229 Association of the hospital frailty risk score with outcomes of patients with cardiovascular diseases: a systematic review
Bibliographic record
Abstract
Introduction Data are limited about the association between the Hospital Frailty Risk Score (HFRS) and outcomes in patients with cerebrovascular and cardiovascular disease (CVD). The aim of this systematic review was to summarise the use of the HFRS in describing the prevalence, clinical characteristics and outcomes of patients with CVD, based on their HFRS risk score category. Methods This study was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Terms related to CVD, cerebrovascular disease and the HFRS were used to systematically search 6 electronic databases: MEDLINE, CINAHL, Web of Science, EMBASE, AgeLine and AMED.Studies were appraised using Newcastle-Ottawa Scale (NOS). Results After screening, 17 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 ischaemic 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 HFRS risk category was associated with greater age, female sex, and non-white racial group across all CVD. Increasing HFRS risk category was also associated with increased length of stay in hospital, total inpatient costs and increased likelihood 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 is associated with adverse health outcomes. Conflict of Interest None
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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 | 0.009 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".