Pancreatitis in Hiv Infection: Predictors of Severity
Bibliographic record
Abstract
OBJECTIVES: Acute pancreatitis occurs at greater frequency in HIV-infected patients than in the general population. We set out to determine the frequency of severe acute pancreatitis in HIV-positive patients and to study the accuracy of The Acute Physiology and Chronic Health Evaluation (APACHE II), Ranson, and Glasgow scales for prediction of clinical disease severity. METHODS: A total of 73 HIV-infected patients with acute pancreatitis were identified retrospectively. Demographic and clinical parameters as well as clinical outcomes were established. Sensitivities and specificities of the three scales mentioned above were calculated and compared. RESULTS: Of the patients, 63 (83.6%) had AIDS. The majority of cases were medication-induced (46%) or idiopathic (26%). The incidence seemed to be declining in the late 1990s. Eleven patients (15%) had a severe course as defined by death, admission to the intensive care unit, or local complications requiring surgery. Eighteen case (24.6%) were considered severe as defined by the criteria established at the International Symposium on Acute Pancreatitis in Atlanta in 1992. APACHE II criteria best predicted outcome with an overall accuracy of 75% (Glasgow 69%, Ranson 48%). Maximal accuracy was achieved with cut-offs of 14 for APACHE II and 4 for the Glasgow and Ranson criteria. CONCLUSIONS: HIV-infected patients have a clinical outcome similar to that of the general population. Clinical predictive scales are applicable and useful in this population.
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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 | 0.003 |
| 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) | 0.002 | 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".