Successful linking of the Society of Thoracic Surgeons Database to Social Security data to examine the accuracy of Society of Thoracic Surgeons mortality data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: The Society of Thoracic Surgeons Adult Cardiac Surgery Database has been linked to the Social Security Death Master File to verify "life status" and evaluate long-term surgical outcomes. The objective of this study is explore practical applications of the linkage of the Society of Thoracic Surgeons Adult Cardiac Surgery Database to Social Securtiy Death Master File, including the use of the Social Securtiy Death Master File to examine the accuracy of the Society of Thoracic Surgeons 30-day mortality data. METHODS: On January 1, 2008, the Society of Thoracic Surgeons Adult Cardiac Surgery Database began collecting Social Security numbers in its new version 2.61. This study includes all Society of Thoracic Surgeons Adult Cardiac Surgery Database records for operations with nonmissing Social Security numbers between January 1, 2008, and December 31, 2010, inclusive. To match records between the Society of Thoracic Surgeons Adult Cardiac Surgery Database and the Social Security Death Master File, we used a combined probabilistic and deterministic matching rule with reported high sensitivity and nearly perfect specificity. RESULTS: Between January 1, 2008, and December 31, 2010, the Society of Thoracic Surgeons Adult Cardiac Surgery Database collected data for 870,406 operations. Social Security numbers were available for 541,953 operations and unavailable for 328,453 operations. According to the Society of Thoracic Surgeons Adult Cardiac Surgery Database, the 30-day mortality rate was 17,757/541,953 = 3.3%. Linkage to the Social Security Death Master File identified 16,565 cases of suspected 30-day deaths (3.1%). Of these, 14,983 were recorded as 30-day deaths in the Society of Thoracic Surgeons database (relative sensitivity = 90.4%). Relative sensitivity was 98.8% (12,863/13,014) for suspected 30-day deaths occurring before discharge and 59.7% (2120/3551) for suspected 30-day deaths occurring after discharge. CONCLUSIONS: Linkage to the Social Security Death Master File confirms the accuracy of data describing "mortality within 30 days of surgery" in the Society of Thoracic Surgeons Adult Cardiac Surgery Database. The Society of Thoracic Surgeons and Social Security Death Master File link reveals that capture of 30-day deaths occurring before discharge is highly accurate, and that these in-hospital deaths represent the majority (79% [13,014/16,565]) of all 30-day deaths. Capture of the remaining 30-day deaths occurring after discharge is less complete and needs improvement. Efforts continue to encourage Society of Thoracic Surgeons Database participants to submit Social Security numbers to the Database, thereby enhancing accurate determination of 30-day life status. The Society of Thoracic Surgeons and Social Security Death Master File linkage can facilitate ongoing refinement of mortality reporting.
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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 | 0.035 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.003 |
| 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 it