Quality of Life on Arterial Hypertension: Validity of Known Groups of MINICHAL
Bibliographic record
Abstract
INTRODUCTIONS: In the care of hypertension, it is important that health professionals possess available tools that allow evaluating the impairment of the health-related quality of life, according to the severity of hypertension and the risk for cardiovascular events. Among the instruments developed for the assessment of health-related quality of life, there is the Mini-Cuestionario of Calidad de Vida en la Hipertensión Arterial (MINICHAL) recently adapted to the Brazilian culture. OBJECTIVE: To estimate the validity of known groups of the Brazilian version of the MINICHAL regarding the classification of risk for cardiovascular events, symptoms, severity of dyspnea and target-organ damage. METHODS: Data of 200 hypertensive outpatients concerning sociodemographic and clinical information and health-related quality of life were gathered by consulting the medical charts and the application of the Brazilian version of MINICHAL. The Mann-Whitney test was used to compare health-related quality of life in relation to symptoms and target-organ damage. The Kruskal-Wallis test and ANOVA with ranks transformation were used to compare health-related quality of life in relation to the classification of risk for cardiovascular events and intensity of dyspnea, respectively. RESULTS: The MINICHAL was able to discriminate health-related quality of life in relation to symptoms and kidney damage, but did not discriminate health-related quality of life in relation to the classification of risk for cardiovascular events. CONCLUSION: The Brazilian version of the MINICHAL is a questionnaire capable of discriminating differences on the health-related quality of life regarding dyspnea, chest pain, palpitation, lipothymy, cephalea and renal damage.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".