A multicomponent de-frailing intervention for hospitalized cardiac patients
Bibliographic record
Abstract
Background: The aging population presents increasing challenges for healthcare professionals to treat patients in the context of both health and function. Frailty is a reversible geriatric syndrome, which refers to the body’s inability to maintain homeostasis in the face of stressors and increases risk for the development of adverse health outcomes or death. Patients with cardiovascular disease (CVD), one of the top causes of death worldwide, are disproportionately impacted by frailty. Hospitalization itself is an important stressor that may lead to the exacerbation or development of frailty due to factors such as bedrest, undernutrition, cognitive stress, and frequent tests/procedures. The purpose of this thesis is to review the literature to understand pathophysiological connections between frailty and CVD and to assess the existing interventions for de-frailing hospitalized older adults with CVD, and to present the results of a randomized clinical trial assessing a novel technique to treat frailty in CVD inpatients.Methods: A literature review was performed on the pathophysiological connections between frailty and CVD, as well as to review existing hospital interventions to treat frailty in CVD patients. Subsequently, a randomized clinical trial (TARGET-EFT) was conducted in the acute cardiology ward at the Jewish General Hospital (Montreal, Canada) to test the effect of a targeted multicomponent de-frailing intervention in hospitalized older adults with CVD. The intervention consisted of physical exercise, cognitive stimulation, protein supplementation and anemia correction. The control group received usual clinical care. Outcomes of interest were physical frailty and functional status at discharge from the hospital and 30 days later, measured using the Short Physical Performance Battery (SPPB) and the SARC-F sarcopenia/strength questionnaire.Results: TARGET-EFT was the first trial to study and successfully de-frail older adults hospitalized with CVD. The analysis consisted of n=135 patients (n=66 in the intervention group and n=69 in the control group), with a mean age of 79.3 ± 7.7 years and 54% females, who survived and completed the frailty assessments. The average post-randomization length of stay of patients was 11.0 ± 11.7 days, and the most common reasons for admission were evenly distributed between ischemic heart disease and heart failure, followed by arrhythmia and valvular heart disease. Patients in the intervention group showed a significant 1.52-point improvement in the SPPB at discharge and maintained these benefits in a short-term follow-up 30 days later, as evidenced by a significant 0.74-point improvement in the SARC-F questionnaire. There were no intervention-related adverse events. Subgroup analyses demonstrated that patients with low left ventricular ejection fraction had significantly attenuated benefits, and patients who underwent invasive cardiac procedures derived significantly greater benefits from the intervention.Conclusions: Our multi-component de-frailing intervention with physical, cognitive, nutritional and anemia components was safe and feasible for hospitalized CVD patients. Furthermore, the intervention led to clinically meaningful improvements in frailty and physical function. The integration of this intervention into usual clinical care is expected to lead to subsequent improvements in the post-hospitalization quality of life of cardiac patients
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".