Publications

BACKGROUND: Data are needed on how life expectancy affects treatment decisions among women ≥80 years with early stage breast cancer. METHODS: We used the linked Surveillance Epidemiology and End Results-Medicare claims dataset from 1992-2005 to identify women aged ≥80 newly diagnosed with lymph node negative, estrogen receptor positive tumors, ≤5 centimeters. To estimate life expectancy, we matched these women to women of similar age, region, and insurance, not diagnosed with breast cancer. We examined 5-year mortality of matched controls by illness burden (measured with the Charlson Comorbidity Index [CCI]) using Kaplan-Meier statistics. We examined treatments received by estimated life expectancy within CCI levels. We further examined factors associated with receipt of radiotherapy after breast conserving surgery (BCS). RESULTS: Of 9,932 women, 39.6% underwent mastectomy, 30.4% received BCS plus radiotherapy, and 30.0% received BCS alone. Estimated 5-year mortality was 72% for women with CCIs of 3+, yet 38.0% of these women underwent mastectomy and 22.9% received radiotherapy after BCS. Conversely, estimated 5-year mortality was 36% for women with CCIs of 0 and 26.6% received BCS alone. Age 80-84, urban residence, higher grade, recent diagnosis, mammography use, and low comorbidity, were factors associated with receiving radiotherapy after BCS. Among women with CCIs of 3+ treated with BCS, 36.9% underwent radiotherapy. CONCLUSIONS: Many women aged ≥80 with limited life expectancies receive radiotherapy after BCS for treatment of early stage breast cancers while many in excellent health do not. More consideration needs to be given to patient life expectancy when considering breast cancer treatments. KEY WORDS: Breast cancer, older women, treatment, life expectancy, radiation.

Delirium (acute confusion) complicates 15% to 50% of major operations in older adults and is associated with other major postoperative complications, prolonged length of stay, poor functional recovery, institutionalization, dementia, and death. Importantly, delirium may be predictable and preventable through proactive intervention. Yet clinicians fail to recognize and address postoperative delirium in up to 80% of cases. Using the case of Ms R, a 76-year-old woman who developed delirium first after colectomy with complications and again after routine surgery, the diagnosis, prevention, and treatment of delirium in the postoperative setting is reviewed. The risk of postoperative delirium can be quantified by the sum of predisposing and precipitating factors. Successful strategies for prevention and treatment of delirium include proactive multifactorial intervention targeted to reversible risk factors, limiting use of sedating medications (especially benzodiazepines), effective management of postoperative pain, and, perhaps, judicious use of antipsychotics.

OBJECTIVES: To investigate whether complications in postacute care (PAC) are associated with delirium persistence 30 days after PAC admission.

DESIGN: Observational cohort study.

SETTING: Eight Boston-area PAC facilities.

PARTICIPANTS: Three hundred fifty individuals with delirium at PAC admission.

MEASUREMENTS: Participants were interviewed at PAC admission and 30 days later. Delirium presence was determined using the Confusion Assessment Method. Medical record reviews were performed to ascertain new cardiac, noncardiac, and geriatric syndrome complications in PAC. Complication status was also determined 30 days after admission or at PAC discharge, whichever came first.

RESULTS: Participants (mean age 83.6, 66% female) experienced the following incidence of PAC complications: cardiac complications (7%), noncardiac complications (21%), and geriatric syndrome complications (39%). Delirium persisted in 56% of participants 1 month after PAC admission. Neither cardiac nor noncardiac complications were associated with delirium persistence. Delirium persistence at 1 month was significantly greater in participants, with more geriatric syndrome complications (no complications, 51%; one complication 61%; ≥ 2 complications, 100%, adjusted P = .048). There was also a trend toward greater delirium persistence in participants with unresolved geriatric syndrome complications (no complications, 51%; resolved complication, 61%; unresolved complication, 68%; adjusted P = .10).

CONCLUSION: Geriatric syndrome complications are common in individuals admitted to PAC with delirium and are associated with persistence of delirium 1 month later. Proactively addressing risk factors for geriatric syndromes may improve outcomes of vulnerable individuals in PAC.

OBJECTIVE: Dissatisfaction is an important threat to high-quality care. The aim of this study was to identify factors independently associated with dissatisfaction with critical care.

DESIGN: Prospectively collected observational cohort study.

SETTING: Nine intensive care units at a tertiary care university hospital in the United States.

PARTICIPANTS: Four hundred forty-nine family members of adult intensive care unit patients who completed the Family Satisfaction with Care in the Intensive Care Unit instrument.

INTERVENTION: None.

MEASUREMENTS AND MAIN RESULTS: Four family-and patient-related factors ascertainable at intensive care unit admission independently predicted low overall satisfaction: living in the same city as the hospital, disagreement within the family regarding care, having a cardiac comorbidity but being hospitalized in a noncardiac-care intensive care unit, and living in a different household than the patient. When three or more risk factors were present, 63% (95% confidence interval 48%-78%) of families were dissatisfied. Among factors ascertained at the end of the intensive care unit stay, dissatisfaction with six items was independently associated with overall dissatisfaction: 1) perceived competence of nurses (odds ratio for dissatisfaction=5.9, 95% confidence interval 2.3-15.2); 2) concern and caring by intensive care unit staff (odds ratio 5.0, 95% confidence interval 1.9-12.6); 3) completeness of information (odds ratio 4.4, 95% confidence interval 2.4-8.1); 4) dissatisfaction with the decision-making process (odds ratio 3.0, 95% confidence interval 1.6- 5.6); 5) atmosphere of the intensive care unit (odds ratio 2.6, 95% confidence interval 1.4-4.8); and 6) atmosphere of the waiting room (odds ratio 2.7, 95% confidence interval 1.2-6.0).

CONCLUSION: Specific factors ascertainable at intensive care unit admission identify families at high risk of dissatisfaction with care. Other discrete aspects of the patient/family experience that develop during the intensive care unit stay are also strongly associated with dissatisfaction with the critical care experience. These results may provide insight into the design of future evidence-based strategies to improve satisfaction with the intensive care unit experience.

OBJECTIVES: To use an expert consensus process to identify indicators of delirium features to help enhance bedside recognition of delirium.

DESIGN: Modified Delphi consensus process to assign existing cognitive and delirium assessment items to delirium features in the Confusion Assessment Method (CAM) diagnostic algorithm.

SETTING: Meetings of expert panel.

PARTICIPANTS: Panel of seven interdisciplinary clinical experts.

MEASUREMENTS: Panelists' assignments of each assessment item to indicate CAM features.

RESULTS: From an initial pool of 119 assessment items, the panel assigned 66 items to at least one CAM feature, and many items were assigned to more than one feature. Experts achieved a high level of consensus, with a postmeeting kappa for agreement of 0.98. The study staff compiled the assignment results to create a comprehensive list of CAM feature indicators, consisting of 107 patient interview questions, cognitive tasks, and interviewer observations, with some items assigned to multiple features. A subpanel shortened this list to 28 indicators of important delirium features.

CONCLUSION: A systematic, well-described qualitative methodology was used to create a list of indicators for delirium based on the features of the CAM diagnostic algorithm. This indicator list may be useful as a clinical tool for enhancing delirium recognition at the bedside and for aiding in the development of a brief delirium screening instrument.

BACKGROUND: Hospitalization, frequently complicated by delirium, can be a life-changing event for patients with Alzheimer disease (AD).

OBJECTIVE: To determine risks for institutionalization, cognitive decline, or death associated with hospitalization and delirium in patients with AD.

DESIGN: Prospective cohort enrolled between 1991 and 2006 into the Massachusetts Alzheimer's Disease Research Center (MADRC) patient registry.

SETTING: Community-based.

PARTICIPANTS: 771 persons aged 65 years or older with a clinical diagnosis of AD.

MEASUREMENTS: Hospitalization, delirium, death, and institutionalization were identified through administrative databases. Cognitive decline was defined as a decrease of 4 or more points on the Blessed Information-Memory-Concentration test score. Multivariate analysis was used to calculate adjusted relative risks (RRs).

RESULTS: Of 771 participants with AD, 367 (48%) were hospitalized and 194 (25%) developed delirium. Hospitalized patients who did not have delirium had an increased risk for death (adjusted RR, 4.7 [95% CI, 1.9 to 11.6]) and institutionalization (adjusted RR, 6.9 [CI, 4.0 to 11.7]). With delirium, risk for death (adjusted RR, 5.4 [CI, 2.3 to 12.5]) and institutionalization (adjusted RR, 9.3 [CI, 5.5 to 15.7]) increased further. With hospitalization and delirium, the adjusted RR for cognitive decline for patients with AD was 1.6 (CI, 1.2 to 2.3). Among hospitalized patients with AD, 21% of the incidences of cognitive decline, 15% of institutionalization, and 6% of deaths were associated with delirium.

LIMITATIONS: Cognitive outcome was missing in 291 patients. Sensitivity analysis was performed to test the effect of missing data, and a composite outcome was used to decrease the effect of missing data.

CONCLUSION: Approximately 1 in 8 hospitalized patients with AD who develop delirium will have at least 1 adverse outcome, including death, institutionalization, or cognitive decline, associated with delirium. Delirium prevention may represent an important strategy for reducing adverse outcomes in this population.

OBJECTIVE: Laws and regulations require many hospitals to implement rapid-response systems. However, the optimal resource intensity for such systems is unknown. We sought to determine whether a rapid-response system that relied on a patient's usual care providers, not a critical-care-trained rapid-response team, would improve patient outcomes.

DESIGN, SETTING, AND PATIENTS: An interrupted time-series analysis of over a 59-month period.

SETTING: Urban, academic hospital.

PATIENTS: One hundred seven-one thousand, three hundred forty-one consecutive adult admissions.

INTERVENTION: In the intervention period, patients were monitored for predefined, standardized, acute, vital-sign abnormalities or marked nursing concern. If these criteria were met, a team consisting of the patient's existing care providers was assembled.

MEASUREMENTS AND MAIN RESULTS: The unadjusted risk of unexpected mortality was 72% lower (95% confidence interval 55%-83%) in the intervention period (absolute risk: 0.02% vs. 0.09%, p < .0001). The unadjusted in-hospital mortality rate was not significantly lower (1.9% vs. 2.1%, p = .07). After adjustment for age, gender, race, season of admission, case mix, Charlson Comorbidity Index, and intensive care unit bed capacity, the intervention period was associated with an 80% reduction (95% confidence interval 63%-89%, p < .0001) in the odds of unexpected death, but no significant change in overall mortality [odds ratio 0.91 (95% confidence interval 0.82-1.02), p = .09]. Analyses that also adjusted for secular time trends confirmed these findings (relative risk reduction for unexpected mortality at end of intervention period: 65%, p = .0001; for in-hospital mortality, relative risk reduction = 5%, p = .2).

CONCLUSIONS: A primary-team-based implementation of a rapid response system was independently associated with reduced unexpected mortality. This system relied on the patient's usual care providers, not an intensive care unit based rapid response team, and may offer a more cost-effective approach to rapid response systems, particularly for systems with limited intensivist availability.

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: Delirium is common after cardiac surgery and may be associated with long-term changes in cognitive function. We examined postoperative delirium and the cognitive trajectory during the first year after cardiac surgery.

METHODS: We enrolled 225 patients 60 years of age or older who were planning to undergo coronary-artery bypass grafting or valve replacement. Patients were assessed preoperatively, daily during hospitalization beginning on postoperative day 2, and at 1, 6, and 12 months after surgery. Cognitive function was assessed with the use of the Mini-Mental State Examination (MMSE; score range, 0 to 30, with lower scores indicating poorer performance). Delirium was diagnosed with the use of the Confusion Assessment Method. We examined performance on the MMSE in the first year after surgery, controlling for demographic characteristics, coexisting conditions, hospital, and surgery type.

RESULTS: The 103 participants (46%) in whom delirium developed postoperatively had lower preoperative mean MMSE scores than those in whom delirium did not develop (25.8 vs. 26.9, P<0.001). In adjusted models, those with delirium had a larger drop in cognitive function (as measured by the MMSE score) 2 days after surgery than did those without delirium (7.7 points vs. 2.1, P<0.001) and had significantly lower postoperative cognitive function than those without delirium, both at 1 month (mean MMSE score, 24.1 vs. 27.4; P<0.001) and at 1 year (25.2 vs. 27.2, P<0.001) after surgery. With adjustment for baseline differences, the between-group difference in mean MMSE scores was significant 30 days after surgery (P<0.001) but not at 6 or 12 months (P=0.056 for both). A higher percentage of patients with delirium than those without delirium had not returned to their preoperative baseline level at 6 months (40% vs. 24%, P=0.01), but the difference was not significant at 12 months (31% vs. 20%, P=0.055).

CONCLUSIONS: Delirium is associated with a significant decline in cognitive ability during the first year after cardiac surgery, with a trajectory characterized by an initial decline and prolonged impairment. (Funded by the Harvard Older Americans Independence Center and others.).

BACKGROUND: Cognitive impairment is often unrecognized among older adults. Meanwhile, current assessment instruments are underused, lack sensitivity, or may be restricted by copyright laws. To address these limitations, we created a new brief cognitive assessment tool: the Sweet 16.

METHODS: The Sweet 16 was developed in a cohort from a large post-acute hospitalization study (n=774) and compared with the Mini-Mental State Examination (MMSE). Equipercentile equating identified Sweet 16 cut points that correlated with widely used MMSE cut points. Sweet 16 performance characteristics were independently validated in a cohort from the Aging, Demographics, and Memory Study (n=709) using clinical consensus diagnosis, the modified Blessed Dementia Rating Scale, and the Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE).

RESULTS: The Sweet 16 correlated highly with the MMSE (Spearman r, 0.94; P<.001). Validated against the IQCODE, the area under the curve was 0.84 for the Sweet 16 and 0.81 for the MMSE (P=.06). A Sweet 16 score of less than 14 (approximating an MMSE score <24) demonstrated a sensitivity of 80% and a specificity of 70%, whereas an MMSE score of less than 24 showed a sensitivity of 64% and a specificity of 86% against the IQCODE. When compared with clinical diagnosis, a Sweet 16 score of less than 14 showed a sensitivity of 99% and a specificity of 72% in contrast to an MMSE score with a sensitivity of 87% and a specificity of 89%. For education of 12 years or more, the area under the curve was 0.90 for the Sweet 16 and 0.84 for the MMSE (P=.03).

CONCLUSIONS: The Sweet 16 is simple, quick to administer, and will be available open access. The performance of the Sweet 16 is equivalent or superior to that of the MMSE.