BACKGROUND
Hospital‐acquired disability (HAD) is common and often related to low physical activity while in the hospital.
OBJECTIVE
To examine whether wearable hospital activity trackers can be used ...to predict HAD.
DESIGN
A prospective observational study between January 2016 and March 2017.
SETTING
An academic medical center.
PARTICIPANTS
Community‐dwelling older adults, aged 60 years or older, enrolled within 24 hours of admission to general medicine (n = 46).
MAIN MEASURES
Primary outcome was HAD, defined as having one or more new activity of daily living deficits, decline of four or greater on the Late‐Life Function and Disability Instrument (calculated between baseline and discharge), or discharge to a skilled nursing facility. Hospital activity (mean active time, mean sedentary time, and mean step counts per day) was measured using ankle‐mounted accelerometers. The association of the literature‐based threshold of 900 steps/day with HAD was also evaluated.
RESULTS
Mean age was 73.2 years (SD = 9.5 years), 48% were male, and 76% were white. Median length of stay was 4 days (interquartile range IQR = 2.0‐6.0 days); 61% (n = 28) reported being able to walk without assistance of another person or walking aid at baseline. Median daily activity time and step counts were 1.1 h/d (IQR = 0.7‐1.7 h/d) and 1455.7 steps/day (IQR = 908.5‐2643 steps/day), respectively. Those with HAD (41%; n = 19) had lower activity time (0.8 vs 1.4 h/d; P = .04) and fewer step counts (1186 vs 1808 steps/day; P = .04), but no difference in sedentary time, compared to those without HAD. The 900 steps/day threshold had poor sensitivity (40%) and high specificity (85%) for detecting HAD.
CONCLUSIONS
Low hospital physical activity, as measured by wearable accelerometers, is associated with HAD. Clinicians can utilize wearable technology data to refer patients to physical/occupational therapy services or other mobility interventions, like walking programs. J Am Geriatr Soc 68:261–265, 2020
Diet and exercise interventions have been tested in cancer survivors as a means to reduce late effects and comorbidity, but few have assessed adherence and health outcomes long term.
Between July ...2005 and May 2007, the Reach Out to Enhance Wellness (RENEW) trial accrued 641 locoregionally staged, long-term (≥ 5 years from diagnosis) colorectal, breast, and prostate cancer survivors in the United States (21 states), Canada, and the United Kingdom. All participants were sedentary (< 150 minutes of physical activity PA a week), overweight or obese (body mass index, 25 to 40 kg/m(2)), and over age 65 years. The trial tested a diet-exercise intervention delivered via mailed print materials and telephone counseling. RENEW used a wait-list control, cross-over design (ie, participants received the year-long intervention immediately or after a 1-year delay), which allowed the opportunity to assess program efficacy (previously reported primary outcome), durability, and reproducibility (reported herein). Measures included diet quality (DQ), PA, BMI, and physical function (PF).
No significant relapse was observed in the immediate-intervention arm for DQ, PA, and BMI; however, rates of functional decline increased when the intervention ceased. From year 1 to year 2, significant improvements were observed in the delayed-intervention arm; mean change scores in behaviors and BMI and PF slopes were as follows: DQ score, 5.2 (95% CI, 3.4 to 7.0); PA, 45.8 min/wk (95% CI, 26.9 to 64.6 min/wk); BMI, -0.56 (95% CI, -0.75 to -0.36); and Short Form-36 PF, -1.02 versus -5.52 (P < .001 for all measures). Overall, both arms experienced significant improvements in DQ, PA, and BMI from baseline to 2-year follow-up (P < .001).
Older cancer survivors respond favorably to lifestyle interventions and make durable changes in DQ and PA that contribute to sustained weight loss. These changes positively reorient functional decline trajectories during intervention delivery.
Background
Central nervous system (CNS) medication use is common among older adults, yet the impact of hospitalizations on use remains unclear. This study details CNS medication use, ...discontinuations, and user profiles during hospitalization periods.
Methods
Retrospective cohort study using electronic health records on patients ≥65 years, from three hospitals (2018–2020), and prescribed a CNS medication around hospitalization (90 days prior to 90 days after). Latent class transitions analysis (LCTA) examined profiles of CNS medication class users across four time points (90 days prior, admission, discharge, 90 days after hospitalization).
Results
Among 4666 patients (mean age 74.3 ± 9.3 years; 63% female; 70% White; mean length of stay 4.6 ± 5.6 days (median 3.0 2.0, 6.0), the most commonly prescribed CNS medications were antidepressants (56%) and opioids (49%). Overall, 74% (n = 3446) of patients were persistent users of a CNS medication across all four time points; 7% (n = 388) had discontinuations during hospitalization, but of these, 64% (216/388) had new starts or restarts within 90 days after hospitalization. LCTA identified three profile groups: (1) low CNS medication users, 54%–60% of patients; (2) mental health medication users, 30%–36%; and (3) acute/chronic pain medication users, 9%–10%. Probability of staying in same group across the four time points was high (0.88–1.00). Transitioning to the low CNS medication use group was highest from admission to discharge (probability of 9% for pain medication users, 5% for mental health medication users). Female gender increased (OR 2.4, 95% CI 1.3–4.3), while chronic kidney disease lowered (OR 0.5, 0.2–0.9) the odds of transitioning to the low CNS medication use profile between admission and discharge.
Conclusions
CNS medication use stays consistent around hospitalization, with discontinuation more likely between admission and discharge, especially among pain medication users. Further research on patient outcomes is needed to understand the benefits and harms of hospital deprescribing, particularly for medications requiring gradual tapering.
While moderate- to vigorous-intensity physical activities (MVPA) confer the greatest health benefits, evidence suggests that light-intensity activities are also beneficial, particularly for older ...adults and individuals with moderate to severe comorbidities.
To examine cross-sectional and longitudinal associations between light-intensity activity and physical function in older cancer survivors at increased risk for age- and treatment-related comorbidities, including accelerated functional decline.
The analysis included data from 641 breast, prostate, and colorectal cancer survivors (54% female) age 65 yr and older who participated in a 1-yr home-based diet and exercise intervention designed to reduce the rate of physical function decline. ANCOVA was used to compare means of physical function across levels of PA intensity (low-light LLPA: 1.5-2.0 METs; high-light HLPA: 2.1-2.9 METs; MVPA: ≥3.0 METs).
In cross-sectional analyses, increasing tertiles of light-intensity activity were associated with higher scores for all three measures of physical function (all P values <0.005), after adjusting for age, sex, body mass index, comorbidity, symptoms, and MVPA. Associations were stronger for HLPA than for LLPA. Compared with survivors who had decreased MVPA or maintained stable MVPA and HLPA at the postintervention follow-up, those who had increased HLPA, but had decreased MVPA or maintained stable MVPA, reported higher physical function scores (LS means 95% confidence interval: SF-36 Physical Function Subscale: -5.58 -7.96 to -3.20 vs -2.54 -5.83 to 0.75, P = 0.14; Basic Lower Extremity Function: -2.00 -3.45 to -0.55 vs 0.28 -1.72 to 2.28, P = 0.07; Advanced Lower Extremity Function: -2.58 -4.00 to -1.15 vs 0.44 -1.52 to 2.40, P = 0.01).
Our findings suggest that increasing light-intensity activities, especially HLPA, may be a viable approach to reducing the rate of physical function decline in individuals who are unable or reluctant to initiate or maintain adequate levels of moderate-intensity activities.
Mitigation behaviors reduce the incidence of COVID-19 infection. Determining characteristics of groups defined by mitigation behaviors compliance may be useful to inform targeted public health ...policies and interventions. This study aimed to identify groups of individuals according to self-reported compliance with COVID-19 mitigation behaviors, define compliance class characteristics, and explore associations between compliance classes and important study and public health outcomes.
We studied 1,410 participants in the Cabarrus County COVID-19 Prevalence and Immunity longitudinal cohort study (June 2020 to December 2021) who were asked 10 questions regarding compliance with recommended COVID-19 mitigation behaviors. By Latent Class Analysis, 1,381 participants were categorized into 3 classes (most 49.4%, moderately 45.0%, and least 5.6% compliant). Compared with the most compliant class, the least and moderately compliant classes were younger (mean = 61.9 v. 59.0 v. 53.8 years), had fewer medical conditions per individual (1.37 v. 1.08 v. 0.77), and differed in Hispanic ethnicity (6.2% v. 2.8% v. 9.1%) and COVID-19 vaccine intention (65.8% v. 59.8% v. 35.1%). Compared to the most compliant class, the least compliant class had fewer women (54.6% v. 76.3%), fewer insured individuals (92.2% v. 97.4%), and more withdrew from study participation early (28.6% v. 16.0%). Relative to the most compliant class, the least compliant class had a higher likelihood of COVID-19 infection (OR = 2.08 95% CI 1.13, 3.85), lower rate of COVID-19 vaccination (72.6% v. 95.1%), and longer time to 50% COVID-19 vaccination following eligibility (8-9 vs 16 days).
Classes defined by mitigation behaviors compliance had distinct characteristics, including age, sex, medical history, and ethnicity, and were associated with important study and public health outcomes. Targeted public health policies and interventions according to the compliance group characteristics may be of value in current and future pandemic responses to increase compliance.
While the majority of healthcare in the US is provided in community hospitals, the epidemiology and treatment of bloodstream infections in this setting is unknown.
We undertook this multicenter, ...retrospective cohort study to 1) describe the epidemiology of bloodstream infections (BSI) in a network of community hospitals and 2) determine risk factors for inappropriate therapy for bloodstream infections in community hospitals. 1,470 patients were identified as having a BSI in 9 community hospitals in the southeastern US from 2003 through 2006. The majority of BSIs were community-onset, healthcare associated (n = 823, 56%); 432 (29%) patients had community-acquired BSI, and 215 (15%) had hospital-onset, healthcare-associated BSI. BSIs due to multidrug-resistant pathogens occurred in 340 patients (23%). Overall, the three most common pathogens were S. aureus (n = 428, 28%), E. coli (n = 359, 24%), coagulase-negative Staphylococci (n = 148, 10%), though type of infecting organism varied by location of acquisition (e.g., community-acquired). Inappropriate empiric antimicrobial therapy was given to 542 (38%) patients. Proportions of inappropriate therapy varied by hospital (median = 33%, range 21-71%). Multivariate logistic regression identified the following factors independently associated with failure to receive appropriate empiric antimicrobial therapy: hospital where the patient received care (p<0.001), assistance with ≥3 ADLs (p = 0.005), Charlson score (p = 0.05), community-onset, healthcare-associated infection (p = 0.01), and hospital-onset, healthcare-associated infection (p = 0.02). Important interaction was observed between Charlson score and location of acquisition.
Our large, multicenter study provides the most complete picture of BSIs in community hospitals in the US to date. The epidemiology of BSIs in community hospitals has changed: community-onset, healthcare-associated BSI is most common, S. aureus is the most common cause, and 1 of 3 patients with a BSI receives inappropriate empiric antimicrobial therapy. Our data suggest that appropriateness of empiric antimicrobial therapy is an important and needed performance metric for physicians and hospital stewardship programs in community hospitals.
Depressive symptoms, assessed using a self-report type of questionnaire, have been associated with poor outcomes in dialysis patients. Here we determined if depressive disorders diagnosed by ...physicians are also associated with such outcomes. Ninety-eight consecutive patients on chronic hemodialysis underwent the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders administered by a physician. Depression was diagnosed in about a quarter of the patients. Associations adjusted for age, gender, race, time on dialysis and co-morbidity were determined using survival analysis. Using time to event (death or hospitalization) models of analysis the hazard ratios were 2.11 and 2.07 in unadjusted and adjusted models respectively. The finding of poor outcome using a formal structured physician interview suggests that a prospective study is needed to determine whether treatment of depression affects clinical outcomes.
OBJECTIVES
To develop a prognostic model for hospital admissions over a 1‐year period among community‐dwelling older adults with self‐reported hearing and/or vision impairments based on readily ...obtainable clinical predictors.
DESIGN
Retrospective cohort study.
SETTING
Medicare Current Beneficiary Survey from 1999 to 2006.
PARTICIPANTS
Community‐dwelling Medicare beneficiaries, aged 65 years and older, with self‐reported hearing and/or vision impairment (N = 15,999).
MEASUREMENTS
The primary outcome was any hospital admission over a predefined 1‐year study period. Candidate predictors included demographic factors, prior healthcare utilization, comorbidities, functional impairment, and patient‐level factors. We analyzed the association of all candidate predictors with any hospital admission over the 1‐year study period using multivariable logistic regression. The final model was created using a penalized regression method known as the least absolute shrinkage and selection operator. Model performance was assessed by discrimination (concordance statistic (c‐statistic)) and calibration (evaluated graphically). Internal validation was performed via bootstrapping, and results were adjusted for overoptimism.
RESULTS
Of the 15,999 participants, the mean age was 78 years and 55% were female. A total of 2,567 participants (16.0%) had at least one hospital admission in the 1‐year study period. The final model included seven variables independently associated with hospitalization: number of inpatient admissions in the previous year, number of emergency department visits in the previous year, activities of daily living difficulty score, poor self‐rated health, and self‐reported history of myocardial infarction, stroke, and nonskin cancer. The c‐statistic of the final model was 0.717. The optimism‐corrected c‐statistic after bootstrap internal validation was 0.716. A calibration plot suggested that the model tended to overestimate risk among patients at the highest risk for hospitalization.
CONCLUSION
This prognostic model can help identify which community‐dwelling older adults with sensory impairments are at highest risk for hospitalization and may inform allocation of healthcare resources.
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