69 research outputs found
Multimorbidity and long-term disability and physical functioning decline in middle-aged and older Americans: an observational study.
BACKGROUND
Multimorbidity is highly prevalent and associated with several adverse health outcomes, including functional limitations. While maintaining physical functioning is relevant for all adults, identifying those with multimorbidity at risk for faster rates of physical functioning decline may help to target interventions to delay the onset and progression of disability. We quantified the association of multimorbidity with rates of long-term disability and objective physical functioning decline.
METHODS
In the Health and Retirement Study, we computed the Multimorbidity-Weighted Index (MWI) by assigning previously validated weights (based on physical functioning) to each chronic condition. We used an adjusted negative binomial regression to assess the association of MWI with disability (measured by basic and instrumental activities of daily living [ADLs, IADLs]) over 16 years, and linear mixed effects models to assess the association of MWI with gait speed and grip strength over 8 years.
RESULTS
Among 16,616 participants (mean age 67.3, SD 9.7 years; 57.8% women), each additional MWI point was associated with a 10% increase in incidence rate of disability (IRR: 1.10; 95%CI: 1.09, 1.10). In 2,748 participants with data on gait speed and grip strength, each additional MWI point was associated with a decline in gait speed of 0.004 m/s (95%CI: -0.006, -0.001). The association with grip strength was not statistically significant (-0.01 kg, 95%CI: -0.73, 0.04). The rate of decline increased with time for all outcomes, with a significant interaction between time and MWI for disability progression only.
CONCLUSION
Multimorbidity, as weighted on physical functioning, was associated with long-term disability, including faster rates of disability progression, and decline in gait speed. Given the importance of maintaining physical functioning and preserving functional independence, MWI is a readily available tool that can help identify adults to target early on for interventions
Definition of patient complexity in adults: A narrative review.
Background: Better identification of complex patients could help to improve their care. However, the definition of patient complexity itself is far from obvious. We conducted a narrative review to identify, describe, and synthesize the definitions of patient complexity used in the last 25 years.
Methods: We searched PubMed for articles published in English between January 1995 and September 2020, defining patient complexity. We extended the search to the references of the included articles. We assessed the domains presented in the definitions, and classified the definitions as based on (1) medical aspects (e.g., number of conditions) or (2) medical and/or non-medical aspects (e.g., socio-economic status). We assessed whether the definition was based on a tool (e.g., index) or conceptual model.
Results: Among 83 articles, there was marked heterogeneity in the patient complexity definitions. Domains contributing to complexity included health, demographics, behavior, socio-economic factors, healthcare system, medical decisionmaking, and environment. Patient complexity was defined according to medical aspects in 30 (36.1%) articles, and to medical and/or non-medical aspects in 53 (63.9%) articles. A tool was used in 36 (43.4%) articles, and a conceptual model in seven (8.4%) articles.
Conclusion: A consensus concerning the definition of patient complexity was lacking. Most definitions incorporated nonmedical factors in the definition, underlining the importance of accounting not only for medical but also for non-medical aspects, as well as for their interrelationship
Outcome Measures for Interventions to Reduce Inappropriate Chronic Drugs: A Narrative Review
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/163374/3/jgs16697-sup-0001-Supinfo.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163374/2/jgs16697_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/163374/1/jgs16697.pd
Risk factors for falls among hospitalized medical patients - A systematic review and meta-analysis.
OBJECTIVE
To identify and quantify risk factors for in-hospital falls in medical patients.
DATA SOURCES
Six databases (MEDLINE, Embase, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, CINAHL, and Google Scholar) were systematically screened until April 11, 2023, to identify relevant articles.
STUDY SELECTION
All titles and abstracts of the retrieved articles were independently screened by two researchers who also read the full texts of the remaining articles. Quantitative studies that assessed risk factors for falls among adult patients acutely hospitalized were included in the review. Publications that did not capture internal medicine patients or focused on other specific populations were excluded.
DATA EXTRACTION
Information on study characteristics and potential risk factors were systematically extracted. Risk of bias was assessed using the Quality in Prognosis Studies (QUIPS) tool. PRISMA and MOOSE guidelines were followed for reporting.
DATA SYNTHESIS
The main outcome was any in-hospital falls. Using a random-effects meta-analysis model, association measures for each risk factor reported in five or more studies were pooled. Separate analyses according to effect measure and studies adjusted for sex and age at least were performed. Of 5,067 records retrieved, 119 original publications from 25 countries were included. In conclusion, 23 potential risk factors were meta-analyzed. Strong evidence with large effect sizes was found for a history of falls (OR 2.54; 95% CI 1.63- 3.96; I2 91%), antidepressants (pooled OR 2.25; 95% confidence interval [95% CI] 1.92-2.65; I2 0%), benzodiazepines (OR 1.97; 95% CI 1.68-2.31; I2 0%), hypnotics-sedatives (OR 1.90; 95% CI 1.53-2.36; I2 46%), and antipsychotics (OR 1.61; 95% CI 1.33-1.95; I2 0%). Furthermore, evidence of associations with male sex (OR 1.22, 95% CI 0.99-1.50, I2 65%) and age (OR 1.17, 95% CI 1.02-1.35, I2 72%) were found, but effect sizes were small.
CONCLUSIONS
The comprehensive list of risk factors, which specifies the strength of evidence and effect sizes, could assist in the prioritization of preventive measures and interventions
HOSPITAL Score and LACE Index to Predict Mortality in Multimorbid Older Patients.
BACKGROUND
Estimating life expectancy of older adults informs whether to pursue future investigation and therapy. Several models to predict mortality have been developed but often require data not immediately available during routine clinical care. The HOSPITAL score and the LACE index were previously validated to predict 30-day readmissions but may also help to assess mortality risk. We assessed their performance to predict 1-year and 30-day mortality in hospitalized older multimorbid patients with polypharmacy.
METHODS
We calculated the HOSPITAL score and LACE index in patients from the OPERAM (OPtimising thERapy to prevent Avoidable hospital admissions in the Multimorbid elderly) trial (patients aged ≥ 70 years with multimorbidity and polypharmacy, admitted to hospital across four European countries in 2016-2018). Our primary and secondary outcomes were 1-year and 30-day mortality. We assessed the overall accuracy (scaled Brier score, the lower the better), calibration (predicted/observed proportions), and discrimination (C-statistic) of the models.
RESULTS
Within 1 year, 375/1879 (20.0%) patients had died, including 94 deaths within 30 days. The overall accuracy was good and similar for both models (scaled Brier score 0.01-0.08). The C-statistics were identical for both models (0.69 for 1-year mortality, p = 0.81; 0.66 for 30-day mortality, p = 0.94). Calibration showed well-matching predicted/observed proportions.
CONCLUSION
The HOSPITAL score and LACE index showed similar performance to predict 1-year and 30-day mortality in older multimorbid patients with polypharmacy. Their overall accuracy was good, their discrimination low to moderate, and the calibration good. These simple tools may help predict older multimorbid patients' mortality after hospitalization, which may inform post-hospitalization intensity of care
Drug-related readmissions in older hospitalized adults: External validation and updating of OPERAM DRA prediction tool.
BACKGROUND
Drug-related readmissions (DRAs) are defined as rehospitalizations with an adverse drug event as their main or significant contributory cause. DRAs represent a major adverse health burden for older patients. A prediction model which identified older hospitalized patients at high risk of a DRA <1 year was previously developed using the OPERAM trial cohort, a European cluster randomized controlled trial including older hospitalized patients with multimorbidity and polypharmacy. This study has performed external validation and updated the prediction model consequently.
METHODS
The MedBridge trial cohort (a multicenter cluster randomized crossover trial performed in Sweden) was used as a validation cohort. It consisted of 2516 hospitalized patients aged ≥65 years. Model performance was assessed by: (1) discriminative power, assessed by the C-statistic with a 95% confidence interval (CI); (2) calibration, assessed by visual examination of the calibration plot and use of the Hosmer-Lemeshow goodness-of-fit test; and (3) overall accuracy, assessed by the scaled Brier score. Several updating methods were carried out to improve model performance.
RESULTS
In total, 2516 older patients were included in the validation cohort, of whom 582 (23.1%) experienced a DRA <1 year. In the validation cohort, the original model showed a good overall accuracy (scaled Brier score 0.03), but discrimination was moderate (C-statistic 0.62 [95% CI 0.59-0.64]), and calibration showed underestimation of risks. In the final updated model, the predictor "cirrhosis with portal hypertension" was removed and "polypharmacy" was added. This improved the model's discriminative capability to a C-statistic of 0.64 (95% CI 0.59-0.70) and enhanced calibration plots. Overall accuracy remained good.
CONCLUSIONS
The updated OPERAM DRA prediction model may be a useful tool in clinical practice to estimate the risk of DRAs in older hospitalized patients subsequent to discharge. Our efforts lay the groundwork for the future development of models with even better performance
Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study.
BACKGROUND
For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal.
METHODS
This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions.
RESULTS
Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44).
CONCLUSIONS
Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate
Feasibility and Acceptability of an INtervention TO Increase MOBility in Older Hospitalized Medical Patients (INTOMOB): A Mixed-Methods Pilot Study.
Background: To reduce adverse outcomes of low hospital mobility, we need interventions that are scalable in everyday practice. This study assessed the feasibility and acceptability of the INTOMOB multilevel intervention addressing barriers to hospital mobility without requiring unavailable resources. Methods: The INTOMOB intervention, targeting older patients, healthcare professionals (HCPs) and the hospital environment, was implemented on acute general internal medicine wards of three hospitals (12/2022-03/2023). Feasibility and acceptability of the intervention were assessed and two types of accelerometers compared in a mixed methods study (patient and HCP surveys and interviews). Quantitative data were analyzed descriptively and qualitative data using a deductive approach. Results were integrated through meta-inferences. Results: Of 20 patients (mean age 74.1 years), 90% found the intervention helpful and 82% said the environment intervention (posters) stimulated mobility. The majority of 44 HCPs described the intervention as clear and helpful. There was no major implementation or technical issue. About 60% of patients and HCPs preferred a wrist-worn over an ankle-worn accelerometer. Conclusions: The INTOMOB intervention is feasible and well accepted. Patients' and HCPs' feedback allowed to further improve the intervention that will be tested in a cluster randomized trial and provides useful information for future mobility-fostering interventions
Comparison of 6 Mortality Risk Scores for Prediction of 1-Year Mortality Risk in Older Adults With Multimorbidity.
Importance
The most appropriate therapy for older adults with multimorbidity may depend on life expectancy (ie, mortality risk), and several scores have been developed to predict 1-year mortality risk. However, often, these mortality risk scores have not been externally validated in large sample sizes, and a head-to-head comparison in a prospective contemporary cohort is lacking.
Objective
To prospectively compare the performance of 6 scores in predicting the 1-year mortality risk in hospitalized older adults with multimorbidity.
Design, Setting, and Participants
This prognostic study analyzed data of participants in the OPERAM (Optimising Therapy to Prevent Avoidable Hospital Admissions in Multimorbid Older People) trial, which was conducted between December 1, 2016, and October 31, 2018, in surgical and nonsurgical departments of 4 university-based hospitals in Louvain, Belgium; Utrecht, the Netherlands; Cork, Republic of Ireland; and Bern, Switzerland. Eligible participants in the OPERAM trial had multimorbidity (≥3 coexisting chronic diseases), were aged 70 years or older, had polypharmacy (≥5 long-term medications), and were admitted to a participating ward. Data were analyzed from April 1 to September 30, 2020.
Main Outcomes and Measures
The outcome of interest was any-cause death occurring in the first year of inclusion in the OPERAM trial. Overall performance, discrimination, and calibration of the following 6 scores were assessed: Burden of Illness Score for Elderly Persons, CARING (Cancer, Admissions ≥2, Residence in a nursing home, Intensive care unit admit with multiorgan failure, ≥2 Noncancer hospice guidelines) Criteria, Charlson Comorbidity Index, Gagné Index, Levine Index, and Walter Index. These scores were assessed using the following measures: Brier score (0 indicates perfect overall performance and 0.25 indicates a noninformative model); C-statistic and 95% CI; Hosmer-Lemeshow goodness-of-fit test and calibration plots; and sensitivity, specificity, and positive and negative predictive values.
Results
The 1879 patients in the study had a median (IQR) age of 79 (74-84) years and 835 were women (44.4%). The median (IQR) number of chronic diseases was 11 (8-16). Within 1 year, 375 participants (20.0%) died. Brier scores ranged from 0.16 (Gagné Index) to 0.24 (Burden of Illness Score for Elderly Persons). C-statistic values ranged from 0.62 (95% CI, 0.59-0.65) for Charlson Comorbidity Index to 0.69 (95% CI, 0.66-0.72) for the Walter Index. Calibration was good for the Gagné Index and moderate for other mortality risk scores.
Conclusions and Relevance
Results of this prognostic study suggest that all 6 of the 1-year mortality risk scores examined had moderate prognostic performance, discriminatory power, and calibration in a large cohort of hospitalized older adults with multimorbidity. Overall, none of these mortality risk scores outperformed the others, and thus none could be recommended for use in daily clinical practice
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