Erektil Disfonksiyon Kardiyovasküler Hastalığın Erken Habercisi Olabilir mi
Bibliographic record
Abstract
Objectives: Our aim was to evaluate cardiovascular health who applied to our clinic for erectile dysfunction. These patients neither had any history of cardiovascular disease nor used medical or surgical treatment for atherosclerotic coronary artery disease. Material and Methods: 100 male patients had been included for this study that were applied to our clinic for erectile dysfunction and planned to be started sildenafil sitrate. As a diagnosis criteria we used the first 5 questions of International Index for Erectile Function and the patients whose score was below 21, were included to our study. We performed blood chemistry, profile of hormones and penile doppler ultrasonography to all patients. The patients had been performed holter monitorisation. Electrocardiography, ecocardiography, myocard perfusion sintigraphy with talium and coronary angiography were performed to the patients according to neccessity who had ST segment depression seems to be ischemia. Results: Mean ages of patients were 50.0±13.0 (22-76). Further investigations were performed to 40 patients who had ST depression seems to be ischemia according to the results of Holter Monitorisation. According to the results of these investigations 3 patients were (3%) transferred for coronary bypass operation. 25 patients (25%) have been diagnosed as atherosclerotic coronary artery disease and medical treatment was started to these patients. Conculation: ED patients with no history of symptomatic cardiovascular disease may have atherosclerotic coronary artery disease with significiant rates. Therefore, ED may be an early predictor for cardiovascular disease in many patients and we believe that these patients should be investigated carefully about cardiovascular diseases. ©2007, Firat University, Medical Faculty
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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; both teacher heads 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".