The accuracy of the Alvarado score in predicting acute appendicitis in the black South African population needs to be validated
Bibliographic record
Abstract
BACKGROUND: The Alvarado score is the most widely used clinical prediction tool to facilitate decision-making in patients with acute appendicitis, but it has not been validated in the black South African population, which has much wider differential diagnosis than developed world populations. We investigated the applicability of this score to our local population and sought to introduce a checklist for rural doctors to facilitate early referral. METHODS: We analyzed patients with proven appendicitis for the period January 2008 to December 2012. Alvarado scores were retrospectively assigned based on patients' admission charts. We generated a clinical probability score (1-4 = low, 5-6 = intermediate, 7-10 = high). RESULTS: We studied 1000 patients (54% male, median age 21 yr). Forty percent had inflamed, nonperforated appendices and 60% had perforated appendices. Alvarado scores were 1-4 in 20.9%, 5-6 in 35.7% and 7-10 in 43.4%, indicating low, intermediate and high clincial probability, respectively. In our subgroup analysis of 510 patients without generalized peritonitis, Alvarado scores were 1-4 in 5.5%, 5-6 in 18.1% and 7-10 in 76.4%, indicating low, intermediate and high clinical probability, respectively. CONCLUSION: The widespread use of the Alvarado score has its merits, but its applicability in the black South African population is unclear, with a significant proportion of patients with the disease being potentially missed. Further prospective validation of the Alvarado score and possible modification is needed to increase its relevance in our setting.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".