Diagnostic Value of Serum Urokinase-Type Plasminogen Activator Receptor in Children With Acute Appendicitis
Bibliographic record
Abstract
OBJECTIVES: Acute appendicitis (AA) is the most common surgical emergency in children. The accurate and timely diagnosis of AA in children can be challenging, and delayed diagnosis rates have been reported to range from 5.9% to 27.6%. Although combining clinical history and repeated physical examination with laboratory tests and radiographic imaging modalities help reach the diagnosis, novel biomarkers can support the surgeons' decision as well. The aims of this study were to evaluate a new plasma marker, urokinase-type plasminogen activator receptor (uPAR), to improve diagnostic accuracy in AA patients, and to determine a cutoff value of uPAR, which can safely include/exclude the diagnosis of AA. METHODS: We conducted a prospective study of children who underwent surgery for AA. Patients were categorized into the following 3 groups: group 1, controls consisted of 32 healthy volunteers; group 2, patients underwent surgery for nonperforated AA (n = 35); and group 3, patients underwent surgery for perforated AA (n = 21). Blood was sampled from group 1 at the admission and from group 2 and 3 before appendectomy. Serum uPAR, white blood cell count, absolute neutrophil count (ANC), and C-reactive protein concentrations were measured. RESULTS: Urokinase-type plasminogen activator receptor, ANC, and white blood cell count values were significantly higher in group 2 and 3 than group 1, but there was no significant difference between group 2 and 3. C-reactive protein values were significantly higher only in group 3 than other groups. The cutoff value for uPAR is 2.2 ng/mL with sensitivity of 85.7% and specificity of 84.3% and ANC is 5900 cells/mm with sensitivity of 91.1% and specificity of 96.9% to diagnose appendicitis. The specificity was 81.3% and sensitivity was raised to 98.2% when evaluated together. CONCLUSIONS: The incorporation of uPAR count and ANC could be a strong predictor of AA in children.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".