Takotsubo syndrome and estrogen receptor genes
Bibliographic record
Abstract
AIMS: We aimed to analyze genetic polymorphism of estrogen receptor (ESR) 1 and ESR2 in a series of postmenopausal women with Takotsubo syndrome (TS). METHODS: In total, 81 consecutive white women were prospectively enrolled: 22 with TS (TS group; mean age 71.2 ± 9.8 years), 22 with acute myocardial infarction (MI group; mean age 73.2 ± 8 years), and 37 asymptomatic healthy controls (CTRL group; mean age 69 ± 4.2 years). Genotyping of ESR1 -397C>T (rs2234693) and -351A>G (rs9340799) and ESR2 -1839G>T (rs 1271572) and 1082G>A (rs1256049) genetic variants was performed. We estimated the odds ratio (OR) between the genotype of each examined locus with the occurrence of TS or MI. RESULTS: The risk of experiencing TS was higher for those study participants carrying the T allele at the rs2234693 locus of the ESR1 gene [OR: 2.0, 95% confidence interval (CI): 0.973-4.11, P = 0.04, TS vs. MI + CTRL; OR: 2.79, 95% CI: 1.17-6.64, P = 0.016, TS vs. MI alone]. Women carrying a T allele at the rs1271572 locus of the ESR2 gene demonstrated an even higher risk (OR: 3.23, 95% CI: 1.55-6.73, P = 0.0019, TS vs. MI + CTRL; OR: 9.13, 95% CI: 2.78-29.9, P = 0.0001, TS vs. MI alone). CONCLUSION: The study reports preliminary findings suggesting a possible link between ESR polymorphisms and the occurrence of TS. Larger studies are needed to confirm our results.
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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".