Association between the appendix and the fecalith in adults
Bibliographic record
Abstract
BACKGROUND: We sought to determine the association between the presence of a fecalith and acute/nonperforated appendicitis, gangrenous/perforated appendicitis and the healthy appendix. METHODS: We retrospectively analyzed appendectomies performed between October 2003 and February 2012. We collected data on age, sex, appendix histology and the presence of a fecalith. RESULTS: During the study period, 1357 appendectomies were performed. Fecaliths were present in 186 patients (13.7%). There were 94 male (50.5%) and 92 female patients, and the mean age was 32 (range of 10-76) years. The fecalith rate was 13%- 16% and was nonexistant after age 80 years. The main groups with fecaliths were those with acute/nonperforated appendicitis (n = 121, 65.1%, p = 0.041) and those with a healthy appendix (n = 65, 34.9%, p = 0.003). The presence of fecaliths in the gangrenous/perforated appendicitis group was not significant (n = 19, 10.2%, p = 0.93). There were no fecaliths in patients with serositis, carcinoid or carcinoma. CONCLUSION: Our data confirm the theory of a statistical association between the presence of a fecalith and acute (nonperforated) appendicitis in adults. There was also a significant association between the healthy appendix and asymptomatic fecaliths. There was no correlation between a gangrenous/perforated appendix and the presence of a fecalith. The fecalith is an incidental finding and not always the primary cause of acute (nonperforated) appendictis or gangrenous (perforated) appendicitis. Further research on the topic is recommended.
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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 | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".