Effects of COVID-19 protective face masks and wearing durations on respiratory haemodynamic physiology and exhaled breath constituents

Introduction

Since early 2020, face masks have gradually become an integral part of our new-normal lifestyle as a component of the public health and social measures employed during the current coronavirus disease 2019 (COVID-19) pandemic [1, 2]. During the second wave of the pandemic, use of surgical and/or FFP2/N95/KN95 masks were strictly mandatory attributes while in public. National and/or global policymakers have recommended even adapting FFP3 masks for further protection considering the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants [3, 4]. In Germany, the government has recommended the use of FFP2 masks for up to 75 min at a stretch, and surgical masks at all times in public; the same guidelines are applied to school-attending children and individuals aged >60 years [5]. A recent meta-analysis demonstrated nearly 70% reduction of infection risk in healthcare workers and an overall reduction of infection risk [6]. Nevertheless, this systemic review was based on only case–control studies, which were not adjusted for bundled approach and aerosol-generating procedures. Conversely, a randomised controlled trial demonstrated that nonoccupational use (∼3 h·day−1) of surgical masks in adults along with some degree of social distancing did not reduce transmission [7]. In the last week of January 2021, Austria and Bavaria (south-east Germany) mandated respirator masks (FFP2 or KN95) in stores and on public transport. Although FFP2 masks were recommended to all members of the general public, there was no association with any preventive effect during explosive third waves (and death toll) of COVID-19 in Austria and Bavaria during the spring of 2021. In line with that, a recent analysis of cases and fatalities in western European countries without mask mandates could not find increases in numbers of infections or deaths in countries adopting generalised mask mandates [8].

While being recommended as protective against COVID-19 transmission, masks are inducing variable side-effects on our cardiorespiratory physiology [911], bronchopulmonary gas-exchange [12] and in vivo metabolic processes [13, 14]. Studies have shown effects of surgical masks on cardiopulmonary parameters, oxygen (O2)–carbon dioxide (CO2) homeostasis, blood pH and thermoregulation [15]. Additionally, studies have shown that conditions such as resistive breathing and/or hypoxia-driven hyperventilation, respiratory alkalosis and increased oxidative stress could cause immediate immune suppression [1619] and might lead to metabolic alkalosis [20].

Studies have indicated both complementary and/or conflicting results on the side-effects of different masks. Chan et al. [21] reported near-zero impact of nonmedical cloth masks and surgical masks on peripheral oxygen saturation (SpO2) and CO2 tension in 50 young adults during sitting and brisk walking for 10 min and minimal effects of nonmedical masks on SpO2 (self-monitored by subjects) in 25 older adults (>65 years) for 1 h in community settings. Rhee et al. [22] have demonstrated significant increases in CO2 (measured by nasal canula) concentrations in 11 healthy subjects within 15 min under FFP2 conditions, which remained within National Institute for Occupational Safety and Health limits for short-term use, but exceeded the long-term exposure threshold of 0.5%. Blad et al. [23] could not find considerable differences in inhaled CO2 within mask space (of medical masks) while experimenting via breathing simulator, particle generator and manikin head, but they found a rise in CO2 rebreathing of ∼10 000 ppm (1% CO2) overall. In contrast, a comprehensive review by Kisielinski et al. [15] has demonstrated a significantly measurable (p<0.05) decrease in O2 saturation under fabric, surgical and N95 masks in 17%, 22% and 44% of studies, respectively. They hypothesised a mask-induced exhaustion syndrome (MIES) which refers to consistent, recurrent and uniform presentation of psychological and physical deterioration and symptoms from multidisciplinary observations. In other studies, blood O2 levels dropped significantly (p<0.05 and p<0.01) below lower limits, with SpO2 values ranging from 92.1% to 93.2% in mask users compared to values from individuals without masks, ranging from 95.8% to 97.6% [2426].

Other human studies have demonstrated clinically concerning side-effects of FFP2 masks on at-risk populations suffering from COPD and other lung conditions, patients undergoing dialysis as well as significant physiometabolic effects on pregnant women and/or healthcare workers and on healthy subjects doing exercise and/or intensive athletics. Those effects triggered compensatory responses, e.g. mild increase in heart rate and increase in the rate of perceived exertion in trained young athletes, reduction in exercise capacity [10] and dyspnoea during short walk [27] in healthy nonathlete adults, significant respiratory compromise in mild COPD, asthma, chronic rhinitis [28] and severe obstructive lung disease [29] patients. During the 2002–2004 SARS outbreak, effects of N95 masks were reported on 39 end-stage renal disease (ESRD) patients, undergoing 4 h of haemodialysis. While dyspnoea was common under N95 masks, during haemodialysis, 70% of patients had significant reduction in arterial oxygen partial pressure, 19% had reached various degrees of hypoxaemia, 11 patients experienced chest discomfort and 17 patients had respiratory distress [30]. Recent analysis on 4747 ESRD patients (1925 on haemodialysis) depicted that universal use of surgical masks in haemodialysis units along with other preventive measures were effective against SARS-CoV-2 transmission in the Republic of Ireland [31]. Pregnancy-driven physiological changes in normal breathing patterns (uplift of diaphragm), increase in O2, nutrient and energy demand (by the developing embryo) and efforts to eliminate additional CO2 (from fetal respiration) in the mid–end phase of gestation often leads to a higher breathing rate (physiological hyperventilation) and increased cardiac output as principal respiratory compensation phenomena. Recent studies have shown significant compromise in such compensation under N95 masks. Prospective observations on 297 pregnant women (37–41 weeks of gestation) have demonstrated moderate (SpO2 up to 93%) and major (SpO2 <92%) decreases in SpO2 under surgical and N95 respirators, respectively [32]. Consequently, N95 respirators were removed to recalibrate the oxygen levels in those cases. Similar observations from a controlled trial on healthy pregnant healthcare workers (27–32 weeks’ gestation) have shown significant reductions in tidal volume, minute ventilation (without significant change in respiratory rate (fR)), O2 consumption and CO2 production under N95 masks [33]. Such effects were more pronounced under low-intensity work (3 metabolic equivalents), which also reduced exhaled O2 exhalation by 3.2% and increased CO2 exhalation by 8.9%. A recent pilot observation of mask-driven cardiopulmonary effects in 12 healthy subjects (age 40.8±12.4 years) at rest and during exercise are interpreted as significant, but modest [11].

However, those studies could not offer an insight into metabolic changes at the downstream level. In order to understand the immediate physiometabolic effects of face masks, we need to monitor continuous changes in metabolic markers along with simultaneous changes in respiratory and haemodynamic parameters. In this context, high-resolution mass-spectrometry based real-time analysis of exhaled volatile organic compounds (VOCs) could offer a unique insight into the body's immediate physiological [3438] and metabolic [39, 40] status. Several studies report on the potential of VOC analysis for SARS-CoV-2 detection, but data on the influence of masks on these profiles are missing. Continuous and breath-resolved measurements allow us to track changes in exhaled metabolic markers over the durations of mask use. As endogenous VOCs are known to originate from metabolic pathways and are influenced by physiological processes, changes in exhaled concentrations due to mask wearing could indicate effects of physiometabolic attributes. Combining VOC profiling with simultaneous pulse oximetry, capnography and haemodynamic monitoring could enable a broader unconventional understanding of clinically relevant effects of face masks.

We applied online high-resolution mass-spectrometry (i.e. proton transfer reaction (PTR) time-of-flight (ToF) mass spectrometry (MS))-based breathomics in parallel with noninvasive measurements of SpO2, fR, end-tidal CO2 partial pressure (PETCO2), exhaled humidity and oxygen, cardiac output, stroke volume, pulse rate and blood pressure. The physiometabolic side-effects of FFP2 and surgical masks over 15–30 min in healthy human subjects aged 20–80 years are addressed in detail. Effects of wearing duration and age from both mask types are compared.

MethodsHuman subjects

All experiments in this pilot study were conducted according to the amended Declaration of Helsinki guidelines and signed informed consent from 30 subjects (aged 20–80 years) were obtained (approval number A2021-0012, issued by the institutional ethics committee of University Medicine Rostock, Germany) prior to inclusion. Inclusion criteria specified adults (male and female) aged up to 80 years. Exclusion criteria specified that included subjects were not suffering from any acute diseases/health condition (during the 6 months before participation) and were not undertaking any special diet and/or medication during inclusion. Among the subjects aged >60 years, three had mild COPD (one male and two females) and two (females) had chronic bronchitis in the past. At the time of inclusion, these five participants had no symptoms, pathological findings or ongoing medications. They had described and confirmed their good health condition (over the past ≥1 year).

Determination of sample size

We applied ANOVA for calculation of sample size. For a minimum detectable difference in mean substance intensities of 450 counts per second, a standard deviation of 300 was estimated. To attain an α-value of 0.005 and a test power of 0.99, two experimental groups, considering a population of 100 000, required a sample size of 26 (with minimal group size of ≥ 10 each). In this study, we included 30 subjects for analysis in order to detect <5% differences in exhaled VOCs up to low parts per trillion by volume levels.

Assignment of groups

We divided the study population in two groups, namely young to middle-aged adults (aged <60 years) and older adults (aged ≥60 years). Anthropometric data were confirmed by participants during inclusion and are presented in table 1.

TABLE 1

Anthropometric information of subjects

Experimental setup

Three devices were synchronised for real-time measurements of several parameters simultaneously (figure 1): continuous monitoring of breath VOCs, O2, CO2 and humidity via PTR-ToF-MS; noninvasive measurements of haemodynamic parameters via volume clamp method; and SpO2 monitoring via pulse oximetry. Mainstream capnography (for PETCO2) was performed immediately before and after mask use. Data acquisition was initiated in parallel.

FIGURE 1FIGURE 1FIGURE 1

Instrumentation and experimental setup of the study. a,b) Customised polyetheretherketone (PEEK) extension of the proton transfer reaction (PTR) transfer line for c) direct sampling from the mask dead space. d) Continuous real-time breathomics via PTR-time-of-flight (ToF)-mass spectrometry (MS) in parallel with continuous noninvasive monitoring of e) haemodynamics via the ClearSight system and f) pulse oximetry. SpO2: peripheral oxygen saturation.

Breath sampling protocol

Volunteers rested by sitting on a chair for ≥ 10 min before actual sampling. Each participant was instructed to maintained the sitting posture [41] and then wore a face mask to breathe only by mouth. They spontaneously inhaled and exhaled only via the mouth [42].

The transfer-line of PTR-ToF-MS was connected (via polyetheretherketone (PEEK) finger-tight fittings) to a PEEK extension line (i.e. 30 cm long, with an outer diameter of 1 mm and inner diameter of 0.75 mm) in order to directly sample breath-resolved VOCs from the mask dead space (figure 1). The PTR transfer line was fixed (via metal clamps) at the back of subject's head (at a level below the left/right earlobe). The PEEK line was placed along the subject's right/left cheek (following the maxillary line) and was inserted within the mask dead space up to the front of the subject's lips. The tip of this sampling line was encased within a conical PEEK ferrule in order to avoid any unwanted contact with mask surface or with subject's lips. These extension lines were sterilised for reuse.

In each volunteer, measurements with two different masks (FFP2 and surgical) were conducted on two consecutive days and at the same time. The recruitment of subjects in FFP2 and surgical mask experiments were at random. Some subjects participated in the FFP2 mask experiment on the first day and others participated in the surgical mask experiment. Young to middle-aged adults were measured for 30 min and older adults were measured for 15 min. The measurements in older adults were stopped once they attained SpO2 <94%.

PTR-ToF-MS measurements of breath VOCs

Breath VOCs were measured continuously via a PTR-ToF-MS 8000 (Ionicon Analytik, Innsbruck, Austria) and with pre-optimised experimental conditions [36, 43], i.e. continuous side-stream mode of sampling via a 6-m heated (at 75°C) silico-steel transfer line connected to a sterile mouthpiece. A continuous sampling flow of 20 mL·min−1 was applied and the time resolution of the PTR-ToF-MS measurements was 200 ms. Thus, data points were generated after every 200 ms and at each data point hundreds of compounds were measured at their trace abundances (in both expiratory and room air). The ion source current was set to 4 mA and the water flow was set to 6 mL·min−1. Drift tube temperature was set to 75°C, voltage was 610 V and the pressure was 2.3 mbar. The resulting electric field/particle density (E/N) ratio was 139 Td. After every minute a new data file was recorded automatically and the mass scale was recalibrated after each run (60 s). We used the following masses for mass calibration: 21.0226 (H3O+-isotope), 29.9980 (NO+) and 59.049 (C3H6O).

VOC data processing

VOCs were measured in counts per seconds and corresponding intensities were normalised onto primary ion (H3O+) counts. Raw data was processed via PTR-MS viewer software (version 3.4). As PTR-MS continuously records both exhaled breath and inhaled room-air, the “breath tracker” algorithm (based on Matlab version 7.12.0.635, R2011a) was applied to identify expiratory and inspiratory phases [36]. Here, acetone was used as the tracker mass, as it is an endogenous substance, which has significantly higher signal intensity at expiration than inhalation. As the mass resolution of PTR-ToF-MS (4000–5000 Δm m−1) can assign volatiles upon their measured mass and corresponding sum formula with high precision [42], compound names are used while discussing results. VOCs were quantified via multicomponent mixture of standard reference substances. Quantification under adapted sample humidity (as in exhaled breath) using a liquid calibration unit (Ionicon Analytik) is our pre-established state-of-the-art process [44].

Selection of VOCs for analysis

We considered compounds with expiratory abundances significantly above the inspiratory/room-air abundance. Out of those markers, 32 substances were selected. These VOCs are well-known breath markers in clinical breathomics and reflect different origins, physicochemical characters and dependencies on physiology, metabolism, pathology, therapy and lifestyle/habits [39, 40, 42, 45, 46]. None of these VOCs were contributed from the applied masks, as we examined the mask emissions for direct comparisons.

Continuous haemodynamic monitoring

Noninvasive measurements of haemodynamic parameters, e.g. cardiac output, stroke volume, pulse rate and mean arterial pressure (MAP) were performed via our pre-optimised setup by using the volume clamp method (ClearSight system-EV1000; Edwards Lifesciences, California, USA) [35, 41].

Mainstream capnography

Mainstream capnography was performed just before and after each mask use via a small portable capnograph (EMMA PN 3639; Masimo Sweden, Danderyd, Sweden) attached to a sterile breathing mouthpiece. PETCO2 values were recorded in mmHg units. Absolute values are considered from the third breath onwards, as first two to three breaths are used to calibrate the CO2 and fR sensor.

Statistical analysis

Analytical mean values (of measured parameters) from each participant were calculated over each minute of breath-resolved measurement. Data from every fifth minute were included for statistical analysis. In cases of nonparametric distribution of data, median values were considered for statistical analysis.

In order to reduce the evident intra-individual variations in measured variables, each participant was used as his/her own control. Thus, variables from each subject were normalised onto the corresponding initial values (of the first minute). Normalisation was performed separately for each mask types (FFP2 and surgical) and in each age group (young to middle-aged and older adults).

As the distribution of measured data in each group is contributed by every individual (of that group), the relative standard deviations (RSDs) in VOC abundances from each group were also calculated for each substance. The RSDs were calculated (as a percentage) by rating sample standard deviations over corresponding sample means.

Statistically significant differences within groups were assessed via repeated measurement ANOVA on ranks (Friedman repeated-measures ANOVA on ranks, Shapiro–Wilk test for normal distribution and post hoc Student–Newman–Keuls method for pairwise multiple comparisons between all groups; p≤0.005) in SigmaPlot software (version 14).

For all measured variables, from all pairwise comparisons, the differences are presented by referring to the corresponding values at the first minute of each mask use and within each age group.

In order to compare between groups (i.e. the effects of both mask types on both age groups), relative changes (percentage) over time (with respect to initial values) were calculated for selected variables in each group. Here, we have selected the principal physiometabolic denominators and candidate VOCs that are potentially originating from several in vivo metabolic processes. Relative changes were calculated at 15th and 30th minutes in young to middle-aged adults and at the 15th minute in older adults. The changes in PETCO2 values were calculated immediately before and after mask use. In case of intergroup comparisons, one-way ANOVA was applied, due to unequal group size. All groups were compared to each other. From all pairwise comparisons between groups, the differences are presented by referring to the corresponding percentage of changes caused by FFP2 masks on older adults.

In order to understand the correlations between exhaled VOCs and physiological parameters within each mask type, dimension reduction factor analyses (factor extraction via the principal components method, factor scores via the regression method and one-tailed significance at p≤0.005) were performed in SPSS.

Results

Figure 2 shows heatmaps of relative changes (normalised mean values) of physiological parameters such as PETCO2, SpO2, fR, cardiac output, stroke volume, pulse rate, MAP and relative changes in exhaled alveolar abundances of 32 VOCs of interest during the use of FFP2 and surgical face masks by young to middle-aged and older adults. Measured variables from each volunteer were normalised onto corresponding median values from the first minute. The mean of those normalised values from every fifth minute is presented in the heatmaps. PETCO2 values are depicted from immediately before and after the mask use and are placed at the first and final minute of heatmaps for direct comparisons. The changes in RSDs of all measured parameters are presented as heatmaps in supplementary figure S1.

FIGURE 2FIGURE 2FIGURE 2

Relative changes in normalised mean values of physiological parameters and of exhaled alveolar volatile organic compound (VOC) abundances during the use of coronavirus disease 2019 protective face masks by young to middle-aged and older adults. The y-axis represents the physiological parameters end-tidal carbon dioxide tension (PETCO2), peripheral oxygen saturation (SpO2), respiratory rate, cardiac output, stroke volume, pulse rate, mean arterial pressure (MAP) values and the protonated/charged VOCs of interest. VOCs were tentatively identified according to their mass/charge ratio. For each individual, VOC data were normalised onto corresponding median values from the first minute. Likewise, respiratory and haemodynamic parameters and SpO2 were normalised; the means of those normalised values from every fifth minute are presented. Only PETCO2 values are presented from immediately before and after mask use and are placed at the first and final minutes of the heatmaps. Red and blue colours symbolise relatively higher and lower abundances of VOCs, respectively. Similarly, dark and light brown colours symbolise relatively higher and lower values of physiological parameters, respectively. In case of PETCO2, the points without any measurements are coloured in black.

Figure 3 depicts absolute or normalised values of physiological parameters and of alveolar concentrations of exhaled VOCs in every fifth minute (starting from the first minute) in four groups. The first two groups consist of data from FFP2 masks on young to middle-aged and older adults and the later two groups contain data from surgical masks on young to middle-aged and older adults. PETCO2 values are presented from immediately before and after the use of masks. Figure 3a represents the physiological parameters absolute values (with units) of SpO2, PETCO2 and fR and normalised haemodynamics values. Figure 3b represents aliphatic aldehydes and organosulfur; figure 3c represents hemiterpene, ketone and smoking-/environment-related VOCs, exhaled humidity and oxygen; and figure 3d represents aliphatic acids, alcohols and monoterpene. Absolute values are only considered for parameters, which are less likely to be affected by inter- or intra-day variations within each individual. From all pairwise comparisons, the differential expressions (statistically significant at p≤0.005) in each variable within each group is indicated with respect to the corresponding “first minute” of measurement.

FIGURE 3FIGURE 3FIGURE 3FIGURE 3FIGURE 3FIGURE 3FIGURE 3FIGURE 3FIGURE 3

Comparison of differences in physiological parameters and in exhaled alveolar volatile organic compound (VOC) concentrations during the use of coronavirus disease 2019-protective face masks by young to middle-aged and older adults. a) physiological parameters; b) aliphatic aldehydes and organosulfur; c) hemiterpene, ketone, nitrile, aromatics, exhaled humidity and oxygen; and d) aliphatic acids, alcohols and monoterpene. The x-axes represent measurement time in four groups: two mask types (FFP2 and surgical) used by two age cohorts (young to middle-aged and older adults). The y-axes represent absolute values (with units) or normalised (onto corresponding initial values) values of measured parameters from every fifth minute, starting from the first minute. For both mask types, young to middle-aged and older adults were measured for 30 min and 15 min, respectively. End-tidal carbon dioxide tension (PETCO2) values were measured immediately before and after the use of masks and absolute values (with units) are presented. Measured values within each group were compared. PETCO2 values before and after mask use are compared statistically. Statistical significance was tested by means of repeated measurement ANOVA on ranks (p≤0.005). From all pairwise-multiple comparisons, statistically significant differences with respect to the “first minute” are indicated as follows. #: FFP2 masks; ¶: surgical masks.

The correlation coefficients and respective p-values between physiological parameters and VOCs of interest are presented in table 2 and between relevant physiological parameters are presented in table 3. Detailed inter-VOC correlations (with respect to physiological parameters) along with corresponding p-values are presented in supplementary tables S1 and S2. It is noteworthy that cardiac output showed strong positive correlation to stroke volume under both masks, whereas pulse rate remained only moderately related to cardiac output under FFP2 conditions. Cardiac output, stroke volume and pulse rate showed relatively higher variations under the surgical masks, whereas pulse rate remained completely unrelated to cardiac output. While fR remained unrelated to other physiological parameters under both masks, MAP has shown significant and moderate negative correlations to SpO2 only under FFP2 masks and good positive correlations to cardiac output and stroke volume under surgical masks.

TABLE 2

Correlation (obtained via factor analysis) between physiological parameters and selected volatile organic compounds (VOCs) of interest

TABLE 3

Correlation (obtained via factor analysis) between physiological parameters of interest

Figure 4 depicts comparison of relative changes (percentages) in physiological parameters and in selected metabolic breath markers within four groups: FFP2 masks on young to middle-aged and older adults and surgical masks on young to middle-aged and older adults. Relative changes (with respect to initial values) in young to middle-aged adults at the 15th and 30th minutes and in older adults at the 15th minute are presented. For PETCO2, relative changes between measured values immediately before and after use of masks are presented. Figure 4a presents physiometabolic parameters and figure 4b presents exhaled alveolar volatile organic metabolites. From all pairwise-multiple comparisons, statistically significant differences are indicated with respect to changes caused by FFP2 masks on older adults. Statistical significance (with corresponding p-values) of differences in all variables between groups are indicated with respect to the “15th minute in older adults with FFP2 mask” in supplementary table S3.

FIGURE 4FIGURE 4FIGURE 4FIGURE 4FIGURE 4

Comparison of relative changes (in %) in physiological parameters and in exhaled metabolic markers during the use of coronavirus disease 2019-protective face masks by young to middle-aged and older adults. a) Physiometabolic parameters and b) exhaled alveolar volatile organic metabolites. The x-axes present measurement time in four groups: two mask types (FFP2 and surgical) used by two age cohorts (young to middle-aged and older adults). The y-axes represent percentage changes (with respect to initial values) in measured parameters at 15th and/or 30th minutes. For both mask types, young to middle-aged and older adults were measured for 30 min and 15 min, respectively. Thus, for both mask types, changes in young to middle-aged adults at the 15th and 30th minutes

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