Beneficial effects of antiplatelet drugs in patients with community-acquired pneumonia and in endotoxin shock in mice
Bibliographic record
Abstract
Data obtained from 224 patients with community-acquired pneumonia (CAP) were retrospectively analysed for an association between prehospital treatment with long-acting antiplatelet drugs such as acetyl salicylic acid ( n = 36) or thienopyridine ADP-receptor antagonists (clopidogrel or ticlopidin, n = 8) and clinical outcome. Use of statins was an exclusion criterion. BALB/c mice were pretreated with clopidogrel for 4 days prior to an intraperitoneal injection of LPS ( Escherichia coli 0111:B4). For platelet counts and blood gas analysis, standard procedures were used. Lung tissues were stained with HE or a FITC-labelled anti-fibrin(ogen) antibody. CAP patients with antiplatelet drugs ( n = 44) were older than control patients ( n = 180; 69 ± 7 vs 58 ± 13 years, P < 0.00001). At the day of hospital admission there were no differences in platelet or leukocyte counts, CRP and SOFA scores between both groups. However, patients on antiplatelet drugs developed organ failure less frequently than control patients (ICU admission: 9.1% vs 26.1%; P < 0.02). In the mouse model of endotoxin shock, clopidogrel reduced the drop in platelet count and the degree of lung injury. Compared with controls we found 20 hours after LPS injection in the clopidogrel-treated animals a lower number of thrombi in the lung vasculature (6.1 ± 2.3 vs 11.5 ± 4.4 thrombi per screen, P < 0.025) as well as higher blood pH and bicarbonate levels (7.01 ± 0.01 vs 6.93 ± 0.04, P < 0.04 and 10.2 ± 0.14 vs 7.3 ± 0.14 mmol/l, P < 0.03, respectively). Antiplatelet drugs may have a beneficial effect in systemic inflammation and sepsis, and could be a novel therapy option, at least in patients of low bleeding risk. One mechanism of their effects could be a reduction in the microvascular thrombus formation.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".