Incidence and Changing Trends of Shoulder Stabilization in the United States
Bibliographic record
Abstract
PURPOSE: To determine the incidence and demographic characteristics of shoulder stabilization in the United States, with particular focus on age, sex, and inpatient versus outpatient treatment. METHODS: The National Hospital Discharge Survey and the National Survey of Ambulatory Surgery databases were searched using a combination of International Classification of Diseases, Ninth Revision diagnosis and procedure codes, encompassing open and arthroscopic shoulder stabilization procedures. Incidence was determined using National Survey of Ambulatory Surgery, National Hospital Discharge Survey, and US census data, and the results were stratified by age, sex, facility, and concomitant diagnoses. Data were analyzed between 1994 and 2006, the most recent year for which data are available within these sources. RESULTS: The incidence of shoulder stabilization in the United States was 5.84 per 100,000 person-years (n = 15,514; 95% confidence interval, 11,975-19,053) in 1994 to 1996 and 6.89 per 100,000 person-years (n = 20,588; 95% confidence interval, 16,254-24,922) in 2006 (P = .0697). The number of inpatient procedures decreased significantly whereas the number of outpatient procedures increased significantly over the same period (P < .0001 for both). The incidence of stabilization increased in patients aged 45 to 64 years (P < .0001) and patients aged 65 years or older (P = .0008) but was unchanged in patients aged 44 years or younger (P = .4745). The average age of patients undergoing stabilization increased over the study period, from 30 years to 47 years for inpatients (P = .01) and from 27 years to 34 years for ambulatory patients (P = .05). The incidence of stabilization increased significantly in male patients (P = .0075) but remained stable in female patients (P = .8057) over the same period. Diagnoses related to rotator cuff pathology and shoulder derangement were the most common concurrent diagnosis codes. CONCLUSIONS: The overall incidence of shoulder stabilization in the United States is 6.89 per 100,000 person-years. The incidence increased by 18% between 1994 and 2006. During the study period, shoulder stabilization shifted to become a largely outpatient procedure, and the average age increased significantly. LEVEL OF EVIDENCE: Level IV, therapeutic case series.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".