Robot-assisted versus laparoscopic partial nephrectomy for localized renal tumors: a meta-analysis.
Bibliographic record
Abstract
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) is being performed more frequently for the minimally invasive management of localized renal tumors. However, it's unclear whether RAPN is more efficacious than the standard laparoscopic partial nephrectomy (LPN). The objective of this meta-analysis is to compare RAPN and LPN in terms of perioperative and oncologic outcomes for the treatment of localized renal tumors. METHODS: A systematic search of electronic databases including MEDLINE, EMBASE and OVID was conducted. Comparative studies comparing RAPN and LPN for the treatment of localized renal tumors were regarded eligible. The mean difference (MD), odds ratio (OR) and their corresponding 95% confidence intervals (CI) were calculated for each outcome. The methodologic quality of the included studies was evaluated using the strict criteria of the Newcastle-Ottawa scale. RESULTS: 14 comparative studies (n = 1539 participants) were included in the present meta-analysis. Operative time was similar for RAPN and LPN (MD = 6.33, 95% CI [-23.93, 36.59]), however, warm ischemia time favored RAPN (MD = -3.29, 95% CI [-6.47, -0.10]). There was no significant difference in estimated blood loss (EBL) (MD = -42.24, 95% CI [-87.10, 2.61]) and length of stay (LOS) (MD = -0.29, 95% CI [-0.89, 0.32]). The incidence of intraoperative complications was similar for RAPN and LPN (OR = 0.68, 95% CI [0.29, 1.58]), as well as incidence of postoperative minor complications (OR = 1.10, 95% CI [0.80, 1.51]) and postoperative major complications distributions by Clavien classification (OR = 0.99, 95% CI [0.61, 1.61]). In addition, no significant difference was found in terms of positive surgical margin rate (OR = 1.12, 95% CI [0.56, 2.25]). CONCLUSIONS: RAPN had similar operative time, LOS, EBL, and perioperative complications compared with LPN, as well as positive margin rates. RAPN appears to offer the advantage of decreased WIT compared with LPN. Studies with long-term follow up are needed to compare RAPN and LPN in terms of long-term complications and oncologic outcomes.
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 | 0.010 | 0.014 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.042 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".