EFFICACY AND CARDIOVASCULAR CONSEQUENCES OF TOTAL LIQUID VENTILATION (TLV) IN EXPERIMENTAL RESPIRATORY DISTRESS SYNDROME (ARDS)
Bibliographic record
Abstract
Objective TLV is an effective strategy in ARDS. However, cardiovascular influence of TLV is still controversial. This study evaluates efficacy, and cardiovascular influence of TLV in a controlled animal trial. Methods 17 anesthetised-paralysed gas-ventilated newborn-lambs instrumented for monitoring of systemic and pulmonary cardiovascular parameters using thermodilution technique (PC-8000-PICCO-VOLEF monitor, Pulsion-Medical-System.ge). Lung injury established using Hcl saline lavages. Post-injury, animals randomised into 3 groups: 1) GV = 6; who remained GV in PRVC (Fr = 60/min, Vt = 10±1 ml.kg, PiP = 20–25 cm.H 2 O, Peep = 9±1 cm H 2 O, FiO 2 = 1.0); 2) TLV = 11, with lungs filled with either 25 ml/kg perfuorooctylbromide (PFOB, n = 5) or perfluorodecalin (PFDEC, n = 6) (F2-chemicals, UK) and ventilated with volume-controlled-pressure-limited-liquid ventilator (INOLIVENT) (Fr = 3–5/min, Vt = 20 ml/kg, FiO = 1.0). Mean arterial pressure (MAP) were maintained using crystalloid volumes and vasopressors. Gas exchanges, Lactate/Pyruvate ratio (L/P) and cardiovascular parameters were recorded (30 min intervals) for 240 min. Results Mean PaO 2 , PaCO 2 and pH were similar in all groups and maintained in the targeted range at a significant low mean airway pressure during TLV. Mean systemic and pulmonary cardiovascular parameters were similar in all groups. As compared to post-injury value a transient but significant decrease in MAP was observed in the TLV groups, with no difference in L/P, however. This could be the result of a significant increase in intrathoracic pressure combined with a decrease in the sympathic autonomic system reactivity due to anesthesia. No significant differences could be demonstrated between the two PFC tested. Conclusion 1) TLV can maintain physiologic gas exchanges without significant cardiovascular effects; 2) Despite a different biophysical profile, PFDEC is as effective as PFOB.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".