Metabolic Syndrome and Its Components in Individuals Undergoing Rehabilitation After Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: : Individuals participating in stroke rehabilitation are in jeopardy of future vascular events, including a second stroke. Nevertheless, vascular risk assessment is often overlooked in this population. Metabolic syndrome (MetS) may be a useful construct for risk assessment because of its predictive ability in distinguishing patients who are at high risk of future morbidity. This study documented the prevalence of MetS and its components in stroke rehabilitation patients. In addition, clinical characteristics of subgroups with and without MetS were compared. METHODS: : Health records of 200 adult patients who had participated in inpatient stroke rehabilitation were reviewed. The prevalence and extent of clustering of the five components of MetS-obesity, hypertension, hypertriglyceridemia, low high-density lipoprotein cholesterol, and insulin resistance-were examined. RESULTS: : Of the total sample, 61% had MetS and 97% had at least one MetS component, with hypertension and low high-density lipoprotein cholesterol being the most prevalent. The number of comorbidities, number of prescription drugs, and history of coronary heart disease were positively related to the presence of MetS. The components were predicted by a single underlying factor, providing support for the validity of using the MetS construct to assess vascular risk in this population. DISCUSSION AND CONCLUSIONS: : Awareness of the high prevalence of MetS in individuals undergoing stroke rehabilitation should motivate physical therapists and other rehabilitation clinicians to intervene to prevent the recurrence of vascular events. Early screening for this high-risk condition and implementation of targeted interventions to reduce future vascular morbidity should become priorities in stroke rehabilitation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".