Abstract

BackgroundIt has been shown that home mechanical ventilation improves quality of life, but it has not been widely studied which particular patient groups benefit the most from starting this type of therapy. The purpose of this prospective observational study was to evaluate quality of life change patterns 6 months after initiation of home mechanical ventilation in patients suffering from chronic respiratory failure using patient reported outcomes.MethodsWe enrolled 74 chronic respiratory failure patients starting invasive or noninvasive home mechanical ventilation through the Semmelweis University Home Mechanical Ventilation Program. Quality of life was evaluated at baseline and at 6 months after initiation of home mechanical ventilation using the Severe Respiratory Insufficiency Questionnaire.ResultsOverall quality of life showed 10.5% improvement 6 months after initiation of home mechanical ventilation (p < 0.001). The greatest improvement was observed in Respiratory complaint (20.4%, p = 0.015), Sleep and attendant symptoms (19.3%, p < 0.001), and Anxiety related subscales (14.4%, p < 0.001). Interface (invasive versus noninvasive ventilation) was not associated with improvement in quality of life (p = 0.660). Severely impaired patients showed the greatest improvement (CC = -0.328, p < 0.001). Initial diagnosis contributed to the observed change (p = 0.025), with chronic obstructive pulmonary disease and obesity hypoventilation syndrome patients showing the greatest improvement, while amyotrophic lateral sclerosis patients showed no improvement in quality of life. We found that patients who were started on long term ventilation in an acute setting, required oxygen supplementation and had low baseline quality of life, showed the most improvement during the six-month study period.ConclusionsOur study highlights the profound effect of home mechanical ventilation on quality of life in chronic respiratory failure patients that is indifferent of ventilation interface but is dependent on initial diagnosis and some baseline characteristics, like acute initiation, oxygen supplementation need and baseline quality of life.Trial registrationThis study was approved by and registered at the ethics committee of Semmelweis University (SE TUKEB 251/2017; 20th of December, 2017).

Highlights

  • It has been shown that home mechanical ventilation improves quality of life, but it has not been widely studied which particular patient groups benefit the most from starting this type of therapy

  • The factors that can possibly affect change in health related quality of life (HRQL) are baseline characteristics, initial diagnosis, initial HRQL, type of interface used for ventilation, duration of ventilation and lung function test parameters

  • When further analyzing factors affecting HRQL changes in patients receiving home mechanical ventilation, we found that change in SRI subscales showed significant correlation with baseline SRI scores (SRI-RC: p < 0.001; Correlation coefficient (CC) = -0.782; Physical functioning (SRI-PF): p = 0.0314; CC = -0.265; Attendant symptoms and sleep (SRI-AS) p < 0.001; CC = -0.769; Social relationships (SRI-SR): p = 0.006; CC = -0.336; SRI-AX: p < 0.001; CC = -0.559; Psychological well-being (SRI-WB): p < 0.001; CC = -0.465; Social functioning (SRI-SF): p = 0.007; CC = -0.328; SRI-SS: p < 0.001; CC = -0.411) (Fig. 4)

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Summary

Introduction

It has been shown that home mechanical ventilation improves quality of life, but it has not been widely studied which particular patient groups benefit the most from starting this type of therapy. The purpose of this prospective observational study was to evaluate quality of life change patterns 6 months after initiation of home mechanical ventilation in patients suffering from chronic respiratory failure using patient reported outcomes. Chronic respiratory failure affects many people, causing hypoxia, hypercapnia, secondary symptoms, diminished health related quality of life (HRQL) and adverse outcomes. HRQL measurements are important tools for quality control, optimization of therapy and even outcome prediction [8]

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