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Original Research |

Maximal Inspiratory Pressure: Does the Choice of Reference Values Actually Matter?

Antenor Rodrigues, MSc; Marianne L. Da Silva, MSc; Danilo C. Berton, MD; Gerson Cipriano, Jr., PT; Fabio Pitta, RT; Denis E. O'Donnell, MD; J Alberto Neder, MD
Author and Funding Information

“This paper is dedicated to the memory of Robert Hyatt (1925-2016)”

Antenor Rodrigues had no conflict of interest to declare; Marianne L. Silva had no conflict of interest to declare; Danilo C. Berton had no conflict of interest to declare; Gerson Cipriano Jr had no conflict of interest to declare; Fabio Pitta had no conflict of interest to declare; Denis O'Donnell has received research funding, via Queen’s University, from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline and has served on speakers bureaus, consultation panels and advisory boards for Almirall, AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline, Novartis and Pfizer; J Alberto Neder had no conflict of interest to declare.

1Pulmonary Function Laboratory, Hotel Dieu Hospital, Kingston, ON, Canada

2Division of Respiratory and Critical Care Medicine, Queen’s University, Kingston, ON, Canada

4Division of Respirology, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil

5Department of Physiotherapy, University of Brasilia, Brasilia, DF, Brazil

6Laboratory of Research in Respiratory Physiotherapy (LFIP), Department of Physiotherapy, State University of Londrina, Londrina, PR, Brazil

Correspondence to: J. Alberto Neder, MD, PhD, DSc. Laboratory of Clinical Exercise Physiology (LACEP), Kingston General Hospital, Connell 2-200. 76 Stuart St., K7L 2V7. Kingston, ON – Canada.


Copyright 2016, . All Rights Reserved.


Chest. 2016. doi:10.1016/j.chest.2016.11.045
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Abstract

Background  Single-point measurements of maximal inspiratory pressure (MIP) are frequently used to suggest muscle weakness in clinical practice. Although there is a large variability in “mean” predicted MIP depending on the chosen reference values, it remains unclear whether those discrepancies actually impact on the prevalence of weakness, i.e., MIP below the lower limit of normal.

Methods  1729 subjects (50.1% males, aged 20 to 94) who underwent MIP measurements in a clinical laboratory comprised the study group. MIP was predicted according to the most cited regression equations as of August 2015. Pre-test probability of weakness was defined by a cluster of clinical and physiological variables.

Results  Prevalence of weakness ranged from 33.4 % (Enright et al.) to 66.9 % (Neder et al.). Black and Hyatt, Bruschi et al. and Neder et al. (set 2 equations) agreed well in indicating weakness (kappa (95% CI) ranging from 0.81 (0.79-0.83) to 0.83 (0.81-0.85); p<0.01) There was a closer agreement between higher pre-test probability of weakness and low MIP according to set 2 compared to Wilson et al., Enright et al. and Harik-Khan et al. (set 1 equations). Thus, a significant fraction of subjects with abnormal MIP according to set 1 but preserved MIP according to set 2 had higher pre-test probability of weakness (p<0.05).

Conclusion  The choice of MIP reference values strongly impacts on the prevalence of weakness. Some specific equations relate better to clinical and physiological indicators of weakness suggesting that they might be particularly useful to screen subjects for advanced respiratory neuromuscular assessment.


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