Purpose Although the prevalence of community-acquired respiratory bacterial coinfection upon hospital admission in patients with coronavirus disease 2019 (COVID-19) has been reported to be < 5%, almost three-quarters of patients received antibiotics. We aim to investigate whether procalcitonin (PCT) or C-reactive protein (CRP) upon admission could be helpful biomarkers to identify bacterial coinfection among patients with COVID-19 pneumonia. Methods We carried out a multicentre, observational cohort study including consecutive COVID-19 patients admitted to 55 Spanish intensive care units (ICUs). The primary outcome was to explore whether PCT or CRP serum levels upon hospital admission could predict bacterial coinfection among patients with COVID-19 pneumonia. The secondary outcome was the evaluation of their association with mortality. We also conducted subgroups analyses in higher risk profile populations. Results Between 5 February 2020 and 21 December 2021, 4076 patients were included, 133 (3%) of whom presented bacterial coinfection. PCT and CRP had low area under curve (AUC) scores at the receiver operating characteristic (ROC) curve analysis [0.57 (95% confidence interval (CI) 0.51–0.61) and 0.6 (95% CI, 0.55–0.64), respectively], but high negative predictive values (NPV) [97.5% (95% CI 96.5–98.5) and 98.2% (95% CI 97.5–98.9) for PCT and CRP, respectively]. CRP alone was associated with bacterial coinfection (OR 2, 95% CI 1.25–3.19; p = 0.004). The overall 15, 30 and 90 days mortality had a higher trend in the bacterial coinfection group, but without significant difference. PCT ≥ 0.12 ng/mL was associated with higher 90 days mortality. Conclusion Our study suggests that measurements of PCT and CRP, alone and at a single time point, are not useful for ruling in or out bacterial coinfection in viral pneumonia by COVID-19.

We investigated the effectiveness of Virtual Reality (VR) and three-dimensional (3D)-printed mannequins in replicating stress levels during pericardiocentesis training and compared their impact on learners’ emotional and physiological responses. A secondary analysis explored how demographic, lifestyle, and academic factors influence stress responses, providing deeper insights into the variability of physiological markers among medical trainees. We conducted a randomized study involving 108 final-year medical students (mean age: 23.6 years, 87% female) to compare stress responses during pericardiocentesis training using a 3D-printed mannequin and VR model as simulation modalities, both custom-designed by the research team. We investigated the influence of demographic, lifestyle, and academic factors, including medication use and perceived stress, on heart rate variability (HRV) markers. The two simulations showed similar HRV parameters, validating their effectiveness in replicating physiological stress levels associated with clinical scenarios. Secondary analysis revealed significant associations between the low frequency/high frequency ratio and family income and a trend-level effect for anxiolytic use, suggesting an interplay of socioeconomic and pharmacological factors on stress responses. Age and sex interacted significantly with HRV metrics, with younger students demonstrating heightened sympathetic activation. Our results suggest that the incorporation of VR into medical training programs may enhance learning outcomes and accessibility.

Background: Training in invasive procedures like pericardiocentesis is a critical component of medical education but poses significant challenges due to its complexity and infrequent clinical application. Pericardiocentesis is an invasive procedure used to remove excess pericardial fluid from the pericardial sac, typically performed to relieve cardiac tamponade. It requires precise anatomical knowledge, ultrasound guidance, and dexterous needle placement to minimize complications. Simulation-based training, particularly with innovative technologies such as 3D printing and virtual reality (VR), offers accessible and cost-effective solutions. This study compared the effectiveness of 3D-printed mannequins and VR simulations in pericardiocentesis training, focusing on learning outcomes, stress responses, and cognitive load. Methods: Thirty-five final-year medical students participated in this quasi-experimental study, receiving training with both models in separate sessions under the supervision of two experienced instructors. Learning outcomes were evaluated using the objective structured clinical examination (OSCE), while stress responses were assessed via heart rate variability (HRV), a measure of fluctuations in heart rate that reflect stress levels. Perceived cognitive load was measured with the NASA Task Load Index (NASA-TLX). Wilcoxon signed-rank and Friedman tests were used for statistical analysis. Results: The 3D-printed mannequin outperformed VR in tasks requiring fine motor skills, such as material handling and drainage placement (Z = − 2.56, p < 0.05; Z = − 2.34, p < 0.05). VR training, however, was associated with lower mental demand and effort (Z = − 2.147, p < 0.05; Z = − 2.356, p < 0.05). Biometric analysis indicated higher stress levels during mannequin-based training (SD1/SD2, chi-square = 14.157, p < 0.01), reflecting its closer replication of real-life clinical conditions. Conclusions: Both 3D-printed mannequins and VR simulations serve as effective tools for pericardiocentesis training, each offering unique advantages. The 3D-printed mannequin supports tactile skill acquisition, while VR enhances cognitive engagement in a low-stress environment. A hybrid approach—beginning with VR and progressing to 3D-printed models—maximizes training outcomes, particularly in resource-limited settings, where affordable simulation tools can improve access to medical education.

Background: Virtual reality (VR) is increasingly used in medical education, providing immersive environments for training in high-risk procedures such as pericardiocentesis. This lifesaving procedure requires technical precision and induces cognitive and physiological stress. Evaluating both usability and stress responses in a VR-based pericardiocentesis simulation is essential. Heart rate variability (HRV) serves as an objective stress marker, while prior VR experience may influence usability and stress perception. Objectives: This study aimed to assess the usability of a VR-based pericardiocentesis simulation, examine the relationship between usability perceptions and physiological stress (HRV), and determine the impact of prior VR experience on usability scores and stress responses. Methods: A total of 119 final-year medical students participated in a VR pericardiocentesis simulation. Usability was evaluated using the System Usability Scale (SUS), the Post-Study System Usability Questionnaire, the Presence Questionnaire, and the Simulator Sickness Questionnaire. Physiological stress was assessed through HRV parameters, including the root-mean-square of successive differences (rMSSDs), percentage of differences greater than 50 ms (PNN50), low-frequency to high-frequency ratio, and nonlinear HRV indices (SD1/SD2 ratio, Poincaré area). Statistical analyses included descriptive statistics, Spearman correlations, and Mann-Whitney U tests to explore relationships between usability, stress, and prior VR experience. Results: The VR simulation received a mean SUS score of 75.00 (SD 6.41; 95% CI 73.42‐76.58), exceeding the general usability threshold of 68 (P=.002). The mean Post-Study System Usability Questionnaire score of 2.92 (SD 1.83; 95% CI 2.55‐3.29) indicated moderate satisfaction, while the mean Presence Questionnaire score of 109.46 (SD 9.12; 95% CI 107.88‐111.04) reflected strong immersion. Simulator sickness symptoms were mild (mean Simulator Sickness Questionnaire score 12.43, SD 15.41; 95% CI 9.28‐15.58), although novice users reported significantly higher nausea levels (P=.02). Physiological stress analysis revealed a mean rMSSD of 281.27 (SD 98.99; 95% CI 259.45‐303.09) ms and PNN50 of 56.85% (SD 19.70%; 95% CI 52.23%‐61.47%), indicating moderate autonomic balance. A significant negative correlation was observed between HRV parameters (rMSSD and PNN50) and simulator sickness (P=.04; Spearman ρ=−0.23), suggesting that higher physiological stress was associated with increased simulator sickness symptoms. Prior VR experience was linked to higher usability scores (SUS +5.2; 95% CI 3.12-7.28; P=.03) and lower simulator sickness symptoms (P=.02) but did not significantly affect HRV markers. Conclusions: VR-based simulations for high-risk medical procedures are effective training tools with high usability (SUS=75) and strong immersion. Simulator sickness correlated with physiological stress, emphasizing the need for design refinements to improve user comfort. Prior VR experience improved usability and reduced simulator sickness but did not significantly impact HRV markers. Future research should refine VR interfaces to balance immersion with minimized cognitive and physical discomfort.

Background: Intensive Care Units (ICUs) are recognized as highly demanding environments that significantly contribute to stress and burnout among nursing staff. Despite increasing concern over burnout in healthcare, the relationship between physiological stress indicators, such as Heart Rate Variability (HRV), and psychometric assessments has not been thoroughly explored in this setting. Objective: This pilot study aimed to evaluate the relationship between HRV metrics and psychometric assessments of stress and anxiety in ICU nursing staff. Additionally, it explored the influence of shift type, shift duration, demographic factors, and lifestyle habits on these stress indicators. Methods: An observational cross-sectional pilot study was conducted with 24 ICU healthcare professionals at a University Hospital in Madrid, Spain. HRV data were collected under controlled conditions, with measurements taken at the beginning and end of shifts. Psychometric assessments were conducted using the State-Trait Anxiety Inventory (STAI), Perceived Stress Scale (PSS-14), Nursing Stress Scale (NSS) and a Visual Analogue Scale for Stress (VASS). Non-parametric statistical tests were used to analyze correlations between HRV metrics, psychometric scores, and demographic/lifestyle variables. Results: Significant negative correlations were observed between HRV metrics and perceived stress levels, particularly between the Low-Frequency to High-Frequency (LF/HF) ratio and stress measures. Night and extended shifts were associated with elevated stress, as indicated by lower HRV and higher psychometric stress scores. These findings suggest that shift type and duration significantly influence stress levels in ICU nursing staff. Conclusion: This pilot study highlights the potential of HRV as an objective measure of stress in ICU nursing staff, with significant correlations observed between HRV metrics and psychometric assessments. The findings suggest that HRV could be a valuable tool for monitoring stress in real time and identifying individuals at risk of burnout. However, further research with larger samples and a longitudinal approach is needed to validate these results and explore their implications for occupational health practices in ICU settings.