Impact of possible tardive dyskinesia on physical wellness and social functioning: results from the real-world RE-KINECT study
Bibliographic record
Abstract
BACKGROUND: Tardive dyskinesia (TD) is a persistent and potentially disabling movement disorder associated with antipsychotic use. Data from RE-KINECT, a real-world study of antipsychotic-treated outpatients, were analyzed to assess the effects of possible TD on patient health and social functioning. METHODS: Analyses were conducted in Cohort 1 (patients with no abnormal involuntary movements) and Cohort 2 (patients with possible TD per clinician judgment). Assessments included: EuroQoL's EQ-5D-5L utility (health); Sheehan Disability Scale (SDS) total score (social functioning); patient- and clinician-rated severity of possible TD ("none", "some", "a lot"); and patient-rated impact of possible TD ("none", "some", "a lot"). Regression models were used to analyze the following: associations between higher (worse) severity/impact scores and lower (worse) EQ-5D-5L utility (indicated by negative regression coefficients); and associations between higher (worse) severity/impact scores and higher (worse) SDS total score (indicated by positive regression coefficients). RESULTS: In Cohort 2 patients who were aware of their abnormal movements, patient-rated TD impact was highly and significantly associated with EQ-5D-5L utility (regression coefficient: - 0.023, P < 0.001) and SDS total score (1.027, P < 0.001). Patient-rated severity was also significantly associated with EQ-5D-5L utility (- 0.028, P < 0.05). Clinician-rated severity was moderately associated with both EQ-5D-5L and SDS, but these associations were not statistically significant. CONCLUSIONS: Patients were consistent in evaluating the impacts of possible TD on their lives, whether based on subjective ratings ("none", "some", "a lot") or standardized instruments (EQ-5D-5L, SDS). Clinician-rated severity of TD may not always correlate with patient perceptions of the significance of TD.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".