β-Adrenergic Receptor Blockers Reduce the Occurrence of Keloids and Hypertrophic Scars after Cardiac Device Implantation: A Single-Institution Case-Control Study
Bibliographic record
Abstract
BACKGROUND: Keloids and hypertrophic scars are characterized by excessive proliferation of fibroblasts; abnormal accumulation of extracellular matrix; and clinical findings of raised, red, itchy, and painful lesions. There are few sufficient interventions for keloids, and the development of new therapeutic agents is urgently needed. Several studies suggest that a therapeutic possibility is β-adrenergic receptor blocker treatment. METHODS: In this single-center case-control study, patients who had undergone cardiac device implantation 7 to 23 months earlier were identified. The implantation incision scars of the patients were deemed to be normal or abnormal depending on their redness. The cases (abnormal scars) and controls (normal scars) were compared in terms of their β-blocker use rates. RESULTS: Of the 45 eligible patients, 12 and 33 patients were cases and controls, respectively. The cases tended to be less likely to have taken blockers than the controls (25 percent versus 45.5 percent). This difference became significant when the patients whose scars were diagnosed 7 or 8 months after implantation were excluded from the analysis: the age-adjusted odds ratios of the patients who were diagnosed 8 to 23 and 9 to 23 months after implantation were 0.10 (95 percent CI, 0.00 to 0.83; p = 0.0309) and 0.11 (95 percent CI, 0.00 to 0.98; p = 0.047), respectively. CONCLUSIONS: β-Blockers may be an effective alternative modality for preventing and treating keloids and hypertrophic scars. Large-scale multicenter prospective studies that use histology to diagnose scars and diagnose the postoperative scars at the most suitable period are needed to confirm the effectiveness of blockers for abnormal scars. CLINICAL QUESTION/LEVEL OF EVIDENCE: Therapeutic, III.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".