Komplikasjoner og liggetid etter urologisk kirurgi
Bibliographic record
Abstract
Objectives: Postoperative complications increase morbidity, delay recovery and increase length of stay (LOS) after surgery, and should be reduced to a minimum. In the first part of this project, we studied the complication rate and LOS after urological surgery. In the second part we tried to survey postoperative symptoms and health related quality of life (HRQoL) after cystectomy, to identify areas for improvement for the perioperative pathway. Methods: Part 1: We retrospectively classified complications according to the Clavien-Dindo classification, and recorded LOS for patients who underwent urological surgery in 2013 and 2014 at Akershus University Hospital. Part 2: We prospectively registered symptoms after cystectomy by using the Edmonton Symptom Assessment Scale. We assessed HRQoL 30 days postoperative by using the SF-12® questionnaire. Results: LOS and complications vary from a short LOS and few complications after endoscopic kidney stone surgery to LOS of 11 days and over 20% major complications after cystectomy. We did not succeed in identifying symptoms after cystectomy. The physical component of the HRQoL (PCS) after cystectomy was reduced from 49,15 points preoperatively to 38,37 points postoperatively. The mental component (MCS) appeared unchanged with 51,13 and 51,2 points pre- and postoperatively. The study size was too small to detect any significant changes in HRQoL. Conclusions: LOS and complications vary after urological surgery. There is a need for further survey of symptoms after cystectomy. There is a trend towards reduction in the PCS score 30 days after cystectomy, but no change in the MCS-score.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.012 |
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".