Prevalence of Metabolic Syndrome X in patients diagnosed with Chronic Kidney Disease undergoing dialysis
Bibliographic record
Abstract
Introduction: Metabolic syndrome X (MSX) encompasses risk factors such as abdominal obesity, hypertension, dyslipidemia, and insulin resistance, which significantly increase cardiovascular morbidity and mortality. In patients with chronic kidney disease (CKD), the presence of MSX is even more relevant, as it accelerates disease progression and increases cardiovascular complications. A retrospective, descriptive study was conducted in which patients treated at the Hemodialysis Unit of Dr. Amador Guerrero Hospital were evaluated, and the presence of cardiovascular risk factors and components of MSX was quantified. Justification: Metabolic syndrome is highly prevalent in patients with chronic kidney disease and increases cardiovascular risk, making its identification essential to improve clinical outcomes. Methodology: Patients with chronic kidney disease undergoing dialysis in the province of Colón during 2005 were studied. Anthropometric and laboratory data were collected, and metabolic syndrome was diagnosed according to the NCEP/ATP III (2005) criteria. Data analysis was performed using EPI-INFO 6.0. Results: A prevalence of 23.7% of MSX was observed among patients treated at the unit. Of these patients, 88.9% presented abdominal obesity and arterial hypertension. However, only abdominal obesity and insulin resistance (measured as fasting hyperglycemia) were statistically significant for the presence of MSX in CKD patients, with reported ORs of 38.4 (95% CI: 3.88379.70, p<0.05) and 6.28 (95% CI: 1.2331.95, p<0.05), respectively. Conclusion: The prevalence of MSX in the studied population was 23.7%. Abdominal obesity and insulin resistance significantly increased the likelihood of MSX. Furthermore, current evidence suggests that genetic variants may predispose CKD patients to the development of MSX, opening new avenues for research.
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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) | 0.001 | 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".