Serum cryptococcal antigen titre as a diagnostic tool and a predictor of mortality in <scp>HIV</scp>‐infected patients with cryptococcal meningitis
Bibliographic record
Abstract
OBJECTIVES: The aim was to determine the effectiveness of the serum cryptococcal antigen (CrAg) test in the diagnosis of concurrent cryptococcal meningitis (CM) and as a predictor of mortality in HIV-infected patients. METHODS: In this retrospective study, all HIV-infected patients admitted to Shanghai Public Health Clinical Center from 1 January 2014 to 31 August 2016 were screened for serum CrAg using the latex agglutination test. Serum CrAg-positive patients underwent lumbar puncture to confirm CM prior to the initiation of appropriate antifungal therapy and were followed up for at least 6 months. RESULTS: One hundred and four (7.1%) of the total of 1474 HIV-infected patients screened were serum CrAg-positive. CM was diagnosed in the majority of serum CrAg-positive patients (71.3%; 67 of 94) and was confirmed in all (46 of 46) of the patients with headache or coma and in 43.8% (21 of 48) of patients without neurological symptoms. CrAg titres ≥ 1:1024 showed a sensitivity of 82.5% and a specificity of 86.7% for the diagnosis of concurrent CM (P < 0.001). The positive predictive value for CM in this population was 94.3%. A total of 13 serum CrAg-positive patients [13.8%; 95% confidence interval (CI) 7.5-22.4%] died (11 as a result of CM and two others as a result of bacterial pneumonia) despite early antifungal treatment initiation. Serum CrAg titres ≥ 1:1024 predicted all-cause mortality (hazard ratio 3.69; P = 0.03). CONCLUSIONS: Serum CrAg titres ≥ 1:1024 not only were associated with concurrent CM but also predicted mortality. HIV-infected patients with a positive serum CrAg test during screening should receive lumbar punctures regardless of symptoms to rule out CM and patients with serum CrAg titres ≥ 1:1024 should be offered immediate care.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".