Development and validation of a risk calculator predicting postoperative respiratory failure

Himani Gupta, Prateek K. Gupta, Xiang Fang, Weldon J. Miller, Samuel Cemaj, R. Armour Forse, Lee E. Morrow

Research output: Contribution to journalArticle

82 Citations (Scopus)

Abstract

Background: Postoperative respiratory failure (PRF) (requiring mechanical ventilation > 48 h after surgery or unplanned intubation within 30 days of surgery) is associated with significant morbidity and mortality. The objective of this study was to identify preoperative factors associated with an increased risk of PRF and subsequently develop and validate a risk calculator. Methods: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP), a multicenter, prospective data set (2007-2008), was used. The 2007 data set (n = 211,410) served as the training set and the 2008 data set (n = 257,385) as the validation set. Results: In the training set, 6,531 patients (3.1%) developed PRF. Patients who developed PRF had a significantly higher 30-day mortality (25.62% vs 0.98%, P <.0001). On multivariate logistic regression analysis, five preoperative predictors of PRF were identified: type of surgery, emergency case, dependent functional status, preoperative sepsis, and higher American Society of Anesthesiologists (ASA) class. The risk model based on the training data set was subsequently validated on the validation data set. The model performance was very similar between the training and the validation data sets (c-statistic, 0.894 and 0.897, respectively). The high c-statistics (area under the receiver operating characteristic curve) indicate excellent predictive performance. The risk model was used to develop an interactive risk calculator. Conclusions: Preoperative variables associated with increased risk of PRF include type of surgery, emergency case, dependent functional status, sepsis, and higher ASA class. The validated risk calculator provides a risk estimate of PRF and is anticipated to aid in surgical decision making and informed patient consent.

Original languageEnglish
Pages (from-to)1207-1215
Number of pages9
JournalChest
Volume140
Issue number5
DOIs
StatePublished - Nov 2011

Fingerprint

Respiratory Insufficiency
Sepsis
Emergencies
Mortality
Quality Improvement
Informed Consent
Ambulatory Surgical Procedures
Artificial Respiration
Intubation
ROC Curve
Datasets
Decision Making
Logistic Models
Regression Analysis
Morbidity

All Science Journal Classification (ASJC) codes

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine
  • Cardiology and Cardiovascular Medicine

Cite this

Gupta, H., Gupta, P. K., Fang, X., Miller, W. J., Cemaj, S., Forse, R. A., & Morrow, L. E. (2011). Development and validation of a risk calculator predicting postoperative respiratory failure. Chest, 140(5), 1207-1215. https://doi.org/10.1378/chest.11-0466

Development and validation of a risk calculator predicting postoperative respiratory failure. / Gupta, Himani; Gupta, Prateek K.; Fang, Xiang; Miller, Weldon J.; Cemaj, Samuel; Forse, R. Armour; Morrow, Lee E.

In: Chest, Vol. 140, No. 5, 11.2011, p. 1207-1215.

Research output: Contribution to journalArticle

Gupta, H, Gupta, PK, Fang, X, Miller, WJ, Cemaj, S, Forse, RA & Morrow, LE 2011, 'Development and validation of a risk calculator predicting postoperative respiratory failure', Chest, vol. 140, no. 5, pp. 1207-1215. https://doi.org/10.1378/chest.11-0466
Gupta H, Gupta PK, Fang X, Miller WJ, Cemaj S, Forse RA et al. Development and validation of a risk calculator predicting postoperative respiratory failure. Chest. 2011 Nov;140(5):1207-1215. https://doi.org/10.1378/chest.11-0466
Gupta, Himani ; Gupta, Prateek K. ; Fang, Xiang ; Miller, Weldon J. ; Cemaj, Samuel ; Forse, R. Armour ; Morrow, Lee E. / Development and validation of a risk calculator predicting postoperative respiratory failure. In: Chest. 2011 ; Vol. 140, No. 5. pp. 1207-1215.
@article{19d3fa1943b741f5a9e002b981f780be,
title = "Development and validation of a risk calculator predicting postoperative respiratory failure",
abstract = "Background: Postoperative respiratory failure (PRF) (requiring mechanical ventilation > 48 h after surgery or unplanned intubation within 30 days of surgery) is associated with significant morbidity and mortality. The objective of this study was to identify preoperative factors associated with an increased risk of PRF and subsequently develop and validate a risk calculator. Methods: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP), a multicenter, prospective data set (2007-2008), was used. The 2007 data set (n = 211,410) served as the training set and the 2008 data set (n = 257,385) as the validation set. Results: In the training set, 6,531 patients (3.1{\%}) developed PRF. Patients who developed PRF had a significantly higher 30-day mortality (25.62{\%} vs 0.98{\%}, P <.0001). On multivariate logistic regression analysis, five preoperative predictors of PRF were identified: type of surgery, emergency case, dependent functional status, preoperative sepsis, and higher American Society of Anesthesiologists (ASA) class. The risk model based on the training data set was subsequently validated on the validation data set. The model performance was very similar between the training and the validation data sets (c-statistic, 0.894 and 0.897, respectively). The high c-statistics (area under the receiver operating characteristic curve) indicate excellent predictive performance. The risk model was used to develop an interactive risk calculator. Conclusions: Preoperative variables associated with increased risk of PRF include type of surgery, emergency case, dependent functional status, sepsis, and higher ASA class. The validated risk calculator provides a risk estimate of PRF and is anticipated to aid in surgical decision making and informed patient consent.",
author = "Himani Gupta and Gupta, {Prateek K.} and Xiang Fang and Miller, {Weldon J.} and Samuel Cemaj and Forse, {R. Armour} and Morrow, {Lee E.}",
year = "2011",
month = "11",
doi = "10.1378/chest.11-0466",
language = "English",
volume = "140",
pages = "1207--1215",
journal = "Chest",
issn = "0012-3692",
publisher = "American College of Chest Physicians",
number = "5",

}

TY - JOUR

T1 - Development and validation of a risk calculator predicting postoperative respiratory failure

AU - Gupta, Himani

AU - Gupta, Prateek K.

AU - Fang, Xiang

AU - Miller, Weldon J.

AU - Cemaj, Samuel

AU - Forse, R. Armour

AU - Morrow, Lee E.

PY - 2011/11

Y1 - 2011/11

N2 - Background: Postoperative respiratory failure (PRF) (requiring mechanical ventilation > 48 h after surgery or unplanned intubation within 30 days of surgery) is associated with significant morbidity and mortality. The objective of this study was to identify preoperative factors associated with an increased risk of PRF and subsequently develop and validate a risk calculator. Methods: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP), a multicenter, prospective data set (2007-2008), was used. The 2007 data set (n = 211,410) served as the training set and the 2008 data set (n = 257,385) as the validation set. Results: In the training set, 6,531 patients (3.1%) developed PRF. Patients who developed PRF had a significantly higher 30-day mortality (25.62% vs 0.98%, P <.0001). On multivariate logistic regression analysis, five preoperative predictors of PRF were identified: type of surgery, emergency case, dependent functional status, preoperative sepsis, and higher American Society of Anesthesiologists (ASA) class. The risk model based on the training data set was subsequently validated on the validation data set. The model performance was very similar between the training and the validation data sets (c-statistic, 0.894 and 0.897, respectively). The high c-statistics (area under the receiver operating characteristic curve) indicate excellent predictive performance. The risk model was used to develop an interactive risk calculator. Conclusions: Preoperative variables associated with increased risk of PRF include type of surgery, emergency case, dependent functional status, sepsis, and higher ASA class. The validated risk calculator provides a risk estimate of PRF and is anticipated to aid in surgical decision making and informed patient consent.

AB - Background: Postoperative respiratory failure (PRF) (requiring mechanical ventilation > 48 h after surgery or unplanned intubation within 30 days of surgery) is associated with significant morbidity and mortality. The objective of this study was to identify preoperative factors associated with an increased risk of PRF and subsequently develop and validate a risk calculator. Methods: The American College of Surgeons National Surgical Quality Improvement Program (NSQIP), a multicenter, prospective data set (2007-2008), was used. The 2007 data set (n = 211,410) served as the training set and the 2008 data set (n = 257,385) as the validation set. Results: In the training set, 6,531 patients (3.1%) developed PRF. Patients who developed PRF had a significantly higher 30-day mortality (25.62% vs 0.98%, P <.0001). On multivariate logistic regression analysis, five preoperative predictors of PRF were identified: type of surgery, emergency case, dependent functional status, preoperative sepsis, and higher American Society of Anesthesiologists (ASA) class. The risk model based on the training data set was subsequently validated on the validation data set. The model performance was very similar between the training and the validation data sets (c-statistic, 0.894 and 0.897, respectively). The high c-statistics (area under the receiver operating characteristic curve) indicate excellent predictive performance. The risk model was used to develop an interactive risk calculator. Conclusions: Preoperative variables associated with increased risk of PRF include type of surgery, emergency case, dependent functional status, sepsis, and higher ASA class. The validated risk calculator provides a risk estimate of PRF and is anticipated to aid in surgical decision making and informed patient consent.

UR - http://www.scopus.com/inward/record.url?scp=81055141262&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=81055141262&partnerID=8YFLogxK

U2 - 10.1378/chest.11-0466

DO - 10.1378/chest.11-0466

M3 - Article

VL - 140

SP - 1207

EP - 1215

JO - Chest

JF - Chest

SN - 0012-3692

IS - 5

ER -