Prevalence and prognosis of respiratory muscle weakness in heart failure patients with preserved ejection fraction

Journal Pre-proof Prevalence and prognosis of respiratory muscle weakness in heart failure patients with preserved ejection fraction Nobuaki Hamazaki, Kentaro Kamiya, Ryota Matsuzawa, Kohei Nozaki, Takafumi Ichikawa, Shinya Tanaka, Takeshi Nakamura, Masashi Yamashita, Emi Maekawa, Chiharu Noda, Minako Yamaoka-Tojo, Atsuhiko Matsunaga, Takashi Masuda, Junya Ako PII:

S0954-6111(19)30348-8

DOI:

https://doi.org/10.1016/j.rmed.2019.105834

Reference:

YRMED 105834

To appear in:

Respiratory Medicine

Received Date: 23 September 2019 Revised Date:

16 November 2019

Accepted Date: 18 November 2019

Please cite this article as: Hamazaki N, Kamiya K, Matsuzawa R, Nozaki K, Ichikawa T, Tanaka S, Nakamura T, Yamashita M, Maekawa E, Noda C, Yamaoka-Tojo M, Matsunaga A, Masuda T, Ako J, Prevalence and prognosis of respiratory muscle weakness in heart failure patients with preserved ejection fraction, Respiratory Medicine (2019), doi: https://doi.org/10.1016/j.rmed.2019.105834. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Elsevier Ltd. All rights reserved.

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Title page

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Title:

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Prevalence and prognosis of respiratory muscle weakness in heart failure patients with

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preserved ejection fraction

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Nobuaki Hamazaki, PT, PhD*1, Kentaro Kamiya, PT, PhD2, Ryota Matsuzawa, PT, PhD3, Kohei

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Nozaki, PT, MSc1, Takafumi Ichikawa, PT1, Shinya Tanaka, PT, PhD4, Takeshi Nakamura, PT, MSc5,

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Masashi Yamashita, PT, MSc5, Emi Maekawa, MD, PhD6, Chiharu Noda, MD, PhD6, Minako

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Yamaoka-Tojo, MD, PhD2, Atsuhiko Matsunaga, PT, PhD2, Takashi Masuda, MD, PhD2, Junya Ako,

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MD, PhD6

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Rehabilitation, Kitasato University School of Allied Health Sciences, Sagamihara, Japan;

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Department of Physiotherapy, School of Rehabilitation, Hyogo University of Health Sciences, Kobe,

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Japan;

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Sciences, Kitasato University Graduate School of Medical Sciences, Sagamihara, Japan;

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Department of Cardiovascular Medicine, Kitasato University School of Medicine, Sagamihara, Japan

Department of Rehabilitation, Kitasato University Hospital, Sagamihara, Japan;

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Department of Rehabilitation, Nagoya University Hospital;

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2

Department of 3

Department of Rehabilitation 6

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* Correspondence: Nobuaki Hamazaki, PhD, Department of Rehabilitation, Kitasato University Hospital,

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1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa 252-0375, Japan

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E-mail: [email protected]

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Word count for text: 2,454 words

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ABSTRACT

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Background: Although respiratory muscle weakness (RMW) is known to predict prognosis in patients with

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heart failure with reduced ejection fraction (HFrEF), RMW prevalence and its prognosis in those with

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preserved ejection fraction (HFpEF) remain unknown. We aimed to investigate whether the RMW predicted

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mortality in HFpEF patients.

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Methods: We conducted a single-centre observational study with consecutive 1023 heart failure patients (445

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in HFrEF and 578 in HFpEF). Maximal inspiratory pressure (PImax) was measured to assess respiratory

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muscle strength at hospital discharge, and RMW was defined as PImax <70% of predicted value. Endpoint

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was all-cause mortality after hospital discharge, and we examined the influence of RMW on the endpoint.

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Results: Over a median follow-up of 1.8 years, 134 patients (13.1%) died; of these 53 (11.9%) were in HFrEF

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and 81 (14.0%) in HFpEF. RMW was evident in 190 (42.7%) HFrEF and 226 (39.1%) HFpEF patients and

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was independently associated with all-cause mortality in both HFrEF (adjusted hazard ratio [HR]: 2.13, 95%

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confidence interval [CI]: 1.17–3.88) and HFpEF (adjusted HR: 2.85, 95% CI: 1.74–4.67) patients. Adding

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RMW to the multivariate logistic regression model significantly increased area under the receiver-operating

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characteristic curve (AUC) for all-cause mortality in HFpEF (AUC including RMW: 0.78, not including

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RMW: 0.74, P = 0.026) but not in HFrEF (AUC including RMW: 0.84, not including RMW: 0.82, P = 0.132).

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Conclusions: RMW was observed in 39% of HFpEF patients, which was independently associated with poor

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prognosis. The additive effect of RWM on prognosis was detected only in HFpEF but not in HFrEF.

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Key words: heart failure; preserved ejection fraction; respiratory muscle; prognosis 2

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Abbreviations

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BMI = body mass index

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BNP = brain natriuretic peptide

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eGFR = estimated glomerular filtration rate

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HFpEF = heart failure with preserved ejection fraction

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HFrEF = heart failure with reduced ejection fraction

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LVEF = left ventricular ejection fraction

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NYHA = New York Heart Association

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PImax = maximal inspiratory pressure

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RMW = respiratory muscle weakness

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Introduction

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Heart failure with preserved left ventricular ejection fraction (HFpEF), which is highly observed

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in elderly patients, comprises approximately 50% of the overall heart failure patients [1, 2]. Patients

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with HFpEF are known to have exercise intolerance and poor prognosis, similar to those with

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reduced ejection fraction (HFrEF) [3, 4]. Conversely, the clinical characteristics and causes of death

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differ between patients with HFpEF and HFrEF[5, 6]. Additionally, strategies that can improve

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prognosis in HFpEF patients remain unclear, although some pharmacological or nonpharmacological

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therapies are recognised to improve prognosis in HFrEF patients [7, 8]. Therefore, to establish the

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proper treatment strategy that can improve prognosis in HFpEF patients, it is crucial to identify

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clinically meaningful predictors.

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Respiratory muscle weakness (RMW) is frequently observed in patients with chronic heart

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failure [9, 10], and several studies have reported that reduced respiratory muscle strength is caused

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by the atrophy of these muscles and/or decreased actin-myosin cross-bridges, resulting from the

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activation of neurohumoral factors due to heart failure [11-13]. Importantly, RMW, estimated using

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maximal inspiratory pressure (PImax), is a known predictor of exercise intolerance and ventilatory

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inefficiency, leading to decreased quality of life and lower survival in HFrEF patients [9, 10, 14, 15].

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Conversely, a previous study by Habedank and colleagues has shown that PImax was not a significant

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predictor of mortality as it varied according to gender, body mass index, and cachexia in severe

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HFrEF patients [16]. Several statements have recommended the use of PImax, relative to a reference 4

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value (%PImax), for assessing weakness and dysfunction of respiratory muscles [11, 17]. Furthermore,

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although RMW in HFpEF patients has been reported to decrease exercise tolerance [18], its

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prevalence and prognostic potential in these patients remains unclear. Therefore, we conducted an

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observational study to clarify the relationships of RMW assessed by %PImax with mortality in heart

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failure patients.

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This study aimed to investigate whether RMW predicted mortality in patients with HFrEF or HFpEF.

81 82

Methods

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The study protocol was approved by the Kitasato Institute Clinical Research Review Board (KMEO

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B18-075) and was performed according to the ethical guidelines of the Declaration of Helsinki.

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Study population

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This study had a retrospective longitudinal observational design. We included consecutive

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patients with HFrEF or HFpEF who were admitted to the Kitasato University Hospital for heart

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failure treatment between May 2009 and December 2017. HFrEF was defined as a left ventricular

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ejection fraction (LVEF) < 40% on an echocardiogram, and HFpEF was diagnosed based on clinical

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guidelines and LVEF ≥ 50% [7, 19]. Patients who had undergone thoracic surgery within the last

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three months or had chronic respiratory diseases were excluded from the study.

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Study protocol

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Patients underwent haematological analysis, echocardiograms, and assessment of pulmonary

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function and respiratory muscle function at hospital discharge. The primary endpoint of this study

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was defined as all-cause mortality after hospital discharge. We collected the data on all variables

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from electronic database.

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Patient characteristics

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Information on age, gender, body mass index (BMI), smoking history, aetiology of heart

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failure, severity of heart failure based on the New York Heart Association functional classification

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(NYHA class), medications, and comorbidities such as hypertension, diabetes mellitus,

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dyslipidaemia, chronic kidney disease or atrial fibrillation, was obtained from medical records at

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study entry. Routine laboratory analysis included haemoglobin, serum albumin and C-reactive

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protein, and plasma brain natriuretic peptide (BNP). The estimated glomerular filtration rate (eGFR)

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was determined based on serum creatinine levels. Additionally, echocardiographic variables

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including LVEF, left atrial diameter (LAD), mitral early diastolic inflow velocity (E), mitral late

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diastolic inflow velocity (A), mitral annular early diastolic velocity (e′) and deceleration time of

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mitral early diastolic inflow (DCT) were measured. The AHEAD score was used for risk assessment

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and was calculated by assigning one point to each of the following factors: A: atrial fibrillation, H:

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haemoglobin < 13 g/dL for men and 12 g/dL for women, A: abnormal renal parameters (creatinine >

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130 µmol/dL) and D: diabetes mellitus[20].

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Pulmonary function and respiratory muscle function

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Pulmonary function was assessed by measuring forced vital capacity (FVC) and forced

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expiratory volume in 1 second (FEV1) using a spirometer (Autospiro AS-507, Minato Medical

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Science, Osaka, Japan) and calculated their percentage based on predictive values issued by the

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Japanese Respiratory Society [21]. To assess respiratory muscle function, maximal inspiratory

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pressure (PImax) was measured using a pressure transducer (Autospiro AAM-377, Minato Medical

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Science, Osaka, Japan) according to the joint statement of the American Thoracic Society and

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European Respiratory Society [17]. To measure PImax, patients in a sitting position were asked to

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hold a 25–mm diameter mouthpiece in their mouth and perform a three-second forced inspiration

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from the maximal expiratory level. PImax was determined based on the average value of the

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maximum inspiratory pressure over a one-second period during the three-second forced inspiration.

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PImax was expressed as its absolute value in the present study, although it has a negative value

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compared to atmospheric pressure. Respiratory pressure measurement was performed three times,

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and the maximum value in PImax was used for analysis. Subsequently, we calculated percentage PImax

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(%PImax) based on predictive values that were estimated using age, gender, height, and body weight

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[22]. Respiratory muscle weakness (RMW) was defined as %PImax < 70% [23, 24]. 7

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Endpoint

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The primary endpoint of this study was all-cause death identified through medical chart

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review. The time period for this event was calculated as the number of days from the date of the

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respiratory muscle strength measurement to event date. We also investigated whether the cause of

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death was cardiovascular (CV) death or non-CV death, including respiratory diseases.

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Statistical analyses

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Differences in clinical parameters between patients with and without RMW were compared

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using the unpaired Student’s t test or the Mann-Whitney U test for continuous variables and by the

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Chi-square test or Fisher’s exact test for categorical variables, as appropriate. We examined the

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influence of respiratory muscle weakness on survival using the Kaplan-Meier method with the

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log-rank test. To identify predictors of all-cause mortality, we used a multivariate Cox proportional

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hazard model that incorporated clinical characteristics and RMW as covariates. The subgroup

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analysis of RMW in various subgroups relevant to the heart failure prognosis was analysed to assess

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any potential effect modification of the association between RMW and all-cause mortality. To assess

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the additive effect of RMW on the predictive capability of all-cause death, the area under the

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receiver-operating characteristic curves (AUC) of multivariate logistic regression models for

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all-cause death were compared between models with and without RMW. The predictive accuracy and 8

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model fit of the logistic regression analyses were examined using Hosmer-Lemeshow statistics. To

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confirm whether the sample size was adequate, we calculated the sample power with an alpha value

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of 0.05, using mortality and RMW rates, hazard ratio, accrual time during which patients were

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recruited, and follow-up time. Continuous variables are reported as mean ± standard deviation or

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median with interquartile range and categorical variables are expressed as patient numbers and their

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percentages. A two-tailed P value of <0.05 was considered statistically significant. All statistical

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analyses were performed using SPSS, ver. 25.0 (IBM, Armonk, NY), JMP, ver. 14.1.0 (SAS Institute,

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Cary, NC), and R, ver. 3.1.2 (R Foundation for Statistical Computing, Vienna, Austria).

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Results

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Patient characteristics

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The potential study population consisted of 2,335 consecutive patients with HFrEF or

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HFpEF. Patients who had undergone thoracic surgery within the last three months (n = 527) or had

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chronic respiratory diseases (n = 175) were excluded, along with those who could not perform a

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respiratory muscle function test at hospital discharge (n = 610). Consequently, 1,023 heart failure

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patients were included for analysis; of these 445 had HFrEF and 578 had HFpEF.

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Table 1 shows demographic and clinical characteristics of both HFrEF and HFpEF patients.

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RMW was observed in 190 (42.7%) HFrEF patients and 226 (39.1%) HFpEF patients. Among

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HFrEF patients, compared to those without RMW, those with RMW were significantly older, and 9

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had higher values for AHEAD score, pack-years, and BNP levels. HFpEF patients with RMW

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showed significantly lower BMI values compared to those without RMW. Both HFrEF and HFpEF

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patients with RMW showed significantly lower albumin levels. Moreover, a higher percentage of

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patients with RMW were NYHA class III at hospital discharge, and patients with RMW also showed

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significantly lower FVC, %FVC, FEV1, and %FEV1 values than those without RMW.

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Association between RMW and all-cause mortality

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During the median follow-up period of 1.8 years, 134 patients died; of these, 53 had HFrEF

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and 81 had HFpEF, and the mortality rate was 72.8/1000 person-years. The cumulative all-cause

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mortality rate was 6.7% and 18.9% in HFrEF patients without and with RMW, respectively, and

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7.4% and 24.3% in HFpEF patients without and with RMW, respectively. The Kaplan-Meier survival

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curves for the two groups are shown in Figure 1. Patients with RMW had a significantly lower

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survival rate than those without RMW in both HFrEF (log-rank: 16.429, P < 0.001) and HFpEF

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(log-rank: 38.295, P < 0.001) groups.

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Cause of death

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The CV deaths occurred in 93 patients (40 in HFrEF and 53 in HFpEF) and non-CV deaths

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occurred in 41 patients (13 in HFrEF and 28 in HFpEF). There were no statistical differences in rates

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of CV and non-CV death between HFrEF and HFpEF (Supplementary file). Patients with RMW 10

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showed significantly higher rates of CV death (P = 0.026 for HFrEF and P = 0.027 for HFpEF) and

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non-CV death (P = 0.012 for HFrEF and P = 0.005 for HFpEF) compared to those without RMW,

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both in HFrEF and HFpEF (Figure 2).

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Cox proportional hazard models for RMW and all-cause death

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Table 2 shows the results of the Cox proportional hazard models for RMW and all-cause

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mortality. In the univariate Cox proportional hazard model, RMW, defined as %PImax < 70%, was a

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significant predictor of all-cause mortality in HFrEF and HFpEF patients. The multivariate model

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identified RMW as a significant independent predictor for all-cause mortality even after adjustment

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for clinical confounding factors, both in HFrEF and in HFpEF patients. No significant interactions

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were observed in the association between RMW and poor prognosis across the various subgroups in

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both HFrEF and HFpEF patients, even after adjustment for confounding factors used in the

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multivariate Cox proportional hazard model (Figure 3). The sample size in this study was sufficient,

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as reflected by a sample power of HFrEF and HFpEF of 0.995 and 0.998, respectively.

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Additive effect of RMW on predictive capability for all-cause death

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The AUCs of the multivariate logistic regression models for all-cause mortality are shown in Figure

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4. The AUC of a model that used clinical characteristics as covariates in HFrEF patients was 0.82

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(95% CI: 0.75–0.87), and the addition of RMW to the model did not increase the AUC (AUC: 0.84, 11

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95% CI: 0.78–0.88, P = 0.132). In HFpEF patients, the AUC of the model without RMW was 0.74

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(95% CI: 0.68–0.80), which significantly increased to 0.78 (95% CI: 0.72–0.83, P = 0.026) when

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RMW was included in the model. In the Hosmer-Lemeshow statistics of logistic regression models,

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both the HFrEF and HFpEF models reached statistical significance for predicting all-cause mortality

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(HFrEF: chi-squared = 7.47, predictive value = 88%, P = 0.487; HFpEF: chi-squared = 11.19,

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predictive value = 86%, P = 0.191).

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Discussion

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The novel findings of this study are as follows. First, RMW was observed in 39% of the patients

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with HFpEF. Second, both HFrEF and HFpEF patients with RMW had a significantly higher

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mortality rate compared to those without RMW, and RMW increased the risk of all-cause mortality

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in HFrEF and HFpEF patients by two- and three-fold, respectively. However, the additive effect of

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RMW on predictive capability for poor prognosis was observed only in patients with HFpEF but not

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in those with HFrEF.

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Previous studies

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To the best of our knowledge, this is the first study to demonstrate that 39% of HFpEF patients

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have RMW and that it is a significant indicator of poor prognosis in these patients. Previous studies

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have reported RMW in 30%–50% of HFrEF patients [11], which is similar to that seen in the present

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study. Thus, we show that the prevalence of RMW is comparable among HFpEF and HFrEF patients.

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Conversely, mean absolute value of PImax was significantly lower in HFpEF patients (50.1 cmH2O) 12

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than in HFrEF patients (56.8 cmH2O), suggesting that the value of PImax as a respiratory muscle

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strength in heart failure differs between HFpEF and HFrEF patients (Supplementary file). Generally,

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respiratory muscle strength is lower in older patients, females, and in patients with severe heart

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failure [16]. Further, our study population tended to include older patients and a higher proportion of

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females in the HFpEF group compared to the HFrEF group, which is consistent with the reported

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higher prevalence of HFpEF in the elderly and in females [2]. Additionally, it is notable that %PImax

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levels were comparable between HFrEF and HFpEF patients in the present study. Thus, we believe

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that the use of %PImax values would be both useful and important in assessing RMW for heart failure

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patients.

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Interpretations of findings

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Although there were no differences in age, gender, smoking habits, comorbidities, or

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medications between HFpEF patients with and without RMW, patients with RMW showed

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significantly lower pulmonary function, as evidenced by the lower FVC and FEV1 values, and a

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higher mortality rate compared to those without RMW. This observation is partially different from

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that seen in HFrEF patients, i.e., RMW in HFrEF was associated with older age, presence of

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comorbid conditions, smoking habits, and higher BNP. Bowen et al. have demonstrated that activated

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levels of ROS and the ubiquitin proteasome system in respiratory muscles, which are known to cause

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muscle atrophy in HFrEF [25], were not elevated in rats with HFpEF even though these animals also

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had significant diaphragm muscle atrophy that resulted in RMW [26]. These molecular and 13

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histological alterations could have contributed to the observed differences between HFrEF and

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HFpEF patients with or without RMW. Furthermore, although RMW was identified as an

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independent predictor of all-cause mortality in both HFrEF and HFpEF in this study, additional effect

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of RMW to traditional prediction model of heart failure that included NYHA and comorbid

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conditions was observed only in HFpEF patients but not in HFrEF patients. Recent studies on the

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cause of death in heart failure patients have reported that while the main causes of death in HFrEF

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patients were heart failure exacerbation and sudden death, non-cardiovascular death, including due to

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respiratory failure or infections of the respiratory system, were the main causes of death in HFpEF

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patients, apart from cardiovascular causes of death [5, 6]. In general, the decline in respiratory

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muscle strength is associated with inefficient ventilation as a cause of dyspnoea [27], and with

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reduced pulmonary function[9, 15], which is a known risk factor for heart failure and/or respiratory

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infection [28-30]. Therefore, in the present study, RMW worsened HFpEF patient prognosis because

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it can decrease pulmonary function that leads to respiratory complications and the incidence of

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cardiovascular events, even in the subgroup analysis stratified into the previously reported indicator

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of HFpEF.

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Clinical implications

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The results presented here have clinical implications that RMW has been identified as a new

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predictor of prognosis in HFpEF patients. As respiratory muscle strength is easily measured in

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clinical practice, RMW might be a useful marker for risk classification not only in HFrEF but also in 14

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HFpEF patients. Furthermore, an increase in respiratory muscle strength due to inspiratory muscle

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training has been reported to improve exercise tolerance and quality of life in HFrEF patients[23, 31],

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and our results imply similar potential benefits due to greater respiratory muscle strength in HFpEF

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patients as well.

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Potential limitations

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There are some limitations in the present study. As this was a single-centre study that only

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included Japanese patients, it is unclear whether these results can apply to patients in other hospitals

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or in other populations. Nevertheless, the sample size used here is larger than that of previous studies

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on respiratory muscle strength in HFpEF patients [18, 24], which statistically satisfied the power

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analysis for estimating sample size. However, given half of potential study population was excluded

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from the analysis, external validity could have been reduced. We also performed the multivariate

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analyses using multiple confounders. Such multiple test might increase the rate of false positives

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(type I error). Therefore, future multi-centre prospective studies are required to investigate the

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validity and reliability of RMW, assessed by %PImax, as a predictor of prognosis in these patients.

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Conclusions

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RMW, defined as %PImax < 70%, was independently associated with poor prognosis in both

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HFrEF and HFpEF patients. However, the additive effect of RMW on risk prediction was observed

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only in HFpEF and not in HFrEF patients.

281 15

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Funding: This work was supported by Japan Society for the Promotion of Science Grant-in-Aid

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[JSPS KAKENHI Grant Number JP16K16442].

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Declaration of conflicting interests: None

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Author Contributions: NH, KK, and TM contributed to the conception and design of the study. NH

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and TM wrote the manuscript. NH, KK, RM, KN, TI, ST, TN, and MY contributed to data collection.

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NH, TM, KK, RM, KN, ST, EM, CN, MT, AM, and JA contributed to interpretation. NH and KK

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contributed to the statistical analysis. JA contributed to supervision and mentorship. All authors have

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critically revised and assisted in the preparation of the manuscript. All gave final approval and agree

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to be accountable for all aspects of work ensuring integrity and accuracy.

291 292

Research ethics and patient consent: Ethical approval for the study was given by Kitasato Institute

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Clinical Research Review Board (KMEO B18-075).

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Figure legends

388

Figure 1 Kaplan-Meier survival curves for the association between respiratory muscle

389

weakness and all-cause death in HFrEF and HFpEF

390

(A), patients with HFrEF and (B), patients with HFpEF

391

Solid line, patients without RMW; dotted line, patients with RMW.

392

HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with reduced ejection

393

fraction; PImax, maximal inspiratory pressure; RMW, respiratory muscle weakness.

394 395

Figure 2 Rates of cardiovascular death and non-cardiovascular death between presence or

396

absence of RMW in HFrEF and HFpEF

397

White bar, patients without RMW; black bar, patients with RMW.

398

CV, cardiovascular; HFpEF, heart failure with preserved ejection fraction; HFrEF, heart failure with

399

reduced ejection fraction; RMW, respiratory muscle weakness.

400 401

Figure 3 Forest plots of hazard ratios for the association between respiratory muscle weakness

402

and all-cause mortality according to major subgroups

403

Hazard ratios were adjusted for age, gender, BMI, AHEAD score, NYHA class at hospital discharge,

404

ischemic heart disease, LVEF, and log BNP.

405

ACE-I, angiotensin convertor enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body 20

406

mass index; BNP, brain natriuretic peptide; HFpEF, heart failure with preserved ejection fraction;

407

HFrEF, heart failure with reduced ejection fraction; NYHA, LVEF, left ventricular ejection fraction;

408

New York Heart Association functional classification.

409 410

Figure 4 Receiver-operating characteristic curves of logistic regression models to predict

411

all-cause mortality in HFrEF and HFpEF

412

(A), patients with HFrEF and (B), patients with HFpEF

413

Independent variables of the logistic regression model (model 1) were age, gender, BMI, AHEAD

414

score, NYHA class at hospital discharge, ischemic heart disease, LVEF, and log BNP.

415

Solid line, model 1 with RMW; Dotted line, model 1 without RMW.

416

AUC, area under the receiver-operating characteristic curve; BMI, body mass index; BNP, brain

417

natriuretic peptide; CI: confidence interval; HFpEF, heart failure with preserved ejection fraction;

418

HFrEF, heart failure with reduced ejection fraction; LVEF, left ventricular ejection fraction; NYHA,

419

New York Heart Association functional classification; RMW, respiratory muscle weakness.

21

Table 1 Demographic and clinical characteristics in HFrEF and HFpEF patients with (%PImax < 70%) and without (%PImax ≥ 70%) RMW HFrEF Variable

HFpEF

Overall

%PImax ≥ 70%

%PImax < 70%

Overall

%PImax ≥ 70%

%PImax < 70%

n (%)

445

255 (57.3)

190 (42.7)

P value

578

352 (60.9)

226 (39.1)

P value

Age, yrs

63.4 ± 15.2

61.5 ± 14.8

65.9 ± 15.5

0.002

71.4 ± 10.8

70.9 ± 10.6

72.2 ± 11.1

0.154

123 (27.6)

72 (28.2)

51 (26.8)

0.830

244 (42.2)

155 (44.0)

89 (39.4)

0.301

22.4 ± 4.4

22.5 ± 4.4

22.2 ± 4.4

0.582

22.5 ± 3.7

22.7 ± 3.7

22.0 ± 3.6

0.029

SBP, mm Hg

116 ± 30

116 ± 30

116 ± 30

0.829

124 ± 29

124 ± 28

125 ± 29

0.581

DBP, mm Hg

70 ± 20

70 ± 20

69 ± 20

0.422

69 ± 17

69 ± 16

68 ± 18

0.745

HR, beats/min

84 ± 21

85 ± 22

83 ± 20

0.464

79 ± 20

80 ± 20

77 ± 19

0.064

II

342 (72.9)

216 (84.7)

126 (66.3)

<0.001

337 (58.3)

223 (63.4)

114 (50.4)

0.003

III

103 (23.1)

39 (15.3)

64 (33.7)

241 (41.7)

129 (36.6)

112 (49.6)

AHEAD score

1.63 ± 1.23

1.47 ± 1.16

1.84 ± 1.30

0.002

2.09 ± 1.15

2.02 ± 1.14

2.20 ± 1.17

0.064

Prior history of HF, n (%)

157 (35.3)

83 (32.5)

74 (38.9)

0.192

157 (27.2)

92 (26.1)

65 (28.8)

0.503

Smoking history, n (%)

282 (65.3)

161 (65.2)

121 (65.4)

1.000

305 (53.8)

186 (54.1)

119 (53.4)

0.931

Pack-years

37.8 ± 32.9

34.3 ± 29.1

42.2 ± 36.7

0.047

37.3 ± 31.0

36.4 ± 28.4

38.7 ± 34.7

0.535

IHD, n (%)

191 (42.9)

109 (42.7)

82 (43.2)

1.000

257 (44.5)

156 (44.3)

101 (44.7)

0.932

Hypertension, n (%)

261 (58.7)

146 (57.3)

115 (60.5)

0.497

397 (68.7)

249 (70.7)

148 (65.5)

0.199

Diabetes mellitus, n (%)

179 (40.2)

101 (39.6)

78 (41.1)

0.770

235 (40.7)

148 (42.0)

87 (38.5)

0.435

Dyslipidaemia, n (%)

212 (47.6)

125 (49.0)

87 (45.8)

0.504

257 (44.5)

162 (46.0)

95 (42.0)

0.391

CKD, n (%)

273 (61.3)

153 (60.0)

120 (63.2)

0.555

404 (70.0)

243 (69.2)

161 (71.2)

0.642

98 (22.0)

49 (19.2)

49 (25.8)

0.106

151 (26.1)

88 (25.0)

63 (27.9)

0.440

ACE-I, n (%)

261 (58.7)

152 (59.6)

109 (57.4)

0.697

191 (33.0)

118 (33.5)

73 (32.3)

0.786

ARB, n (%)

157 (35.3)

89 (34.9)

68 (35.8)

0.920

260 (45.0)

158 (44.9)

102 (45.1)

1.000

Beta-blockers, n (%)

410 (92.1)

233 (91.4)

177 (93.2)

0.594

388 (67.1)

238 (67.6)

150 (66.4)

0.786

Diuretics, n (%)

401 (90.1)

227 (89.0)

174 (91.6)

0.424

364 (63.0)

214 (60.8)

150 (66.4)

0.186

Haemoglobin, g/dL

13.2 ± 2.4

13.4 ± 2.5

13.0 ± 2.3

0.060

11.9 ± 2.1

11.9 ± 2.0

11.8 ± 2.2

0.635

Albumin, g/dL

3.66 ± 0.51

3.71 ± 0.51

3.59 ± 0.49

0.009

3.53 ± 0.53

3.57 ± 0.49

3.46 ± 0.58

0.009

0.65 ± 1.16

0.69 ± 1.32

0.61 ± 0.90

0.472

0.92 ± 1.43

0.97 ± 1.49

0.84 ± 1.32

0.276

52.9 ± 23.1

53.9 ± 20.9

51.6 ± 25.8

0.295

49.3 ± 22.9

49.5 ± 20.1

49.0 ± 26.8

0.807

390.2 [196.7 - 789.5]

348.4 [181.9 - 720.0]

478.5 [215.3 - 898.4]

0.014

254.8 [115.6 - 509.6]

0.090

28.7 ± 6.9

28.4 ± 7.2

0.652

62.2 ± 8.8

0.103

Gender female, n (%) BMI, kg/cm

2

NYHA at hospital discharge, n (%)

Medical history

Atrial fibrillation, n (%) Medications

Blood examination

CRP, mg/dL eGFR, mL/min/1.73m BNP, pg/mL

2

236.5 [114.6 226.2 [115.0 - 443.6] - 384.1]

Echocardiographic measurements LVEF, %

28.6 ± 7.0

22

61.5 ± 8.1

61.1 ± 7.7

LAD, mm

44.4 ± 8.6

43.9 ± 8.4

45.1 ± 8.9

0.154

43.3 ± 10.4

42.9 ± 9.5

43.9 ± 11.6

0.267

E/A

1.6 ± 1.1

1.6 ± 1.1

1.7 ± 1.1

0.566

1.2 ± 1.0

1.2 ± 1.1

1.3 ± 0.9

0.383

E', cm/s

5.8 ± 2.7

5.8 ± 2.7

5.7 ± 2.7

0.754

6.8 ± 3.2

6.7 ± 3.2

6.8 ± 3.2

0.858

16.3 ± 7.9

15.9 ± 7.8

16.9 ± 8.0

0.280

14.8 ± 7.5

14.7 ± 7.9

14.8 ± 6.9

0.873

176.3 ± 67.0

179.4 ± 69.5

172.2 ± 63.4

0.317

207.2 ± 76.6

0.113

FVC, L

2.58 ± 0.87

2.79 ± 0.84

2.28 ± 0.83

<0.001

2.18 ± 0.81

2.28 ± 0.78

2.02 ± 0.83

<0.001

FEV1, L

2.02 ± 0.77

2.2 ± 0.73

1.77 ± 0.75

<0.001

1.67 ± 0.67

1.77 ± 0.64

1.51 ± 0.69

<0.001

FEV1/FVC, %

78.0 ± 10.1

78.8 ± 8.8

76.9 ± 11.5

0.052

76.1 ± 9.9

77.6 ± 8.2

73.9 ± 11.7

<0.001

%FVC, %

76.3 ± 17.0

81.4 ± 15.1

69.4 ± 17.2

<0.001

74.4 ± 19.0

78.4 ± 17.5

68.0 ± 19.6

<0.001

%FEV１, %

73.3 ± 18.6

78.5 ± 15.8

66.4 ± 19.7

<0.001

71.6 ± 20.6

76.4 ± 18.7

63.9 ± 21.1

<0.001

PImax, cmH2O

56.8 ± 28.6

73.2 ± 25.9

34.8 ± 15.7

<0.001

50.1 ± 25.9

63.4 ± 22.9

29.3 ± 14.0

<0.001

%PImax, %

76.2 ± 31.6

97.5 ± 23.0

47.8 ± 14.7

<0.001

79.3 ± 35.4 101.1 ± 25.7

45.3 ± 16.5

<0.001

53 (11.9)

17 (6.7)

36 (18.9)

<0.001

55 (24.3)

<0.001

E/E' DCT, ms

214.6 ± 78.4 219.4 ± 79.3

Respiratory function

All-cause mortality, n (%)

81 (14.0)

26 (7.4)

Values are mean ± SD or median [interquartile range]. A, mitral late diastolic inflow velocity; ACE-I, angiotensin convertor enzyme inhibitor; ARB, angiotensin II receptor blocker; BMI, body mass index; BNP, brain natriuretic peptide; CKD, chronic kidney disease; CRP, C-reactive protein; DBP, diastolic blood pressure; DCT, deceleration time of mitral early diastolic inflow; E, mitral early diastolic inflow velocity; E’, mitral annular early diastolic velocity; eGFR, estimated glomerular filtration rate; FEV1, forced expiratory volume in 1-second; FVC, forced vital capacity; HFpEF, heart failure preserved ejection fraction; HFrEF, heart failure with reduced ejection fraction; HR, heart rate; IHD, ischemic heart disease; LAD, left atrial diameter; LVEF, left ventricular ejection fraction; NYHA, New York Heart Association; RMW, respiratory muscle weakness; PImax, maximal inspiratory pressure; SBP, systolic blood pressure.

420

23

421

TABLE 2

Cox proportional hazard models of respiratory muscle weakness for all-cause

mortality in HFrEF and HFpEF %PImax ≥ 70%

%PI

HR

95% CI

HR

95% CI

P value

Univariate analysis

1

Reference

3.09

1.74 - 5.48

<0.001

Multivariate analysis

1

Reference

2.17

1.20 - 3.95

0.011

Univariate analysis

1

Reference

3.93

2.46 - 6.27

<0.001

Multivariate analysis

1

Reference

2.85

1.74 - 4.67

<0.001

max

< 70%

HFrEF

HFpEF

Multivariate analyses were adjusted for age, gender, BMI, AHEAD score, NYHA class at hospital discharge, IHD, LVEF, and log BNP. CI, confidence interval; HFrEF, heart failure with reduced ejection fraction; HFpEF, heart failure with preserved ejection fraction; HR, hazard ratio; PImax, maximal inspiratory pressure. 422 423 424

24

1

Highlights

2

• Respiratory muscle weakness (RMW) was observed in 39% of patients with HFpEF.

3

• RMW was associated with poor prognosis in both patients with HFrEF and HFpEF.

4

• RMW showed the additive effect for risk prediction only in patients with HFpEF.

5

• Respiratory muscle assessment is useful for risk prediction in HFpEF patients.

1

1

Author Contributions Section

2

Subject: YRMED-D-19-00814

3 4

Title:

5

Prevalence and prognosis of respiratory muscle weakness in heart failure patients with

6

preserved ejection fraction

7 8

Nobuaki Hamazaki, PT, PhD*, Kentaro Kamiya, PT, PhD, Ryota Matsuzawa, PT, PhD, Kohei

9

Nozaki, PT, MSc, Takafumi Ichikawa, PT, Shinya Tanaka, PT, PhD, Takeshi Nakamura, PT, MSc,

10

Masashi Yamashita, PT, MSc, Emi Maekawa, MD, PhD, Chiharu Noda, MD, PhD, Minako

11

Yamaoka-Tojo, MD, PhD, Atsuhiko Matsunaga, PT, PhD, Takashi Masuda, MD, PhD, Junya Ako,

12

MD, PhD

13 14

* Correspondence: Nobuaki Hamazaki, PhD, Department of Rehabilitation, Kitasato University Hospital,

15

1-15-1 Kitasato, Minami-ku, Sagamihara, Kanagawa 252-0375, Japan

16

E-mail: [email protected]

17

18

Author Contributions: NH, KK, and TM contributed to the conception and design of the study. NH

19

and TM wrote the manuscript. NH, KK, RM, KN, TI, ST, TN, and MY contributed to data collection.

20

NH, TM, KK, RM, KN, ST, EM, CN, MT, AM, and JA contributed to interpretation. NH and KK

21

contributed to the statistical analysis. JA contributed to supervision and mentorship. All authors have

22

critically revised and assisted in the preparation of the manuscript. All gave final approval and agree

23

to be accountable for all aspects of work ensuring integrity and accuracy.

1

Conflict of Interest Statement

Title: Prevalence and prognosis of respiratory muscle weakness in heart failure patients with preserved ejection fraction

Nobuaki Hamazaki, PT, PhD1, Kentaro Kamiya, PT, PhD2, Ryota Matsuzawa, PT, PhD3, Kohei Nozaki, PT, MSc1, Takafumi Ichikawa, PT1, Shinya Tanaka, PT, PhD4, Takeshi Nakamura, PT, MSc5, Masashi Yamashita, PT, MSc5, Emi Maekawa, MD, PhD6, Chiharu Noda, MD, PhD6, Minako Yamaoka-Tojo, MD, PhD2, Atsuhiko Matsunaga, PT, PhD2, Takashi Masuda, MD, PhD2, Junya Ako, MD, PhD6

1

Department of Rehabilitation, Kitasato University Hospital, Sagamihara, Japan; 2 Department of

Rehabilitation, Kitasato University School of Allied Health Sciences, Sagamihara, Japan;

3

Department of Physiotherapy, School of Rehabilitation, Hyogo University of Health Sciences, Kobe, Japan;

4

Department of Rehabilitation, Nagoya University Hospital;

5

Department of

Rehabilitation Sciences, Kitasato University Graduate School of Medical Sciences, Sagamihara, Japan;

6

Department of Cardiovascular Medicine, Kitasato University School of Medicine,

Sagamihara, Japan

Conflicts of interest: none.