SCORE model underestimates cardiovascular risk in hypertensive patients: Results of the Polish Hypertension Registry
Bibliographic record
Abstract
OBJECTIVE. The aim of the present study was to compare the effectiveness of Systemic COronary Risk Evaluation (SCORE) charts and European Society of Hypertension/European Society of Cardiology (ESH/ESC) hypertension guidelines for identifying high-risk hypertensive patients. METHODS. The data on hypertensive patients was collected using the Polish Hypertension Registry. We enrolled 636 patients (357 females and 279 males, mean age 54.4 (+/-) 7.9 years) from hypertension centres in Poland. RESULTS. Only 3.5% of the subjects had no additional risk factors. Thirty-six per cent of the patients had three or more risk factors. Metabolic syndrome was found in 40.1% of the patients. According to the SCORE charts, 9.0% of females and 27.2% of males had high to very high cardiovascular risk (p < 0.001). Taking into account risk factors and the metabolic syndrome, 55.7% of females and 56.3% of males (p = NS) had high or very high additional cardiovascular risk according to the 2007 ESH/ESC guidelines. For both females and males, the prevalence of high to very high risk was greater (p < 0.001) from the calculation based on the 2007 ESH/ESC guidelines than from the SCORE charts. Fifty-two per cent of patients classified as low to moderate risk according to the SCORE system, had high or very high risk according to the 2007 ESH/ESC guidelines. CONCLUSIONS. The SCORE charts seem to underestimate the burden of the cardiovascular risk among hypertensive patients. The cardiovascular risk, especially in the hypertensive female population, seems to be much higher when estimated according to the 2007 ESH/ESC guidelines.
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 | 0.006 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".