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J. Cardiothorac. Vasc. Anesth. · Mar 2022
Observational StudyDevelopment and Validation of a Predictive Score for Prolonged Mechanical Ventilation After Cardiac Surgery.
- Ludovic Michaud, Pauline Dureau, Basile Kerleroux, Ahmed Charfeddine, Mary Regan, Jean-Michel Constantin, Pascal Leprince, and Adrien Bouglé.
- Sorbonne Université, Assistance Publique - Hôpitaux de Paris (AP-HP), Department of Anesthesiology and Critical Care Medicine, Institute of Cardiology, GRC 29, Pitié-Salpêtrière Hospital, Paris, France.
- J. Cardiothorac. Vasc. Anesth. 2022 Mar 1; 36 (3): 825-832.
ObjectivesThe authors aimed to identify risk factors associated with prolonged mechanical ventilation (PMV) after scheduled cardiac surgery under cardiopulmonary bypass (CPB).DesignA single-center, observational study.SettingTertiary hospital.ParticipantsAll adult patients who underwent scheduled cardiac surgery under cardiopulmonary bypass between January 2017 and December 2017.InterventionsNone.Measurement And Main ResultsAmong the 568 patients included, 68 (12.0%) presented a PMV. The median ventilation time was 5.7 hours in the group without PMV and 85.2 hours in the group with PMV. A logistic regression found five variables independently associated with the occurrence of PMV: (1) prior cardiac surgery, (2) preoperative congestive heart failure, (3) preoperative creatinine clearance <30 mL/min/1.73 m², (4) intraoperative implantation of extracorporeal membrane oxygenation, and (5) serum lactate >4 mmol/L on admission. A predictive score to allow the authors to anticipate PMV was developed from the regression coefficient of perioperative factors independently associated with PMV. With a threshold of 2/13, the score had a sensitivity of 80.9%, a specificity of 80.5%, a positive predictive value of 37.2%, and a negative predictive value of 96.7%. The score then was validated in a distinct cohort.ConclusionsThe study authors have developed a simple score to predict PMV in patients undergoing cardiac surgery with CPB. This score could allow clinicians to identify a high-risk population that might benefit from specific management upon arrival in the intensive care unit.Copyright © 2021 Elsevier Inc. All rights reserved.
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