Caracterización de las alteraciones vestibulares en pacientes con síndrome de latigazo cervical
Bibliographic record
Abstract
Objetivo: Determinar la prevalencia de alteraciones vestibulares en pacientes con sindrome de latigazo cervical (SLC). Material y metodo: Estudio transversal en 24 pacientes consecutivos atendidos por presentar SLC con grado II o III de la Quebec Task Force y tiempo de evolucion menor de seis meses. Se realizo exploracion clinica vestibular completa y exploracion instrumental con videonistagmografia (VNG), incluyendo prueba calorica bitermica, registro de potenciales evocados miogenicos vestibulares (VEMPs), prueba de la vertical visual subjetiva (VVS) y posturografia dinamica. Tambien fueron evaluados mediante los cuestionarios SF-36 (salud general), DHI-S (discapacidad vestibular) y SIMS (simulacion). Resultados: La prevalencia de alteraciones vestibulares se situo en el 25%. El reflejo vestibulo-colico evaluado mediante VEMPs estaba alterado en el 25% de los pacientes con SLC. La VSV se encontraba alterada en el 17% de los casos. La posturografia dinamica identifico un patron vestibular en el 25% de los casos. La estimacion de simulacion entre los pacientes con SLC se produjo, al menos, en el 25% de los casos. Conclusion: La alteracion de varias pruebas vestibulares en pacientes con SLC sugiere una disfuncion vestibular asociada a ILT prolongada. Las puntuaciones elevadas en los cuestionarios de discapacidad vestibular (DHI) y de simulacion de sintomas (SIMS) podrian ser utilizadas como indicadores de percepcion de trastorno vestibular grave e ILT prolongada
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".