Search

Your search keyword '"Engoren, Milo C."' showing total 22 results
Start Over Author "Engoren, Milo C." Publisher ovid technologies (wolters kluwer health)
22 results on '"Engoren, Milo C."'

2. Prediction of Postoperative Deterioration in Cardiac Surgery Patients Using Electronic Health Record and Physiologic Waveform Data

Author

Mathis, Michael R., Engoren, Milo C., Williams, Aaron M., Biesterveld, Ben E., Croteau, Alfred J., Cai, Lingrui, Kim, Renaid B., Liu, Gang, Ward, Kevin R., Najarian, Kayvan, and Gryak, Jonathan

Subjects
Adult, Machine Learning, Anesthesiology and Pain Medicine, Epinephrine, Humans, Electronic Health Records, Hypotension, Cardiac Surgical Procedures, Article
Abstract

Background Postoperative hemodynamic deterioration among cardiac surgical patients can indicate or lead to adverse outcomes. Whereas prediction models for such events using electronic health records or physiologic waveform data are previously described, their combined value remains incompletely defined. The authors hypothesized that models incorporating electronic health record and processed waveform signal data (electrocardiogram lead II, pulse plethysmography, arterial catheter tracing) would yield improved performance versus either modality alone. Methods Intensive care unit data were reviewed after elective adult cardiac surgical procedures at an academic center between 2013 and 2020. Model features included electronic health record features and physiologic waveforms. Tensor decomposition was used for waveform feature reduction. Machine learning–based prediction models included a 2013 to 2017 training set and a 2017 to 2020 temporal holdout test set. The primary outcome was a postoperative deterioration event, defined as a composite of low cardiac index of less than 2.0 ml min˗1 m˗2, mean arterial pressure of less than 55 mmHg sustained for 120 min or longer, new or escalated inotrope/vasopressor infusion, epinephrine bolus of 1 mg or more, or intensive care unit mortality. Prediction models analyzed data 8 h before events. Results Among 1,555 cases, 185 (12%) experienced 276 deterioration events, most commonly including low cardiac index (7.0% of patients), new inotrope (1.9%), and sustained hypotension (1.4%). The best performing model on the 2013 to 2017 training set yielded a C-statistic of 0.803 (95% CI, 0.799 to 0.807), although performance was substantially lower in the 2017 to 2020 test set (0.709, 0.705 to 0.712). Test set performance of the combined model was greater than corresponding models limited to solely electronic health record features (0.641; 95% CI, 0.637 to 0.646) or waveform features (0.697; 95% CI, 0.693 to 0.701). Conclusions Clinical deterioration prediction models combining electronic health record data and waveform data were superior to either modality alone, and performance of combined models was primarily driven by waveform data. Decreased performance of prediction models during temporal validation may be explained by data set shift, a core challenge of healthcare prediction modeling. Editor’s Perspective What We Already Know about This Topic What This Article Tells Us That Is New

Published
2022

5. Difficulty in Advancing Flexible Epidural Catheters When Establishing Labor Analgesia: An Observational Open-Label Randomized Trial

Author

Pancaro, Carlo, primary, Purtell, Jasmine, additional, LaBuda, Dana, additional, Saager, Leif, additional, Klumpner, Thomas T., additional, Dubovoy, Timur, additional, Rajala, Baskar, additional, Singh, Shubhangi, additional, Cassidy, Ruth, additional, Vahabzadeh, Christie, additional, Maxwell, Sean, additional, Manica, Virgil, additional, Eckmann, David M., additional, Mhyre, Jill M., additional, and Engoren, Milo C., additional

Published
2021
Full Text
View/download PDF

7. Lung-protective Ventilation in Cardiac Surgery: Reply

Author

Mathis, Michael R., primary, Likosky, Donald S., additional, Haft, Jonathan W., additional, Maile, Michael D., additional, Blank, Randal S., additional, Colquhoun, Douglas A., additional, Janda, Allison M., additional, Kheterpal, Sachin, additional, and Engoren, Milo C., additional

Published
2020
Full Text
View/download PDF

8. Early Detection of Heart Failure With Reduced Ejection Fraction Using Perioperative Data Among Noncardiac Surgical Patients

Author

Mathis, Michael R., primary, Engoren, Milo C., additional, Joo, Hyeon, additional, Maile, Michael D., additional, Aaronson, Keith D., additional, Burns, Michael L., additional, Sjoding, Michael W., additional, Douville, Nicholas J., additional, Janda, Allison M., additional, Hu, Yaokun, additional, Najarian, Kayvan, additional, and Kheterpal, Sachin, additional

Published
2020
Full Text
View/download PDF

10. Intraoperative Mechanical Ventilation and Postoperative Pulmonary Complications after Cardiac Surgery

Author

Mathis, Michael R., primary, Duggal, Neal M., additional, Likosky, Donald S., additional, Haft, Jonathan W., additional, Douville, Nicholas J., additional, Vaughn, Michelle T., additional, Maile, Michael D., additional, Blank, Randal S., additional, Colquhoun, Douglas A., additional, Strobel, Raymond J., additional, Janda, Allison M., additional, Zhang, Min, additional, Kheterpal, Sachin, additional, and Engoren, Milo C., additional

Published
2019
Full Text
View/download PDF

12. In Reply

Author

Mathis, Michael R., primary, Sathishkumar, Subramanian, additional, and Engoren, Milo C., additional

Published
2017
Full Text
View/download PDF

15. In Response

Author

Maile, Michael D., primary, Engoren, Milo C., additional, Tremper, Kevin K., additional, Tremper, Tyler T., additional, Jewell, Elizabeth S., additional, and Kheterpal, Sachin, additional

Published
2016
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results