Fluid status assessment in mechanically ventilated septic patients
Bibliographic record
Abstract
Early optimization of fluid status is of major importance in the treatment of critically ill patients. It is unclear whether sonographic measurement of the inferior vena cava (IVC) diameter is valuable in the evaluation of fluid status in mechanically ventilated septic patients. Thirty mechanically ventilated patients with severe sepsis or septic shock (age 59.9 ± 15.4 years; APACHE II score 30.6 ± 7.7; 18 males) requiring advanced invasive hemodynamic monitoring due to cardiovascular instability were included in a prospective observational study in a university hospital setting with a 24-bed medical ICU and a 14-bed anaesthesiological ICU. Volume-based hemodynamic parameters were determined using the thermal-dye transpulmonary dilution technique. Simultaneously, the IVC diameter was measured throughout the respiratory cycle by trans-abdominal ultrasonography. We found a statistically significant correlation of both inspiratory and expiratory IVC diameter with central venous pressure ( P = 0.004 and P = 0.001), extravascular lung water index ( P = 0.001 and P < 0.001), intrathoracic blood volume index ( P = 0.026 and P = 0.05), the intrathoracic thermal volume (both P < 0.001), and the paO 2 /FiO 2 oxygenation index ( P = 0.007 and P = 0.008, respectively). Sonographic determination of the IVC diameter is useful in the assessment of volume status in mechanically ventilated septic patients. This approach is rapidly available, noninvasive, inexpensive, easy to learn and applicable in almost any clinical situation without doing harm. IVC sonography may contribute to a faster, more goal-oriented optimization of fluid status and may help to identify patients in whom deleterious volume expansion should be avoided. It remains to be elucidated whether this approach influences the outcome of septic 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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".