Person:

Inouye, Sharon

Objectives: Delirium, a costly, life-threatening, and potentially preventable condition, is a common complication for older adults following major surgery. Although the basic epidemiology of delirium after surgery has been defined, the contribution of delirium to long term outcomes remains uncertain, and novel biomarkers from plasma and neuroimaging have yet to be examined. This program project was designed to contribute to our understanding of the complex multifactorial syndrome of delirium. Design: Long term prospective cohort study. Setting: Three academic medical centers (2 hospitals and 1 coordinating center). Participants: Patients without recognized dementia (targeted cohort = 550 patients) age 70 and older scheduled to undergo elective major surgery are assessed at baseline before surgery, daily during their hospital stay, and for 18 to 36 months after discharge. Measurements: The Successful Aging after Elective Surgery (SAGES) study is an innovative, interdisciplinary study that includes biomarkers, neuroimaging, cognitive reserve markers, and serial neuropsychological testing to examine the contribution of delirium to long term cognitive and functional decline. The primary goal is to examine the contribution of delirium to long term cognitive and functional decline. In addition, novel risk markers for delirium are being examined, including plasma biomarkers (eg, cytokines, proteomics), advanced neuroimaging markers (eg, volumetric, white matter hyperintensity, noncontrast blood flow, and diffusion tensor measures), and cognitive reserve markers (eg, education, occupation, lifetime activities). Conclusion: Results from this study will contribute to a fuller understanding of the etiology and prognosis of delirium. Ultimately, we hope this project will provide the groundwork for future development of prevention and treatment strategies for delirium, designed to minimize the long term negative impact of delirium in older adults.

Background: The nested case-control study (NCC) design within a prospective cohort study is used when outcome data are available for all subjects, but the exposure of interest has not been collected, and is difficult or prohibitively expensive to obtain for all subjects. A NCC analysis with good matching procedures yields estimates that are as efficient and unbiased as estimates from the full cohort study. We present methodological considerations in a matched NCC design and analysis, which include the choice of match algorithms, analysis methods to evaluate the association of exposures of interest with outcomes, and consideration of overmatching. Methods: Matched, NCC design within a longitudinal observational prospective cohort study in the setting of two academic hospitals. Study participants are patients aged over 70 years who underwent scheduled major non-cardiac surgery. The primary outcome was postoperative delirium from in-hospital interviews and medical record review. The main exposure was IL-6 concentration (pg/ml) from blood sampled at three time points before delirium occurred. We used nonparametric signed ranked test to test for the median of the paired differences. We used conditional logistic regression to model the risk of IL-6 on delirium incidence. Simulation was used to generate a sample of cohort data on which unconditional multivariable logistic regression was used, and the results were compared to those of the conditional logistic regression. Partial R-square was used to assess the level of overmatching. Results: We found that the optimal match algorithm yielded more matched pairs than the greedy algorithm. The choice of analytic strategy—whether to consider measured cytokine levels as the predictor or outcome-- yielded inferences that have different clinical interpretations but similar levels of statistical significance. Estimation results from NCC design using conditional logistic regression, and from simulated cohort design using unconditional logistic regression, were similar. We found minimal evidence for overmatching. Conclusions: Using a matched NCC approach introduces methodological challenges into the study design and data analysis. Nonetheless, with careful selection of the match algorithm, match factors, and analysis methods, this design is cost effective and, for our study, yields estimates that are similar to those from a prospective cohort study design.