Older Patients with Alzheimer’s Disease-Related Cortical Atrophy Who Develop Post-Operative Delirium May Be at Increased Risk of Long-Term Cognitive Decline After Surgery

INTRODUCTION

Patients with dementia due to Alzheimer’s disease (AD) who develop delirium are at increased risk for poor post-operative outcomes, including accelerated cognitive decline [1, 2]. Increasing evidence suggests that an interrelationship between delirium and AD occurs even before the onset of dementia [1, 3–5]. The associations between delirium and preclinical or prodromal AD, and implications for cognitive function following surgery, are still being investigated.

Preclinical AD refers to the stage of the disease where pathological changes are present prior to the onset of cognitive or functional impairment; therefore, biomarkers sensitive to early preclinical changes are required for probing this phase of the disease. The AD signature, a specific set of brain regions that show reduction of cortical thickness due to AD, has previously been shown to be associated with cognitive decline and progression to dementia [6–11], as well as with cerebrospinal fluid (CSF) biomarkers of AD [9]. Thus, the AD signature is a good surrogate marker for preclinical AD in the absence of available molecular markers for amyloid-β (Aβ) and tau, and provides a window into associations between delirium and preclinical AD. Indeed, we have previously shown that patients with thinner cortex in the AD-signature experience delirium with greater severity [3]. This study uses this magnetic resonance imaging (MRI)-based AD biomarker to investigate associations between a preclinical AD risk marker, delirium, and long-term cognitive decline following surgery.

We hypothesized that patients with the thinnest cortex in the AD-signature regions, suggestive of preclinical AD, would have the steepest rates of cognitive decline after surgery. We additionally hypothesized that development of delirium would hasten such decline, such that patients with the most AD-related atrophy and delirium would have the fastest rates of post-operative cognitive decline. To determine if our findings were AD-specific, we also examined associations with the ‘Aging-Only signature,’ which is another set of regions of interest (ROIs) that is associated with reduction of cortical thickness due to aging but is relatively spared in AD [10].

MATERIALS AND METHODS

RESULTS

Of the 140 SAGES participants with MRIs and at least six months of cognitive follow-up (mean age 76.1 years, 61% women), thirty participants (21%) developed delirium. Other baseline characteristics are described in Table 1. Sample characteristics by the six AD signature tertile/delirium groups are also available in Supplementary Table 3 and baseline test scores are reported in Supplementary Table 4. Covariate model coefficients for standardized cognitive outcomes (z-scores) are reported in Supplementary Table 6.

To facilitate comparison across models, the following results are presented using standardized beta coefficients (β), which refer to the standard deviation change in cognitive score (or slope) per standard deviation increase in AD signature. Because we reverse-scored the AD signature, a negative β indicates that greater atrophy is associated with worse cognitive performance.

Although effect sizes were estimated using cortical signature tertiles, statistical inference was based on analysis of the cortical signatures as continuous variables. Therefore, graphical representations of our models (Figs. 1 and 2) visually depict the model estimates from the analyses of the cortical signatures as continuous variables, but are displayed using categorical groups (i.e., tertiles) for descriptive purposes only. Below, effect sizes (Cohen’s d) are reported from the effect size analysis utilizing tertiles and β-coefficients with 95% confidence intervals are reported from the analysis of the cortical signature as a continuous variable.

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Fig.1

Group effects of cortical atrophy due to AD (A) or aging (B) and post-operative delirium on short- and long-term change in general cognitive performance after surgery. The cortical signatures were analyzed as continuous variables, but for illustration purposes, results are displayed by groups based on cortical signature tertiles (tertile 1 has the thickest cortex, tertile 3 has the thinnest cortex, interpreted as the greatest atrophy) and delirium (present [+] or absent [−]). Tertiles are generated separately for AD signature and for Aging-Only signature measures, leading to slight differences in group size. Estimated slopes are reported based on model coefficients and average cortical thickness in the respective tertile.

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Fig.2

Group effects of cortical atrophy due to AD and post-operative delirium on short- and long-term change on selected individual neuropsychological tests. The cortical signatures were analyzed as continuous variables, but for illustration purposes, results are displayed by groups based on cortical signature tertiles (see Fig. 1 for details) and delirium (present [+] or absent [−]). Estimated slopes are reported based on model coefficients and average cortical thickness in the respective tertile. A) HVLT, Hopkins Verbal Learning Test – Revised total score. B) Trails B, Trail Making Test B (reverse-scored so that lower numbers indicate worse performance). Neuropsychological tests were transformed into z-scores before being entered into the models.

DISCUSSION

AD signature cortical atrophy and delirium have previously been shown to independently predict cognitive decline and progression to dementia in people who at baseline are cognitively normal or have mild cognitive impairment [1, 21]. This study builds on this prior work by showing that greater baseline AD signature atrophy—an MRI biomarker probabilistically associated with AD-related neurodegeneration [9, 11]—was associated with greater long-term cognitive decline following surgery over the ensuing 3 years. We also found evidence that delirium and AD signature atrophy interact to influence the post-operative cognitive trajectory. Specifically, declining performance in HVLT, a test of learning and memory, was accelerated in patients with greater AD signature atrophy who also developed delirium. These results indicate that older adults with a cortical signature suggestive of preclinical AD who develop delirium during hospitalization for elective surgery may be at higher risk for long-term post-operative cognitive decline. However, these findings are largely hypothesis-generating, and future studies with larger sample sizes are needed in order to make stronger conclusions.

Although the effect size for the interaction of AD signature and delirium on GCP slope was large when examined using group comparisons (Table 3 and Fig. 1A), it was not statistically significant in an LME model. By examining two of the most sensitive tests to early AD cognitive changes [23], HVLT-R and Trails B, we were able to gain insight into this apparent discrepancy. For the HVLT-R total learning score, we found consistent effects using both group comparison analyses and the LME model. That is, participants with the greatest baseline AD-signature atrophy who developed delirium showed consistent long-term decline on this measure with a very large Cohen’s d effect size. The HVLT-R is a commonly used clinical neuropsychological test of verbal learning and episodic memory. Our results are consistent with prior studies showing that list learning scores are predictive of dementia [23, 24], decline in preclinical AD [25, 26], and are associated with atrophy in regions that are vulnerable to AD-related neurodegeneration [27] and that are captured by AD-signature ROIs. Interestingly, we observed an association of steeper slopes on HVLT delayed recall with delirium, but not with the AD signature as we would have expected. For Trails B, the AD signature—but neither delirium nor the interaction of delirium and the AD signature—was associated with steeper slopes of decline. These findings suggest domain-specific interactions between AD and delirium, which may not always be captured by global neuropsychological composite scores. However, there are also limitations to using individual tests, including potential floor and ceiling effects, or differing sensitivity to practice effects. Indeed, despite adjusting for retest effects, marginal gains were observed over time on the HVLT-R total learning score (but not on Trails B or GCP) in the lowest risk patients (those without delirium and those with delirium but who had the least AD signature atrophy; Fig. 2A). These observations point to the value of examining both general cognitive scores like the GCP, as well as individual tests or domain-specific tests or composites.

Lower baseline cognitive performance was consistently associated with higher risk of delirium across most of our models. Low cognitive ability is a known risk factor for delirium, and in fact has previously been shown to dominate risk in the SAGES cohort [19]. The one exception in the current study was that worse pre-operative performance on Trails B was not a statistically significant predictor of delirium. Although this could be a consequence of the small sample size, it could also indicate some cognitive specificity in terms of delirium risk. Future studies may wish to further examine this finding and its implications for delirium prediction.

Unlike the AD signature, the Aging-Only signature was not associated with cognitive outcomes and did not interact with delirium. This observation supports the specificity of our findings to likely AD-related neurodegeneration, rather than reflecting an effect that is more diffuse due to global aging effects or pathological processes not due to AD. Thus, the previously reported observation in SAGES that lower baseline performance on certain neuropsychological tests—including HVLT-R total learning and Trails B—is associated with increased risk of delirium [28] is possibly referable to preclinical AD-related neurodegeneration of brain networks subserving learning/memory and executive function, rather than advanced brain aging, in at least a subset of individuals. However, AD-related and aging-related neurodegeneration are not mutually exclusive, and patients may experience both to varying degrees simultaneously. The unique and overlapping contributions of these two brain signatures to cognitive decline is an important area for continued investigation.

Our results align with previous work showing that delirium and neurodegenerative pathologies are independently and synergistically associated with cognitive decline [29], and highlight the need to further investigate the pathophysiologic mechanisms of these complex interactions. Neuroinflammation is the predominant theoretical pathophysiological basis of postoperative delirium and related post-operative cognitive decline [30–33]. There is also extensive evidence that neuroinflammation is involved in AD [34, 35] and that neuroinflammation and AD pathology may interact to accelerate disease worsening [35–38]. Since delirium may be seen as the end result of neuroinflammation, our findings are consistent with the notion that AD pathology and neuroinflammation interact to accelerate cognitive decline. Because the pathophysiology of delirium is still being investigated, it is also possible that the present results are due to interactions between AD pathology and other mechanisms involved in the pathogenesis of delirium, including oxidative stress, neurotransmitter deficiency, blood-brain barrier dysfunction, and network disconnectivity, among others [31, 32]. This is an important area for continued research.

This study has several limitations. Although SAGES is one of the largest cohort studies of its kind including detailed pre-operative MRI and cognitive assessment with long-term follow-up, the sample for this study was relatively small since it was limited to only those with both pre-operative MRI and at least six months of cognitive follow-up. Thus, this study was likely underpowered to detect some effects, which is further supported by the lack of statistical significance despite large effect sizes. Statistical inference was based on the mixed effects models which analyzed the cortical signatures as continuous variables; in contrast, the effect size analysis utilized tertiles, which further exacerbated concerns about small sample sizes. We used the tertile approach since the use of ordered categories is a commonly selected methodology in clinical research, which helps to enhance clinical relevance and interpretability. However, due to the small sample size, the effect is estimated with low precision and we cannot rule out chance as a possible explanation for the observed effects. Practice/retest effects are a known challenge in longitudinal cognitive research; although we attempted to control for these effects using a non-surgical cohort, which is a robust, recommended approach [39] and one which we have specifically validated in this cohort [22], we acknowledge that there is no perfect method. To further probe the possible influence of retest correction on our interpretations, we performed a supplementary analysis using retest-uncorrected cognitive scores (Supplementary Figure 3; Supplementary Table 7); although absolute scores showed increases at months 1 and 2 (as expected) the cognitive slopes were identical and the relationships between the cortical signatures and/or delirium at other timepoints were minimally affected. Additionally, we attempted to control for relevant confounding without overfitting. To further probe potential confounding, we performed a sensitivity analysis testing the effect of three health-related variables (vascular comorbidity, medical comorbidity, and depression) as additional covariates; they did not notably change the results (Supplementary Table 8). While the AD signature has been shown to be associated with preclinical AD, molecular markers of amyloid or tau were not collected in SAGES, so the AD signature can only be considered as a probabilistic marker. Finally, generalizability may be limited, since SAGES is largely a white and well-educated sample of adults undergoing select surgical procedures. Indeed, future studies are needed to investigate other populations including but not limited to adults hospitalized for reasons other than surgery (or different surgeries than those studied herein) and adults who develop delirium unrelated to hospitalization or surgery. It will also be important to study these various populations across different geographical, racial, and socioeconomic contexts.

In conclusion, we found that AD-related cortical atrophy was associated with cognitive decline after surgery. Our results also suggest that development of post-operative delirium may further accelerate this decline. However, this latter finding was not statistically significant, and thus must be interpreted with caution as only preliminary evidence for an early association between AD, delirium, and post-operative cognitive decline during the preclinical/prodromal timeframe. Future studies with larger sample sizes are needed to further probe this possible, but as yet unsubstantiated, interaction.

As additional follow-up is collected in the SAGES cohort, we intend to investigate longitudinally measured atrophy as well as progression to mild cognitive impairment and/or dementia, which will provide greater insights into the clinical applicability of these findings. It will be important to replicate the results of the current study and to determine if they generalize to other populations and other causes of delirium outside of the setting of elective surgery. If they do, then it will also be important to consider optimal methods to risk-stratify patients undergoing elective surgery for expensive or invasive pre-operative assessments, such as MRI, and for intensive post-operative monitoring and brain health programs aiming to slow or prevent long-term cognitive decline.