Clinicopathological Analysis of Autopsy of 36 Cases with Sudden Cardiac Death
Bibliographic record
Abstract
Objective: To analyze the clinicopathological characteristics of autopsy of thirty-six cases with sudden cardiac death and provide a theoretical basis for the diagnosis and prevention of sudden cardiac death.Methods: Thirty-six patients with sudden cardiac death were autopsied and the histopathological examinations were performed by being routinely embedded in paraffin,complete serial sections and stained with HE and then observed light microscope and the information of thirty-six autopsy cases were collected with sudden cardiac death.Results:Among thirty-six died of sudden cardiac death,the cases with coronary heart disease was the most abundant accounting for 21 cases and for 58.33% of the total cases,and the cases with arrhiythmogenic right ventricular cardiomyopathy accounted for 3 cases and for 8.33% of the total cases.Conclusion: Correct and systematic autopsy could determine the causes of sudden death and offer scientific evidence for medical identification,otherwise,it was important to improve medical quality,early diagnosing,treatment of cardiovascular diseases and decrease the sudden cardiac death rate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".