Literature DB >> 32350352

Inappropriate Peak Inspiratory Flow Rate with Dry Powder Inhaler in Chronic Obstructive Pulmonary Disease.

Shih-Yu Chen1, Chun-Kai Huang1,2, Hui-Chuan Peng3, Chong-Jen Yu1, Jung-Yien Chien4.   

Abstract

Optimal peak inspiratory flow rate (PIFR) is crucial for optimizing dry powder inhaler (DPI) effectiveness for chronic obstructive pulmonary disease (COPD). This study provide an insight that there was a substantial proportion of improper PIFRs (not only insufficient but also excessive) among COPD patients using DPIs. We enrolled 138 COPD patients from a medical center in Taiwan and measured PIFRs against different internal resistances of DPIs. Proportion of excessive, optimal, suboptimal, and insufficient PIFRs were 2%, 54%, 41%, 3%, respectively, against medium-high resistance; 2%, 77%, 20%, 1%, respectively, against medium resistance; 27%, 63%, 9%, 1%, respectively, against medium-low resistance; and 42%, 57%, 1%, 0%, respectively, against low resistance (p < 0.01). Although most PIFRs against medium-high (54%), medium (77%), medium-low (63%) and low (57%) resistance were optimal, a substantial proportion of PIFRs against low resistance were excessive (42%, p < 0.01), irrespective of age, body-mass index, dyspnea severity score, and COPD severity. Insufficient PIFRs were infrequent, but suboptimal/insufficient PIFRs were most prevalent in patients older than 75 years than in younger patients (36% vs. 56%, p = 0.036) against medium-high resistance. Regularly monitoring PIFRs against the specific resistance of the DPIs and instructing patients to employ a proper inspiration effort may help to optimize the effects of DPIs.

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Year:  2020        PMID: 32350352      PMCID: PMC7190738          DOI: 10.1038/s41598-020-64235-6

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


Introduction

Dry powder inhalers (DPIs), a breath-actuated inhalation systems, required patients to generate sufficient inspiratory flow and turbulence in the device to disaggregate the powder into fine particles[1,2]. Thus, it is generally advised to inhale with a forced inspiratory maneuver to generate adequate peak inspiratory flow rate (PIFR) to overcome the internal resistance of the devices[1-5]. The PIFR is impacted by several factors, such as sex, age, height, the internal resistance of DPIs, inhalation effort, pulmonary function, and even the period following acute exacerbation due to chronic obstructive pulmonary disease (COPD)[6-8]. It is generally suggested that PIFR less than 30 L/min is insufficient and the suggested optimal PIFR is at least 60 L/min for Turbuhaler, Ellipta and Accuhaler, and 50 L/min for Breezhaler[5,6]. However, compared to optimal PIFR, excessive PIFR also lead to more oropharyngeal deposition and less lung deposition and a PIFR more than 90 L/min was considered excessive[9,10]. Different DPIs have different internal resistances, which can be categorized to medium-high, medium, medium-low and low internal resistances[11]. We aim to investigate the prevalence of improper PIFRs and the influencing factors against different internal resistances of DPIs, among COPD patients with varying disease severity.

Methods

Adult patients with stable COPD, who receiving medical treatment in our outpatient clinics without acute exacerbation during previous 3 months, were recruited from National Taiwan University Hospital from May 2017 to February 2019. The patients were diagnosed according to the GOLD criteria defined by <70% post-bronchodilator forced expiratory volume in one second (FEV1) to forced vital capacity (FVC) ratio (FEV1/FVC ratio). Data on patients’ demographics, results of pulmonary function tests, smoking status, dyspnea severity classified by scores of modified medical research council (mMRC) and COPD assessment test (CAT) were recorded. According to GOLD guideline, we classified COPD patients into GOLD Group ABCD according to frequency of exacerbation and mMRC or CAT scoring system with the greater score. PIFRs were measured against four-degrees of internal resistances (low, medium-low, medium, and medium-high) using the In-Check Dial G16 (Clement-Clarke International Ltd, Harlow, UK), a handheld inspiratory flow device simulates different internal resistances of DPIs[11]. For low resistance devices, measured PIFRs were classified to excessive (≥100 L/min), optimal (50–99 L/min), suboptimal (30–49 L/min), and insufficient (<30 L/min)[12], and for those other than low resistance devices, measured PIFRs were classified into four categories, excessive (≥90 L/min), optimal (60–89 L/min), suboptimal (30–59 L/min), and insufficient (<30 L/min)[5,6,10]. The institution board of National Taiwan University Hospital (201905058RINB) approved this study and written informed consent was waived by the ethics committee due to the retrospective nature of the study. All methods were carried out in accordance with relevant guidelines and regulations.

Statistical analysis

Categorical variables were compared using a chi-square test or Fisher’s exact test, as appropriate. Differences in continuous variables were analyzed using the Mann-Whitney U test or ANOVA. The data are presented as numbers (percentages), median (range), mean ± standard deviation, and p = 0.05 is considered a statistically significant difference. Linear regression analysis was used to investigate the relationship between PIFR and FEV1, FVC, age and body height. The statistical analyses were performed using STATA version 14 software (StataCorp LLC, TX).

Results

A total of 138 patients with stable COPD underwent PIFR measurement during the study. The median age was 72 (37–91) years, and most participants were men (131, 94.9%). The median height was 164 (146–180) cm while the median weight was 63 (40–102) kg. Mean forced expiratory volume in one second (FEV1) was 1.53 ± 0.49 L, and the mean percentage of predicted value was 70.9 ± 21.8%. Table 1 shows the demographic parameters.
Table 1

Characteristics of patients with chronic obstructive pulmonary disease.

VariableAllGOLD Groupp Value
Group A(n = 36)Group B(n = 75)Group C(n = 7)Group D(n = 20)
Age in years72 (37–91)71 (37–87)72 (54–85)79 (65–82)73 (56–87)0.406
Male131 (95)32 (89)73 (97)6 (86)20 (100)0.099
Weight, kg63 (40–102)63.2 (43–87)62.9 (40–102)56 (49–71)66 (52–81)0.319
Height, cm164 (146–180)162 (147–180)162.8 (146–180)165 (158–170)164.5 (158–172)0.567
Body mass index, kg/m223.2 (16–36.1)22.85 (19.4–29.1)23.7 (16–36.1)20.6 (19.1–21.6)24 (19.3–28.6)0.289
FEV1, L1.46 (0.45–3.25)1.79 (0.75–3.25)1.35 (0.45–2.54)1.46 (0.85–2.32)1.36 (0.83–2.44)0.009
FEV1, % predicted71.8 (22.3–131.1)80 (34.5–130.9)69.2 (22.3–131.1)75.7 (54.9–89.8)63.6 (32.3–124.4)0.014
Smoking status0.576
Current smoker28 (20)10 (28)14 (19)1 (14)3 (15)
Former smoker74 (54)18 (50)44 (59)3 (43)9 (45)
Never smoker19 (14)3 (8)10 (13)2 (29)4 (20)
mMRC dyspnea score<0.001
Grade 04 (3)3 (8)1 (1)00
Grade 143 (31)33 (92)3 (4)7 (100)0
Grade 267 (49)056 (75)011 (55)
Grade 324 (17)015 (20)09 (45)
Grade 400000
CAT score<0.001
≤10106 (77)36 (100)51 (68)7 (100)12 (60)
11–2029 (21)023 (31)06 (30)
21–303 (2)01 (1)02 (10)
31–4000000
Comorbidity
Cerebrovascular accident or neuromuscular disease12 (9)1 (3)10 (13)1 (14)00.120
Head and neck tumor5 (4)2 (6)3 (4)000.698
Cardiovascular diseases50 (36)7 (19)31 (41)2 (29)10 (50)0.070
Asthma13 (9)2 (6)7 (9)1 (14)3 (15)0.670
Hypertension65 (47)13 (36)40 (53)012 (60)0.015
Diabetes mellitus36 (26)8 (22)17 (23)04 (20)0.566

Data presented as n (%) or median (range).

CAT, Chronic obstructive pulmonary disease assessment test; FEV1, forced expiratory volume in one second; GOLD: Global Initiative for Chronic Obstructive; mMRC, modified medical research council.

Characteristics of patients with chronic obstructive pulmonary disease. Data presented as n (%) or median (range). CAT, Chronic obstructive pulmonary disease assessment test; FEV1, forced expiratory volume in one second; GOLD: Global Initiative for Chronic Obstructive; mMRC, modified medical research council. The median PIFR was 63 (21–98) L/min against medium-high, 71 (25–103) L/min against medium, 80 (26–116) L/min against medium-low, and 97 (34–150) L/min against low resistances. Measured PIFRs positively correlated with FEV1 and forced vital capacity (FVC) but negatively correlated with age and didn’t correlate with body height (Fig. 1). The percentage of insufficient, suboptimal, optimal and excessive PIFRs against low resistance were 0% (n = 0), 1% (n = 2), 57% (n = 78), 42% (n = 58), respectively, against medium-low resistance were 1% (n = 1), 9% (n = 13), 63% (n = 87), 27% (n = 37), respectively, and against medium resistance were 1% (n = 1), 20% (n = 28), 77% (n = 106), 2% (n = 3), respectively (p < 0.01). Among 127 patients, PIFRs measured against medium-high resistance of DPIs, 4 (3%) were insufficient, 52 (41%) were suboptimal, 69 (54%) were optimal, and 2 (2%) were excessive, respectively (Fig. 2, p < 0.01). Further subgroup analysis in Table 2 and Figs. 3–5 show that regardless of age groups, gender, body mass index (BMI), severity of dyspnea by mMRC score, GOLD stages or GOLD groups, there were more optimal PIFRs as measured against medium internal resistance, while there was a majority of excessive PIFRs as measured against low resistance and more suboptimal PIFRs as measured against medium-high resistance. Figure 3 also shows that patients >75 years have a higher prevalence of suboptimal or insufficient PIFRs than younger patients (36% vs. 56%, p = 0.036) when measured against DPIs with medium-high internal resistance.
Figure 1

Scatter plot and regression line between peak inspiratory flow rate and forced expiratory volume in one second (FEV1, Panel A–D), percent predicted value of forced vital capacity (FVC%, Panel E–H), age (Panel I–L) and body height (Panel M–P) against different simulated internal resistances of dry powder devices.

Figure 2

Prevalence of excessive, optimal, suboptimal, and insufficient peak inspiratory flow rates measured against different resistances (p < 0.01). ** represents p < 0.01 between each resistance.

Table 2

Forced peak inspiratory flow rates against different simulated internal resistances of dry powder inhalers.

VariableInternal resistance
Med-highMediumMed-lowLow
Age, years
<6568 (36–85)75.5 (44–95)84 (47–103)103.5 (62–128)
65–7063.5 (21–95)72 (25–103)80 (26–113)100 (34–150)
70–7564.5 (40–98)74.5 (46–90)86 (53–116)103.5 (66–128)
75–8057 (28–85)70 (38–86)75 (46–98)93 (58–135)
≥8058 (28–82)65.5 (35–83)76.5 (38–95)91.5 (43–115)
p value0.1260.2040.1880.124
Body mass index, kg/m2
<18.570.5 (52–79)76 (56–80)86 (69–95)104 (78–112)
18.5–2459 (21–88)66.5 (25–90)75 (26–101)95 (34–150)
24–2766 (28–95)72 (35–103)82.5 (38–113)102 (43–140)
≥2762 (34–98)74 (42–95)86 (51–116)103 (61–122)
p Value0.2830.0680.0360.300
Sex
Man63 (21–98)71 (25–103)81 (26–116)98 (34–150)
Woman56 (28–74)60 (40–75)73 (46–88)89 (64–110)
p Value0.1710.040.0770.182
mMRC
Grade 046 (28–62)51.5 (40–76)57.5 (46–91)70 (64–113)
Grade 164 (28–98)72 (38–103)84 (40–116)97 (52–140)
Grade 260.5 (21–95)70 (25–95)78 (26–110)97 (34–135)
Grade 363 (34–88)70.5 (38–90)82 (46–103)102.5 (58–150)
p Value0.1380.1400.1570.275
COPD GOLD stage
GOLD 162.5 (28–98)71.5 (38–90)82.5 (40–116)96.5 (52–135)
GOLD 261.5 (21–95)70 (25–103)78 (26–113)97 (34–140)
GOLD 362.5 (34–85)67.5 (38–86)79.5 (46–103)101 (58–122)
GOLD 470 (68–88)86 (74–90)98 (86–101)122 (103–150)
p Value0.3480.1840.3780.083
COPD GOLD group
Group A62.5 (28–98)72 (40–90)85 (46–116)97 (64–135)
Group B61.5 (21–95)70 (25–103)78 (26–113)97 (34–140)
Group C60 (34–84)65 (38–86)70 (46–102)91 (58–122)
Group D63.5 (40–88)71 (44–90)82 (61–103)103 (68–150)
p Value0.7580.7360.6380.400

Data presented as median (range).

GOLD: Global Initiative for Chronic Obstructive; mMRC, modified medical research council.

Figure 3

Percentage of excessive, optimal, suboptimal and insufficient peak inspiratory flow rates measured against different resistances among patients <65 (Panel A, p < 0.01), 65–69 (Panel B, p < 0.01), 70–74 (Panel C, p < 0.01), 75–79 (Panel D, p < 0.01) and ≥80 years of age (Panel E, p < 0.01). * represents p < 0.05, ** represents p < 0.01.

Figure 5

Percentage of excessive, optimal, suboptimal and insufficient peak inspiratory flow rates measured against different resistances among patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) group A (Panel A, p < 0.01), group B (Panel B, p < 0.01), group C (Panel C, p = 0.22), group D (Panel D, p < 0.01) and GOLD stage 1 (Panel E, p < 0.01), stage 2 (Panel F, p < 0.01), stage 3 (Panel G, p < 0.01) and stage 4 (Panel H, p = 0.045). * represents p < 0.05; ** represents p < 0.01.

Scatter plot and regression line between peak inspiratory flow rate and forced expiratory volume in one second (FEV1, Panel A–D), percent predicted value of forced vital capacity (FVC%, Panel E–H), age (Panel I–L) and body height (Panel M–P) against different simulated internal resistances of dry powder devices. Prevalence of excessive, optimal, suboptimal, and insufficient peak inspiratory flow rates measured against different resistances (p < 0.01). ** represents p < 0.01 between each resistance. Forced peak inspiratory flow rates against different simulated internal resistances of dry powder inhalers. Data presented as median (range). GOLD: Global Initiative for Chronic Obstructive; mMRC, modified medical research council. Percentage of excessive, optimal, suboptimal and insufficient peak inspiratory flow rates measured against different resistances among patients <65 (Panel A, p < 0.01), 65–69 (Panel B, p < 0.01), 70–74 (Panel C, p < 0.01), 75–79 (Panel D, p < 0.01) and ≥80 years of age (Panel E, p < 0.01). * represents p < 0.05, ** represents p < 0.01. Percentage of excessive, optimal, suboptimal and insufficient peak inspiratory flow rates measured against different resistances among patients with body mass index <18.5 (Panel A, p < 0.01), 18.5–23.9 (Panel B, p < 0.01), 24–26.9 (Panel C, p < 0.01) and ≥ 27 kg/m2 (Panel D, p < 0.01). * represents p < 0.05; ** represents p < 0.01. Percentage of excessive, optimal, suboptimal and insufficient peak inspiratory flow rates measured against different resistances among patients with Global Initiative for Chronic Obstructive Lung Disease (GOLD) group A (Panel A, p < 0.01), group B (Panel B, p < 0.01), group C (Panel C, p = 0.22), group D (Panel D, p < 0.01) and GOLD stage 1 (Panel E, p < 0.01), stage 2 (Panel F, p < 0.01), stage 3 (Panel G, p < 0.01) and stage 4 (Panel H, p = 0.045). * represents p < 0.05; ** represents p < 0.01.

Discussion

We investigated the PIFRs against different internal resistances of DPIs among stable COPD patients and found correlations between PIFRs and FEV1, FVC, and age. Moreover, among stable COPD patients, we found that more PIFRs measured against medium resistance were optimal, more PIFRs against medium-high resistance were suboptimal, while a majority of PIFRs against low resistance were excessive. Forced inspiration could provide faster acceleration rates, which increases the deaglommeration of particles before the dose leaves the device. Therefore, the guideline of inhalation therapies suggests “instruct the patient to inhale forcefully from the beginning”[1]. This forced inspiration method provides a simple and precise instruction to the patients. This method is easy to remember, readily found in most prescribing information for DPIs and allows patients to perform the inhalation consistently in daily life[5]. More importantly, without the maximum inhalation effort, the relationship between the flow rate and the pressure drop will be inconsistent[4]. A PIFR between 60 and 90 L/min was suggested as optimal by several previous studies[13-15], and 30 L/min is considered the minimum effective PIFR, making the range of 30–60 L/min a debatable area[6,10,11,16]. Thus, in this study, this flow range of 30–60 L/min was classified as suboptimal while those less than 30 L/min as insufficient. Pavkov et al. studied 26 patients using Breezhaler, a low resistance device and found that a consistent fine particle mass can be achieved at rate of 50–100 L/min. In this way, the flow range of 50–100 L/min was classified as optimal while 30–49 L/min as suboptimal for low resistance devices[12]. High prevalence of suboptimal PIFRs were reported in previous studies which accounts for approximately 20–78% of studied population[5,13,17-21]. Similarly, our study found the proportion of suboptimal or insufficient PIFRs range from 3–44% among stable COPD patients with different severity. However, although most studies emphasized on suboptimal PIFRs as a major problem of inappropriate DPI usage, we further found a substantial proportion of PIFRs were excessive when measured against medium-low and low resistance (27% and 42%, respectively). Excessive inspiratory flow rates also have negative impact on drug deposition in respiratory tract[2]. Usmani et al. used inhaled technetium-99m-labeled monodisperse albuterol aerosols and compared the respiratory deposition at slow and fast inspiratory flow rates, and found that faster inspiratory flows yield more oropharyngeal and central lung deposition (regardless of particle size), decreased total lung deposition, and lesser clinical effectiveness[9]. We found that patients tend to have excessive PIFRs as measured against medium-low or low resistance, while suboptimal or insufficient PIFR values resulted when measured against medium-high resistance. This remained true when patients were subdivided by BMI, age, COPD group or COPD stage, emphasizing that the prevalence of excessive or suboptimal peak inspiratory flow rates could be highly correlated with an internal resistance of DPIs per se. Several pulmonary function parameters were also found to have association with PIFRs. Mahler et al. measured PIFR against medium-low resistance in COPD GOLD stage 3 and 4 patients (mean FEV1 of 0.92 ± 0.26 L) and found that PIFRs are associated with FVC and inspiratory capacity[19]. Duates et al. demonstrated a significant correlation between PIFRs and severity of air trapping, represented by the ratio of residual volume over total lung capacity (RV/TLC)[22]. We found values of PIFRs correlated positively with FEV1 and FVC. This finding was different from Janssens et al. where PIFRs were not statistically correlated with FEV1. This possibly is because they measured PIFRs against zero resistance and the smaller study population (26 COPD patients) in their study[13]. Similar to previous studies[13,18-20], we found a negative correlation between age and PIFRs (p < 0.05). Furthermore, as measured against medium-high resistance, patients more than 75 years have a higher prevalence of suboptimal or insufficient PIFR (36% vs. 56%, p = 0.036). In contrast, the prevalence of suboptimal or insufficient PIFRs did not significantly correlate with age among medium, medium-low, and low resistance of DPIs. It was similar to the study conducted by Kawamatawong et al. that older patients had a higher proportion of suboptimal PIFR breathing against Turbuhaler than Accuhaler (19.3% vs 9.3%)[18]. There are some limitations to our study. First, our COPD population is predominantly male, which may not be representative of the spectrum of the COPD population worldwide, although our papulation was similar to a random cross-sectional national survey in Taiwan which showed males accounted for 78.9% of the COPD population[23]. However, this male predominant papulation could lead to female gender and short stature, two important predictors of reduced PIFRs in the previous studies, did not have significant roles in this study[17,19,20,22,24]. Second, as patients may not exert maximal inspiratory effort every time in daily life, there may be a difference between in-office evaluation and daily practice at home. The very small number of participants with BMI < 18.5 (n = 7), GOLD stage 4 (n = 3) and mMRC grade 0 (n = 4) substantially led to great variations and pseudo-higher PIFRs in patients with BMI < 18.5 and GOLD stage 4 and pseudo-lower PIFRs in those with mMRC grade 0 (all the differences were not statistically significant). Therefore, there was great limitation and the interpretation of those findings should be very cautious. Fourth, this is a cross-sectional study and all patients had received effective treatment and pulmonary rehabilitation program without inspiratory muscle training for a period of time. A further prospective study design was needed in the future to address the effects of treatment and pulmonary rehabilitation on the PIFR. Finally, our study population is mainly stable COPD patients without acute exacerbation in previous 3 months. The result cannot be applied to those experiencing acute exacerbation of chronic obstructive disease or who just recover from acute illness. Our study identified that PIFRs are correlated with FEV1, FVC, and age. We also revealed a substantial proportion of improper PIFRs (excessive and suboptimal) as measured against different resistances of DPIs, but insufficient PIFRs were infrequent (<5%). The highest probability of optimal PIFR was measured against medium resistance. The lower the internal resistance, the higher the probability of excessive PIFR was noted, and suboptimal PIFRs were more often noticed when measured against higher internal resistance. Both excessive and suboptimal PIFRs may negatively impact drug deposition, therefore, regularly monitoring PIFR against the resistance of specific DPI and instructing patients to employ a proper inspiration effort may help to optimize the effects of DPIs.
  5 in total

1.  Peak Inspiratory Flow Rate as a Criterion for Dry Powder Inhaler Use in Chronic Obstructive Pulmonary Disease.

Authors:  Donald A Mahler
Journal:  Ann Am Thorac Soc       Date:  2017-07

2.  Influences of gender and anthropometric features on inspiratory inhaler acoustics and peak inspiratory flow rate.

Authors:  Terence E Taylor; Martin S Holmes; Imran Sulaiman; Richard W Costello; Richard B Reilly
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2015

3.  Spirometry Measurement of Peak Inspiratory Flow Identifies Suboptimal Use of Dry Powder Inhalers in Ambulatory Patients with COPD.

Authors:  Alexander G Duarte; Leon Tung; Wei Zhang; En Shuo Hsu; Yong-Fang Kuo; Gulshan Sharma
Journal:  Chronic Obstr Pulm Dis       Date:  2019-07-24

Review 4.  Inhalation drug delivery devices: technology update.

Authors:  Mariam Ibrahim; Rahul Verma; Lucila Garcia-Contreras
Journal:  Med Devices (Auckl)       Date:  2015-02-12

5.  COPD in Taiwan: a National Epidemiology Survey.

Authors:  Shih-Lung Cheng; Ming-Cheng Chan; Chin-Chou Wang; Ching-Hsiung Lin; Hao-Chien Wang; Jeng-Yuan Hsu; Liang-Wen Hang; Chee-Jen Chang; Diahn-Warng Perng; Chong-Jen Yu
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2015-11-11
  5 in total
  10 in total

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Authors:  Ashlee D Brunaugh; Amanda Walz; Zachary Warnken; Camron Pearce; Juan Munoz Gutierrez; John J Koleng; Hugh D C Smyth; Mercedes Gonzalez-Juarrero
Journal:  Antimicrob Agents Chemother       Date:  2022-08-09       Impact factor: 5.938

2.  Inspiratory flow patterns with dry powder inhalers of low and medium flow resistance in patients with pulmonary arterial hypertension.

Authors:  Mariana Faria-Urbina; Keith T Ung; Laurie Lawler; Lawrence S Zisman; Aaron B Waxman
Journal:  Pulm Circ       Date:  2021-05-13       Impact factor: 3.017

3.  Evaluation of Suboptimal Peak Inspiratory Flow in Patients with Stable COPD.

Authors:  Cristina Represas-Represas; Luz Aballe-Santos; Alberto Fernández-García; Ana Priegue-Carrera; José-Luis López-Campos; Almudena González-Montaos; Maribel Botana-Rial; Alberto Fernández-Villar
Journal:  J Clin Med       Date:  2020-12-05       Impact factor: 4.241

4.  Peak Inspiratory Flow Rate in COPD: An Analysis of Clinical Trial and Real-World Data.

Authors:  Martin Anderson; Kathryn Collison; M Bradley Drummond; Melanie Hamilton; Renu Jain; Neil Martin; Richard A Mularski; Mike Thomas; Chang-Qing Zhu; Gary T Ferguson
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2021-04-12

Review 5.  Measuring Peak Inspiratory Flow in Patients with Chronic Obstructive Pulmonary Disease.

Authors:  Jill A Ohar; Gary T Ferguson; Donald A Mahler; M Bradley Drummond; Rajiv Dhand; Roy A Pleasants; Antonio Anzueto; David M G Halpin; David B Price; Gail S Drescher; Haley M Hoy; John Haughney; Michael W Hess; Omar S Usmani
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2022-01-06

Review 6.  Relationship between Peak Inspiratory Flow and Patient and Disease Characteristics in Individuals with COPD-A Systematic Scoping Review.

Authors:  Marika T Leving; Janwillem Kocks; Sinthia Bosnic-Anticevich; Richard Dekhuijzen; Omar S Usmani
Journal:  Biomedicines       Date:  2022-02-16

7.  Shared Decision-Making Facilitates Inhaler Choice in Patients with Newly-Diagnosed Chronic Obstructive Pulmonary Disease: A Multicenter Prospective Study.

Authors:  Ming-Ju Tsai; Yen-Fu Chen; Yi-Han Hsiao; Ching-Min Tseng; Chau-Chyun Sheu; Hsin-Yi Wang; Hsin-Kuo Ko; Kang-Cheng Su; Chi-Wei Tao
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2022-09-02

8.  Peak-Inspiratory-Flow-Rate Guided Inhalation Therapy Reduce Severe Exacerbation of COPD.

Authors:  Shih-Yu Chen; Chun-Kai Huang; Hui-Chuan Peng; Hsing-Chen Tsai; Szu-Ying Huang; Chong-Jen Yu; Jung-Yien Chien
Journal:  Front Pharmacol       Date:  2021-06-29       Impact factor: 5.810

9.  Prevalence and Associated Factors of Suboptimal Daily Peak Inspiratory Flow and Technique Misuse of Dry Powder Inhalers in Outpatients with Stable Chronic Airway Diseases.

Authors:  Nan Ding; Wei Zhang; Zhuo Wang; Chong Bai; Qian He; Yuchao Dong; Xiumin Feng; Jingxi Zhang; Shen Gao
Journal:  Int J Chron Obstruct Pulmon Dis       Date:  2021-06-23

10.  Experimental Evaluation of Dry Powder Inhalers during Inhalation and Exhalation Using a Model of the Human Respiratory System (xPULM™).

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Journal:  Pharmaceutics       Date:  2022-02-24       Impact factor: 6.321

  10 in total

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