Gene Expression Profiling in Pediatric Appendicitis
Bibliographic record
Abstract
Importance: Appendicitis is the most common indication for urgent surgery in the pediatric population, presenting across a range of severity and with variable complications. Differentiating simple appendicitis (SA) and perforated appendicitis (PA) on presentation may help direct further diagnostic workup and appropriate therapy selection, including antibiotic choice and timing of surgery. Objective: To provide a mechanistic understanding of the differences in disease severity of appendicitis with the objective of developing improved diagnostics and treatments, specifically for the pediatric population. Design, Setting, and Participants: The Gene Expression Profiling of Pediatric Appendicitis (GEPPA) study was a single-center prospective exploratory diagnostic study with transcriptomic profiling of peripheral blood collected from a cohort of children aged 5 to 17 years with abdominal pain and suspected appendicitis between November 2016 and April 2017 at the Alberta Children's Hospital in Calgary, Alberta, Canada, with data analysis reported in August 2023. There was no patient follow-up in this study. Exposure: SA, PA, or nonappendicitis abdominal pain. Main Outcomes and Measures: Blood transcriptomics was used to develop a hypothesis of underlying mechanistic differences between SA and PA to build mechanistic hypotheses and blood-based diagnostics. Results: Seventy-one children (mean [SD] age, 11.8 [3.0] years; 48 [67.6%] male) presenting to the emergency department with abdominal pain and suspected appendicitis were investigated using whole-blood transcriptomics. A central role for immune system pathways was revealed in PA, including a dampening of major innate interferon responses. Gene expression changes in patients with PA were consistent with downregulation of immune response and inflammation pathways and shared similarities with gene expression signatures derived from patients with sepsis, including the most severe sepsis endotypes. Despite the challenges in identifying early biomarkers of severe appendicitis, a 4-gene signature that was predictive of PA compared to SA, with an accuracy of 85.7% (95% CI, 72.8-94.1) was identified. Conclusions: This study found that PA was complicated by a dysregulated immune response. This finding should inform improved diagnostics of severity, early management strategies, and prevention of further postsurgical complications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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; both teacher heads agree on what is shown here.
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".