A significant rate of tibial overcorrection with an increased JLO occurred after isolated high tibial osteotomy without considering international consensus
Bibliographic record
Abstract
Abstract Purpose The recent ESSKA consensus recommendations defined indications and outlined parameters for osteotomies around a degenerative varus knee. The consensus collated these guidelines based on the published literature available to answer commonly asked questions including the importance of identifying the site and degree of the lower limb deformity. In the consensus, the authors suggest that a knee joint line obliquity (JLO) greater than 5° or a planned medial proximal tibial angle (MPTA) > 94° preferentially indicates a double level osteotomy (DLO) compared to an isolated opening wedge high tibial osteotomy (OWHTO). This study aimed to analyze the corrections performed on a cohort of isolated opening wedge high tibial osteotomies (OWHTOs) prior to the recent ESSKA recommendations, with a focus on the impact of knee joint line obliquity (JLO) and medial proximal tibial angle (MPTA) on the choice of osteotomy procedure. Methods This monocentric, retrospective study included 129 patients undergoing medial OWHTO for symptomatic isolated medial knee osteoarthritis (Ahlbäck grade I or II) and a global varus malalignment (hip–knee–ankle angle ≤ 177°). An automated software trained to automatically detect lower limb deformity was implemented using patients preoperative long leg alignment X‐rays to identify suitability for an isolated HTO in knee varus deformity. Based on the ESSKA recommendations, the site of the osteotomy was identified as well as the degree of correction required. The ESSKA consensus considers avoiding an isolated high tibial osteotomy if the planned resultant knee joint line orientation exceeds 5 ̊ or MPTA exceeds 94°. A preoperative abnormal MPTA was defined by a value lower than 85° and a preoperative abnormal LDFA by a value greater than 90°. The cases of DLO or DFO suggested by the software and the number of extra‐tibial anomalies were collected. Multiple linear regression models were developed to establish a relationship between preoperative values and the risk of being outside of ESSKA recommendations postoperatively. Results Based on ESSKA recommendations and on threshold values considered abnormal, the software suggested a DLO in 17.8% (n = 23/129) of cases, a distal femoral osteotomy in 27.9% (n = 36/129) of cases and advised against an osteotomy procedure in 24% (n = 31/129) of cases. The software detected a femoral anomaly in 34.9% (n = 45/129) of cases and an JLCA > 6° in 9.3% (n = 12/129). Postoperatively, the MPTA exceeds 94° in 41.1% (n = 53/129) and the JLO exceeds 5° in 29.4% (n = 38/129). On multivariate analysis, a high preoperative MPTA was associated with higher risk of postoperative MPTA > 94° (R2 = 0.36; p < 0.001). Similarly, the probability of the software advising a DLO or DFO was associated with the presence of an “normal” preoperative MPTA (R2 = 0.42; p < 0.001) or an abnormal preoperative LDFA (R2 = 0.48; p < 0.001) or a planned JLO > 5° (R2 = 0.27; p < 0.001). Conclusions Analysis of patients who underwent an isolated OWHTO prior to the ESSKA guidelines, demonstrated a significant rate of post‐operative tibial overcorrection and a resultant increased JLO. Pre‐operative planning that considers the ESSKA guidelines, allows for better identification of those patients requiring a DFO or DLO and avoidance of resultant post‐operative deformities. Level of evidence IV, 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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".