A pilot study to evaluate the changes in venous blood gas parameters and hypoxia biomarkers in health care workers using different kinds of masks : Lung India

Secondary Logo

Journal Logo

Original Article

A pilot study to evaluate the changes in venous blood gas parameters and hypoxia biomarkers in health care workers using different kinds of masks

Patel, Suprava1; Mohapatra, Eli1,; Suganthy, Asha K.1; Shah, Seema1; Abraham, Jessy1; Nanda, Rachita1; Behera, Ajoy K.2; Gupta, Ashish3

Author Information
Lung India 40(2):p 134-142, Mar–Apr 2023. | DOI: 10.4103/lungindia.lungindia_343_22
  • Open



The human respiratory mechanism ensures an efficient gaseous exchange with the surrounding. The inspiration process involves inhalation of surrounding air around the immediate vicinity of the face through mouth and nostril. Expiration, in turn involves exhalation of carbon dioxide (CO2) rich and low oxygen (O2) content hot, humid air away from the body, both from mouth and nostrils. The exhalation is in a jet form so that the air is vented out far away from the face and gets diluted into the surrounding air. The airflow pattern during the expiration and inspiration processes ensures to keep the respiration at a controlled rate with effective gaseous exchange. So, when a mask or filtering facepiece respirator (FFR) or personal protective equipment (PPE) is put on, which cover the mouth and nostrils, it significantly affects the gaseous exchange that eventually increase the dynamic dead-space volume of the mask/N95-FFR itself, and thus the airflow pattern of respiration.[1] The total dynamic dead space was shown to increase from 32% to 42% of tidal volume during spontaneous respiration through a face mask.[2] Furthermore, use of face mask with respirator increased resistance to air inflow. Breathing becomes more labored if theses masks are used for a longer duration due to clogging of pores by the absorbed dust. Subsequently, the levels of CO2 in the dead space increases during each respiration cycle.[3,4] Symptoms of hypercapnia including discomfort, fatigue, dizziness, headache, muscular weakness and drowsiness is commonly reported by all.[5]

Earlier studies have shown that the combination of venous blood gas analysis plus oxygen saturation percentage by pulse oximetry (SpO2) provide an accurate information on acid-base, ventilation, and oxygenation status of critically ill patients.[6–8] According to bulletin released by American Thoracic Society, the oxygen level from a pulse oximeter is reasonably accurate. Most oximeters give a reading ±2% of oxygen saturation obtained by an arterial blood gas.[9] As it is known that heat and moisture trapping occur beneath all masks and respirators, it seems reasonable that increased CO2 may induce a decrease in blood oxygenation or hypoxia.[10] Among the various studied molecular mechanisms involved in the response to hypoxia at the cellular level, hypoxia-inducible factor-α (HIF-α) and erythropoietin (EPO) are used as key markers to detect hypoxia.[11] Therefore, measuring venous blood gas parameters along with measurement of oxygenation saturation (using pulse oximeter) and levels of HIF-α and EPO, should give an estimate of the metabolic changes occurring in blood that can affect the overall health of health care workers. Due to the ongoing COVID-19 pandemic, both Indian Council of Medical Research (ICMR), India and World Health Organization (WHO) guidelines mandates the use of varied protective measures by healthcare workers for their safety. This includes the use of PPE with N95-FFR by healthcare workers coming in direct contact with a COVID-19-positive patient while other healthcare works and laboratory personnel are required to wear either a triple layer surgical mask or mask made of 2-to-3-layered cotton cloth. Depending on their nature of work, the surgical/cotton mask are generally worn at a stretch of no less than 4–8 h while removing them only for short water and food breaks. Similarly, PPEs are donned at a stretch for no less than 2–4 h, if not more.

Although several studies exist for physiological changes induced by continued use of surgical mask or N95-FFR like ventilation rate, heart rate, oxygen saturation, perfusion index, rating of perceived exertion, oxygen uptake, cardiac output, lactate, there are no previous studies comparing the changes in the blood parameters associated with prolonged mask or N95-FFR use in individuals.[10,12–14] The study was designed to investigate the changes in biochemical parameters associated with extended mask use specifically in relation to blood gas parameters and markers of hypoxia.


The prospective comparative study was conducted in one hundred twenty-nine (n = 129) study participants. The study was approved by the Institute Ethical Committee and Helsinki’s guidelines for good clinical practice were followed. The study population comprised of 37 (n = 37) apparently healthy subjects as control group and 92 (n = 92) health care workers as exposed groups. All study participants were of age group 2050 years.

Inclusion criteria

Exposed group

The exposed group were apparently healthy individuals who have been posted as part of COVID-19 duty or other departments in the hospital or laboratory personals handling blood saliva and/or blood samples collected from COVID-19 patients were included for the study. They must be wearing masks (cloth/surgical mask/N95-FFR/PPE) continuously for at least 2 hr a day for 10 days. Health care workers included faculties, residents, nursing staffs, technicians, attendants, cleaning staffs, and office staffs posted in hospital wing.

As health professionals who were posted for ten continuous days in direct care of COVID-19 patients were enrolled for the study. Two blood samples were collected from each participant on the start of duty, and at end of 10 days. The first sample was collected on the first day (start of the duty) was considered as First sample and that collected on tenth day was counted as Second sample. All the participants enrolled in exposed groups were health care workers working in our institute since last 2 years and hence, they have been wearing mask since the start of COVID pandemic. Hence, the base line values of the parameters were compared with control group who were not health care workers and have not been continuously wearing mask.

  1. Groups-1: Health workers posted in COVID-ward or in-patient departments (IPDs) using N95-FFR with or without PPE were enrolled under this group.
  2. Group-2: Health workers posted in laboratories and other wards using surgical masks only were enrolled under group-2.
  3. Group-3: Health workers in various departments or office using cloth mask only were enrolled as group-3 participants.

Control group

The group comprised of apparently healthy adults who used mask intermittently and not on continuous basis for more than 2 h a day. Family members of the hospital staffs and other workers who full fill the criteria were included.

Exclusion criteria

i). Individuals having with history of acute or chronic respiratory illness, hemoglobinopathies, chronic inflammatory diseases, cancer, diabetes mellitus or hypertension for more than 5 years duration or with any present manifestation of microangiopathy, pregnant women.

Exposed group

i). Health workers who admit that they did not wear mask continuously for more than 2 h a day.

Demographic details were documented. SpO2 by pulse oximetry was noted for each participant on both days. Three to four milliliter (mL) of venous blood was collected on day 1 and day 10. At least one mL each was collected in plain tube with clot activator, in ethylenediamine tetra acetic acid (EDTA) tube and in heparinized syringe. The heparinized blood was immediately analyzed for venous blood gas in RAPIDPoint 500 Blood Gas System, Seimens for quantification of pH, partial pressure of oxygen in mmHg (pO2), partial pressure of carbon dioxide in mmHg (pCO2), bicarbonate (HCO3) in mmol/L, O2 saturation percentage (sO2%), percent fractional oxy-hemoglobin (FO2Hb%), percent fractional deoxy-hemoglobin (FHHb%), sodium ion (Na+) in mmol/L, potassium ion (K+) in mmol/L, chloride ion (Cl) in mmol/L, calcium ion (Ca2+) in mmol/L, glucose in mg/dL, lactate in mmol/L and anion gap in mmol/L. The EDTA tube was processed for reticulocyte count (retic count). Blood collected in plain tube was centrifuged and the serum separated was stored at −80°C for further analysis of HIF-α in ng/mL and EPO levels in mIU/mL. Serum HIF-a and EPO were quantified using enzyme linked immunosorbent assay (ELISA) technique. The biological reference ranges of the parameters measured in venous blood are provided in Table suppl-1. The same process for sample collection was performed for both first and second samples for the exposed group. For healthy controls, only first sample was collected for baseline levels for comparison between the groups.


Statistical analysis

The data analysis was performed in SPSS software version 20 (IBM Corp.). The frequency of distribution was expressed in percentages and compared within the study groups by Chi-square or Fisher’s exact test. Mean with standard deviation (SD) was depicted for the continuous variables. The mean (SD) among the exposed and control group was compared using independent student’s t-test. Analysis of variance (ANOVA) was performed for comparison of continuous variables among the four study groups. The changes in the variables between the first and second samples (first sample – second sample) was analyzed by paired-t-test. Pearson’s correlation was used to observe the relationship between the variables along with the linear regression to estimate the variation per unit change of parameter.


Frequency distribution and demographic details of the study population (N = 129)

A total of 129 study participants were enrolled for the study. It comprised of 37 apparently healthy controls and 92 health care workers as participants in exposed group. The study population consisted of 32 (24.8%) females and 97 (74.4%) males. The number of males and females enrolled in exposed group were respectively, 66 (71.7%) and 26 (28.3%) [Figure 1]. The control group comprised of 31 (83.8%) males and 6 (16.2%) females [Figure 1]. The mean with standard deviation (SD) of age in the study population was 30.33 (7.45) years. The mean (SD) of height, weight, and body mass index (BMI) of study participants were uniformly distributed between the two study groups [Figure 2].

Figure 1:
Percentage distribution of the gender in the control and exposed groups
Figure 2:
Comparison of the demographic variables between the Control and Exposed groups

Comparison of variables among the control and exposed groups (N = 129)

The mean (SD) duration of wearing mask in the control group was 1.08 (1.03) h and that in the exposed group was 6.78 (1.2) h [Table 1]. The mean (SD) SpO2 was 97.75% (3.5) in the study population. Parameters like SpO2, pO2, and pCO2 were elevated in exposed group than control (P > 0.05) [Table 1]. However, sO2% was significantly lower in mask users with a mean (SD) of 72.88 (19.26) (P = 0.033). Ions like HCO3, Cl, and K+, metabolites like glucose, lactate, did not differ significantly between the two groups, although, Na+ was found slightly raised in exposed individuals (P = 0.05) than the healthy controls. Similarly, the mean (SD) of Ca2+ was 1.18 (0.07) mmol/L was found greatly elevated in exposed group (P < 0.001). However, no significant difference was reported for anion gap (P = 0.62). The mean serum HIF-α level of 3.26 (3.27) ng/mL was considerable higher in the exposed individuals than the healthy controls (P = 0.001). Similarly, substantially reduced percentage of reticulocyte count (1.93) was observed in the exposed group (P = 0.011).

Table 1:
Comparison of the mean (SD) of the variables between the control and exposed groups

Comparison of variables of the first sample among the study groups (N = 129)

As delineated in Table 2, the venous pO2 was significantly higher in group-3 (cloth mask) than group-1 (P = 0.008). The difference in mean values among the study groups was significant for pCO2 (P = 0.001), pH (P = 0.013), and Na+ (P = 0.006) but considering individual group, no difference in values was observed. sO2% was highest in control group with a mean (SD) of 80.28 (12.9). The value was significantly reduced in group-1 (62.36%) than the controls (P < 0.001). The sO2 in group-1 was also substantially lower when compared to group-2 (P = 0.011) and -3 individuals (P = 0.001). The Ca2+ was higher in all the exposed groups when compared to control group (P < 0.01). The individuals of group-1 depicted the lowest mean (SD) for FO2Hb%, 64.65 (19.6) than the other three groups (P < 0.01). On the contrary, FHHb% was the highest in group-1 with a mean (SD) of 33.04 (20.2) (P < 0.001). The value was significantly higher than other three. The mean (SD) of serum HIF-a in group-1 was 3.74 (3.6) ng/mL and in group-2 was 4.18 (3.5) ng/mL. When compared to control group, the mean serum HIF-α levels were considerably raised in group-1 (P = 0.002) and group-2 (P < 0.001). Similarly, both the groups depicted higher HIF-α levels than participants of group-3 (P < 0.05). Serum EPO also revealed considerably elevated levels in group-1 subjects than healthy controls (P = 0.047). The mean (SD) was 25.55 (33.5) mIU/mL in group-1 and it was greater than both the exposed groups (P < 0.05). Although the Hb values within the study groups were comparable among the study groups, however, the reticulocyte count was lower in group-3 individuals when compared to group-1 (P = 0.008).

Table 2:
Comparison of mean (SD) of variables among the study groups for the first sample (n=129)

Comparison of variables in second samples among the exposed groups (N = 92)

The comparison of variables in the second sample of the exposed groups have been depicted in Table 3. Biochemical variables that showed difference among the exposed group were pO2 (P = 0.002), Na+ (P = 0.02), Hb (P < 0.05), FO2Hb (P = 0.02), HIF- α (P < 0.05), and EPO (P < 0.05). Parameters such as pO2, Na+, Hb, FO2Hb depicted a significantly reduced, whereas, serum HIF-α and EPO levels was found to be elevated in group-1 than the other exposed groups.

Table 3:
Comparison of the variables in the second samples of the exposed study groups (n=92)

Comparison of variables between the first and second samples in the exposed groups (N = 92)

The overall changes observed in variables of first and second samples in exposed groups have been reflected in Table 4. pO2 and sO2 levels didn’t reflect any significant difference. On the contrary, the mean (SD) of pCO2 was lower by 3.74 in the second sample than the first one (P < 0.001). The rise in pH by 0.03 units in second sample was (P < 0.001) was evident in 64.1% (n = 59) health care workers. Na+ level depicted an increase by 1.62 mmol/L (P = 0.026) whereas Ca2+ was reduced significantly by 0.027 mmol/L (P = 0.001) in the second sample. Serum HIF-α level was raised by 0.24 ng/mL (P = 0.14) in the second sample of the exposed participants. 50% (n = 46) revealed raised serum HIF-α in the second sample with a difference of 0.24 ng/mL (P = 0.01). Almost 58.7% (n = 54) of exposed group reported higher serum EPO in second sample than the first one with a difference between the two samples by 3.89 (P = 0.003). Similarly, the values of hemoglobin (P = 0.75) and reticulocyte count (P = 0.131) showed no marked difference in the two samples, although, nearly 55% participants recorded higher value in first sample than the second one.

Table 4:
Changes observed in variables between first and second samples in exposed groups (n=92)

Changes in variables between the first and second samples in exposed groups [Figure suppl 1]

Figure suppl 1:
The difference of biochemical variables in the second sample in comparison to the first sample in exposed group (n = 92). The blood parameters have been depicted in two graphs and significant changes were observed in pCO2, Na+, FHHb, EPO, pH, Ca2+, Hb, HIF-α.

The mean difference (first sample – second sample) observed in the biochemical variables between the first and second samples of the exposed groups have been detailed in Figure suppl 1. Rise in pH in second sample was observed for both group-1 and -2 (−0.04, P < 0.001; −0.015, P = 0.048 respectively). The difference in Hb (0.69, P = 0.011), FHHb (8.93, P = 0.007), and EPO (−5.75, P = 0.001) was more evident in N95-FFR/PPE users (group-1). On the contrary, significant change in Na+ (−2.033, P = 0.006) was observed in cloth mask users (group-3).

Both group-1 and -3 individuals revealed remarkable decrease in pCO2 (4.57, P = 0.003; 6.94, P < 0.001 respectively) and Ca2+ (0.029, P = 0.019; 0.037, P = 0.036 respectively) levels.

Relationship between duration of mask use and HIF-α levels in the study population (N = 129)

Correlation analysis revealed a positive correlation between the duration of mask use (in hours) with HIF-α (r = 0.247, P = 0.005) in the first sample in the study population [Figure 3a]. Similarly, Ca2+ (r = 0.306, P < 0.001) and Na+ (r = 0.174, P = 0.048) levels also depicted a linear relationship with the hours of mask use as shown in Figures 3b and 3c. The linear regression model indicated that 5.4% of the variance in HIF-α values can be explained by the hours of mask use [F (1,127) = 8.275, P = 0.005]. For every 1 h increase in use of mask, the serum HIF-α level would rise by 0.261 units. Similarly, it was also observed that percentage effect was 8.6% on Ca2+ level (F (1,127) = 13.085, P < 0.001) with a slope of 0.007. For every hour use of mask, the Ca2+ level would increase by 0.007 unit.

Figure 3:
(a-c) Relationship between duration of mask use with HIF-α, Na+ and Ca2+ levels in the study population (N = 129). r denotes the Pearsons’ correlation value; *denotes significance at P < 0.05

Association of clinical symptoms with use of different masks among the exposed groups (n = 92)

The frequency percentage distribution of the individuals who had one or more clinical symptoms in the exposed groups has been reflected in Figure 4. 63.3% (n = 19) group-1 individuals gave history for some sort of symptoms as against 18.8% in group-2. None of the group-3 participants gave history of any sort of clinical symptoms. The odds for having a clinical symptom in group-1 individuals was 7.21 (95%CI = 2.319–24.74, P < 0.001) as against group-2. When compared to group-3, the chances were more than 50 times (P < 0.001). Participants using surgical mask (group-2) depicted nearly 10 times higher probability than group-3 for symptoms (95%CI = 1.156–326.1, P = 0.013). Of all those using N95-FFR/PPE (group-1), almost 40% (n = 12) had at least one the symptoms and 33.3% (n = 10) had more than one (Fischer exact χ2 = 45.51, P < 0.001). Headache was the most common symptoms (15.2%) complained by the health workers in the exposed groups. 33.3% of group-1 participants complained of frequent headache as major symptom, followed by frequent polydipsia (26.7%), blackouts (20%), shortness of breath (16.7%), sleep disturbances (16.7%) and weakness (6.7%) [Figure 5]. Similarly, 12.5% of group-2 individuals also had frequent headache as most common symptoms. On further analysis, it was observed that individuals who used to exercise were 44 times protective for clinical symptoms (OR: 95%CI = 0.562:0.201–1.571, P = 0.27). Nearly, 65.7% participants who used to exercise had no symptoms (χ2 = 1.217, P = 0.27).

Figure 4:
Frequency percentage of clinical symptoms of the individuals enrolled under exposed groups
Figure 5:
Frequency percentages of various clinical symptoms in the exposed groups


Use of N95-FFR/PPEs and other masks during this COVID-19 pandemic, though minimize the spread of COVID-19 virus droplets, but the gaseous exchange is considered to be compromised.[15] Thus, depending on the level of inhaled oxygen and carbon dioxide during the usage hours of mask, may be potentially hazardous depending on the individual susceptibility and pre-existing diseases. It remains as major concern among health care workers that it might lead to health problems of variable severity in them. Although several studies exist for physiological changes induced by continued use of surgical mask or N95-FFR/PPE, there are no previous studies comparing the changes in venous blood gas parameters associated with prolonged mask or N95-FFR/PPE use in individuals.[16,17] Hence, the study was conducted to compare the changes in venous blood gas parameters associated with extended use of various kinds of mask among health care workers due to COVID-19 pandemic

A small study in 2006 looked at healthcare workers wearing N95 masks during the SARS epidemic. It concluded that the use of N95 masks may cause the healthcare workers to develop headaches and wearing them for shorter amounts of time helped reduce the frequency and severity of the headaches.[15] During expiration, CO2 levels increase and O2 concentration reduces significantly than the ambient concentration of the environment as CO2-enriched exhaled breath only partially escapes the mask and O2 inhalation is compromised to a large extent in rebreathed air. Chen and colleagues studied the physiological and subjective responses to breathing resistance of N95 masks. During the study the subjects were asked to either sit or walk for 5 min while wearing 2 different models of N95-FFRs. The subjective survey showed that when compared with no respirator, wearing N95-FFR had a direct effect on increasing respiratory amplitude, muscle activity and fatigue of abdominal muscle and scalene.[18] But another study showed that N95-FFR fitted with various filter resistances did not have significant impacts on physiological and subjective responses.[19] Beder and colleagues measured the oxygen saturation of arterial pulsations by a pulse oximeter and found a statistically significant decrease in the blood sO2 level of the surgeons post operationally during major surgery, which is not due to prolonged standing or stress.[10] Present study did show a significantly reduction in sO2 in the exposed health workers [Table 1], more so in N95-FFR/PPE mask users than other groups [Table 2]. In-spite of the fact that the pulse oximetry SpO2 level was uniformly distributed among the exposed study groups, the pO2, sO2, and FO2Hb levels were consistently low in both first and second samples in individuals using N95-FFR/PPE (group-1) [Tables 2 and 3]. The difference was because the exposed groups were the healthcare workers who had been working in the hospital (our institute) for at least last two years and as per ICMR guideline had been using mask since the start of COVID-19 pandemic. Hence, the base line was compared between the exposed group and control individuals. Due to chronic use of the protective masks, breathing higher levels of carbon dioxide can cause a drop-in blood pH, leading to a state of respiratory acidosis and hypercapnia followed by hyperventilation. Taking altogether into consideration of the said findings, might explain that these individuals were chronically exposed to altered hypoxemia-driven hyperpnea or tachypnea and altered pCO2 levels such as episodes of hypocapnia or hypercapnia. A repeated episodes of such metabolic alterations would have induced changes to oxyhemoglobin dissociation curve for improved oxygen deliver to tissues. The phenomenon is similar to the pathophysiologic changes in high altitude hypoxemia, in which hypercapnia would impart a right shift of oxygen dissociation curve (ODC) for improving oxygen saturation.[20,21] This explains the reduced FO2Hb (P = 0.005) and elevated FHHb (P < 0.001) percentages in N95-FFR/PPE mask users than control and other two mask users [Table 2] in the present study. Increase in pH also correlated inversely with pCO2 in the exposed group (r = −0.797, P < 0.001). A consistent cycle of hypoxemia, hypercapnia, hyperventilation on virtue of equating the alveolar gas equation, might have led to lower pCO2 and raised pH in the second samples with altered Na+ and Ca2+ levels [Table 4]. Na+ and Ca2+ levels recorded a linear relation with duration of hours of mask use [Figure 3] and thus, recorded higher levels in exposed individuals than the healthy controls [Table 1]. Such metabolic alterations leads to clinical discomfort, fatigue, dizziness, headache, muscular weakness and drowsiness.[22] This might have resulted in high percentage of clinical symptoms (63.3%) associated with these participants [P < 0.001, Figure 4].

Some studies have suggested that exhalation valves are useful in dissipating humidity, heat, and carbon dioxide from the dead space of N95-FFR and decreasing exhalation resistance, thereby making the respirator more comfortable and less physiologically demanding. This is important when N95-FFRs are worn for extended periods.[23] Kim et al.[24] also found insignificant increase in pulmonary and heart rate responses while using N95-FFR for <1 h. But another study by Roberge et al.,[25] showed that in healthy healthcare workers, N95-FFR fitted with exhalation valve did not impose any important physiological burden for <1 h of use in clinical environment. However, the N95-FFR dead-space carbon dioxide and oxygen levels were significantly above and below, the ambient workplace standards, respectively.

Exposure of health workers to acute or chronic hypoxia might have resulted an upregulation of the cellular expression of mRNA of HIF-α, EPO, and hemoglobin as an effector response. An elevation of these parameters was observed in the exposed individuals in their second samples collected [Table 4]. One of the key cellular responses to hypoxia is activation of HIF-α which justifies the positive correlation with hours of mask use observed in the present study (P = 0.005, Figure 3a). Hypoxia and HIF-α activation, may contribute to transcriptional regulation of oxygen-sensitive pathways and genetic modifiers.[26] HIF-α is known as an essential component of the cellular oxygen sensing signaling and mediate transcriptional activation of various proteins, including the globin-associated transcription factors for EPO and hemoglobin synthesis.[27,28] This might have resulted in increase in Hb, FO2Hb, and EPO in second samples [Table 4]. A noticeable increase in the plasma concentration of HIF-α and EPO after short exposures to hypoxia has been reported before.[29,30] Similarly, serum HIF-α and EPO were found considerably elevated in N95-FFR/PPE exposed individuals (group-1) [Tables 2 and 3].

Berna et al.,[31] study observed a rise in intracellular calcium [Ca2+]i in the human endothelial cells under hypoxic environment that involved glycolysis activation and activation of Na+/Ca2+ exchanger that induced influx of Ca2+. The calcium level alteration could be a response mechanism in synthesis and release of inflammatory mediators during the hypoxic event. In agreement to Berna et al. study, the present study revealed an increased levels of blood Ca2+ in exposed group [P < 0.001, Table 1] and linear relationship with duration of mask use (P < 0.001, Figure 3b). Ionic calcium and sodium levels are temporarily altered in acute hypoxia to skeletal muscles or other tissues that causes metabolic alterations like acidosis in the surrounding areas.[32]

In a study by environmental health scientists at the University of Massachusetts Amherst, it was shown that inexpensive cloth masks were less effective in filtering airborne particulate matter compared to N95-FFR and surgical mask.[33] Based on this result, it could be safely assumed that that cotton mask may be more permeable to CO2 thus causing less build-up of CO2 in the dead-space volume compared to surgical mask/N95-FFRs [Figure 1a]. This might explain the fact that about 33.3% of N95-FFR/PPE users had complaints for shortness of breath while none in cloth mask users [Figure 5]. If so, extended use of cotton mask should not cause significant changes in blood gas parameters compared to use of surgical or N95-FFR/PPE. To its agreement, the present study analysis revealed that the pCO2 levels were lower by 6.94 (P < 0.001) in second sample of group-3, while in group-1 the difference was 4.57 (P = 0.003) [Figure suppl 1]. Besides pCO2, group-1 individuals depicted considerable difference in Hb, FHHb, EPO, pH and Ca2+ levels in second sample after 10th day [Figure suppl 1]. A substantially low Na+ and Cl levels in group-1 participants [Table 3] might explain the presence of polydispsia in nearly 26.7% while none in participants using cloth mask [Figure 5]. Summing up the findings, it was observed that the odds for having a clinical symptom in N95-FFR/PPE users was 7.21 (95%CI = 2.319-24.74, P < 0.001) as against surgical mask users and 50 times more as against cloth mask users (P < 0.001). Exercise is known to increase respiratory capacity. Hence, individuals who exercise on regular basis would tend to tolerate the biochemical alterations due to mask and thus they might be protected. It was observed that individuals exercising were 44 times more protective for clinical symptoms.


The major limitation of the study is the use of venous blood gas parameters owing to the complexity of collection of the arterial samples. However, few studies have suggested that in individuals with normal SpO2 with satisfactory venous pH of >7.35 and pCO2 <45 mmHg could provide a reasonably satisfactory guide regarding the overall blood gas status.[34,35]

In addition, a good sample size and inclusion of all type of mask users and the control group justifies the strength of the study design. To the best of our knowledge, this is a very type of its kind to provide an insight regarding the effect of various blood parameters including HIF-α and EPO levels. It is important to understand the changes in venous blood gas parameters occurring in workers due to prolonged use of respiratory protective devices like N95-FFR/PPE or surgical or cotton mask which have to be donned for extended periods as part of protective measures to reduce risk of COVID-19 infection.


The comparative study of various blood parameters among the various type of mask users and healthy control individuals depicted a significant alterations in sO2 levels, pH, ions like Ca2+ and Na+ and serum HIF-α. The levels of HIF-α and Ca2+ have been significantly associated with the duration of mask use. Of all the exposed group, PPE/N95 users registered significant clinical symptoms like shortness of breath and polydipsia which could have been associated with the altered metabolic effect due to chronic hypoxic exposure of the tissues. It has been predicted that COVID-19 pandemic might prolong for a long duration of time. In such a scenario it is important to not just protect the healthcare and associated workers from the risk of getting infection from COVID-19 but also overall health of these workers.

Financial support and sponsorship

This prospective comparative study was funded by All India Institute of Medical Sciences, Raipur, Chhattisgarh, India under institutional intramural grant.

Conflicts of interest

There are no conflicts of interest.


1. Birgersson E, Tang EH, Lee WLJ, Sak KJ. Reduction of carbon dioxide in filtering facepiece respirators with an active-venting system:A computational study. Plos One 2015;10:e0130306.
2. Saatci E, Miller DM, Stell IM, Lee KC, Moxham J. Dynamic dead space in face masks used with noninvasive ventilators:a lung model study. Eur Respir J 2004;23:129–35.
3. Smereka J, Ruetzler K, Szarpak L, Filipiak KJ, Jaguszewski M. Role of Mask/Respirator Protection Against SARS-CoV-2. Anesth Analg 2020;131:e33.
4. Szarpak L, Smereka J, Filipiak KJ, Ladny JR, Jaguszewski M. Cloth masks versus medical masks for COVID-19 protection. Cardiol J 2020;27:218–9.
5. Chapman K, Dragan KE. Hypercarbia. StatPearls. StatPearls Publishing; 2021. Available from: http://www.ncbi.nlm.nih.gov/books/NBK559154. [Last accessed on 2021 Oct 19].
6. Zeserson E, Goodgame B, Hess JD, Schultz K, Hoon C, Lamb K, et al. Correlation of venous blood gas and pulse oximetry with arterial blood gas in the undifferentiated critically ill patient. J Intensive Care Med 2018;33:176–81.
7. Kim BR, Park SJ, Shin HS, Jung YS, Rim H. Correlation between peripheral venous and arterial blood gas measurements in patients admitted to the intensive care unit:A single-center study. Kidney Res Clin Pract 2013;32:32–8.
8. Awasthi S, Rani R, Malviya D. Peripheral venous blood gas analysis:An alternative to arterial blood gas analysis for initial assessment and resuscitation in emergency and intensive care unit patients. Anesth Essays Res 2013;7:355–8.
9. Pulse-oximetry. ATS Patient education information series. American Thoracic Society. Online version March 2021. Available from: https://www.thoracic.org/patients/patient-resources/resources/pulse-oximetry.pdf.
10. Beder A, Büyükkoçak U, Sabuncuoğlu H, Keskil ZA, Keskil S. Preliminary report on surgical mask induced deoxygenation during major surgery. Neurocir Astur Spain 2008;19:121–6.
11. Schödel J, Ratcliffe PJ. Mechanisms of hypoxia signalling:New implications for nephrology. Nat Rev Nephrol 2019;15:641–59.
12. Choudhury A, Singh M, Khurana DK, Mustafi SM, Ganapathy U, Kumar A, et al. Physiological effects of N95 FFP and PPE in healthcare workers in COVID intensive care unit:A prospective cohort study. Indian J Crit Care Med Peer-Rev Off Publ Indian Soc Crit Care Med 2020;24:1169–73.
13. Spang RP, Pieper K. The tiny effects of respiratory masks on physiological, subjective, and behavioral measures under mental load in a randomized controlled trial. Sci Rep 2021;11:19601.
14. Lässing J, Falz R, Pökel C, Fikenzer S, Laufs U, Schulze A, et al. Effects of surgical face masks on cardiopulmonary parameters during steady state exercise. Sci Rep 2020;10:22363.
15. Lim ECH, Seet RCS, Lee KH, Wilder-Smith EPV, Chuah BYS, Ong BKC. Headaches and the N95 face-mask amongst healthcare providers. Acta Neurol Scand 2006;113:199–202.
16. Smith JD, MacDougall CC, Johnstone J, Copes RA, Schwartz B, Garber GE. Effectiveness of N95 respirators versus surgical masks in protecting health care workers from acute respiratory infection:A systematic review and meta-analysis. CMAJ 2016;188:567–74.
17. Radonovich LJ, Simberkoff MS, Bessesen MT, Brown AC, Cummings DAT, Gaydos CA, et al. N95 Respirators vs medical masks for preventing influenza among health care personnel:A randomized clinical trial. JAMA 2019;322:824–33.
18. Chen Y, Yang Z, Wang J, Gong H. Physiological and subjective responses to breathing resistance of N95 filtering facepiece respirators in still-sitting and walking. Int J Ind Ergon 2016;53:93–101.
19. Roberge RJ, Kim JH, Powell JB, Shaffer RE, Ylitalo CM, Sebastian JM. Impact of low filter resistances on subjective and physiological responses to filtering facepiece respirators. PLoS One 2013;8:e84901.
20. Dhont S, Derom E, Van Braeckel E, Depuydt P, Lambrecht BN. The pathophysiology of 'happy'hypoxemia in COVID-19. Respir Res 2020;21:198.
21. Østergaard L, Gassmann M. Hypoxia, focus hypobaric hypoxia Mooren FC. Encyclopedia of Exercise Medicine in Health and Disease. Springer;2012:428–31.
22. Smith CL, Whitelaw JL, Davies B. Carbon dioxide rebreathing in respiratory protective devices:influence of speech and work rate in full-face masks. Ergonomics 2013;56:781–90.
23. Roberge RJ. Are exhalation valves on N95 filtering facepiece respirators beneficial at low-moderate work rates:An overview. J Occup Environ Hyg 2012;9:617–23.
24. Kim JH, Benson SM, Roberge RJ. Pulmonary and heart rate responses to wearing N95 filtering facepiece respirators. Am J Infect Control 2013;41:24–7.
25. Roberge RJ, Coca A, Williams WJ, Powell JB, Palmiero AJ. Physiological impact of the N95 filtering facepiece respirator on healthcare workers. Respir Care 2010;55:569–77.
26. Kindrick JD, Mole DR. Hypoxic regulation of gene transcription and chromatin:Cause and effect. Int J Mol Sci 2020;21:E8320.
27. Grek CL, Newton DA, Spyropoulos DD, Baatz JE. Hypoxia up-regulates expression of hemoglobin in alveolar epithelial cells. Am J Respir Cell Mol Biol 2011;44:439–47.
28. Watts D, Gaete D, Rodriguez D, Hoogewijs D, Rauner M, Sormendi S, et al. Hypoxia pathway proteins are master regulators of erythropoiesis. Int J Mol Sci 2020;21:8131.
29. Brugniaux JV, Pialoux V, Foster GE, Duggan CTC, Eliasziw M, Hanly PJ, et al. Effects of intermittent hypoxia on erythropoietin, soluble erythropoietin receptor and ventilation in humans. Eur Respir J 2011;37:880–7.
30. Viscor G, Torrella JR, Corral L, Ricart A, Javierre C, Pages T, et al. Physiological and biological responses to short-term intermittent hypobaric hypoxia exposure:from sports and mountain medicine to new biomedical applications. Front Physiol 2018;9:814.
31. Berna N, Arnould T, Remacle J, Michiels C. Hypoxia-induced increase in intracellular calcium concentration in endothelial cells:role of the Na(+)-glucose cotransporter. J Cell Biochem 2001;84:115–31.
32. Agrawal A, Suryakumar G, Rathor R. Role of defective Ca2+signaling in skeletal muscle weakness:Pharmacological implications. J Cell Commun Signal 2018;12:645–59.
33. Shakya KM, Noyes A, Kallin R, Peltier RE. Evaluating the efficacy of cloth facemasks in reducing particulate matter exposure. J Expo Sci Environ Epidemiol 2017;27:352–7.
34. Collins JA, Rudenski A, Gibson J, Howard L, O'Driscoll R. Relating oxygen partial pressure, saturation and content:The haemoglobin–oxygen dissociation curve. Breathe 2015;11:194–201.
35. Kelly AM, Kyle E, McAlpine R. Venous pCO(2) and pH can be used to screen for significant hypercarbia in emergency patients with acute respiratory disease. J Emerg Med 2002;22:15–9.

Blood gas parameters; clinical symptoms; erythropoietin; hypoxia inducible factor; N95-FFR; PPE

Copyright: © 2023 Indian Chest Society