Does the Degree of Trunk Bending Predict Patient Disability, Motor Impairment, Falls, and Back Pain in Parkinson's Disease?
Bibliographic record
Abstract
BACKGROUND: Postural abnormalities in Parkinson’s disease(PD) form a spectrum of functional trunk misalignment, ranging from a “typical” parkinsonian stooped posture to progressively greater degrees of spine deviation. OBJECTIVE: To analyze the association between degree of postural abnormalities and disability and to determine cut-off values of trunk bending associated with limitations in activities of daily living(ADLs), motor impairment, falls, and back pain. METHODS: The study population was 283 PD patients with ≥5° of forward trunk bending (FTB), lateral trunk bending (LTB) or forward neck bending (FNB). The degrees were calculated using a wall goniometer (WG) and software-based measurements (SBM). Logistic regression models were used to identify the degree of bending associated with moderate/severe limitation in ADLs (Movement Disorders Society Unified PD Rating Scale [MDS-UPDRS] part II ≥ 17), moderate/severe motor impairment (MDS-UPDRS part III ≥ 33), history of falls (≥ 1), and moderate/severe back pain intensity (numeric rating scale ≥ 4). The optimal cut-off was identified using receiver operating characteristic (ROC) curves. RESULTS: We found significant associations between modified Hoehn&Yahr stage, disease duration, and sex and limitation in ADLs, motor impairment, back pain intensity, and history of falls. Degree of trunk bending was associated only with motor impairment in LTB (odds ratio [OR] 1.12; 95% confidence interval [CI], 1.03-1.22). ROC curves showed that patients with LTB of 10.5° (SBM, AUC 0.626) may have moderate/severe motor impairment. CONCLUSIONS: The severity of trunk misalignment does not fully explain limitation in ADLs, motor impairment, falls, and back pain. Multiple factors possibly related to an aggressive PD phenotype may account for disability in PD patients with FTB, LTB, and FNB.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".