questionnair on Cognitive Decline in the Eldery – short form, IQR= inter quartile range, CCI= Charlson Comorbidity Index, ADL= Activities of Daily Living *first post-operative measurement
Association between delirium and S100B levels
The model with a random intercept for each patient yielded the best fit, a random slope for each patients did not result in improvement. The final model, adjusted for age, prior cognitive impairment, surgery and infection, showed that S100B values did not differ between delirious and non-delirious patients (p=0.670). Factors that were significantly associated with increased S100B levels were sampling time with regard to surgery (before or after surgery)(p<0.001), presence of infection (p=0.03) and older age (p=0.01).
S100B levels during admission and subsequent cognitive decline or death
At 12 months post-discharge, 185 patients remained cognitively stable, 32 experienced cognitive decline and 113 patients died in the follow-up period. The 55 patients who were excluded from this analysis were similar to the included patients (table 2). Of the patients with peri-operative delirium, 58.6% (65/111) experienced either cognitive decline or died during follow-up, versus 36.5% (80/219) of patients without peri-operative delirium (χ2 = 14.5, p<0.001). Patients who
comorbidities, more often had premorbid cognitive and functional impairment on admission than patients who did not show cognitive decline. During admission, the former group more often experienced delirium and had higher post-operative S100B values than the latter group (table 2). The highest post-operative S100B values were found in the patients without premorbid cognitive impairment who experienced cognitive decline or death (median 0.12 µg/L, IQR 0.09, 0.13 µg/L) as compared to patients with both premorbid cognitive impairment and the combined endpoint (median 0.10 µg/L, IQR 0.06, 0.14 µg/L), patients with only premorbid cognitive impairment (median 0.08 µg/L, IQR 0.05, 0.12 µg/L) or patients with neither premorbid impairment nor decline or death (median 0.08 µg/L, IQR 0.05, 0.12 µg/L) (p=0.01).
Table 2. Baseline characteristics of patients with and without cognitive decline/death during
follow-up and patients that were excluded from follow-follow-up analyses
Variable Cognitive decline or deceased (n=145) Not declined (185) Excluded (55) p-value** Mean age (SD) 87.0 (7.8) 82.1 (6.3) 82.4 (7.6) <0.001 Sex, male (%) 43 (29.7) 54 (29.3) 14 (25.5) 0.95 Living at home (%) 67 (46.2) 135 (73.0) 34 (61.8) <0.001 Premorbid cognitive impairment (%) 112 (77.2) 89 (48.1) 31 (56.4) <0.001
CCI, median (IQR) 2 (1, 3) 1 (0, 2) 1 (0, 2) 0.01
Katz ADL, median (IQR) 8 (4, 12) 4 (1, 8) 5 (1, 9.5) <0.001
missing data 4 0 2
MMSE admission, median (IQR) 20.0 (13.0, 24.0) 26.0 (20.4, 28.0) 22.8 (14.0, 27.8) <0.001 missing data 38 25 7 Peri-operative delirium (%) 65 (44.8) 46 (24.9) 16 (29.9) <0.001 Median S100B mcg/L (IQR)* missing data 0.10 (0.07, 0.14) 9 0.08 (0.05, 0.12) 7 0.09 (0.06, 0.14) 0 0.02
SD= standard deviation, CCI= Charlson Comorbidity Index, ADL= Activities of Daily Living, IQR= inter quartile range, *first post-operative measurement, **tested with One way-ANOVA or Kruskal Wallis (as appropriate)
In the multivariate analysis, corrected for age, premorbid cognitive and functional impairment, perioperative delirium and LnS100B, only higher age was associated with increased odds of cognitive decline or death (OR 1.07, 95% Confidence Interval (CI) 1.03, 1.11, p<0.001) (table 3). However, when the analysis was stratified for peri-operative delirium, both LnS100B (OR 1.56, 95% CI 1.20, 2.03, p=0.001), premorbid cognitive impairment (OR 2.26 (95% CI 1.04, 4.90, p=0.04) and higher age (OR 1.07, 95% CI 1.02, 1.12, p=0.005) were associated with the combined outcome in patients without peri-operative delirium. In patients with peri-operative delirium, only age (OR 1.10, 95% CI 1.03, 1.18, p=0.008) remained associated with cognitive decline or death (table 4).
Table 3. Odds Ratio’s for outcome decline/deceased
Factor Univariable analysis* p-value Multivariable analysis* p-value
Age 1.10 (1.07, 1.14) <0.001 1.07 (1.03, 1.11) <0.001 Premorbid cognitive impairment 3.48 (2.15, 5.63) <0.001 1.63 (0.86, 3.09) 0.13 Premorbid Katz-ADL 1.14 (1.08, 1.19) <0.001 1.05 (0.98, 1.12) 0.15 Peri-operative delirium 2.36 (1.48, 3.76) <0.001 1.49 (0.87, 2.58) 0.15 Peri-operative infection 1.50 (0.88, 2.56) 0.14 LnS100B 1.30 (1.07, 1.59) 0.009 1.20 (0.98, 1.47) 0.08
*Odds ratio (95% confidence interval), ADL= Activities of Daily Living
Table 4. Odds Ratio’s for outcome decline/deceased, stratified for peri-operative delirium
Factor Delirium absent Multivariable analysis*
p-value Delirium present Multivariable analysis* p-value Age 1.07 (1.02, 1.12) 0.005 1.10 (1.03, 1.11) 0.008 Premorbid cognitive impairment 2.26 (1.04, 4.90) 0.04 0.63 (0.18, 2.12) 0.45 Premorbid Katz-ADL 1.07 (0.99, 1.17) 0.11 1.01 (0.91, 1.11) 0.93 LnS100B 1.56 (1.20, 2.03) 0.001 0.82 (0.61, 1.10) 0.18
DISCUSSION
In this study of 385 older hip fracture patients we found no association between peri-operative S100B levels and delirium. In patients without peri-operative delirium, of whom 36.5% experienced cognitive decline or death in the following year, higher S100B values were associated with increased odds of this outcome. For patients with peri-operative delirium there was no association between S100B and cognitive decline or death. These results suggest that a minimal cognitive reserve is necessary in order to produce increased serum S100B levels, and that S100B is of limited value as a biomarker of brain damage in patients with delirium
The association between S100B levels and delirium is by no means established. In a previous cohort study from our group of older hip fracture patients with a study design similar to the current cohort, higher serum S100B levels were found in delirious patients as compared to non-delirious patients.7,8 A possible explanation for the fact that we could not replicate these findings
is that our cohort was composed of relatively older patients with a higher rate of premorbid cognitive impairment (60% in the current cohort vs 41% in our previous studies7,8,11). These are
both factors that can contribute to higher baseline S100B levels, which might explain why the difference between patients with and without delirium was less clear in our cohort.3 Another
explanation might lie in the fact that serum S100B is not specific enough to cerebral origin, because extra-neuronal sources can also contribute to elevated S100B levels. In a population of vulnerable older patients with a high burden of medical and surgical problems these factors can be difficult to disentangle. Indeed several other authors have also failed to find an association between delirium and S100B levels in their cohorts of geriatric medical and intensive care unit patients.13-15
To our knowledge this is the first study that has assessed the relation between S100B levels after hip fracture, delirium and long term cognitive outcome. There are some smaller studies in ICU 25
and elective surgery 26-28 patients that have addressed the association between S100B levels and
long term cognitive outcomes. Unfortunately in these studies delirium assessment was not performed at baseline 26,28, or not incorporated in the analysis of cognitive outcomes. 25,27
Plaschke reported that S100B had an increased OR of 1.001 (95% CI 1.000-1.001) for cognitive decline in 117 patients 3 months after elective cardiac surgery. 27 The other studies found no
death in the first year after hip fracture in the patients that had not suffered from peri-operative delirium, but that it could not predict this outcome for delirious patients. There are several explanations for the absence of an association between S100B and cognitive decline or death in delirious patients. Firstly, a certain level of cognitive functioning is necessary to be able to measure a decline over time. Most patients with peri-operative delirium already had (severe) premorbid cognitive impairment and therefore we were not able to measure any further decline on the cognitive tests uses in this study during follow-up. A second possible explanation is that enough brain tissue needs to be preserved to be able to shed S100B from astrocytes that are damaged. This hypothesis is supported by the work of Peskind and colleagues 27 who found that
S100B levels in cerebrospinal fluid (CSF) of non-delirious patients were higher in mild to moderate Alzheimer’s disease (AD) as compared to advanced AD and healthy age matched controls.29 The difference between mild to moderate versus advanced AD could be explained by
the fact that patients with advanced AD have less brain tissue ‘to lose’. Further research on this highly interesting hypothesis is needed.
It is intriguing that 36.5% of patients without peri-operative delirium experienced cognitive decline or death following surgery, given that they were relatively the youngest, and also the most physically and mentally healthy patients in our cohort. Most research in the field of hip fracture and associated cognitive decline has focused on delirium as an intermediate, so little is known about risk factors for cognitive decline in the absence of delirium. The association with higher S100B levels implicates that brain damage in the peri-operative period might be the underlying mechanism. Causes for brain damage could be surgery related, for example due to fat emboli arising from the bone marrow or the release of inflammatory mediators.30 Other factors,
not directly related to surgery, have been less studied.
There are some limitations to this study worth mentioning. First of all there is no consensus on how cognitive decline over time should be defined and measured. We have used two screening scales in our definition that are widely used and implemented in clinical practice. However, the IQCODE-sf is not specifically validated for repetitive use over time, and we noticed that it was difficult to detect further decline in patients who already had an almost maximal score on the IQCODE-sf on admission. Consensus is needed on how cognitive decline can best be measured in this vulnerable group. We based cut-off points on the available evidence (MMSE)24 and on
constructing a combined outcome (cognitive decline or death) we have tried to increase the generalizability of our results. The population of hip fracture patients consists of old and fragile patients, and excluding patients who die within one year after hip fracture would mean excluding one third of our population. A second limitation is that we only measured S100B in serum. S100B measured in CSF is presumably more specific to cerebral pathology, so having additional CSF samples would have strengthened our findings. Due to practical and ethical reasons this was not feasible.
A strength of our study is that we were able to include a relatively large number of patients that are representative for a true hip fracture population. We have shown (in table 2) that excluding 55 patients because of insufficient follow-up data did not introduce selection bias into our analysis. A second strength is that we had several serum samples per patient available, which enabled us to relate the timing of delirium onset to the S100B level on that day. By also including cognitive follow-up assessments in our analysis we have provided new information on the value of S100B as a biomarker of brain damage in a vulnerable patient population at risk for delirium and subsequent cognitive decline. Although this study was designed as a RCT in which half of the patients received melatonin 3mg ante noctem during admission, we feel that this did not influence our results as no effect of melatonin was found on delirium incidence or severity. Our findings have implications for clinical practice and future research. It appears that S100B cannot be used as a marker of brain damage specifically associated with delirium, and therefore S100B measurement will not be easily integrated in the standard diagnostic procedures in delirious patients. S100B might be more valuable in patients who are at risk of cognitive deterioration but still have some cognitive reserve, that is in patients who are not already severely cognitive impaired at baseline. We have shown that a substantial proportion of these patients also experience either cognitive decline or death after hip fracture even if they ended up not having peri-operative delirium. Currently researchers are bypassing these patients by heavily focusing on delirium as a mediator of cognitive decline. Further studying the mechanisms of cognitive decline in this group could possibly lead to the identification of new targets for prevention strategies.
CONCLUSION
In this study of older hip fracture patients we found no association between peri-operative S100B levels and delirium. S100B levels were associated with higher odds of cognitive decline or death in the first year after hip fracture in patients who did not experienced delirium in the peri-operative period. For delirious patients this association was absent. This could suggest that a minimal cognitive reserve is necessary in order to produce significant increased serum S100B levels. S100B seems to be of limited value as a biomarker of brain damage during delirium. Future studies should focus on the value of S100B as a biomarker of brain damage in patients who still have some cognitive reserve and on mechanisms of cognitive decline after hip fracture in the absence of delirium.
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