Use of preoperative erythropoietin in head and neck surgery.
Bibliographic record
Abstract
OBJECTIVE: To determine whether preoperative erythropoietin can raise the hemoglobin levels of head and neck cancer patients prior to major ablative surgery. STUDY DESIGN: Prospective, consecutive series. METHODS: Ten patients who were to undergo major head and neck surgery were scheduled to receive subcutaneous doses of erythropoietin (600 IU/kg) on days 21, 14, 7, and 1 prior to surgery. Serial hemoglobin levels and reticulocyte counts were obtained throughout the course of treatment. RESULTS: Eight patients experienced a significant increase in hemoglobin. There were two nonresponders. The mean preoperative hemoglobin level for all 10 patients increased 12.6 g/L, from 135.5 +/- 16.2 g/L (baseline) to 148.1 +/- 23.7 g/L (1 day preoperatively, p < .0001). CONCLUSIONS: Erythropoietin significantly increases hemoglobin levels in patients awaiting major head and neck oncologic surgery. It can be viewed as an important adjunct to other well-established blood conservation techniques aimed at reducing perioperative transfusion rates.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".