Esophageal Balloon-Directed Ventilator Management for Postpneumonectomy Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
Objective. Postpneumonectomy patients may develop acute respiratory distress syndrome (ARDS). There is a paucity of data regarding the optimal management of mechanical ventilation for postpneumonectomy patients. Esophageal balloon pressure monitoring has been used in traditional ARDS patients to set positive end-expiratory pressure (PEEP) and minimize transpulmonary driving pressure ( <math xmlns="http://www.w3.org/1998/Math/MathML" id="M1"> <mi>Δ</mi> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>L</mtext> </mrow> </msub> </math> ), but its clinical use has not been previously described nor validated in postpneumonectomy patients. The primary objective of this report was to describe the potential clinical application of esophageal pressure monitoring to manage the postpneumonectomy patient with ARDS. Design. Case report. Setting. Surgical intensive care unit (ICU) of a university-affiliated teaching hospital. Patient. A 28-year-old patient was involved in a motor vehicle collision, with a right main bronchus injury, that required a right-sided pneumonectomy to stabilize his condition. In the perioperative phase, they subsequently developed ventilator-associated pneumonia, significant cumulative positive fluid balance, and ARDS. Interventions. Prone positioning and neuromuscular blockade were initiated. An esophageal balloon was inserted to direct ventilator management. Measurements and Main Results. <math xmlns="http://www.w3.org/1998/Math/MathML" id="M2"> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mtext>T</mtext> </mrow> </msub> </math> was kept around 3.6 mL/kg PBW, <math xmlns="http://www.w3.org/1998/Math/MathML" id="M3"> <mi>Δ</mi> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>L</mtext> </mrow> </msub> </math> at ≤14 cm H2O, and plateau pressure at ≤30 cm H2O. Lung compliance was measured to be 37 mL/cm H2O. PEEP was optimized to maintain end-inspiratory transpulmonary <math xmlns="http://www.w3.org/1998/Math/MathML" id="M4"> <mtext>pressure</mtext> <mtext> </mtext> <mfenced open="(" close=")"> <mrow> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>L</mtext> </mrow> </msub> </mrow> </mfenced> <mo><</mo> <mn>15</mn> </math> cm H2O, and end-expiratory <math xmlns="http://www.w3.org/1998/Math/MathML" id="M5"> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>L</mtext> </mrow> </msub> </math> between 0 and 5 cm H2O. The maximal <math xmlns="http://www.w3.org/1998/Math/MathML" id="M6"> <mi>Δ</mi> <msub> <mrow> <mi>P</mi> </mrow> <mrow> <mtext>L</mtext> </mrow> </msub> </math> was measured to be 11 cm H2O during the care of this patient. The patient improved with esophageal balloon-directed ventilator management and was eventually liberated from mechanical ventilation. Conclusions. The optimal targets for <math xmlns="http://www.w3.org/1998/Math/MathML" id="M7"> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mtext>T</mtext> </mrow> </msub> </math> remain unknown in the postpneumonectomy patient. However, postpneumonectomy patients with ARDS may potentially benefit from very low <math xmlns="http://www.w3.org/1998/Math/MathML" id="M8"> <msub> <mrow> <mi>V</mi> </mrow> <mrow> <mtext>T</mtext> </mrow> </msub> </math> and optimization of PEEP. We demonstrate the application of esophageal balloon pressure monitoring that clinicians could potentially use to limit injurious ventilation and improve outcomes in postpneumonectomy patients with ARDS. However, esophageal balloon pressure monitoring has not been extensively validated in this patient population.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".