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Background and Objectives: This study aims to identify patterns of caregiving intensity and assess associations between caregiving intensity and multidimensional physical health indicators and health behaviors among spousal caregivers of persons with Alzheimer's disease and related dementia. Research Design and Methods: Using data from 152 spousal caregivers aged 65 and older, the intensity of their caregiving experience was measured as the number and frequency of health- and medical-related helping activities for their care recipient. Multidimensional health indicators included self-reported fatigue, sleep disturbance, physical functioning, pain interference, general health, and the number of chronic conditions from the electronic health records. Self-reported health promotion behaviors were assessed as health responsibility, physical activity, nutrition, interpersonal relations, and stress management. Results: Two distinct caregiving intensity patterns, high-intensity (37.5%) and low-intensity (62.5%) caregiving, were identified with cluster analysis. Caregivers in the high-intensity caregiving cluster reported feeling more tired (tâ =â 2.25, pâ <â .05), experiencing more sleep disturbance (tâ =â 3.06, pâ <â .01), and performing less physical activity (tâ =â 2.05, pâ <â .05) compared with caregivers in the low-intensity group. Discussion and Implications: Future studies are needed to develop effective interventions to address caregiving intensity and its consequences on the health of spousal caregivers of persons with dementia.
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BACKGROUND: Postoperative delirium is prevalent in older adults and has been shown to increase the risk of long-term cognitive decline. Plasma biomarkers to identify the risk for postoperative delirium and the risk of Alzheimer's disease and related dementias are needed. METHODS: This biomarker discovery case-control study aimed to identify plasma biomarkers associated with postoperative delirium. Patients aged ≥65 years undergoing major elective noncardiac surgery were recruited. The preoperative plasma proteome was interrogated with SOMAmer-based technology targeting 1433 biomarkers. RESULTS: In 40 patients (20 with vs. 20 without postoperative delirium), a preoperative panel of 12 biomarkers discriminated patients with postoperative delirium with an accuracy of 97.5%. The final model of five biomarkers delivered a leave-one-out cross-validation accuracy of 80%. Represented biological pathways included lysosomal and immune response functions. CONCLUSION: In older patients who have undergone major surgery, plasma SOMAmer proteomics may provide a relatively non-invasive benchmark to identify biomarkers associated with postoperative delirium.
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Delírio , Delírio do Despertar , Humanos , Idoso , Delírio/diagnóstico , Delírio/etiologia , Complicações Pós-Operatórias , Estudos de Casos e Controles , Proteômica , BiomarcadoresRESUMO
Background and Objectives: Many older adults adopt equipment to address physical limitations and reduce dependence on others to complete basic activities of daily living. Although a few prior studies have considered injuries associated with assistive devices for older adults, those studies focused on older adults' health and functional risks for injury. There is limited analysis of older adult injuries involving defective or malfunctioning assistive devices. Research Design and Methods: Data from this study are from the National Electronic Surveillance System All Injury Program which collected data on consumer product-related injuries from a probability sample of 66 hospital Emergency Departments across the United States. Data from 30 776 older adult Emergency Department (ED) injury narratives from 2016 to 2020 were coded according to the assistive device involved and whether malfunctioning led to the injury. The study team manually examined all narratives in which the assistive device was coded to have malfunctioned. Results: A total of 10 974 older adult ED cases were treated for 12 488 injuries involving a defective device. Injuries included 4 212 head and neck injuries (eg, concussion), 4 317 trunk injuries (eg, hip fractures), and 3 959 arm or leg injuries (eg, leg fracture). Of these patients, 4 586 were admitted to a hospital ward for further evaluation and treatment. Seventy percent of these patients were injured while using a walker; in contrast, wheelchairs were implicated in only 4% of the above cases. Design flaws were identified in 8 158 cases and part breakage/decoupling incidents in 2 816 cases. Discussion and Implications: Our findings provide evidence that assistive devices are actively involved in older adult injuries. Further research is needed to reduce injuries associated with assistive devices by educating patients and their careproviders about device use and assembly and developing effective methods for informing manufacturers about malfunctioning devices.
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OBJECTIVES: Prior studies reported incidence of hypoactive and hyperactive subtypes of postoperative delirium, but did not consider cognitive symptoms of delirium which are highlighted in the DSM-5 criteria for delirium. This study aims to address this gap in the literature by classifying cases of delirium according to their constellation of cognitive and motoric symptoms of delirium using a statistical technique called Latent Class Analysis (LCA). METHODS: Data were from five independent study cohorts (N = 1968) of patients who underwent elective spine, knee/hip, or elective gastrointestinal and thoracic procedures, between 2001 and 2017. Assessments of delirium symptoms were conducted using the long form of the Confusion Assessment Method (CAM) pre- and post-surgery. Latent class analyses of CAM data from the first 2 days after surgery were conducted to determine subtypes of delirium based on patterns of cognitive and motoric symptoms of delirium. We also determined perioperative patient characteristics associated with each latent class of delirium and assessed whether the length of delirium for each of the patterns of delirium symptoms identified by the latent class analysis. RESULTS: The latent class model from postoperative day 1 revealed three distinct patterns of delirium symptoms. One pattern of symptoms, denoted as the Hyperalert class, included patients whose predominant symptoms were being hyperalert or overly sensitive to environmental stimuli and having a low level of motor activity. Another pattern of symptoms, denoted as the Hypoalert class, included patients whose predominant symptom was being hypoalert (lethargic or drowsy). A third pattern of symptoms, denoted as the Cognitive Changes class, included patients who experienced new onset of disorganized thinking, memory impairment, and disorientation. Among 352 patients who met CAM criteria for delirium on postoperative day 1, 34% had symptoms that fit within the Hyperalert latent class, 39% had symptoms that fit within the Hypoalert latent class, and 27% had symptoms that fit within the Cognitive Changes latent class. Similar findings were found when latent class analysis was applied to those who met CAM criteria for delirium on postoperative day 2. Multinomial regression analyses revealed that ASA class, surgery type, and preoperative cognitive status as measured by the Telephone Interview for Cognitive Status (TICS) scores were associated with class membership. Length of delirium differed between the latent classes with the Cognitive Changes latent class having a longer duration compared to the other two classes. CONCLUSIONS: Older elective surgery patients who did not have acute events or illnesses or a diagnosis of dementia prior to surgery displayed varying symptoms of delirium after surgery. Compared to prior studies that described hypoactive and hyperactive subtypes of delirium, we identified a novel subtype of delirium that reflects cognitive symptoms of delirium. The three subtypes of delirium reveal distinct patterns of delirium symptoms which provide insight into varying risks and care needs of patients with delirium, indicating the necessity of future research on reducing risk for cognitive symptoms of delirium.