| Title: |
A Least Absolute Shrinkage and Selection Operator-Derived Predictive Model for Postoperative Respiratory Failure in a Heterogeneous Adult Elective Surgery Patient Population |
| Authors: |
Stocking, Jacqueline C; Taylor, Sandra L; Fan, Sili; Wingert, Theodora; Drake, Christiana; Aldrich, J Matthew; Ong, Michael K; Amin, Alpesh N; Marmor, Rebecca A; Godat, Laura; Cannesson, Maxime; Gropper, Michael A; Utter, Garth H; Sandrock, Christian E; Bime, Christian; Mosier, Jarrod; Subbian, Vignesh; Adams, Jason Y; Kenyon, Nicholas J; Albertson, Timothy E; Garcia, Joe GN; Abraham, Ivo |
| Source: |
CHEST Critical Care, vol 1, iss 3 |
| Publisher Information: |
eScholarship, University of California |
| Publication Year: |
2023 |
| Collection: |
University of California: eScholarship |
| Subject Terms: |
32 Biomedical and Clinical Sciences (for-2020); 3202 Clinical Sciences (for-2020); Clinical Research (rcdc); Patient Safety (rcdc); 3 Good Health and Well Being (sdg); bootstrapping; least absolute shrinkage and selection operator; phenotyping; postoperative; predictive model; respiratory failure |
| Description: |
BACKGROUND: Postoperative respiratory failure (PRF) is associated with increased hospital charges and worse patient outcomes. Reliable prediction models can help to guide postoperative planning to optimize care, to guide resource allocation, and to foster shared decision-making with patients. RESEARCH QUESTION: Can a predictive model be developed to accurately identify patients at high risk of PRF? STUDY DESIGN AND METHODS: In this single-site proof-of-concept study, we used structured query language to extract, transform, and load electronic health record data from 23,999 consecutive adult patients admitted for elective surgery (2014-2021). Our primary outcome was PRF, defined as mechanical ventilation after surgery of > 48 h. Predictors of interest included demographics, comorbidities, and intraoperative factors. We used logistic regression to build a predictive model and the least absolute shrinkage and selection operator procedure to select variables and to estimate model coefficients. We evaluated model performance using optimism-corrected area under the receiver operating curve and area under the precision-recall curve and calculated sensitivity, specificity, positive and negative predictive values, and Brier scores. RESULTS: Two hundred twenty-five patients (0.94%) demonstrated PRF. The 18-variable predictive model included: operations on the cardiovascular, nervous, digestive, urinary, or musculoskeletal system; surgical specialty orthopedic (nonspine); Medicare or Medicaid (as the primary payer); race unknown; American Society of Anesthesiologists class ≥ III; BMI of 30 to 34.9 kg/m2; anesthesia duration (per hour); net fluid at end of the operation (per liter); median intraoperative FIO2, end title CO2, heart rate, and tidal volume; and intraoperative vasopressor medications. The optimism-corrected area under the receiver operating curve was 0.835 (95% CI,0.808-0.862) and the area under the precision-recall curve was 0.156 (95% CI, 0.105-0.203). INTERPRETATION: This single-center proof-of-concept ... |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
qt16z563r5; https://escholarship.org/uc/item/16z563r5; https://escholarship.org/content/qt16z563r5/qt16z563r5.pdf |
| DOI: |
10.1016/j.chstcc.2023.100025 |
| Availability: |
https://escholarship.org/uc/item/16z563r5; https://escholarship.org/content/qt16z563r5/qt16z563r5.pdf; https://doi.org/10.1016/j.chstcc.2023.100025 |
| Rights: |
CC-BY |
| Accession Number: |
edsbas.DB8D9FDA |
| Database: |
BASE |