Correlation between CD4 lymphocytes count and the opportunistic infections in treated glioblastoma.
Bibliographic record
Abstract
2102 Background: Less than 200 CD4 lymphocytopenia happens frequently with temozolomide treatment of glioblastoma. This immunosuppression is associated with many opportunistic infections and antibiotic prophylaxis is given in some centers to prevent Pneumocystis pneumonia. Methods: We analyzed the association between documented culture-proved infections and CD4 lymphocytes level in 140 patients treated with temozolomide in first-line glioblastoma in Notre-Dame Hospital from 2006 to 2009. Demographic and treatment data were collected and analyzed with Kaplan-Meier survival plots and Log Rank tests. Results: The cohort of infected patients was represented by 31 patients who developed 49 culture-proved infections: 21 urinary origin, 8 pulmonary (1 Pneumocytis and 2 Aspergillosis), 5 brain, 5 bacteremia and 2 other. The infected cohort (n=31) had similar demographs, but also similar outcome compared to our control non infected glioblastoma treated patients cohort (n=109) with a 2 year survival of 40.8% vs 50.2% (p=). The median CD4 lymphocytes level was 260, but clearly infections were associated with less than 200 CD4 lymphocytes. During their infection, 20 patients had a CD4 level less than 200, compared with 11 patients with more than 200 CD4 lymphocytes count. Conclusions: CD4 lymphocytopenia less than 200 is associated with increase in number of documented culture-proven infections in patients treated with temozolomide, but the survival is not altered by the infection.
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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 | 0.001 |
| 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) | 0.001 | 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".