Systematic Review of the Association of the Hospital Frailty Risk Score with Mortality in Patients with Cerebrovascular and Cardiovascular Disease
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: There is limited systematic data on the association between the Hospital Frailty Risk Score (HFRS) and characteristics and mortality in patients with cerebrovascular and cardiovascular disease (CVD). This systematic review aimed to summarise the use of the HFRS in describing the prevalence of frailty in patients with CVD, the clinical characteristics of patients with CVD, and the association between frailty on the likelihood of mortality in patients with CVD. METHODS: A systematic literature search for observational studies using terms related to CVD, cerebrovascular disease, and the HFRS was conducted using 6 databases in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies were appraised using the Newcastle-Ottawa Scale (NOS). RESULTS: Seventeen observational studies were included, all rated 'good' quality according to the NOS. One study investigated 5 different CVD cohorts (atrial fibrillation (AF), heart failure (HF), hypotension, hypertension, and chronic ischemic heart disease), 1 study investigated 2 different CVD cohorts (AF and acute myocardial infarction (AMI)), 6 studies investigated HF, 3 studies investigated AMI, 4 studies investigated stroke, 1 study investigated AF, and 1 study investigated cardiac arrest. Increasing frailty risk category was associated with increased age, female sex, and non-white racial group across all CVD. Increasing frailty risk category is also associated with increased length of hospital stay, total costs, and increased odds of 30-day all-cause mortality across all CVD. CONCLUSIONS: The HFRS is an efficient and effective tool for stratifying frailty in patients with CVD and predicting adverse health outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it