Subjects
The study was conducted at the Department of Cardiology, University of Leipzig. The 12 active and healthy male volunteers were recruited from medical staff. Subjects with cardiac, pulmonary or inflammatory diseases or any other medical contraindications were not included. The characteristics of the participants are shown in Table 1. The study was conducted in accordance with the latest revision of the Declaration of Helsinki and was approved by the Ethical Committee of the Medical Faculty, University of Leipzig (reference number 088/18-ek). Written informed consent was obtained from all the participants.
Table 1 Baseline characteristics Study design
Medical history was taken using a questionnaire. Subjects received physical examination and vital parameters, body measurements and a resting electrocardiogram (ECG). Each subject performed three incremental exertion tests (IET), one “no mask” (nm), one with surgical mask (sm) and one with FFP2/N95 mask (ffpm). The order of the masks worn was randomly assigned using the GraphPad Quickcalcs online randomization tool [13]. Tests were performed at the same time of day with a minimum of 48 h between two tests. To assess baseline respiratory function, spirometry for each setting (nm, sm, ffpm) was performed. The participants were blinded with regard to their respective test results to avoid influence by an anticipation bias. Statistical analysis was performed by an independent and fully blinded scientist who was not involved in the conduction of the tests.
Incremental exertion test (IET)
IET were performed on a semi-recumbent ergometer (GE eBike, GE Healthcare GmbH, Solingen, Germany, Germany) at a constant speed of 60–70 revolutions per minute (rpm). The test began at a workload of 50 W with an increase of 50 W within 3 min (as a ramp) until voluntary exhaustion occurred. Each subject continued for an additional 10-min recovery period at a workload of 25 W.
Masks
We used typical and widely used disposable FFP2/N95 protective face masks (Shaoguan Taijie Protection Technology Co., Ltd., Gao Jie, China) and surgical masks (Suavel® Protec Plus, Meditrade, Kiefersfelden, Germany), both with earloops.
The spirometry mask was placed over the fm and fixed with head straps in a leak-proof manner (see Fig. 1A1, B1). After fitting the spirometry mask, subjects performed (a) inspiration and (b) expiration with maximal force. During both maneuvers, the valve of the mask was closed leading to abrupt stop of the air flow (see Fig. 1A2, B2). The fitting was carefully checked for the absence of any acoustic, sensory or visual indication of leakage (e.g., lifting of the mask, whistling or lateral airflow) by the investigators and the test person. The correct fitting and leak tightness were confirmed before each test was started.
Measurements
Cardiac output (CO), stroke volume (SV) (measured by impedance cardiography; Physioflow, Manatec Biomedical, Macheren, France), heart rate (HR) (GE-Cardiosoft, GE Healthcare GmbH, Solingen, Germany), maximum oxygen consumption (VO2max) and minute ventilation (VE) were monitored continuously at rest, during IET and during recovery. Lung function and spirometry data were collected through a digital spirometer (Vyntus™ CPX, Vyaire Germany, Hoechberg, Germany). For each modality (nm, sm, ffpm), data of three expiratory maneuvers with 1‐min intervals were collected using the best values obtained for maximum forced vital capacity (FVC), forced expiratory volume in 1st second (FEV1), peak expiratory flow (PEF) and Tiffeneau index (TIFF). The arterio-venous oxygen difference was computed using Fick’s principle with avDO2 = VO2/CO. Cardiac work (CW) was measured in joules (J) and calculated according to the formula CW = SV (in m3) × SBP (in Pa). Capillary blood samples (55 µl) were taken from the earlobe at baseline and immediately after cessation of maximum load and analyzed (ABL90 FLEX blood gas analyzer, Radiometer GmbH, Krefeld, Germany). Blood pressures (BP) was observed at rest, every 3 min during the IET and after the first 5 min of recovery period.
Quantification of comfort/discomfort
We used a published questionnaire published by [14] to quantify the following ten domains of comfort/discomfort of wearing a mask: humidity, heat, breathing resistance, itchiness, tightness, saltiness, feeling unfit, odor, fatigue, and overall discomfort. The participants were asked 10 min after each IET how they perceived the comfort in the test.
Statistical analysis
All values are expressed as means and standard deviations unless otherwise stated, and the significance level was defined as p < 0.05. Data were analyzed using Microsoft Office Excel® 2010 for Windows (Microsoft Corporation, Redmond, Washington, USA) and GraphPad Prism 8 (GraphPad Software Inc., California, USA). For distribution analysis, the D’Agostino–Pearson normality test was used. For normal distribution, comparisons were made using one-way repeated measures ANOVA with Turkey’s post hoc test for multiple comparisons. Otherwise, the Friedman non-parametric test and Dunn’s post hoc test were used. The study was powered to detect a difference of 10% in VO2max/kg between nm and ffpm.