The relationship between peak inspiratory flow and hand grip strength measurement in men with mild chronic obstructive pulmonary disease

Abstract

Background Chronic obstructive pulmonary disease (COPD) decreases quality of life and muscular strength. Inspiratory flow is important for inhalants in the bronchi but is complicated to measure in routine practice. We hypothesized that hand grip strength (HGS) would correlate with inhalation rate in patients with mild COPD. Methods The COPD patients were recruited at the St. Marianna University School of Medicine, Yokohama Seibu Hospital, from 2015 to 2018. We measured peak inspiratory flow (PIF) through an In-Check flow meter attached with Diskus [PIF(D)] and Turbuhaler [PIF(T)] inhalers. The 6-min walking test (6MWT), and the fraction of exhaled nitric oxide (FENO), spirometry, HGS, or forced oscillation technique (FOT) parameters were measured. Results Forty-four subjects were enrolled. All were men, with a mean age (± SD) of 77.8 ± 9.36 years. Thirty-nine patients had mild COPD. PIF(D) was 110 (80, 140) L/min (median, interquartile range), PIF(T) was 80 (70, 90) L/min, and HGS was 28.7 (13.8, 43.6) kgf. PIF(D) and PIF(T) were significantly correlated (r = 0.443, p = 0.003). PIF(D) was significantly correlated with age (r = − 0.327, p = 0.030) and HGS (r = 0.326, p = 0.031). PIF(T) was significantly correlated with age (r = − 0.328, p = 0.030), FVC (r = 0.351, p = 0.019), 6MWT distance (r = 0.392, p = 0.011), and HGS (r = 0.328, p = 0.030). Conclusion HGS might be more useful for predicting PIF than other parameters. Also, elderly COPD patients need to be taught inhaled methods carefully.

Correlation between Hand Grip Strength and Peak Inspiratory Flow Rate in Patients with Stable Chronic Obstructive Pulmonary Disease

“…This study differed from our study in that the investigators did not derive a prediction equation for PIFR considering both genders and all stages of disease, and they did not identify a HGS cutoff value associated with suboptimal PIFR. Our study showed higher correlation coefficients of HGS and PIFR (r = 0.591 for Accuhaler and r = 0.614 for Turbuhaler) than the study by Tsuburai [ 21 ], probably because of the larger number of patients in our study and the broader range of HGS. A study of 75 hospitalized patients with acute exacerbation of COPD by Samarghandi et al [ 3 ] demonstrated that HGS was significantly correlated with Accuhaler PIFR.…”

“…A previous study of 44 clinically stable patients with COPD by Tsuburai et al [ 21 ] showed a significant positive correlation between HGS and PIFR for Accuhaler (r = 0.326, p = 0.031) and Turbuhaler (r = 0.328, p = 0.030). This study differed from our study in that the investigators did not derive a prediction equation for PIFR considering both genders and all stages of disease, and they did not identify a HGS cutoff value associated with suboptimal PIFR.…”

Influence of Nurse-Led Health Education on Self-Management Ability, Satisfaction, and Compliance of Elderly Patients with Chronic Obstructive Pulmonary Disease Based on Knowledge, Belief, and Practice Model

“…Knowledge (knowledge and learning) is the foundation, belief (belief and attitude) is the motivation, and action (promoting healthy behavior) is the goal. COPD patients have a long course of disease and repeated attacks of disease, which brings a heavy economic burden to the family and society [ 42 ]. Nurse-led health education based on knowledge, belief, and practice is a scientific nursing method.…”

Patient Characteristics to Consider When Selecting an Inhaler for the Treatment of Chronic Obstructive Pulmonary Disease and Available Assessment Methods: A Narrative Review

“…It has been shown to have excellent reproducibility and a good correlation with PIF derived from spirometry [39, 42, 43, 45] and is increasingly recognized as an easy and fast way to evaluate PIF [46–49]. Different studies show a good correlation between low handgrip strength and weak PIF, which may serve as a surrogate to estimate PIF [23, 50–53]. For example, Frohnhofen et al [50] demonstrated this correlation, with a positive predictive value of 79% and a negative predictive value of 84%.…”