Outpatient Thyroid Surgery Data from the University Health System (UHC) Consortium
Bibliographic record
Abstract
OBJECTIVE: Describe data from patients undergoing outpatient thyroid surgeries for benign and malignant disease at academic medical centers in the United States. STUDY DESIGN: Retrospective database search. SETTING: The University Health System Consortium (UHC), Oak Brook, Illinois, data compiled from discharge summaries. SUBJECTS AND METHODS: Discharge data were collected from the first quarter of 2005 through the fourth quarter of 2010. Searching strategy was based on diagnosis of thyroid disease and patients undergoing thyroid surgery across all UHC facilities. Demographic information was collected as well as charges. Complications were also evaluated in this analysis. RESULTS: During the study period, 38,362 outpatient thyroidectomies were performed from our sample, 32% for thyroid cancer. More total thyroidectomies (43%) and fewer hemithyroidectomies (36%) were being performed overall; 64.1% of patients stayed 23 hours. CONCLUSION: This is one of the largest series reporting outcomes for outpatient thyroid surgery. Since these surgeries appear to be shifting to an outpatient setting, this report reflects the experience with the majority of endocrine surgeries from the UHC database being performed presently. These results are derived from teaching hospitals and their affiliates and may not reflect the entirety of thyroid surgery in the United States.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".