Posturography for evaluating risk of falls in elderly unstable patients
Bibliographic record
Abstract
Objective:The aim of this study was to evaluate a screening protocol for detecting potential fallers among elderly individuals with instability, using objective indicators of dynamic equilibration performance. Material and methods:Dynamic balance in 273 patients with postural instability (59 with and 214 without a history of falls) older than 60 years of age were tested using the SPS (SYNAPSYS) posturography platform, which evaluates equilibration responses to induced postural disturbances. Results:Among nonfallers, 23% exhibited dynamic balance alterations as severe as those in same-aged fallers. Potential fallers were detected with 97% sensitivity and nonfallers with 77% specificity. Positive and negative predictive values were 54% and 99%, respectively. Conclusions:The protocol required 5 to 8 minutes. It produced valuable information on postural deficiencies in potential fallers. It is reliable for evaluating the risk of falls in elderly patients with instability. The postural deficiencies identified by our protocol would help to develop effective rehabilitation programs. ( Fr ORL - 2005 ; 88 : 97 - 103)
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".