Linking the Congenital Heart Surgery Databases of the Society of Thoracic Surgeons and the Congenital Heart Surgeons’ Society
Bibliographic record
Abstract
PURPOSE: The Society of Thoracic Surgeons Congenital Heart Surgery Database (STS-CHSD) is the largest Registry in the world of patients who have undergone congenital and pediatric cardiac surgical operations. The Congenital Heart Surgeons' Society Database (CHSS-D) is an Academic Database designed for specialized detailed analyses of specific congenital cardiac malformations and related treatment strategies. The goal of this project was to create a link between the STS-CHSD and the CHSS-D in order to facilitate studies not possible using either individual database alone and to help identify patients who are potentially eligible for enrollment in CHSS studies. METHODS: Centers were classified on the basis of participation in the STS-CHSD, the CHSS-D, or both. Five matrices, based on CHSS inclusionary criteria and STS-CHSD codes, were created to facilitate the automated identification of patients in the STS-CHSD who meet eligibility criteria for the five active CHSS studies. The matrices were evaluated with a manual adjudication process and were iteratively refined. The sensitivity and specificity of the original matrices and the refined matrices were assessed. RESULTS: In January 2012, a total of 100 centers participated in the STS-CHSD and 74 centers participated in the CHSS. A total of 70 centers participate in both and 40 of these 70 agreed to participate in this linkage project. The manual adjudication process and the refinement of the matrices resulted in an increase in the sensitivity of the matrices from 93% to 100% and an increase in the specificity of the matrices from 94% to 98%. CONCLUSION: Matrices were created to facilitate the automated identification of patients potentially eligible for the five active CHSS studies using the STS-CHSD. These matrices have a sensitivity of 100% and a specificity of 98%. In addition to facilitating identification of patients potentially eligible for enrollment in CHSS studies, these matrices will allow (1) estimation of the denominator of patients potentially eligible for CHSS studies and (2) comparison of eligible and enrolled patients to potentially eligible and not enrolled patients to assess the generalizability of CHSS studies.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".