Normal Glenoid Relationships Used for Unilateral Quantification of Glenoid Bone Loss in Glenohumeral Instability
Bibliographic record
Abstract
Objectives: Current methods used to quantify glenoid bone loss following anterior shoulder instability rely on bilateral shoulder imaging to obtain normal linear and surface area parameters of the uninjured glenoid fossa. This method is based on the assumption that there is little side-side variability in these anatomical relationships. Previous reports have demonstrated differences in the morphology of the glenoid fossa based on the anterior glenoid notch. The purpose of this study was to determine the normal dimensions of height, width, surface area, and shape of the human glenoid fossa as function of glenoid notch, and to determine if side-to-side differences exist for these parameters. Due to notch variation, we hypothesize that the inferior glenoid fossa is better represented as an ellipse versus a perfect circle as previously described. We also hypothesize that side-to-side differences exist in glenoid surface area. Methods: The authors studied 58 human scapulae pairs between 18 and 35 years of age from the Hamann-Todd Osteological Collection. Age, sex, race, body height and weight were known for each specimen. Paired specimens were sorted into groups of 5 according to race, sex, and notch type. All specimens were digitized using a 3-D laser scanner, with a stated accuracy of 0.005 inches. Height, width, surface area, and notch angle measurements were calculated using software written in the MATLAB platform. A best fit ellipse was applied to the inferior glenoid based on the glenoid circumference below the notch. Differences in surface area of paired glenoids were assessed using a matched pairs T-test. Multiple stepwise linear regression models were created to select predictors of glenoid surface area. Lastly, the intra-rater and inter-rater reliability of the notch classification as reported by Merrill et al. was assessed among 13 raters. Results: The mean height (s.d.) of the glenoid fossae was 35.0 ± 2.8 mm. Inferior width was 24.8 ± 2.5 mm. The best-fit ellipse of the inferior glenoid had a mean eccentricity of 0.425 ± 0.099. The right glenoid, when compared to its left counterpart, had greater overall surface area (x̄ right = 679.6 mm 2 , x̄ left = 657.2 mm 2 , P< 0.0001*) and inferior surface area (x̄ right = 548.2 mm 2 , x̄ left = 533.1 mm 2 , P< 0.0076*). Patient height, sex, and glenoid height correlated with total and inferior glenoid surface area with r 2 = 0.902 and 0.779, respectively (P< 0.0001*). Analysis of intra-observer reliability showed a consistency of 0.56 (95% CI= 0.26- 0.77), while the inter-observer reliability kappa coefficient was 0.43 (95% CI= 0.41- 0.45). Conclusion: By considering unilateral anatomic relationships of the glenoid fossa, we were able to determine alternative methods of evaluating glenoid bone loss. Glenoid notch angle had moderate reliability and was not considered clinically useful to stratify glenoid morphology. Based on non-zero eccentricity values of the best-fit ellipse, the inferior glenoid fossa did not represent a perfect circle. In addition, side-to-side differences were found between glenoid surface area measurements. The latter two findings contradict assumptions made by current techniques used in clinical practice to calculate bone loss and raise concern as to their validity. Using easily obtainable patient (height and sex) and glenoid (height) parameters, glenoid surface area can be predicted by means of regression modeling, permitting unilateral measurements of glenoid bone loss to be made in clinical practice.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".