Interplay Between Adiponectin, Resistin, Lipoprotein (A) and Prognosis in Middle to old age Female Cases with ST / Non ST Elevation Myocardial Infarction
Bibliographic record
Abstract
Acute myocardial infarction (AMI) refers to ST-elevated myocardial infarction and non ST elevation myocardial infarction, is the known presentation of coronary artery disease. Study was planned to explore the interplay of the adipokines, resistin / lipoprotein (a) and prognosis in middle to old age female patients with ST / Non ST Elevation Myocardial Infarction. Material and Methods: A cross-sectional study was conducted on 150 middle to old age female patients with acute myocardial infarction (AMI). Consented patients were divided into 2 groups based on ST and Non ST elevation. Duration of study was six months from December 2015 to May 2016. Levels of adiponectin, lipoprotein (a) and resistin were measured. 50 healthy subjects matched for age and gender also participated in study. Results: Mean age of patients with NSTEMI was 58.89 while with STEMI was 50.59 years. Decreased levels of serum adinopectin, resistin and lipoprotein A was observed in female patients with NSTEMI in comparison with these parameters of STEMI, but significantly high level was seen in context of resistin. Positive correlation of age with serum adiponectin and resistin and a negative correlation of age with serum lipoprotein (a) was in female patients with STEMI and NSTEMI. Conclusion: Study found a direct interaction of adiponectin and resistin with strong prognosis of ST and weak prognosis of Non ST elevation of myocardial infarction; whereas lipoprotein (a) showed a strong indirect interaction with age in women with both STEMI and NSTEMI. Keywords: Adiponectin, lipoprotein (a), resistin, STEMI and NSTEMI.
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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 | 0.000 |
| 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) | 0.001 | 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".