InfluÃncia da mecÃnica e padrÃo respiratÃrios e do tipo de ventilador pulmonar mecÃnico na assincronia paciente-ventilador durante a ventilaÃÃo nÃo invasiva

• Autor(a) principal: Luiz Henrique de Paula Melo
• Data de Publicação: 2014
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFC
• Texto Completo: http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=12073
• topic: FISIOTERAPIA E TERAPIA OCUPACIONAL

Contextualization: Ideal patient-ventilator synchrony can be very difficult to achieve, especially during NIV, due presence of. Intensive care unit (ICU) ventilators were designed to function without the presence of leaks and are likely to suffer interference in their presence during NIV, but the latest generation of ventilators incorporated NIV algorithms (âNIV modesâ) to compensate e deal better with leaks. Auto-Trak consists in a technology capable to automatically adjust, cycle by cycle, triggering and cycling mechanisms during PSV. Objectives: Determine the influence of the type of pulmonary ventilator, respiratory mechanics and breathing pattern on patient-ventilator asynchrony during NIV, with and without the use of NIV algorithms, and with and without an automatic triggering and cycling system. Methods: Experimental bench study using the mechanic lung model, ASL 5000TM. Three profiles of respiratory mechanics were studied: normal, obstructive and restrictive, with neural inspiratory time of 0.5, 1.0, 1.5 and 2.0 seconds and maximum intensity of muscle effort (Pmus) fixed in -7.5 cmH2O. We simulated NIV in five ICU ventilators and in four noninvasive ventilators. Auto-TrakTM was studied when available in the ventilator. Primary outcomes were: respiratory asynchronies, inspiratory delay time and cycling asynchrony time identifying, in the second case, two possible types, late or premature cycling. Results: Inspiratory delay time was shorter on dedicated NIV ventilators in most of situations. A short neural time was associated with late cycling and a long neural time with premature cycling. Dedicated NIV ventilators cycled later than the ICU ventilators, when the neural time was 0,5s and mostly in the obstructive pattern, but was associated with a shorter cycling asynchrony time when the neural time was longer (> 1,0s). NIV algorithms and Auto-TrakTM had little impact on triggering and cycling, however remained slightly more stable the effective PEEP. Conclusion: Respiratory mechanics and breathing pattern influence the degree of patient-ventilator asynchrony during NIV. Neural time is a determinant factor of triggering and cycling asynchronies, associated to late cycling when short and to premature cycling when long. The type of mechanical ventilator influence, on varying intensity, the degree of asynchrony. NIV algoritms and Auto-TrakTM have little impact on triggering and cycling. Keywords: Artificial Respiration. Respiratory Mechanics. Noninvasive Ventilation