Boyd, Cynthia M.

ABSTRACT Background Dementia often goes undetected in hospital settings, where cognitive assessments are challenging due to illness severity and delirium. This study aimed to (1) evaluate the accuracy of the Clinical Dementia Rating (CDR), based solely on knowledgeable informant reports, for detecting preexisting dementia and cognitive impairment in hospitalized patients compared to a gold‐standard diagnosis, (2) and compare its performance to the 16‐item Informant Questionnaire on Cognitive Decline in the Elderly (IQCODE‐16). Methods This cross‐sectional study assessed consecutive patients aged ≥ 65 admitted to inpatient units from five hospitals in Brazil. The informant‐based CDR was administered to knowledgeable informants within 48 h of admission, capturing patients' cognitive status 3 months before hospitalization to avoid the influence of acute cognitive impairments. Blinded experts provided a gold standard clinical diagnosis of dementia or cognitive impairment no dementia (CIND) based on a 90‐min comprehensive assessment, including a standardized neuropsychology battery. Areas under the curve (AUC) examined diagnostic accuracy. Results Of 65 participants (mean age = 79.4 years; women = 54%), 34% had dementia and 32% had CIND . Compared to the gold standard, the informant‐based CDR showed excellent diagnostic accuracy for detecting dementia ( AUC = 0.92; 95% confidence interval [ CI ] = 0.86–0.98) and cognitive impairment ( AUC = 0.93; 95% CI = 0.88–0.98), with a cutoff of ≥ 1 showing 98% specificity for dementia and a cutoff of ≥ 0.5 showing 98% sensitivity for cognitive impairment. Compared to the IQCODE ‐16, the informant‐based CDR had similar performance in detecting dementia and a nonsignificant slight advantage in identifying cognitive impairment ( AUC = 0.93 vs. 0.84, p = 0.069), reducing unrecognized cognitive impairment based on medical record documentation from 70% to 2%. Conclusions Informant‐based CDR is a valid and efficient tool for detecting dementia and cognitive impairment in hospitalized older adults, supporting early diagnosis and guiding multidisciplinary interventions in acute care. Its use in routine hospitals may help clinicians reduce undetected cognitive impairment, enhance decision making, and improve patient care.

Objectives To compare the agreement between percentile ranks from 4 multi-morbidity scores. Design Population-based descriptive study. Setting Olmsted County, Minnesota (USA). Participants We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org ) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods For each person, we calculated 4 multi-morbidity scores using readily available diagnostic code lists from the US Department of Health and Human Services, the Clinical Classifications Software, and the Elixhauser Comorbidity Index. We calculated scores using diagnostic codes received in the 5 years before the index birthday and fit quantile regression models across age and separately by sex to transform unweighted, simple counts of conditions into percentile ranks as compared to peers of same age and of same sex. We compared the percentile ranks of the 4 multi-morbidity scores using intra-class correlation coefficients (ICCs). Results We assessed agreement in 181,553 persons who reached a total of 1,075,433 birthdays at ages 18 years through 85 years during the study period. In general, the percentile ranks of the 4 multi-morbidity scores exhibited high levels of agreement in 6 score-to-score pairwise comparisons. The agreement increased with older age for all pairwise comparisons, and ICCs were consistently greater than 0.65 at ages 50 years and older. Conclusions The assignment of percentile ranks may be a simple and intuitive way to assess the underlying trait of multi-morbidity across studies that use different measures.

Background Persons who accumulate chronic conditions at a rate faster than their peers may experience accelerated aging and poor health outcomes, including functional limitations. Methods Adults aged ≥40 years who resided in Olmsted County, Minnesota on 1 January 2006 were identified. The prevalence of 21 chronic conditions was ascertained, and age-specific quartiles of the number of chronic conditions was estimated within 4 age groups: 40–54, 55–64, 65–74, and ≥75 years. Difficulty with nine patient-reported functional limitations (including basic and instrumental activities of daily living and mobility activities) were ascertained through 31 October 2018. Cox regression was used to model associations of chronic condition quartiles with new-onset functional limitations considered separately. We estimated absolute risk differences and hazard ratios stratified by age group, and adjusted for sex, race, ethnicity, marital status, education, and the residual effect of age. Results Among 39,624 persons (44.5% men, 93.2% white), the most common reported new functional limitations were difficulty with climbing stairs, walking, and housekeeping. For all functional limitations, the absolute risk differences were largest among the oldest age group (≥75 years). Approximately twofold increased hazard ratios were observed among those in the highest vs. lowest quartile for the three oldest age groups, and approximately threefold or higher hazard ratios were observed for persons aged 40-54 years. Conclusion Persons with increased accumulation of chronic conditions experience increased risks of developing functional limitations compared to their peers. These findings underscore the importance of assessing health status and of employing interventions to prevent and effectively manage multi-morbidity at all ages.

Abstract Introduction End‐of‐life care differs by serious illness diagnosis. Cancer and dementia are serious illnesses that have been associated with less intensive end‐of‐life health care use. It is not known how health care utilization varies in the presence of >1 serious illness. Methods We used the Rochester Epidemiology Project to identify persons living in a midwestern area who died on July 1, 2017–June 30, 2018 at age ≥65 years, and were seriously ill. We examined the number of emergency department (ED), hospital, and intensive care unit (ICU) stays in the last 6 months and the last 30 days of life. We used Poisson regression to determine the incidence rate ratio for ED, hospital, and ICU stay in the last 6 months and 30 days of life by number of serious illness diagnoses. For cancer and dementia, we examined the effect of an additional serious illness. Results We included a population of 1372 adults who were, on average, 84 years, 52% female, and 96% white. Approximately 41% had multiple serious illnesses. Compared to older adults with 1 serious illness diagnosis, rates of hospitalization, and ICU stay for adults with 2 or ≥3 serious illness diagnoses were at least 1.5 times higher in the last 6 months and the last 30 days of life. Rates of ED visits were significantly higher for older adults with 2 or ≥3 serious illness diagnoses in the last 6 months of life, but only higher for those with ≥3 versus 1 serious illness diagnosis in the last 30 days of life. For both cancer and dementia, rates of ED visits, hospitalization and ICU stay were lower for the condition alone than when an additional serious illness diagnosis was present. Conclusion Having multiple serious illnesses increases the risk of health care utilization at the end of life.

Background: Whether age alone explains the comorbidity burden in heart failure (HF) is unclear. In particular, differences in the burden of co-morbid conditions in HF patients compared to population controls has not been well documented. Methods: The prevalence of 17 chronic conditions defined by the US Department of Health and Human Services were obtained in 1746 incident HF patients from 2000-2010 and controls matched 1:1 on sex and age from Olmsted County, MN. Conditions were ascertained requiring 2 occurrences of a diagnostic code. Logistic regression determined associations of each condition with HF. Results: Among the 1746 matched pairs (mean age 76.2 years, 43.5% men), the prevalence was higher in HF cases for all conditions (p<0.05) except dementia and osteoporosis. After adjusting for all conditions, hypertension, coronary artery disease, arrhythmia, asthma, chronic kidney disease, chronic obstructive pulmonary disease, diabetes, hepatitis, and substance abuse were significantly more common in HF (figure). More than a 2-fold increased odds of hepatitis, arrhythmia, and coronary artery disease was observed among HF cases. Arrhythmia (34.2%), hypertension (31.1%), and coronary artery disease (27.8%) had the largest attributable risk of HF; for example, assuming a causal relationship, if arrhythmias were eliminated, 34% of HF would be avoided. Conclusions: Compared to age- and sex-matched controls, HF patients have a higher prevalence of many chronic conditions, indicating the excess comorbidity in HF is not due to age alone. Some cardiovascular conditions, including arrhythmia, coronary artery disease, and hypertension were more common in HF. Of the non-cardiovascular conditions, hepatitis had the strongest association with HF and was an unanticipated finding that deserves additional investigation. It is important to understand comorbidities as they play a key role in the excess mortality and healthcare utilization experienced by HF patients.

Introduction: Little is known about the characteristics and resources that enable patients with heart failure (HF) to engage in effective self-management. To address this gap in knowledge, we measured personal and health care resources for self-management and examined associations with mortality among patients with HF. Methods: We surveyed 5543 residents of 11 counties in Southeast Minnesota with a first-ever code for HF [International Classification of Disease, Ninth Revision code 428 or Tenth Revision code I50] between 1/1/2013 and 3/31/2016. Self-management resources were measured with the health care and personal subscales of the Chronic Illness Resources Survey (CIRS), both of which included 3 questions on a 5-point scale. The responses were averaged and participants were categorized as low if the mean score was below the median of the distribution (range from 1 to 5). The survey was returned by 2866 participants (response rate 52%) and those with complete data on the main items of interest were retained for analysis (N=2212). Cox proportional hazards regression was used to determine the association between each subscale and mortality. Results: Among 2212 participants (mean age 72.8 years, 54.1% men) the median health care score was 4, while the personal score was 3. Those with low health care resources were older and less educated than those with a higher score (p<0.05), while those with low personal resources had less comorbidities and lower education attainment compared to those with a higher score (p<0.05). After a mean (SD) follow-up of 1.3 ± 0.6 years, 207 deaths occurred. Low levels of both self-management resources were associated with an increased risk of death compared with patients with high levels (Table). Conclusions: Having limited self-management resources is associated with an increased risk of mortality among patients with HF. Thus, interventions aimed at supporting self-management among patients with HF may improve outcomes.

Objectives To describe the percentile distribution of multimorbidity across age by sex, race and ethnicity, and to demonstrate the utility of multimorbidity percentiles to predict mortality. Design Population-based descriptive study and cohort study. Setting Olmsted County, Minnesota (USA). Participants We used the medical records-linkage system of the Rochester Epidemiology Project (REP; http://www.rochesterproject.org ) to identify all residents of Olmsted County, Minnesota who reached one or more birthdays between 1 January 2005 and 31 December 2014 (10 years). Methods For each person, we obtained the count of chronic conditions (out of 20 conditions) present on each birthday by extracting all of the diagnostic codes received in the 5 years before the index birthday from the electronic indexes of the REP. To compare each person’s count to peers of same age, the counts were transformed into percentiles of the total population and displayed graphically across age by sex, race and ethnicity. In addition, quintiles 1, 2, 4 and 5 were compared with quintile 3 (reference) to predict the risk of death at 1 year, 5 years and through end of follow-up using time-to-event analyses. Follow-up was passive using the REP. Results We identified 238 010 persons who experienced a total of 1 458 094 birthdays during the study period (median of 6 birthdays per person; IQR 3–10). The percentiles of multimorbidity across age did not vary noticeably by sex, race or ethnicity. In general, there was an increased risk of mortality at 1 and 5 years for quintiles 4 and 5 of multimorbidity. The risk of mortality for quintile 5 was greater for younger age groups and for women. Conclusions The assignment of multimorbidity percentiles to persons in a population may be a simple and intuitive tool to assess relative health status, and to predict short-term mortality, especially in younger persons and in women.

Background As the population with cardiovascular disease ages, geriatric conditions are of increasing relevance. A possible geriatric prognostic indicator may be a fall risk score, which is mandated by The Joint Commission to be measured on all hospitalized patients. The prognostic value of a fall risk score on outcomes after dismissal is not well known. Thus, we aimed to determine whether a fall risk score is associated with death and hospital readmissions in patients with a recent incident cardiovascular disease event. Methods and Results In this retrospective cohort study, Olmsted County, MN patients with incident heart failure, myocardial infarction, or atrial fibrillation between August 1, 2005, and December 31, 2011, who were hospitalized within 180 days after the event were studied. Fall risk was measured by the Hendrich II fall risk model. Patients were followed for death or readmission within 30 days or 1 year. Among 2456 hospitalized patients with recent incident cardiovascular disease (549 heart failure, 784 myocardial infarction, 1123 atrial fibrillation; mean [SD] age, 71 [15] years; 55% men), the fall risk score was high in 22% of patients and moderate in 38%. The risk of death was increased if the fall risk score was increased, independent of age and comorbidities (moderate hazard ratio, 1.51; 95% CI, 1.09–2.08; high hazard ratio, 3.49; 95% CI, 2.52–4.85). Similarly, the risk of 30-day readmissions was substantially increased with a greater fall risk score (moderate hazard ratio, 1.29; 95% CI, 1.03–1.62; high hazard ratio, 1.63; 95% CI, 1.23–2.15). Results were similar for readmissions within 1 year. Conclusions More than half of hospitalized patients with recent incident cardiovascular disease have an elevated fall risk score, which is associated with an increased risk in readmissions and death. These results delineate an approach for risk stratification and management that may prevent readmissions and improve survival.