Literature DB >> 20842209

Predicting Acute Hypotensive Episodes: The 10th Annual PhysioNet/Computers in Cardiology Challenge.

Gb Moody1, Lh Lehman.   

Abstract

This year's PhysioNet/Computers in Cardiology Challenge aimed to stimulate development of methods for identifying intensive care unit (ICU) patients at imminent risk of acute hypotensive episodes (AHEs), motivated by the possibility of improving care and survival of these patients. Participants were asked to forecast the occurrence of an AHE up to an hour in advance, in two groups of ICU patient records from the MIMIC II Database, drawing on data that included at least 10 hours of physiologic waveforms, time series, and accompanying clinical data prior to the one-hour forecast window. In event 1, most participants were able to identify without errors, in a group of 10 high-risk patients receiving pressor medication, which five of the patients experienced AHEs during the forecast window. In event 2, participants were able to classify correctly as many as 37 (93%) of a diverse group of 40 patients, including nearly all of those who experienced AHEs.

Entities:  

Year:  2009        PMID: 20842209      PMCID: PMC2937253     

Source DB:  PubMed          Journal:  Comput Cardiol        ISSN: 0276-6574


  2 in total

1.  PhysioBank, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals.

Authors:  A L Goldberger; L A Amaral; L Glass; J M Hausdorff; P C Ivanov; R G Mark; J E Mietus; G B Moody; C K Peng; H E Stanley
Journal:  Circulation       Date:  2000-06-13       Impact factor: 29.690

2.  MIMIC II: a massive temporal ICU patient database to support research in intelligent patient monitoring.

Authors:  M Saeed; C Lieu; G Raber; R G Mark
Journal:  Comput Cardiol       Date:  2002
  2 in total
  11 in total

1.  Forewarning of hypotensive events using a Bayesian artificial neural network in neurocritical care.

Authors:  Rob Donald; Tim Howells; Ian Piper; P Enblad; P Nilsson; I Chambers; B Gregson; G Citerio; K Kiening; J Neumann; A Ragauskas; J Sahuquillo; R Sinnott; A Stell
Journal:  J Clin Monit Comput       Date:  2018-05-24       Impact factor: 2.502

2.  Hypotension Risk Prediction via Sequential Contrast Patterns of ICU Blood Pressure.

Authors:  Shameek Ghosh; Mengling Feng; Hung Nguyen; Jinyan Li
Journal:  IEEE J Biomed Health Inform       Date:  2015-07-07       Impact factor: 5.772

3.  Risk prediction for acute hypotensive patients by using gap constrained sequential contrast patterns.

Authors:  Shameek Ghosh; Mengling Feng; Hung Nguyen; Jinyan Li
Journal:  AMIA Annu Symp Proc       Date:  2014-11-14

4.  A Machine Learning Approach for Predicting Real-time Risk of Intraoperative Hypotension in Traumatic Brain Injury.

Authors:  Shara I Feld; Daniel S Hippe; Ljubomir Miljacic; Nayak L Polissar; Shu-Fang Newman; Bala G Nair; Monica S Vavilala
Journal:  J Neurosurg Anesthesiol       Date:  2021-11-11       Impact factor: 3.969

5.  Real-time prediction of disordered breathing events in people with obstructive sleep apnea.

Authors:  Jonathan A Waxman; Daniel Graupe; David W Carley
Journal:  Sleep Breath       Date:  2014-05-08       Impact factor: 2.816

Review 6.  Multimodality monitoring: informatics, integration data display and analysis.

Authors:  J Michael Schmidt; Michael De Georgia
Journal:  Neurocrit Care       Date:  2014-12       Impact factor: 3.210

7.  Accessing the public MIMIC-II intensive care relational database for clinical research.

Authors:  Daniel J Scott; Joon Lee; Ikaro Silva; Shinhyuk Park; George B Moody; Leo A Celi; Roger G Mark
Journal:  BMC Med Inform Decis Mak       Date:  2013-01-10       Impact factor: 2.796

8.  Learning stochastic finite-state transducer to predict individual patient outcomes.

Authors:  Patricia Ordoñez; Nelson Schwarz; Adnel Figueroa-Jiménez; Leonardo A Garcia-Lebron; Abiel Roche-Lima
Journal:  Health Technol (Berl)       Date:  2016-10-17

9.  A dual boundary classifier for predicting acute hypotensive episodes in critical care.

Authors:  Sakyajit Bhattacharya; Vijay Huddar; Vaibhav Rajan; Chandan K Reddy
Journal:  PLoS One       Date:  2018-02-23       Impact factor: 3.240

10.  Generalizable deep temporal models for predicting episodes of sudden hypotension in critically ill patients: a personalized approach.

Authors:  Brandon Chan; Brian Chen; Alireza Sedghi; Philip Laird; David Maslove; Parvin Mousavi
Journal:  Sci Rep       Date:  2020-07-10       Impact factor: 4.379

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