An Exploratory Analysis of Spine Patients’ Preoperative Concerns and Decision-making Process
Bibliographic record
Abstract
STUDY DESIGN: Cross-sectional, pre-post patient survey. OBJECTIVE: The aim of this study was to determine what factors affect a patient's decision to undergo elective surgery following a surgical consultation. SUMMARY OF BACKGROUND DATA: The surgical consultation is an important step in selecting and preparing patients for elective surgery. Despite the proven effectiveness and low risk of complications, many spine procedure candidates may still choose to forgo surgery after an appropriate discussion and clear surgical indications. METHODS: Survey and open-response questions regarding pre- and post-consultation surgical concerns and overall willingness to undergo surgery were collected and analyzed from 124 patients deemed surgical candidates. Demographics, surgical willingness, and patient concerns were analyzed. Open-ended response data were tallied for surgical concerns and responses were analyzed line-by-line to assess for main themes. Sub-analysis was included on patients who reconsidered their willingness post-consultation. RESULTS: Qualitative thematic analysis of patient's concerns regarding surgery uncovered six major themes: Interference on quality of life (QOL), fear, physical concerns, success, risk, and concerns regarding the surgeon (CS). Success and risk were most commonly mentioned pre-consultation (27%, 26%); risk and QOL were most commonly mentioned post-consultation (22%, 21%). Of 124 patients, 103 were willing to have surgery before consultation and remained willing post-consultation; six patients became unwilling. Twenty-one patients were unwilling to consider surgery before consultation; only five remained unwilling. No differences were found between degenerative and deformity patients regarding initial willingness or changes thereafter. CONCLUSION: The decision to undergo surgery is a multifactorial and complex process with a variety of patient concerns. We grouped these concerns into six categories to aid in future discussion with patients. 87% of patients have made up their mind before attending their surgical consultation. Appropriate understanding of patient-specific willingness and concerns should help facilitate necessary discussion and aid in a more efficient and useful shared decision-making process. LEVEL OF EVIDENCE: 4.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".