Feasibility of a Physiatry Assessment Clinic to Address Physical Impairment in Head and Neck Cancer Patients Following Neck Resection and Free Flap Reconstruction
Bibliographic record
Abstract
Individuals with head and neck cancers are living longer than ever before, yet many live with the long-term effects of their cancer and treatment. The purpose of this study was to assess the feasibility of a physiatry assessment clinic (PAC) following neck resection and free flap reconstruction, during which physical function was assessed. Methods: Adult patients participating in a larger prehabilitation study were included. Attendance and the ability to complete the physical function assessment were examined. Exploratory analyses were completed to describe physical function, fitness, shoulder, and neck function among PAC attenders. To further understand PAC feasibility, patient-reported outcomes among PAC attenders and non-attenders were examined over 12 months (QuickDASH, NDII, EAT-10). Results: A total of 36 eligible participants (78.2%) from the larger prehabilitation study were approached to participate in the PAC, and 19 of the 36 attended (52.8%). Participants attended on average 8.6 ± 3.6 weeks post surgery, and 100% were able to complete the functional measures. Exploratory data suggest that those who did not attend (17 of 36 approached) had more advanced disease compared to those who attended (p < 0.05). Patient-reported outcomes suggested better shoulder function and swallow function at 6 months among those who attended the clinic versus those who did not. Conclusions: While recruitment to the PAC and assessment completion demonstrated feasibility, attendance posed challenges for patients. These findings highlight the need for innovative approaches to screening patients and tailoring rehabilitation services based on physical impairment.
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 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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".