Analysis of esthetic assessment scales in two surgical approaches for hyperthophic pyloric stenosis
Bibliographic record
Abstract
INTRODUCTION: Hypertrophic pyloric stenosis (HPS) is a frequent pathology in neonates, with extramucosal pyloromyotomy being a healing surgery. It may be performed through a transverse subcostal incision (TSI) or a transumbilical incision (TUI). OBJECTIVE: To compare complications, operating times, hospital stay, and esthetic results between both techniques. MATERIALS AND METHODS: A retrospective, descriptive study of patients undergoing HPS surgery between January 2010 and January 2020 was carried out. Qualitative variables (sex and complications) were expressed as absolute frequency and percentage, whereas quantitative variables (age at surgery, operating time, hospital stay, and scar esthetic assessment scales: MVSS [Modified Vancouver Scar Scale] and P-SAS [Patient Scar Assessment Scale]) were expressed as median and interquartile range. RESULTS: 107 patients were analyzed: TSI (60.7%, n = 65) vs. TUI (39.3%, n = 42). Male patients: 89.2%, n = 58 vs. 83.3%, n = 35; age (days): 31 (24.5-39.5) vs. 34.5 (29.5-47.25); operating time (minutes): 41 (33.75-60) vs. 46 (38.5-60); and hospital stay (days): 2 (2-4) vs. 3 (2-3). Clavien-Dindo grade II complications were more frequent in the TUI Group (1.54%, n = 1 vs. 23.81%, n = 10; p <0.001), with most of them being wound infections. The opinion regarding the scar according to the MVSS scale was better in the TUI Group (1.5 [0-4] vs. 0 [0-2]; p = 0.022). No significant differences were found in the P-SAS scale (10 (6-18) vs. 6 (6-9); p = 0.060). CONCLUSIONS: TUI is preferred from an esthetic point of view, and even though surgical wound infections are more frequent, it is not associated with longer operating times, longer hospital stay, or severe complications.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".