Development and validation of severe hypoxemia associated risk prediction model in 1,000 mechanically ventilated patients*.
Crit Care Med
; 43(2): 308-17, 2015 Feb.
Article
in En
| MEDLINE
| ID: mdl-25318386
ABSTRACT
OBJECTIVES:
Patients with severe, persistent hypoxemic respiratory failure have a higher mortality. Early identification is critical for informing clinical decisions, using rescue strategies, and enrollment in clinical trials. The objective of this investigation was to develop and validate a prediction model to accurately and timely identify patients with severe hypoxemic respiratory failure at high risk of death, in whom novel rescue strategies can be efficiently evaluated.DESIGN:
Electronic medical record analysis.SETTING:
Medical, surgical, and mixed ICU setting at a tertiary care institution. PATIENTS Mechanically-ventilated ICU patients. MEASUREMENTS AND MAINRESULTS:
Mechanically ventilated ICU patients were screened for severe hypoxemic respiratory failure (Murray lung injury score of ≥ 3). Survival to hospital discharge was the dependent variable. Clinical predictors within 24 hours of onset of severe hypoxemia were considered as the independent variables. An area under the curve and a Hosmer-Lemeshow goodness-of-fit test were used to assess discrimination and calibration. A logistic regression model was developed in the derivation cohort (2005-2007). The model was validated in an independent cohort (2008-2010). Among 79,341 screened patients, 1,032 met inclusion criteria. Mortality was 41% in the derivation cohort (n = 464) and 35% in the validation cohort (n = 568). The final model included hematologic malignancy, cirrhosis, aspiration, estimated dead space, oxygenation index, pH, and vasopressor use. The area under the curve of the model was 0.85 (0.82-0.89) and 0.79 (0.75-0.82) in the derivation and validation cohorts, respectively, and showed good calibration. A modified model, including only physiologic variables, performed similarly. It had comparable performance in patients with acute respiratory distress syndrome and outperformed previous prognostic models.CONCLUSIONS:
A model using comorbid conditions and physiologic variables on the day of developing severe hypoxemic respiratory failure can predict hospital mortality.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Respiration, Artificial
/
Respiratory Insufficiency
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Intensive Care Units
/
Hypoxia
Type of study:
Etiology_studies
/
Prognostic_studies
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Risk_factors_studies
Limits:
Adult
/
Aged
/
Female
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Humans
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Male
/
Middle aged
Language:
En
Journal:
Crit Care Med
Year:
2015
Type:
Article