Characterization of users of Santa Maria Maior continuous care unit (CCU) and social response after discharge of users with cerebrovascular accident (CVA)
Bibliographic record
Abstract
Introduction The stroke is a neurological disease caused by the sudden decrease in blood supply to a particular brain region. It is a state of medical emergency and, in Portugal, is the leading cause of death. Objective To identify the social responses after discharge of stroke patients Methods A cross-sectional, quantitative, observational and descriptive study was developed. This study was conducted at a Continuous Care and Long Term Maintenance Unit. A sample of 222 patients admitted over the period December 2008 to November 2013 was selected. Data collection was made, using Gestcare Integrated Continuous Care, in the last quarter of 2013, after authorization granted by the responsible Unit. Results Of the 222 patients, 79 were admitted to the CCU with the diagnosis of stroke, noting this pathology a prevalence of 35.6% during the analysis period. From the total CVA patients, the majority were male (53.2%), lived in rural areas (61.3%) and had family support (78.5%). Their ages ranged from 48 years to 95 years old. Patients after discharge, had the following destinations: 25.3% were transferred to other units to receive more specialized care; 24.1% patients enrolled in a nursing home; 13.9% returned to the home with family support; 8.9% patients returned to their home with support of a home care; 3.8% patients went to a foster family and, the remaining (24,1%), died. Conclusions The family plays a key role in supporting the patient. However, there is also the need for institutions and social support services that meet and complement the needs of the patient and family.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".