Literature DB >> 7842784

Predictors of weaning after 6 weeks of mechanical ventilation.

D J Scheinhorn1, M Hassenpflug, B M Artinian, L LaBree, J L Catlin.   

Abstract

STUDY
OBJECTIVE: To identify variables associated with weaning outcome in long-term ventilator-dependent patients. Using those variables, to construct models to predict weaning success and to test the accuracy of those models.
DESIGN: Retrospective medical record review.
SETTING: Regional weaning center (RWC). PATIENTS: An initial group of 421 and a subsequent group of 170 consecutive patients referred for attempted weaning after 6 weeks of mechanical ventilation. MEASUREMENTS AND
RESULTS: Data obtained on admission to our facility were analyzed for correlation with weaning outcome. In the initial patient group, selected variables which correlated with weaning success were alveolar-arterial oxygen pressure difference (P[A-a]O2), BUN, BUN/creatinine ratio (each with p < or = 0.001), and female gender (p = 0.04). We used these variables in logistic regression models to predict weaning success in this population. We then tested the models in the 170-patient validation group using both standard and receiver operating characteristic (ROC) curve analysis. The ROC analysis indicated 59% accuracy using P(A-a)O2 alone and 68% accuracy using all previously mentioned variables. We used data from all 565 patients with known outcome and omitted BUN/creatinine ratio to fashion a simple scoring system to predict weaning success with 70% accuracy using P(A-a)O2, BUN, and Gender--the A+B+G score.
CONCLUSION: In patients suffering prolonged mechanical ventilation, models incorporating simple measurements allowed construction of a score to predict weaning success at our RWC.

Entities:  

Mesh:

Year:  1995        PMID: 7842784     DOI: 10.1378/chest.107.2.500

Source DB:  PubMed          Journal:  Chest        ISSN: 0012-3692            Impact factor:   9.410


  13 in total

1.  Testing the prognostic value of the rapid shallow breathing index in predicting successful weaning in patients requiring prolonged mechanical ventilation.

Authors:  Avelino C Verceles; Montserrat Diaz-Abad; Jeanne Geiger-Brown; Steven M Scharf
Journal:  Heart Lung       Date:  2012-07-06       Impact factor: 2.210

2.  Outcomes, cost and long term survival of patients referred to a regional weaning centre.

Authors:  D V Pilcher; M J Bailey; D F Treacher; S Hamid; A J Williams; A C Davidson
Journal:  Thorax       Date:  2005-03       Impact factor: 9.139

3.  Inspiratory muscle strength training improves weaning outcome in failure to wean patients: a randomized trial.

Authors:  A Daniel Martin; Barbara K Smith; Paul D Davenport; Eloise Harman; Ricardo J Gonzalez-Rothi; Maher Baz; A Joseph Layon; Michael J Banner; Lawrence J Caruso; Harsha Deoghare; Tseng-Tien Huang; Andrea Gabrielli
Journal:  Crit Care       Date:  2011-03-07       Impact factor: 9.097

4.  Impact of renal dysfunction on weaning from prolonged mechanical ventilation.

Authors: 
Journal:  Crit Care       Date:  1997       Impact factor: 9.097

5.  Predictors and pattern of weaning and long-term outcome of patients with prolonged mechanical ventilation at an acute intensive care unit in North India.

Authors:  Syed Nabeel Muzaffar; Mohan Gurjar; Arvind K Baronia; Afzal Azim; Prabhakar Mishra; Banani Poddar; Ratender K Singh
Journal:  Rev Bras Ter Intensiva       Date:  2017 Jan-Mar

6.  Predicting weaning difficulty for planned extubation patients with an artificial neural network.

Authors:  Meng Hsuen Hsieh; Meng Ju Hsieh; Ai-Chin Cheng; Chin-Ming Chen; Chia-Chang Hsieh; Chien-Ming Chao; Chih-Cheng Lai; Kuo-Chen Cheng; Willy Chou
Journal:  Medicine (Baltimore)       Date:  2019-10       Impact factor: 1.889

7.  Association of weaning preparedness with extubation outcome of mechanically ventilated patients in medical intensive care units: a retrospective analysis.

Authors:  Feng-Ching Lin; Yao-Wen Kuo; Jih-Shuin Jerng; Huey-Dong Wu
Journal:  PeerJ       Date:  2020-04-13       Impact factor: 2.984

8.  Development and prospective validation of a model for predicting weaning in chronic ventilator dependent patients.

Authors:  Katherine P Hendra; Peter A L Bonis; Martin Joyce-Brady
Journal:  BMC Pulm Med       Date:  2003-11-13       Impact factor: 3.317

9.  An Artificial Neural Network Model for Predicting Successful Extubation in Intensive Care Units.

Authors:  Meng-Hsuen Hsieh; Meng-Ju Hsieh; Chin-Ming Chen; Chia-Chang Hsieh; Chien-Ming Chao; Chih-Cheng Lai
Journal:  J Clin Med       Date:  2018-08-25       Impact factor: 4.241

10.  Data Science for Extubation Prediction and Value of Information in Surgical Intensive Care Unit.

Authors:  Tsung-Lun Tsai; Min-Hsin Huang; Chia-Yen Lee; Wu-Wei Lai
Journal:  J Clin Med       Date:  2019-10-17       Impact factor: 4.241

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