Influence of sociodemographic and clinical characteristics at the impact of valvular heart disease.
Bibliographic record
Abstract
OBJECTIVE: to analyze the sociodemographic and clinical characteristics of patients with valvular heart disease and to verify the influence of these variables on the impact of valve disease in daily life. METHOD: the study involved 86 outpatients. Data collection was performed in two stages - face-to-face interview for sociodemographic and clinical characterization and through telephone contact for the application of the Instrument to Measure the Impact of Valvular Heart Disease on Patient's Everyday Life (IDCV). Data were analyzed through descriptive statistics and multiple regression analysis. RESULTS: it was noticed that the total score of IDCV and its domains were influenced by age, schooling, presence or absence of symptoms, use or not of diuretic. CONCLUSION: The impact of the disease was influenced by sociodemographic and clinical variables. The results provide subsidies for the design of nursing interventions aimed at reducing the impact of the disease on the patient's daily life with valve disease.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".