Relationship between Peak Inspiratory Flow and Patient and Disease Characteristics in Individuals with COPD-A Systematic Scoping Review.
Marika T LevingJanwillem W H KocksSinthia Bosnic-AnticevichRichard DekhuijzenOmar S UsmaniPublished in: Biomedicines (2022)
Optimal delivery of medication via dry powder inhalers, the most commonly prescribed inhaler type, is dependent on a patient achieving a minimum level of inspiratory flow during inhalation. However, measurement of peak inspiratory flow (PIF) against the simulated resistance of a dry powder inhaler is not frequently performed in clinical practice due to time or equipment limitations. Therefore, defining which patient characteristics are associated with lower PIF is critically important to help clinicians optimize their inhaler choice through a more personalized approach to prescribing. The objective of this scoping review was to systematically evaluate patient and disease characteristics determining PIF in patients with chronic obstructive pulmonary disease (COPD). Medline, Cochrane and Embase databases were systematically searched for relevant studies on PIF in patients with COPD published in English between January 2000 and May 2021. The quality of evidence was assessed using a modified Grading of Recommendations Assessment, Development and Evaluation checklist. Of 3382 citations retrieved, 35 publications were included in the review (nine scored as high quality, 13 as moderate, nine as low, and four as very low). Factors correlating with PIF in >70% of papers included both patient characteristics (lower PIF correlated with increased age, female gender, shorter height, decreased handgrip and inspiratory muscle strength, and certain comorbidities) and disease characteristics (lower PIF correlated with markers of lung hyperinflation, lower peak expiratory flow [PEF] and increased disease severity). Other factors correlating with adequate/optimal or improved PIF included education/counseling and exercise/inspiratory muscle training; impaired physical function and errors in inhalation technique/non-adherence were associated with low/suboptimal PIF. In conclusion, clinicians should measure PIF against the simulated resistance of a particular device wherever possible. However, as this often cannot be done due to lack of resources or time, the patient and disease characteristics that influence PIF, as identified in this review, can help clinicians to choose the most appropriate inhaler type for their patients.
Keyphrases
- case report
- chronic obstructive pulmonary disease
- healthcare
- palliative care
- randomized controlled trial
- systematic review
- lung function
- type diabetes
- newly diagnosed
- deep learning
- ejection fraction
- cystic fibrosis
- end stage renal disease
- emergency department
- prognostic factors
- quality improvement
- machine learning
- adverse drug
- artificial intelligence
- patient reported
- human immunodeficiency virus
- men who have sex with men
- weight loss
- smoking cessation
- hiv infected
- big data
- extracorporeal membrane oxygenation
- clinical evaluation