Literature DB >> 7711709

Weaning and outcome from mechanical ventilation.

S Nava1, E Zanotti, F Rubini.   

Abstract

Weaning means the ability of a patient to breath spontaneously after mechanical ventilation. In chronic obstructive pulmonary disease (COPD) patients, inability to tolerate discontinuation of mechanical ventilation is reported to have an incidence of 25-60%. It is, therefore, important to employ simple parameters able to predict weaning success, since, in the case of failure, the validation of predictive indices of weaning may also contribute to the decision of whether or not these patients should eventually enter a programme of home ventilation. Among other indices employed, respiratory frequency/tidal volume (f/VT) ratio, compliance, rate, oxygenation and pressure (CROP) index, mouth occlusion pressure (P0.1) and static compliance of the respiratory system have been shown to be quite accurate. The survival at one year of these patients requiring mechanical ventilation ranges 34-49%. Indeed, there is a particular subset of COPD patients in whom mechanical ventilation is prolonged due to the severity of their pathology. We studied 42 of these patients requiring mechanical ventilation for more than 21 days, to assess with simple parameters (arterial blood gases, pulmonary function tests, respiratory muscle force, P0.1, nutritional status) their potential for weaning and their survival at 2 yrs. Using discriminant analysis, and employing an equation comprising maximal inspiratory pressure (MIP) and arterial carbon dioxide tension (PaCO2), we were able to predict the patients able or unable to be weaned with an accuracy of almost 85%.(ABSTRACT TRUNCATED AT 250 WORDS)

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Mesh:

Year:  1994        PMID: 7711709

Source DB:  PubMed          Journal:  Monaldi Arch Chest Dis        ISSN: 1122-0643


  3 in total

1.  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

Review 2.  Clinical review: liberation from mechanical ventilation.

Authors:  Mohamad F El-Khatib; Pierre Bou-Khalil
Journal:  Crit Care       Date:  2008-08-06       Impact factor: 9.097

3.  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

  3 in total

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