Health-Related Quality of Life in Stroke Survivors at the University Hospital of the West Indies
Bibliographic record
Abstract
Background: Stroke remains a major contributor to mortality and morbidity both locally and globally. To date, there has been no study examining the impact of stroke on quality of life (QOL) in the Jamaican population. Our study was the first to look at QOL among Jamaican stroke survivors across the vast spectrum of stroke severity ranging from mild to severe. We also aimed to identify variables that led to decreased QOL in this cohort when compared to healthy adults. Methods: This was a hospital-based case-control study comparing the QOL of 50 stroke patients admitted to the University Hospital of the West Indies (UHWI) in Jamaica between 2012 and 2013 to that of 50 apparently healthy adults (AHAs). Stroke severity was calculated using the National Institutes of Health stroke scale (NIHSS) at admission. The health-related quality of life in stroke patients (HRQOLISP) tool was used to attain the QOL score in each group. Results: Of the 108 patients that were coded as having an acute ischemic stroke in the year 2012, 38 (35.1%) were deceased and 20 (18.5%) were lost to follow-up at the time of the study. There was no statistical difference between the stroke group and the AHAs with regard to age, race and traditional risk factors for stroke. Within the stroke population, the mean age was 61 ± 17.8 years. The mean age among the AHAs was 60 ± 13.1 years. Of the stroke survivors, 25 (50%) were male and 25 (50%) were female. Forty-five (90%) patients were hypertensive. Health-related quality of life (HRQOL) was significantly reduced across most domains when compared to AHAs (P = 0.0001). Greater stroke severity, presence of depression and previous stroke were all significantly associated with worse QOL. Conclusions: In Jamaica, HRQOL among stroke survivors at the UHWI is consistently and significantly lower than that of healthy adults. Strategic interventions that target stroke severity, depression and non-adherence to secondary prevention regimens must be implemented in order to improve patient outcomes. J Neurol Res. 2017;7(3):46-58 doi: https://doi.org/10.14740/jnr422w
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".