A Comparison of Two Electrophysiology Centers in Different Social And Economic Regions Of Turkey During First Quarter of the Year
Bibliographic record
Abstract
Introduction: More and more patients have been undergoing electrophysiological study (EPS) as the number of rhythmologists have increased. Due to the increased interest in the study, today EPS applications are made even in second step public hospitals or private hospitals. Our aim is to compare two electrophysiology labs, that are in different regions with social and economic development, in terms of patient demography, diagnosis, amount of diagnostic and curative interventions. Materials and Methods: In this study, two centers from two different regions of Turkey were selected; a training and research center (center 1) in the Western part and a public hospital (center 2) in the Eastern part of the country. Records of the patients who undergone EPS in these two centers were retrospectively analyzed. Independent parametric data were evaluated by T-test, and categorical data via Mann-Whitney U test. A p value below 0.05 was accepted for significance. Results: A total of 83 patients were retrospectively analyzed (42 from center 1, 41 from center 2). Patients’ baseline demographic data was similar except intellectual status. Nevertheless, both groups differed based on the number of patients with diagnosis of atrioventricular reciprocating tachycardia (p=0.047). There was a significant difference in procedure types. Center 1 performed significantly higher number of curative procedures (p=0.039) than center 2. Conclusions: Nowadays, EPS is spread from specialized centers to middle-sized hospitals. Since specialized centers have more access to the advanced devices such as electro-anatomic mapping rather than conventional equipment, they are evaluating more complex cases with a variety of different diagnosis. Constructing a referral system from peripheral hospitals to distinguished centers in electrophysiology field would eliminate unnecessary and/or repeated procedures and decrease the expenses.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".