Elevated C-reactive protein in early COVID-19 predicts worse survival among hospitalized geriatric patients
Bibliographic record
Abstract
BACKGROUND: The objective of this cohort study was to determine whether elevated CRP in early COVID-19 was associated with 14-day mortality in geriatric patients. METHODS: Plasma CRP levels at hospital admission and 14-day all-cause mortality were assessed in geriatric inpatients hospitalized for COVID-19. Potential confounders were age, sex, functional abilities, history of malignancies, hypertension, cardiomyopathy, albuminemia, number of acute health issues, use of antibiotics and respiratory treatments. RESULTS: Ninety-five participants (mean±SD 88.0±5.5years; 49.5%women; mean CRP, 76.7±77.5mg/L; mean albuminemia, 32.9±6.0g/L) were included. Sixteen participants who did not survive at day 14 exhibited higher CRP level at baseline than the others (120.3±71.2 versus 67.9±76.1 mg/L, P = 0.002). There was no difference in albuminemia (P = 0.329). Plasma CRP level was directly associated with 14-day mortality (fully adjusted HR = 1.11, P = 0.025). The cut-off for CRP associated with 14-day mortality was set at 35mg/L (sensitivity = 0.88; specificity = 0.56). Those with CRP<35mg/L had longer survival time than the others (log-rank P<0.001). CONCLUSIONS: Elevated CRP levels were associated with poorer 14-day survival in hospitalized geriatric COVID-19 patients.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".