Length of hospital stay and procedure time after partial nephrectomy or percutaneous thermal ablation
Bibliographic record
Abstract
INTRODUCTION: This systematic review addressed the length of hospital stay (LOS) and procedure time in patients with small renal masses (SRM) undergoing open, conventional laparoscopic (OPN), and robot-assisted partial nephrectomy (RAPN), as well as percutaneous thermal ablation (PTA) in different geographic areas. METHODS: We conducted a comprehensive search in databases (MEDLINE, EMBASE, CINAHL) until July 2023, and we applied random-effect meta-analysis, with evidence certainty assessed by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) framework. RESULTS: We screened 3456 titles and abstracts, ultimately identifying 60 eligible studies. For the length of LOS (days) following OPN, our pooled estimates revealed means of 5.7 in North America, 7.1 in Europe, and 13.4 in Asia; laparoscopic partial nephrectomy means were 3.1, 5.4, and 5.8, respectively; for RAPN, means were 2.7, 3.8, and 7.1, respectively; and for PTA, means were 1.2, 1.6, and 1.6, respectively. Regarding procedure time (minutes) after OPN, means were 187 in North America, 132 in Europe, and 184 in Asia; after laparoscopic partial nephrectomy, means were 198, 127, and 200, respectively; after RAPN, means were 189, 150, and 192, respectively; and for PTA, mean was 144 in North America and no studies addressed procedure time in Europe and Asia. CONCLUSIONS: Our study provides the most trustworthy available estimates of LOS and procedure time for patients undergoing invasive procedures for the management of SRM. These findings emphasize the need for context-specific considerations when informing patients and making treatment decisions.
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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 | 0.011 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.015 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".