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Titration of Ventilator Settings to Target Driving Pressure and Mechanical Power.
Kassis, Elias Baedorf; Hu, Stephanie; Lu, MingYu; Johnson, Alistair; Bose, Somnath; Schaefer, Maximilian S; Talmor, Daniel; Lehman, Li-Wei H; Shahn, Zach.
Afiliação
  • Kassis EB; Division of Pulmonary and Critical Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston MA, 02115 enbaedor@bidmc.harvard.edu.
  • Hu S; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge MA, 02142.
  • Lu M; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge MA, 02142.
  • Johnson A; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge MA, 02142.
  • Bose S; Department of Anesthesia, Pain and Critical Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston MA, 02115.
  • Schaefer MS; Department of Anesthesia, Pain and Critical Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston MA, 02115.
  • Talmor D; Department of Anesthesia, Pain and Critical Care, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston MA, 02115.
  • Lehman LH; Laboratory for Computational Physiology, Massachusetts Institute of Technology, Cambridge MA, 02142.
  • Shahn Z; MIT-IBM Watson AI Lab, Cambridge, Massachusetts.
Respir Care ; 2022 Jul 22.
Article em En | MEDLINE | ID: mdl-35868844
ABSTRACT

PURPOSE:

Driving pressure (ΔP) and mechanical power (MP) may be important mediators of lung injury in acute respiratory distress syndrome (ARDS) however there is little evidence for strategies directed at lowering these parameters. We applied predictive modeling to estimate the effects of modifying ventilator parameters on ΔP and MP.

METHODS:

2,622 ARDS patients (Berlin criteria) from the Medical Information Mart for Intensive Care IV database (MIMIC-IV version1.0) admitted to the intensive care unit (ICU) at Beth Israel Deaconess Medical Center between 2008 and 2019 were included. Flexible confounding-adjusted regression models for time varying data were fit to estimate the effects of adjusting PEEP and tidal volume (VT) on ΔP, and adjusting VT and respiratory rate (f) on MP.

RESULTS:

Reduction in VT reduced ΔP and MP, with more pronounced effect on MP with lower compliance. Strategies reducing f, consistently increased MP (when VT was adjusted to maintain consistent minute ventilation). Adjustment of PEEP yielded a U-shaped effect on ΔP.

CONCLUSIONS:

This novel conditional modeling confirmed expected response patterns for ΔP, with the response to adjustments depending on patients' lung mechanics. Furthermore a VT -driven approach should be favored over a f -driven approach when aiming to reduce MP.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Respir Care Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Respir Care Ano de publicação: 2022 Tipo de documento: Article