The ongoing COVID-19 pandemic requires wearing face masks in many areas of our daily life; hence, the potential side effects of mask use are discussed. Therefore, the present study explores whether wearing a medical face mask (MedMask) affects physical working capacity (PWC). Secondary, the influence of a filtering facepiece mask with exhalation valve class 2 (FFP2exhal) and a cotton fabric mask (community mask) on PWC was also investigated. Furthermore, corresponding physiological and subjective responses when wearing face masks as well as a potential moderating role of subjects' individual cardiorespiratory fitness and sex on face mask effects were analyzed. Thirty-nine subjects (20 males, 19 females) with different cardiorespiratory fitness levels participated in a standardized submaximal bicycle ergometer protocol using either a MedMask, FFP2exhal, community mask, or no mask (control) on four days, in randomized order. PWC130 and PWC150 as the mechanical load at the heart rates of 130 and 150 beats per minute were measured as well as transcutaneous carbon dioxide partial pressure, saturation of peripheral capillary oxygen, breathing frequency, blood pressure, perceived respiratory effort, and physical exhaustion. Using the MedMask did not lead to changes in PWC or physiological response compared to control. Neither appeared changes exceeding normal ranges when the FFP2exhal or community mask was worn. Perceived respiratory effort was up to one point higher (zero-to-ten Likert scale) when using face masks ( < 0.05) compared to control. Sex and cardiorespiratory fitness were not factors influencing the effects of the masks. The results of the present study provide reason to believe that wearing face masks for infection prevention during the COVID-19 pandemic does not pose relevant additional physical demands on the user although some more respiratory effort is required.
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http://dx.doi.org/10.3390/ijerph19031063 | DOI Listing |
Anesth Analg
February 2025
Department of Anesthesia, Critical Care and Pain Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts.
Background: Several health care networks have fully adopted second-generation supraglottic airway (SGA) i-gel. Real-world evidence of enhanced patient safety after such practice change is lacking. We hypothesized that the implementation of i-gel compared to the previous LMA®-Unique™ would be associated with a lower risk of airway-related safety events.
View Article and Find Full Text PDFHeliyon
January 2025
Radiology, Department of Surgical Sciences, Uppsala University, Uppsala, SE-75185, Sweden.
: Accurate tumor detection and quantification are important for optimized therapy planning and evaluation. Total tumor burden is also an appealing biomarker for clinical trials. Manual examination and annotation of oncologic PET/CT is labor-intensive and demands a high level of expertise.
View Article and Find Full Text PDFACS Sens
January 2025
School of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Republic of Korea.
Bioelectronic face masks can easily collect biomarkers in saliva, in which free cortisol is abundant. However, conventional bioelectronic face masks involve significant challenges in terms of permeability and inhalation due to their nonpermeable film-type structure. Herein, we introduce a flexible and permeable nanomesh-based wearable biosensor designed for bioelectronic face masks that monitor cortisol levels.
View Article and Find Full Text PDFNative joint septic arthritis (SA) is a severe, potentially life-threatening condition characterized by the invasion of synovial fluid and membrane by pathogens, most commonly bacteria. The rising frequency of intra-articular procedures such as joint aspirations and injections has led to increased concern regarding iatrogenic septic arthritis. This mini-review aims to summarize current understanding of the incidence, risk factors, bacterial etiology, and strategies for preventing SA associated with intra-articular procedures.
View Article and Find Full Text PDFSensors (Basel)
December 2024
School of Software Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
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