Patients' perceptions of awake and outpatient craniotomy for brain tumor: a qualitative study
Bibliographic record
Abstract
OBJECT: Routine and nonselective use of awake and outpatient craniotomy for supratentorial tumors has been shown to be safe and effective from a medical standpoint. In this study the authors aim was to explore patients' perceptions about awake and outpatient craniotomy. METHODS: Qualitative research methodology was used. Two semistructured, open-ended interviews were conducted with 27 participants, who were ambulatory adult patients who underwent craniotomy for brain tumor excision between October 2008 and April 2009. The participants were each assigned to one of the following categories: 1) awake outpatient; 2) awake inpatient; 3) outpatient under general anesthesia; and 4) inpatient under general anesthesia. Interviews were audiotaped and transcribed, and the data were subjected to thematic analysis. RESULTS: The following 6 overarching themes emerged from the data: 1) patients had a positive experience with awake craniotomy; 2) patient satisfaction with outpatient surgery was high; 3) patients understood the rationale behind awake surgery; 4) patients were surprised that brain surgery can be done on an outpatient basis; 5) trust in one's surgeon was important; and 6) patients were more concerned about the disease than the procedure. CONCLUSIONS: The results reflected positively on the patients' awake and outpatient surgery experience, but there were some areas that require improvement, specifically perioperative pain control and postoperative care. These insights on patients' perspectives can lead to better delivery of care, and ultimately, improved health outcomes.
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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 | 0.012 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| 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".