Modern Treatment of Inflammatory Pulmonary Pathology: Theoretical Justification and Implementation of the Extracorporeal Blood Hyperthermia Apparatus into Medical Practice
Bibliographic record
Abstract
For the first time in Ukraine, our team successfully applied extracorporeal blood hyperthermia (EBH) within a closed-loop circuit to manage inflammatory conditions of the lungs and pleura. Controlled warming of autologous blood to 38°C and its subsequent reinfusion produced rapid, clinically significant reductions in exudative pleurisy, pleural empyema, and paracancerous inflammatory lesions. Earlier, EBH had been incorporated into U.S. military field protocols between 2003 and 2007, and it is now formally included in therapeutic guidelines across the United States, Canada, New Zealand, multiple European nations, and several African healthcare systems. Our findings corroborate international data showing that mild systemic hyperthermia enhances phagocytic activity, improves microcirculation within the pleural cavity, and accelerates resorption of inflammatory exudate while maintaining a favorable safety profile. No severe adverse events or hemodynamic instabilities were observed during or after the procedures in our cohort. Beyond its direct anti-inflammatory impact, EBH may potentiate antibiotic penetration into pleural tissues, offering a valuable adjunct in the era of rising antimicrobial resistance. Future multicenter trials with larger patient populations and comparative cost-effectiveness analyses are warranted to refine treatment parameters and confirm long-term benefits of this promising modality.
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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 | 0.002 | 0.002 |
| 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 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".