Predictors of health‐related quality of life recovery following laparoscopic simple, radical and donor nephrectomy
Bibliographic record
Abstract
Study Type – Therapy (case series) Level of Evidence 4 What’s known on the subject? and What does the study add? Despite laparoscopy becoming the favoured approach for nephrectomy, there is very little research into the predictors of recovery following surgery and return of health‐related quality of life following laparoscopic nephrectomy. The current study demonstrates that patients who are younger, have lower BMI, have more active lifestyles and those who are not donating a kidney recover more quickly following surgery. Older, more obese, less active patients, and those donating a kidney take longer to recover from surgery. OBJECTIVES To objectively quantify the recovery of health‐related quality of life (HRQL) in patients undergoing laparoscopic nephrectomy. To determine which factors are predictive of a more expedited recovery. MATERIALS AND METHODS Patient recovery was prospectively measured among patients undergoing laparoscopic simple ( n = 12), radical ( n = 42) and donor ( n = 95) nephrectomy. All procedures were performed using a 3‐ or 4‐trocar, transperitoneal fully‐laparoscopic technique with intact specimen extraction using impermeable sacs for simple and radical nephrectomy, and hand extraction for donor nephrectomy. Postoperative recovery and quality of life were measured using the Postoperative Recovery Scale (PRS) administered preoperatively, immediately postoperatively and as an outpatient at 4, 8, 12, and 16 weeks postoperatively. ANOVA and Pearson’s χ 2 tests were performed on demographic data. Multivariate logistic regression analysis was used to calculate odds ratios for factors predictive of recovery. RESULTS Statistically significant differences were found at baseline for age ( P = 0.02), gender ( P < 0.01), body mass index (BMI; P = 0.03), surgical side ( P < 0.01) and activity‐based lifestyle ( P = 0.04) across the three groups. Minimal adverse events were seen. Factors predictive of expedited recovery include age < 50 years (OR: 2.1, P < 0.01), body‐mass index (BMI) < 30 kg/m 2 (OR: 1.7, P < 0.01), active lifestyles (OR: 1.3, P < 0.01) and those patients undergoing nephrectomy for benign or malignant indications rather than for organ donation (OR: 1.4, P < 0.01). There was a significant delay in the donor group vs the non‐donor group with respect to the median number of days both groups took to recover 75% and 90% of their baseline PRS scores (11 days, P = 0.02; 20 days, P = 0.02, respectively). CONCLUSIONS Predictive factors of recovery from laparoscopic nephrectomy include age, BMI, lifestyle and surgical indication. Differences between HRQL recovery following donor vs non‐donor laparoscopic nephrectomy are significant, and suggest the possible interplay of underlying psychological factors.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".