Person:

Travison, Thomas

Cluster-randomized clinical trials (CRT) are trials in which the unit of randomization is not a participant but a group (e.g. healthcare systems or community centers). They are suitable when the intervention applies naturally to the cluster (e.g. healthcare policy); when lack of independence among participants may occur (e.g. nursing home hygiene); or when it is most ethical to apply an intervention to all within a group (e.g. school-level immunization). Because participants in the same cluster receive the same intervention, CRT may approximate clinical practice, and may produce generalizable findings. However, when not properly designed or interpreted, CRT may induce biased results. CRT designs have features that add complexity to statistical estimation and inference. Chief among these is the cluster-level correlation in response measurements induced by the randomization. A critical consideration is the experimental unit of inference; often it is desirable to consider intervention effects at the level of the individual rather than the cluster. Finally, given that the number of clusters available may be limited, simple forms of randomization may not achieve balance between intervention and control arms at either the cluster- or participant-level. In non-clustered clinical trials, balance of key factors may be easier to achieve because the sample can be homogenous by exclusion of participants with multiple chronic conditions (MCC). CRTs, which are often pragmatic, may eschew such restrictions. Failure to account for imbalance may induce bias and reducing validity. This article focuses on the complexities of randomization in the design of CRTs, such as the inclusion of patients with MCC, and imbalances in covariate factors across clusters.

Background: Falls may occur as unpredictable events or in patterns indicative of potentially modifiable risks and predictive of adverse outcomes. Knowing the patterns, risks, and outcomes of falls trajectories may help clinicians plan appropriate preventive measures. We hypothesized that clinically distinct trajectories of falls progression, baseline predictors and their coincident clinical outcomes could be identified. Methods: We studied 765 community-dwelling participants in the MOBILIZE Boston Study, who were aged 70 and older and followed prospectively for falls over 5 years. Baseline demographic and clinical data were collected by questionnaire and a comprehensive clinic examination. Falls, injuries, and hospitalizations were recorded prospectively on daily calendars. Group-Based Trajectory Modeling (GBTM) was used to identify trajectories. Results: We identified 4 distinct trajectories: No Falls (30.1%), Cluster Falls (46.1%), Increasing Falls (5.8%) and Chronic Recurring Falls (18.0%). Predictors of Cluster Falls were faster gait speed (OR 1.69 (95CI, 1.50–2.56)) and fall in the past year (OR 3.52 (95CI, 2.16–6.34)). Predictors of Increasing Falls were Diabetes Mellitus (OR 4.3 (95CI, 1.4–13.3)) and Cognitive Impairment (OR 2.82 (95CI, 1.34–5.82)). Predictors of Chronic Recurring Falls were multi-morbidity (OR 2.24 (95CI, 1.60–3.16)) and fall in the past year (OR 3.82 (95CI, 2.34–6.23)). Symptoms of depression were predictive of all falls trajectories. In the Chronic Recurring Falls trajectory group the incidence rate of Hospital visits was 121 (95% CI 63–169) per 1,000 person-years; Injurious falls 172 (95% CI 111–237) per 1,000 person-years and Fractures 41 (95% CI 9–78) per 1,000 person-years. Conclusions: Falls may occur in clusters over discrete intervals in time, or as chronically increasing or recurring events that have a relatively greater risk of adverse outcomes. Patients with multiple falls, multimorbidity, and depressive symptoms should be targeted for preventive measures.

Background: Circulating vascular adhesion molecule-1 (sVCAM-1) is a presumed marker of endothelial activation and dysfunction, but little is known about its association with mood. We hypothesized that elevated plasma concentrations of sVCAM-1 may be a marker of depressive symptoms due to cerebral vascular disease. Methods: We studied 680 community-dwelling participants in the MOBILIZE Boston Study, aged 65 years and older. sICAM-1 and sVCAM-1 were measured by ELISA assay and depressive symptoms were assessed during home interviews using the Revised Center for Epidemiological Studies Depression Scale (CESD-R). Cerebral White Matter Hyperintensities (WMHs) were quantified by MRI in a subgroup of 25 participants. Results: One hundred seventy nine (27 %) subjects had a CESD-R Score ≥ 16, indicative of depressive symptoms. The mean sVCAM-1 concentration (±SD) was 1176 ± 417 ng/mL in a group with CESD-R Scores <16 and 1239 ± 451 ng/mL in those with CESD-R Scores ≥16 (p = 0.036). CESD-R Score was positively associated with sVCAM-1 (r = 0.11, p = 0.004). The highest quintile of sVCAM-1, which is indicative of endothelial dysfunction, was significantly associated with depressive symptoms compared to the lowest quintile (OR = 1.97 (1.14-3.57) p = 0.015). In a subset of subjects, sVCAM-1 concentration was positively correlated with cerebral WMHs volume (p = 0.018). Conclusions: The association between high levels of sVCAM-1 and depressive symptoms may be due to endothelial dysfunction from cerebral microvascular damage. Future longitudinal studies are needed to determine whether sVCAM-1 can serve as a biomarker for cerebrovascular causes of depression.

Background/Objectives

Delirium is the most common complication of major elective surgery in older patients. The Successful Aging after Elective Surgery (SAGES) study was designed to examine novel risk factors and long-term outcomes associated with delirium. This report describes the cohort, quality assurance procedures, and results. Design

Long-term prospective cohort study. Setting

Three academic medical centers. Participants

A total of 566 patients age 70 and older without recognized dementia scheduled for elective major surgery. Measurements

Participants were assessed preoperatively, daily during hospitalization, and at variable monthly intervals for up to 36 months post-discharge. Delirium was assessed in hospital by trained study staff. Study outcomes included cognitive and physical function. Novel risk factors for delirium were assessed including genetic and plasma biomarkers, neuroimaging markers, and cognitive reserve markers. Interrater reliability (kappa and weighted kappa) was assessed for key variables in 119 of the patient interviews. Results

Participants were an average of 77 years old and 58% were female. The majority of patients (81%) were undergoing orthopedic surgery and 24% developed delirium post-operatively. Over 95% of eligible patients were followed for 18 months. There was >99% capture of key study outcomes (cognitive and functional status) at every study interview and interrater reliability was high (weighted kappas for delirium = 0.92 and for overall cognitive and functional outcomes = 0.94 -1.0). Completion rates for plasma biomarkers (4 timepoints) were 95%-99% and for neuroimaging (one year follow-up) was 86%. Conclusion

The SAGES study will contribute to the understanding of novel risk factors, pathophysiology and long-term outcomes of delirium. This manuscript describes the cohort and data quality procedures, and will serve as a reference source for future studies based on SAGES.

Because of its anabolic effects on muscle, testosterone is being explored as a function-promoting anabolic therapy for functional limitations associated with aging; however, concerns about testosterone’s adverse effects on prostate have inspired efforts to develop strategies that selectively increase muscle mass while sparing the prostate. Testosterone’s promyogenic effects are mediated through upregulation of follistatin. We show here that the administration of recombinant follistatin (rFst) increased muscle mass in mice, but had no effect on prostate mass. Consistent with the results of rFst administration, follistatin transgenic mice with constitutively elevated follistatin levels displayed greater muscle mass than controls, but had similar prostate weights. To elucidate signaling pathways regulated differentially by testosterone and rFst in prostate and muscle, we performed microarray analysis of mRNAs from prostate and levator ani of castrated male mice treated with vehicle, testosterone, or rFst. Testosterone and rFst shared the regulation of many transcripts in levator ani; however, in prostate, 593 transcripts in several growth-promoting pathways were differentially expressed after testosterone treatment, while rFst showed a negligible effect with only 9 transcripts differentially expressed. Among pathways that were differentially responsive to testosterone in prostate, we identified ornithine decarboxylase (Odc1), an enzyme in polyamine biosynthesis, as a testosterone-responsive gene that is unresponsive to rFst. Accordingly, we administered testosterone with and without α-difluoromethylornithine (DFMO), an Odc1 inhibitor, to castrated mice. DFMO selectively blocked testosterone’s effects on prostate, but did not affect testosterone’s anabolic effects on muscle. Co-administration of testosterone and Odc1 inhibitor presents a novel therapeutic strategy for prostate-sparing anabolic therapy.

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.

Patients with dementia due to Alzheimer’s disease (AD) have increased risk of developing delirium. This study investigated the relationship between a magnetic resonance imaging (MRI)-derived biomarker associated with preclinical AD and postoperative delirium. Participants were older adults (≥70 years) without dementia who underwent preoperative MRI and elective surgery. Delirium incidence and severity were evaluated daily during hospitalization. Cortical thickness was averaged across a published set of a priori brain regions to derive a measure known as the “AD signature.” Logistic and linear regression was used, respectively, to test whether the AD signature was associated with delirium incidence in the entire sample (N=145) or with the severity of delirium among those who developed delirium (N=32). Thinner cortex in the AD signature did not predict incidence of delirium (odds ratio=1.15, p=.38), but was associated with greater delirium severity among those who developed delirium (b=−1.2, p=.014). These results suggest that thinner cortices, perhaps reflecting underlying neurodegeneration due to preclinical AD, may serve as a vulnerability factor that increases severity once delirium occurs.

Background: This study aimed to demonstrate the feasibility of measuring frailty in patients with cardiac implantable electrical devices while validating the physiologic significance of device‐detected physical activity by evaluating its association with frailty and mobility. Methods and Results: Outpatients with cardiac implantable electrical devices compatible with physical activity analysis with at least 7 days of data were eligible. Office testing included frailty status (Study of Osteoporotic Fractures instrument), gait speed (m/s), mobility according to the Timed Up and Go (TUG) test (seconds), and daily physical activity (h/d) as measured by cardiac implantable electrical device. Among 219 patients, Study of Osteoporotic Fractures testing found 39.7% to be robust, 47.5% prefrail, and 12.8% frail. The mean gait speed for the cohort was 0.8±0.3 m/s, mean TUG time was 10.9±4.4 seconds, and mean activity was 2.8±1.9 h/d. Frail patients were markedly more likely to have gait speeds <0.8 m/s (OR 6.25, 95% CI 1.79‐33.3). In unadjusted analyses each 1‐hour increase in mean daily activity was associated with a 46% reduction of frail phenotype (OR 0.54, 95% CI 0.40‐0.74) versus robust and with a 27% reduction in the odds of having the prefrail phenotype (OR 0.73, 95% CI 0.62‐0.86). After adjustment this association per hour of activity persisted, with an adjusted OR for frailty of 0.71 (95% CI 0.51‐0.99) and adjusted OR for prefrailty of 0.81 (95% CI 0.67‐0.99). Conclusions: Frailty and mobility limitation are common among cardiac implantable electrical device patients and are correlated to device‐detected physical activity.

Hyperkyphosis is a common spinal disorder in older adults, characterized by excessive forward curvature of the thoracic spine and adverse health outcomes. The etiology of hyperkyphosis has not been firmly established, but may be related to changes that occur with aging in the vertebrae, discs, joints, and muscles, which function as a unit to support the spine. Determining the contribution of genetics to thoracic spine curvature and the degree of genetic sharing among co-occurring measures of spine health may provide insight into the etiology of hyperkyphosis. The purpose of our study was to estimate heritability of thoracic spine curvature using T4–T12 kyphosis (Cobb) angle and genetic correlations between thoracic spine curvature and vertebral fracture, intervertebral disc height narrowing, facet joint osteoarthritis (OA), lumbar spine volumetric bone mineral density (vBMD), and paraspinal muscle area and density, which were all assessed from computed tomography (CT) images. Participants included 2063 women and men in the second and third generation offspring of the original cohort of the Framingham Study. Heritability of kyphosis angle, adjusted for age, sex, and weight, was 54% (95% confidence interval [CI], 43% to 64%). We found moderate genetic correlations between kyphosis angle and paraspinal muscle area (math formulaG, –0.46; 95% CI, –0.67 to –0.26), vertebral fracture (math formulaG, 0.39; 95% CI, 0.18 to 0.61), vBMD (math formulaG, –0.23; 95% CI, –0.41 to –0.04), and paraspinal muscle density (math formulaG, –0.22; 95% CI, –0.48 to 0.03). Genetic correlations between kyphosis angle and disc height narrowing (math formulaG, 0.17; 95% CI, –0.05 to 0.38) and facet joint OA (math formulaG, 0.05; 95% CI, –0.15 to 0.24) were low. Thoracic spine curvature may be heritable and share genetic factors with other age-related spine traits including trunk muscle size, vertebral fracture, and bone mineral density.

Background: Delirium has been associated with more rapid cognitive decline. However, it is unknown whether increased delirium severity is associated with a higher rate of long-term cognitive decline. Objective: To evaluate delirium severity and the presence and rate of cognitive decline over 36 months following surgery. Methods: We examined patients from the Successful Aging after Elective Surgery Study, who were age ≥70 years undergoing major elective surgery (N=560). Delirium severity was determined by the peak Confusion Assessment Method-Severity (CAM-S) score for each patient’s hospitalization and grouped based on the sample distribution: scores of 0-2, 3-7, and 8-19. A neuropsychological composite, General Cognitive Performance (GCP), and proxy-reported Informant Questionnaire for Cognitive Decline (IQCODE) were used to examine cognitive outcomes following surgery at 0, 1, 2 months, and every 6 months for up to 3 years. Results: No significant cognitive decline was observed for patients with peak CAM-S scores 0-2 (-0.17 GCP units/year, 95% confidence interval [CI] -0.35, 0.01). GCP scores decreased significantly in the group with peak CAM-S scores 3-7 (-0.30 GCP units/year, 95% CI-0.51, -0.09), and decreased almost three times faster in the highest delirium severity group (peak CAM-S scores 8-19; -0.82 GCP units/year, 95% CI -1.28, -0.37). A similar association was found for delirium severity and the proportion of patients who developed IQCODE impairment over time.
Conclusion: Patients with the highest delirium severity experienced the greatest rate of cognitive decline, which exceeds the rate previously observed for patients with dementia, on serial neuropsychological testing administered over 3 years, with a dose-response relationship between delirium severity and long-term cognitive decline.