EXTERNAL VALIDATION OF SAFES 6-WEEK MORTALITY-RISK INDEX ON AN AFRO-CARIBBEAN OLDER PATIENTS COHORT
Bibliographic record
Abstract
Geriatric guidelines recommend considering prognosis in the context of clinical decision making. Several mortality-risk indexes have been developed. While external validation is a recognized crucial step before implementation in clinical practice, few of these indexes have actually been externally validated. Our aim was to test the external validity of the SAFEs (Sujets Ages Fragiles: Evaluation et suivi) 6-week mortality-risk index developed from a multicentre prospective French cohort on an Afro-Caribbean cohort of older patients. This cohort was collected through a prospective study of 287 patients from the University Hospital of Martinique (French West Indies) from January to June 2012. Patients 75+ hospitalized for an acute condition were eligible. The SAFEs 6-week mortality-risk index of each patient was collected. It included assessments of delirium, risk of malnutrition and functional impairment. Mean age was 86 years. Six-week mortality rate was 19.9%, 52.1% were severely dependant for activities of daily living, 96.1% were at risk of malnutrition, 16.0% had a delirium. The external validity of the SAFEs 6-week mortality-risk index was poor in terms of calibration and discrimination: observed and predicted probability of mortality differed of more than 10% for two out of three risk levels, and the area under the receiver operating curve was 0.58 [0.49–0.66]. Our results corroborate a recent literature review on external validation of risk prediction models showing that external validation is rarely done and often leads to poor results when performed. Clinicians should be aware of these limitations and exercise caution before implementing prognostic indexes in their practice.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".