A New Histology Scoring System for the Assessment of the Quality of Human Cartilage Repair: ICRS II
Bibliographic record
Abstract
BACKGROUND: A reliable and reproducible method is needed to assess cartilage repair. PURPOSE: This study was undertaken to test the reproducibility of 2 established histological scoring systems, the Modified O'Driscoll Scale (MODS) and International Cartilage Research Society (ICRS) Visual Assessment Scale (ICRS I), and subsequently to develop and evaluate a new grading system for cartilage repair. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: A total of 107 cartilage biopsy specimens were graded using MODS and ICRS I, and the reader variability was measured. The new grading system, ICRS II, was developed and the inter- and intrareader variability determined by 3 independent readers. Collagen type II deposition was assessed immunohistochemically. RESULTS: The MODS and ICRS I demonstrated high interreader variability, with MODS also showing high intrareader variability. A new histological scoring system, ICRS II, was developed comprising 14 criteria to assess parameters related to chondrocyte phenotype and tissue structure. The ICRS II demonstrated lower inter- and intrareader variability compared with MODS or ICRS I. The overall assessment and matrix staining scores had the best correlation coefficients for inter- and intrareader variability (r = .81 and .82, respectively). The extent of collagen type II in cartilage, considered a marker of differentiation toward hyaline cartilage, could represent a measure of good cartilage repair. A correlation coefficient of .56 was obtained between the extent of collagen type II staining and the overall assessment score. CONCLUSION: The ICRS II represents an improvement over current histological cartilage repair grading systems in terms of reader reproducibility. The clinical relevance and its ability to predict long-term repair durability will be assessed once long-term clinical data become available.
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 | 0.022 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".