PATIENT SATISFACTION WITH CONVENTIONAL AND NURSE‐LED TELEPHONE FOLLOW‐UP AFTER NASAL SEPTAL SURGERY
Bibliographic record
Abstract
The need to bring down costs while maintaining a high standard of care has led to the expansion in the role of nurses in recent years. We present results of an audit of patient satisfaction with conventional and nurse-led telephone follow-up after nasal septal surgery. Our results indicate that patient satisfaction with nurse-led telephone follow-up is significantly higher than conventional follow-up (p=0.001, two-tailed). More patients in the conventional follow-up group felt that a follow-up appointment with an ENT doctor was essential compared with the patients in the nurse-led telephone follow-up group (p<0.001, two-tailed). We conclude that nurse-led telephone follow-up avoids unnecessary outpatient appointments, while identifying patients who require further care. It makes more appointment slots available for patients with pressing clinical problems and has the potential to reduce outpatient access times in the NHS.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".