Caracterización de pacientes con enfermedad cerebrovascular isquémica y deterioro cognitivo. Cienfuegos, 2018
Bibliographic record
Abstract
Foundation: cerebrovascular disease occupies the third place as a cause of death to be overcome only by cardiovascular diseases and cancer. It constitutes the first cause of permanent disability in the adult and the second of dementia. Objective: to characterize patients with cerebrovascular disease and cognitive disorder. Methods: an observational, descriptive, cross-sectional study, carried out in the Neurology Service of the Gustavo Aldereguia Lima Hospital in Cienfuegos, which included 27 patients hospitalized in this center, with cognitive impairment, after the first event of ischemic cerebrovascular disease. The variables were analyzed: sex, age, skin color, schooling, occupation, marital status, origin, toxic habits, personal pathological history, type of cerebrovascular disease, affected brain structure, cognitive impairment (using the minimum Folstein mental state test and the Montreal cognitive assessment test), neuropsychological alterations, depression (using the Yessavage geriatric depression scale). Results: Elderly adults, male sex and white skin color predominated, as well as low level of schooling and singles. The atherothrombotic ischemic event was the most common and the right hemisphere the most affected. There was cognitive impairment in all patients. The risk factors mostly associated with the disease were high blood pressure, diabetes mellitus and smoking. The majority of patients did not suffer depression after cerebral infarction. Conclusions: older, single adults are more likely to suffer strokes. The low educational level may be a factor associated to cognitive impairment after this disease, but depression that does not always manifests deeply.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.005 | 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".