Publications

BACKGROUND: Intracranial volume (ICV) has been proposed as a measure of maximum lifetime brain size. Accurate ICV measures require neuroimaging which is not always feasible for epidemiologic investigations. We examined head circumference as a useful surrogate for ICV in older adults.

METHODS: 99 older adults underwent Magnetic Resonance Imaging (MRI). ICV was measured by Statistical Parametric Mapping 8 (SPM8) software or Functional MRI of the Brain Software Library (FSL) extraction with manual editing, typically considered the gold standard. Head circumferences were determined using standardized tape measurement. We examined estimated correlation coefficients between head circumference and the two MRI-based ICV measurements.

RESULTS: Head circumference and ICV by SPM8 were moderately correlated (overall r = 0.73, men r = 0.67, women r = 0.63). Head circumference and ICV by FSL were also moderately correlated (overall r = 0.69, men r = 0.63, women r = 0.49).

CONCLUSIONS: Head circumference measurement was strongly correlated with MRI-derived ICV. Our study presents a simple method to approximate ICV among older patients, which may prove useful as a surrogate for cognitive reserve in large scale epidemiologic studies of cognitive outcomes. This study also suggests the stability of head circumference correlation with ICV throughout the lifespan.

BACKGROUND: The Breast Cancer Risk Assessment Tool (BCRAT, "Gail model") is commonly used for breast cancer prediction; however, it has not been validated for women age 75 years and older.

METHODS: We used Nurses' Health Study (NHS) data beginning in 2004 and Women's Health Initiative (WHI) data beginning in 2005 to compare BCRAT's performance among women age 75 years and older with that in women age 55 to 74 years in predicting five-year breast cancer incidence. BCRAT risk factors include: age, race/ethnicity, age at menarche, age at first birth, family history, history of benign breast biopsy, and atypia. We examined BCRAT's calibration by age by comparing expected/observed (E/O) ratios of breast cancer incidence. We examined discrimination by computing c-statistics for the model by age. All statistical tests were two-sided.

RESULTS: Seventy-three thousand seventy-two NHS and 97 081 WHI women participated. NHS participants were more likely to be non-Hispanic white (96.2% vs 84.7% in WHI, P < .001) and were less likely to develop breast cancer (1.8% vs 2.0%, P = .02). E/O ratios by age in NHS were 1.16 (95% confidence interval [CI] = 1.09 to 1.23, age 57-74 years) and 1.31 (95% CI = 1.18 to 1.45, age ≥ 75 years, P = .02), and in WHI 1.03 (95% CI = 0.97 to 1.09, age 55-74 years) and 1.10 (95% CI = 1.00 to 1.21, age ≥ 75 years, P = .21). E/O ratio 95% confidence intervals crossed one among women age 75 years and older when samples were limited to women who underwent mammography and were without significant illness. C-statistics ranged between 0.56 and 0.58 in both cohorts regardless of age.

CONCLUSIONS: BCRAT accurately predicted breast cancer for women age 75 years and older who underwent mammography and were without significant illness but had modest discrimination. Models that consider individual competing risks of non-breast cancer death may improve breast cancer risk prediction for older women.

OBJECTIVES: To investigate patterns and predictors of use of antipsychotics in hospitalized adults.

DESIGN: Retrospective cohort study.

SETTING: Academic medical center.

PARTICIPANTS: Individuals aged 18 and older hospitalized from August 2012 to August 2013, excluding those admitted to obstetrics and gynecology or psychiatry or with a psychotic disorder.

MEASUREMENTS: Use was ascertained from pharmacy charges. Potentially excessive dosing was defined using guidelines for long-term care facilities. A review of 100 records was performed to determine reasons for use.

RESULTS: The cohort included 17,775 admissions with a median age 64; individuals could have been admitted more than once during the study period. Antipsychotics were used in 9%, 55% of which were initiations. The most common reasons for initiation were delirium (53%) and probable delirium (12%). Potentially excessive dosing occurred in 16% of admissions exposed to an antipsychotic. Of admissions with antipsychotic initiation, 26% were discharged on these medications. Characteristics associated with initiation included age 75 and older (relative risk (RR) = 1.4, 95% confidence interval (CI) = 1.2-1.7), male sex (RR = 1.2, 95% CI = 1.1-1.4), black race (RR = 0.8, 95% CI = 0.6-0.96), delirium (RR = 4.8, 95% CI = 4.2-5.7), dementia (RR = 2.1, 95% CI = 1.7-2.6), admission to a medical service (RR = 1.2, 95% CI = 1.1-1.4), intensive care unit stay (RR = 2.1, 95% CI = 1.8-2.4), and mechanical ventilation (RR = 2.0, 95% CI = 1.7-2.4). In individuals who were initiated on an antipsychotic, characteristics associated with discharge on antipsychotics were age 75 and older (RR = 0.6, 95% CI = 0.4-0.7), discharge to any location other than home (RR = 2.5, 95% CI = 1.8-3.3), and class of in-hospital antipsychotic exposure (RR = 1.6, 95% CI = 1.1-2.3 for atypical vs typical; RR = 2.7, 95% CI = 1.9-3.8 for both vs typical).

CONCLUSION: Antipsychotic initiation and use were common during hospitalization, most often for delirium, and individuals were frequently discharged on these medications. Several predictors of use on discharge were identified, suggesting potential targets for decision support tools that would be used to prompt consideration of ongoing necessity.

Despite the significant impact of postoperative delirium on surgical outcomes and the long-term prognosis of older patients, its neural basis has not yet been clarified. In this study we investigated the impact of premorbid brain microstructural integrity, as measured by diffusion tensor imaging before surgery, on postoperative delirium incidence and severity, as well as the relationship among presurgical cognitive performance, diffusion tensor imaging abnormalities and postoperative delirium. Presurgical diffusion tensor imaging scans of 136 older (≥70 years), dementia-free subjects from the prospective Successful Aging after Elective Surgery study were analysed blind to the clinical data and delirium status. Primary outcomes were postoperative delirium incidence and severity during the hospital stay, as assessed by the Confusion Assessment Method. We measured cognition before surgery using general cognitive performance, a composite score based on a battery of neuropsychological tests. We investigated the association between presurgical diffusion tensor imaging parameters of brain microstructural integrity (i.e. fractional anisotropy, axial, mean and radial diffusivity) with postoperative delirium incidence and severity. Analyses were adjusted for the following potential confounders: age, gender, vascular comorbidity status, and general cognitive performance. Postoperative delirium occurred in 29 of 136 subjects (21%) during hospitalization. Presurgical diffusion tensor imaging abnormalities of the cerebellum, cingulum, corpus callosum, internal capsule, thalamus, basal forebrain, occipital, parietal and temporal lobes, including the hippocampus, were associated with delirium incidence and severity, after controlling for age, gender and vascular comorbidities. After further controlling for general cognitive performance, diffusion tensor imaging abnormalities of the cerebellum, hippocampus, thalamus and basal forebrain still remained associated with delirium incidence and severity. This study raises the intriguing possibility that structural dysconnectivity involving interhemispheric and fronto-thalamo-cerebellar networks, as well as microstructural changes of structures involved in limbic and memory functions predispose to delirium under the stress of surgery. While the diffusion tensor imaging abnormalities observed in the corpus callosum, cingulum, and temporal lobe likely constitute the neural substrate for the association between premorbid cognition, as measured by general cognitive performance, and postoperative delirium, the microstructural changes observed in the cerebellum, hippocampus, thalamus and basal forebrain seem to constitute a separate phenomenon that predisposes to postsurgical delirium independent of presurgical cognitive status.

INTRODUCTION: As the relationship between delirium and long-term cognitive decline has not been well-explored, we evaluated this association in a prospective study.

METHODS: SAGES is an ongoing study involving 560 adults age 70 years or more without dementia scheduled for major surgery. Delirium was assessed daily in the postoperative period using the Confusion Assessment Method. General Cognitive Performance (GCP) and the Informant Questionnaire for Cognitive Decline in the Elderly were assessed preoperatively then repeatedly out to 36 months.

RESULTS: On average, patients with postoperative delirium had significantly lower preoperative cognitive performance, greater immediate (1 month) impairment, equivalent recovery at 2 months, and significantly greater long-term cognitive decline relative to the nondelirium group. Proxy reports corroborated the clinical significance of the long-term cognitive decline in delirious patients.

DISCUSSION: Cognitive decline after surgery is biphasic and accelerated among persons with delirium. The pace of long-term decline is similar to that seen with mild cognitive impairment.

BACKGROUND: Although antipsychotics are used for treatment of delirium/agitation in hospitalized patients, their scope of use has not been investigated in a large, multicenter cohort.

OBJECTIVE: To determine rates of use and hospital variation in use of antipsychotics in nonpsychiatric admissions.

DESIGN, SETTING, PATIENTS: Cohort study of adult, nonpsychiatric admissions to 300 US hospitals contributing data to the Premier database, from July 1, 2009 to June 30, 2010.

MEASUREMENTS: Antipsychotic exposure defined using pharmacy charges. Potentially excessive dosing defined using guidelines for long-term care facilities.

RESULTS: Our cohort included 2,695,081 admissions (median age, 63 years; 56% female). Antipsychotic exposure occurred in 160,773 (6%) admissions; 102,148 (64%) received atypical antipsychotics, 76,979 (48%) received typical, and 18,354 (11%) received both. Among exposed admissions, 47% received ≥1 potentially excessive daily dose. Among the variables we analyzed, the strongest predictors of antipsychotic receipt were delirium (relative risk [RR]: 2.93, 95% CI: 2.88-2.98) and dementia (RR: 2.78, 95% CI: 2.72-2.83). After adjustment for patient characteristics, patients admitted to hospitals in the highest antipsychotic prescribing quintile were more than twice as likely to be exposed compared to patients admitted to hospitals in the lowest prescribing quintile (RR: 2.56, 95% CI: 2.50-2.61). This relationship was similar across subgroups of admissions with delirium and dementia.

CONCLUSIONS: Antipsychotic medication exposure is common in nonpsychiatric admissions to US hospitals. The observed variation in antipsychotic prescribing was not fully explained by measured patient characteristics, suggesting the possibility of differing hospital prescribing cultures. Additional research and guidelines are necessary to define appropriate use of these potentially harmful medications in the hospital setting. Journal of Hospital Medicine 2016;11:543-549. © 2016 Society of Hospital Medicine.

OBJECTIVES: To derive and validate a method for scoring delirium severity using a recently validated, brief, structured diagnostic interview for Confusion Assessment Method (CAM)-defined delirium (3D-CAM) and to demonstrate its agreement with the CAM Severity short form (CAM-S SF) as the reference standard.

DESIGN: Derivation and validation analysis in a prospective cohort study.

SETTING: Two academic medical centers.

PARTICIPANTS: Individuals aged 70 and older enrolled in the Successful Aging after Elective Surgery Study undergoing major elective noncardiac surgery (N = 566).

MEASUREMENTS: The sample was randomly divided into a derivation dataset (n = 377) and an independent validation dataset (n = 189). These datasets were used to develop a severity scoring method using the 3D-CAM based on the four-item CAM-S SF (3D-CAM-S) and evaluate agreement between the 3D-CAM-S and the traditional CAM-S SF using weighted kappa statistics.

RESULTS: A method for scoring severity using 3D-CAM items was developed that achieved good agreement with the CAM-S SF in the derivation dataset (κ = 0.94, 95% confidence interval (CI) = 0.93-0.95). The 3D-CAM-S achieved nearly identical agreement in the independent validation dataset (κ = 0.93, 95% CI = 0.92-0.95), and 100% of 3D-CAM-S scores were within 1 point of the CAM-S SF score in both datasets. The 3D-CAM-S also strongly predicts clinical outcomes.

CONCLUSION: A newly developed method for scoring delirium severity using the 3D-CAM (the 3D-CAM-S) has excellent agreement with the CAM-S SF. This new methodology enables clinicians and researchers using the 3D-CAM for surveillance to measure delirium severity and monitor its course simultaneously by tracking changes over time. The 3D-CAM-S expands the utility of the 3D-CAM as an important tool for delirium recognition and management.

BACKGROUND: The ability to determine which episodes of delirium are likely to lead to poor clinical outcomes has remained a major area of challenge.

OBJECTIVE: To quantify delirium severity and course over an entire hospitalization using several measures, and to evaluate their predictive validity for 30- and 90-day outcomes post-discharge.

DESIGN: Two prospective cohort studies.

PARTICIPANTS: Analysis was conducted in two independent cohorts of adult patients aged ≥70.

MAIN MEASURES: Nine delirium episode severity measures were examined: (1) measures reflecting delirium intensity (peak Confusion Assessment Method-Severity [CAM-S] and mean CAM-S score), (2) a measure reflecting delirium intensity and duration (sum of all CAM-S scores, sum of all CAM-S scores on delirium days only, peak CAM-S score x days with delirium), (3) measures requiring information on delirium duration and delirium at discharge (total number of delirium days, percentage of delirium days, delirium at discharge), and (4) a measure of cognitive change. Associations of the delirium episode severity measures with 30- and 90-day post-hospital outcomes (death, nursing home placement, and readmission) relevant to delirium were examined.

KEY RESULTS: The delirium episode severity measure that required information on both delirium intensity and duration (sum of all CAM-S scores) was the most strongly associated with 30- and 90-day post-hospital outcomes. Using this measure, the relative risk [95 % confidence interval] for death at 30-days increased across levels of sum of all CAM-S scores from 1.0 (referent) to 2.1 [0.8, 5.4] for 'low,' to 2.9 [1.2, 7.1] for 'moderate,' to 6.4 [2.9, 14.0] for 'high' (p for trend <.01).

CONCLUSIONS: The delirium episode severity measure that included both intensity and duration had the strongest association with important post-hospital outcomes.

Postoperative delirium is associated with increased morbidity, mortality and cost. However, its neuropathogenesis remains largely unknown, partially owing to lack of animal model(s). We therefore set out to employ a battery of behavior tests, including natural and learned behavior, in mice to determine the effects of laparotomy under isoflurane anesthesia (Anesthesia/Surgery) on these behaviors. The mice were tested at 24 hours before and at 6, 9 and 24 hours after the Anesthesia/Surgery. Composite Z scores were calculated. Cyclosporine A, an inhibitor of mitochondria permeability transient pore, was used to determine potential mitochondria-associated mechanisms of these behavioral changes. Anesthesia/Surgery selectively impaired behaviors, including latency to eat food in buried food test, freezing time and time spent in the center in open field test, and entries and duration in the novel arm of Y maze test, with acute onset and various timecourse. The composite Z scores quantitatively demonstrated the Anesthesia/Surgery-induced behavior impairment in mice. Cyclosporine A selectively ameliorated the Anesthesia/Surgery-induced reduction in ATP levels, the increases in latency to eat food, and the decreases in entries in the novel arm. These findings suggest that we could use a battery of behavior tests to establish a mouse model to study postoperative delirium.