Causes and outcomes of markedly elevated C-reactive protein levels.
Bibliographic record
Abstract
OBJECTIVE: To characterize the causes of marked elevation of C-reactive protein (CRP) levels, investigate patient outcomes, and examine factors that might influence the CRP response. DESIGN: Health records were used to retrospectively determine patient characteristics, diagnoses, and outcomes over a 2-year period (2012 to 2013). SETTING: A large referral centre in Moncton, NB. PARTICIPANTS: Adult inpatients and outpatients with a CRP level above 100 mg/L. MAIN OUTCOME MEASURES: Differences among the CRP distributions of various diagnosis categories were examined using Kruskal-Wallis tests, and factors affecting outcomes were examined using Fisher exact tests. RESULTS: = .002). CONCLUSION: Most patients had infections and the proportion of patients with infections increased with the level of CRP, although many diagnoses were associated with markedly elevated CRP levels. These data could help guide health care professionals in the evaluation and management of these patients.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".