Minimal Clinically Important Difference of Four Commonly Used Balance Assessment Tools in Individuals after Total Knee Arthroplasty: A Prospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Although balance is commonly assessed during the recovery of total knee arthroplasty (TKA), the minimal clinically important difference (MCID) values of frequently used balance assessment tools have not been established previously in this population. OBJECTIVE: To determine the MCID of four balance tests-ie, the Balance Evaluation Systems Test (BESTest), Mini-BESTest, Brief-BESTest, and the Berg Balance Scale (BBS)-in individuals post-TKA. DESIGN: Prospective cohort. SETTING: Outpatient rehabilitation. PARTICIPANTS: Inclusion criteria: (1) first primary TKA with diagnosed knee osteoarthritis; (2) aged 50-85 years. EXCLUSION CRITERIA: (1) TKA due to rheumatoid arthritis of the knee or traumatic injury; (2) known medical conditions that influence balance ability. One hundred forty-six participants were recruited, and 134 of them with complete data were included in the analysis. INTERVENTIONS: Participants received individualized physiotherapy, consisting of electrotherapy for pain and edema control, mobilization and strengthening exercises, and gait and balance training, once or twice per week between assessments. MAIN OUTCOME MEASUREMENTS: Participants were assessed on the BESTest, Mini-BESTest, Brief-BESTest, BBS, and Functional Gait Assessment (FGA) 2 and 4 weeks after surgery. The FGA was used as the anchor reference measure to calculate the MCID of the other four balance tests. A distribution-based approach was also employed to derive the MCID (ie, standardized effect size of 0.5). RESULTS: The BESTest (area under curve [AUC] = 0.811, 95% confidence interval [CI] 0.739-0.883) had the highest accuracy in detecting clinically important improvements on the FGA (≥4 points), followed by the Mini-BESTest (AUC = 0.782, 95% CI 0.704-0.860), Brief-BESTest (AUC = 0.701, 95% CI 0.618-0.795), and BBS (AUC = 0.586, 95% CI 0.490-0.682). The anchor- and distribution-based MCIDs were 6-8 for the BESTest, 1-2 for the Mini-BESTest, and 2-3 for the Brief-BESTest. CONCLUSIONS: Improvements exceeding MCIDs established above are indicative of significant progress in balance function post-TKA. The BBS is not a recommended tool due to its low AUC value.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".