Abstract
BACKGROUND: Assessment of a patient's readiness for removal of the endotracheal tube in the ICU is based on respiratory, airway, and neurological measures. However, nearly 20% of patients require reintubation. We created a prediction model for the need for reintubation, which incorporates variables importantly contributing to extubation failure. METHODS: This was a cohort study of 2,007 endotracheally intubated subjects who required ICU admission at a tertiary care center. Data collection included demographic, hemodynamic, respiratory, and neurological variables preceding extubation. Data were compared between subjects extubated successfully and those who required reintubation, using bivariate logistic regression models, with the binary outcome reintubation and the baseline characteristics as predictors. Multivariable logistic regression analysis with robust variance was used to build the prediction model. RESULTS: Of the 2,007 subjects analyzed, 376 (19%) required reintubation. In the bivariate analysis, admission Simplified Acute Physiology Score II, minute ventilation, breathing frequency, oxygenation, number of prior SBTs, rapid shallow breathing index, airway-secretions suctioning frequency and quantity, heart rate, and diastolic blood pressure differed significantly between the extubation success and failure groups. In the multivariable analysis, higher Simplified Acute Physiology Score II and suctioning frequency were associated with failed extubation. The area under the receiver operating characteristic curve was 0.68 for failure at any time, and 0.71 for failure within 24 hours. However, prior failed SBT, minute ventilation, and diastolic blood pressure were additional independent predictors of failure at any time, whereas oxygenation predicted extubation failure within 24 hours. CONCLUSIONS: A small number of independent variables explains a substantial portion of the variability of extubation failure, and can help identify patients at high risk of needing reintubation. These characteristics should be incorporated in the decision-making process of ICU extubation.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 178-185 |
| Number of pages | 8 |
| Journal | Respiratory Care |
| Volume | 59 |
| Issue number | 2 |
| DOIs | |
| State | Published - Feb 1 2014 |
| Externally published | Yes |
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Keywords
- Airway management
- Clinical prediction model
- Cohort study
- Extubation
- Human
- ICU
- Mechanical ventilation
ASJC Scopus subject areas
- Pulmonary and Respiratory Medicine
- Critical Care and Intensive Care Medicine
Cite this
Predictors of reintubation in critically Ill patients. / Miu, Timothy; Joffe, Aaron M.; Yanez, Norbert; Khandelwal, Nita; Dagal, Armagan H C; Deem, Steven; Treggiari, Miriam.
In: Respiratory Care, Vol. 59, No. 2, 01.02.2014, p. 178-185.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Predictors of reintubation in critically Ill patients
AU - Miu, Timothy
AU - Joffe, Aaron M.
AU - Yanez, Norbert
AU - Khandelwal, Nita
AU - Dagal, Armagan H C
AU - Deem, Steven
AU - Treggiari, Miriam
PY - 2014/2/1
Y1 - 2014/2/1
N2 - BACKGROUND: Assessment of a patient's readiness for removal of the endotracheal tube in the ICU is based on respiratory, airway, and neurological measures. However, nearly 20% of patients require reintubation. We created a prediction model for the need for reintubation, which incorporates variables importantly contributing to extubation failure. METHODS: This was a cohort study of 2,007 endotracheally intubated subjects who required ICU admission at a tertiary care center. Data collection included demographic, hemodynamic, respiratory, and neurological variables preceding extubation. Data were compared between subjects extubated successfully and those who required reintubation, using bivariate logistic regression models, with the binary outcome reintubation and the baseline characteristics as predictors. Multivariable logistic regression analysis with robust variance was used to build the prediction model. RESULTS: Of the 2,007 subjects analyzed, 376 (19%) required reintubation. In the bivariate analysis, admission Simplified Acute Physiology Score II, minute ventilation, breathing frequency, oxygenation, number of prior SBTs, rapid shallow breathing index, airway-secretions suctioning frequency and quantity, heart rate, and diastolic blood pressure differed significantly between the extubation success and failure groups. In the multivariable analysis, higher Simplified Acute Physiology Score II and suctioning frequency were associated with failed extubation. The area under the receiver operating characteristic curve was 0.68 for failure at any time, and 0.71 for failure within 24 hours. However, prior failed SBT, minute ventilation, and diastolic blood pressure were additional independent predictors of failure at any time, whereas oxygenation predicted extubation failure within 24 hours. CONCLUSIONS: A small number of independent variables explains a substantial portion of the variability of extubation failure, and can help identify patients at high risk of needing reintubation. These characteristics should be incorporated in the decision-making process of ICU extubation.
AB - BACKGROUND: Assessment of a patient's readiness for removal of the endotracheal tube in the ICU is based on respiratory, airway, and neurological measures. However, nearly 20% of patients require reintubation. We created a prediction model for the need for reintubation, which incorporates variables importantly contributing to extubation failure. METHODS: This was a cohort study of 2,007 endotracheally intubated subjects who required ICU admission at a tertiary care center. Data collection included demographic, hemodynamic, respiratory, and neurological variables preceding extubation. Data were compared between subjects extubated successfully and those who required reintubation, using bivariate logistic regression models, with the binary outcome reintubation and the baseline characteristics as predictors. Multivariable logistic regression analysis with robust variance was used to build the prediction model. RESULTS: Of the 2,007 subjects analyzed, 376 (19%) required reintubation. In the bivariate analysis, admission Simplified Acute Physiology Score II, minute ventilation, breathing frequency, oxygenation, number of prior SBTs, rapid shallow breathing index, airway-secretions suctioning frequency and quantity, heart rate, and diastolic blood pressure differed significantly between the extubation success and failure groups. In the multivariable analysis, higher Simplified Acute Physiology Score II and suctioning frequency were associated with failed extubation. The area under the receiver operating characteristic curve was 0.68 for failure at any time, and 0.71 for failure within 24 hours. However, prior failed SBT, minute ventilation, and diastolic blood pressure were additional independent predictors of failure at any time, whereas oxygenation predicted extubation failure within 24 hours. CONCLUSIONS: A small number of independent variables explains a substantial portion of the variability of extubation failure, and can help identify patients at high risk of needing reintubation. These characteristics should be incorporated in the decision-making process of ICU extubation.
KW - Airway management
KW - Clinical prediction model
KW - Cohort study
KW - Extubation
KW - Human
KW - ICU
KW - Mechanical ventilation
UR - http://www.scopus.com/inward/record.url?scp=84893318146&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893318146&partnerID=8YFLogxK
U2 - 10.4187/respcare.02527
DO - 10.4187/respcare.02527
M3 - Article
C2 - 23882103
AN - SCOPUS:84893318146
VL - 59
SP - 178
EP - 185
JO - Respiratory Care
JF - Respiratory Care
SN - 0020-1324
IS - 2
ER -