Predictors of Surgical Complications and Survival in Pediatric Wilms’ Tumor: A 20-Year Retrospective Study from Two Thai Centers
Bibliographic record
Abstract
(1) Background: Wilms' tumor (WT) is the most common pediatric renal malignancy. Although survival outcomes have improved with multimodal therapy, the optimal sequence of surgery and chemotherapy remains debated, particularly in resource-limited settings. This study evaluates the effect of treatment strategy on surgical complications and survival, utilizing two decades of data from Thai tertiary centers. (2) Methods: A retrospective cohort study was conducted on 83 children who underwent radical nephrectomy for WT between 2002 and 2022 at two university hospitals in Thailand. Patients were grouped by treatment protocol: primary nephrectomy (n = 59) or neoadjuvant chemotherapy (n = 24). Clinical, pathological, operative, and follow-up data were analyzed to identify predictors of surgical complications and survival. (3) Results: Short-term postoperative complications occurred in 16.9% of cases, more frequently in males and in patients with hypoalbuminemia, anemia, or large tumors. Estimated blood loss greater than 5 mL/kg, serum albumin less than 3.5 g/dL, and hemoglobin lower than 10 g/dL were independent predictors of complications. The five-year overall survival (OS) and progression-free survival (PFS) rates were 82.4% and 68.1%, respectively. Patients with unfavorable histology or short-term complications experienced significantly poorer OS. Neoadjuvant chemotherapy was associated with increased nutritional compromise and a trend toward higher complication rates, although it was not directly linked to inferior OS. (4) Conclusions: In pediatric WT, the perioperative nutritional and hematologic statuses significantly influence surgical outcomes. While neoadjuvant chemotherapy may assist in tumor downsizing, it might also compromise surgical fitness. Customized preoperative risk assessment and nutritional support can enhance outcomes, particularly in low- and middle-income countries.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".