Bibliographic record
Abstract
Topic: Arrhythmias, General OtherThe metabolic syndrome (MetS) is characterized by a cluster of atherosclerotic risk factors, including obesity, hypertension (HTA), insulin resistance and dyslipidemia.Objective: To determine the presence and frequency of cardiac arrhythmias in individuals with obesity and metabolic syndrome.Methods: The study included 150 subjects divided into two groups (mean age 56,78Æ9,34; 88 women, 62 men).The first group consisted of patients with MetS based on the criteria of the International Diabetes Federation, n=100; the second control group healthy subjects, n=50.For all patients was determined: anamnesis, physical examination, anthropometric measurements, continuous 24-h ambulatory ECG monitoring, exercise stress test, echocardiography, blood chemistry.Results: The presence of MetS components is statistically more frequent in first group than in the control group (p<0.001).In the first group the most prevalent MetS components were waist circumference and HTA (100%), in the control group elevated triglycerides (56%).Heart rhythm disorders were registered in 44 (29.33%) of all respondents.Heart rhythm disorders were more often in the first compared to second group, a statistically significant permanent AF(p<0.05),paroxysmal AF(p<0.01) and ventricular arrhythmia (VA) p<0.001.Number of respondents with one of the tested disorder was significantly higher in the study compared to the control group (p<0.001).Results of univariate regression analysis showed that obesity increases the probability for the occurrence of AF 3.61 times (IP 1,12-11,65), increasing BMI for one unit of measurement by 15% (IP 1,02-1,29), and increasing the number of components of MS by 73% (IP 1,07-2,82).Age, obesity (BMI!30) and the number of components of MetS were determined to be significant predictors for occurrence of VA.With statistical significance of p<0.05 the probability for the occurrence of VA in obese grows 3.52 times (IP 1,31-9,45), with increase the number of MetS components for one the probability for the occurrence of the VA grows 55% (IP 1,06-2,27).Conclusion: Atrial and ventricular heart rhythm disorders were more common in patients with MetS compared to healthy subjects, a statistically significant permanent AF, paroxysmal AF and VA.The most important parameters for the occurrence of AF and VA were obesity and the number of components of MetS.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.684 | 0.480 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".