Prognostic Value of Serum Fibrinogen Level in Determining the Severity of Appendicitis Inflammation in Adult and Pediatric Patients Undergoing Appendectomy in Two Local Centres in Tehran
Bibliographic record
Abstract
Background: Despite the recent advancements, negative appendectomy cases are notable, especially in children. We evaluated the prognostic value of serum fibrinogen level for the prediction of the severity of acute appendicitis. Methods: A cross-sectional study of children and adults who had undergone appendectomy at Ali Asghar and Rasool-e Akram hospitals, Iran, was performed. Before surgery, serum fibrinogen level was assessed by using the Clauss technique. Finally, serum fibrinogen was compared between the two groups of complicated acute appendicitis and uncomplicated ones. Results: In the adult's complicated and uncomplicated appendicitis, no significant differences were noted in gender distribution, WBC count, and segment levels. Serum fibrinogen and C-reactive protein levels in children with complicated appendicitis were significantly higher than those in the uncomplicated ones. Serum fibrinogen level of 450 mg/dl was the optimum cut-off for predicting the severity of appendicitis in children. Serum fibrinogen level in adults with the complicated appendicitis was significantly higher than the uncomplicated appendicitis group. Also, 530 mg/dl was found the best serum fibrinogen cut-off to predict the severity of appendicitis in adults. Conclusion: Serum fibrinogen level is an appropriate diagnostic marker for the distinction of acute complicated appendicitis from uncomplicated appendicitis in children and adults.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".