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Less than 7% of the world's population live at an altitude above 1500 m. Yet, as many as 67% of medalists in the 2020 men's and women's Olympic marathon, and 100% of medalists in the 2020 men's and women's Olympic 5000 m track race may have been born or raised above this otherwise rare threshold. As a possible explanation, research spanning nearly a quarter of a century demonstrates that indigenous highlanders exhibit pulmonary adaptations distinct from their lowland counterparts. These adaptations may then promote endurance performance. Indeed, healthy indigenous highlanders often exhibit a larger aerobic exercise capacity compared to sea‐level residents who travel to high altitude. However, questions remain on whether high‐altitude birth is advantageous for sea‐level competitions. In this review, we ask whether being born at a high altitude generates an ergogenic advantage for endurance performance in the Summer Olympics—a venue that is generally held at sea level. In so doing, we distinguish between three groups of high‐altitude residents: (i) the indigenous highlander, (ii) the highland newcomer, and (iii) the highland sojourner. Concentrating specifically on altitude‐induced alterations to pulmonary physiology beginning in the perinatal period, we propose that if altitude‐related maladaptations are avoided, genomic and developmental alterations accompanying highland birth may present benefits for endurance competitions at sea level. What is the topic of this review? Whether being born at high altitude contributes to endurance exercise performance at sea level. Does highland birth set the stage for lowland success? What advances does it highlight? The physiological effects and ergogenic potential of highland birth, especially as it pertains to the respiratory system. Possible (mal)adaptations evoked by perinatal hypoxia in various groups of highlanders and the influence of these pulmonary‐related alterations on endurance performance at sea level, for example, in the Summer Olympics.

The application of artificial intelligence (AI) has provided new capabilities to develop advanced medical monitoring sensors for detection of clinical conditions of low circulating blood volume such as hemorrhage. The purpose of this study was to compare for the first time the discriminative ability of two machine learning (ML) algorithms based on real-time feature analysis of arterial waveforms obtained from a non-invasive continuous blood pressure system (Finometer®) signal to predict the onset of decompensated shock: the compensatory reserve index (CRI) and the compensatory reserve metric (CRM). One hundred ninety-one healthy volunteers underwent progressive simulated hemorrhage using lower body negative pressure (LBNP). The least squares means and standard deviations for each measure were assessed by LBNP level and stratified by tolerance status (high vs. low tolerance to central hypovolemia). Generalized Linear Mixed Models were used to perform repeated measures logistic regression analysis by regressing the onset of decompensated shock on CRI and CRM. Sensitivity and specificity were assessed by calculation of receiver-operating characteristic (ROC) area under the curve (AUC) for CRI and CRM. Values for CRI and CRM were not distinguishable across levels of LBNP independent of LBNP tolerance classification, with CRM ROC AUC (0.9268) being statistically similar (p = 0.134) to CRI ROC AUC (0.9164). Both CRI and CRM ML algorithms displayed discriminative ability to predict decompensated shock to include individual subjects with varying levels of tolerance to central hypovolemia. Arterial waveform feature analysis provides a highly sensitive and specific monitoring approach for the detection of ongoing hemorrhage, particularly for those patients at greatest risk for early onset of decompensated shock and requirement for implementation of life-saving interventions.

We describe here a novel protocol that sequentially combines venous followed by arterial occlusions to determine muscle blood flow and O 2 uptake from a single measurement point using near-infrared spectroscopy (NIRS) during handgrip exercise. NIRS data were obtained from the flexor digitorum superficialis (FDS) muscle on the dominant arm of 15 young, healthy adults (3 women; 26 ± 7 years; 78.6 ± 9.1 kg). Participants completed a series of 15-s static handgrip contractions at 20, 40 and 60% of maximal voluntary contraction (MVC) immediately followed by either a: (i) venous occlusion (VO); (ii); arterial occlusion (AO); or venous then arterial occlusion (COMBO). Each condition was repeated 3 times for each exercise-intensity. The concordance correlation coefficient (CCC) and robust linear mixed effects modeling were used to determine measurement agreement between vascular occlusion conditions. FDS muscle blood flow ( Q ˙ FDS ) and conductance ( C FDS ) demonstrated strong absolute agreement between VO and COMBO trials from rest up to 60%MVC, as evidenced by high values for CCC (> 0.82) and a linear relationship between conditions that closely approximated the line-of-identity (perfect agreement). Conversely, although FDS muscle O 2 uptake ( V ˙ O 2 FDS ) displayed “substantial” to “near perfect” agreement between methods across exercise intensities (i.e., CCC > 0.80), there was a tendency for COMBO trials to underestimate V ˙ O 2 FDS by up to 7%. These findings indicate that the COMBO method provides valid estimates of Q ˙ FDS and, to a slightly lesser extent, V ˙ O 2 FDS at rest and during static handgrip exercise up to 60%MVC. Practical implications and suggested improvements of the method are discussed.

Respiratory epithelium in the conducting airways of the human body is one of the primary targets of SARS-CoV-2 infection, however, there is a paucity of studies describing the association between COVID-19 and physical characteristics of the conducting airways. To better understand the pathophysiology of COVID-19 on the size of larger conducting airways, we determined the luminal area of the central airways in patients with a history of COVID-19 compared to a height-matched cohort of controls using a case–control study design. Using three-dimensional reconstruction from low-dose high-resolution computed tomography, we retrospectively assessed airway luminal cross-sectional area in 114 patients with COVID-19 (66 females, 48 males) and 114 healthy, sex- and height-matched controls (66 females, 48 males). People with a history of smoking, cardiopulmonary disease, or a body mass index greater than 40 kg·m −2 were excluded. Luminal areas of seven conducting airways were analyzed, including trachea, left and right main bronchus, intermediate bronchus, left and right upper lobe, and left lower lobe. For the central conducting airways, luminal area was ~ 15% greater patients with COVID-19 compared to matched controls ( p  < 0.05). Among patients with COVID-19, there were generally no differences in the luminal areas of the conducting airways between hospitalized patients compared to patients who did not require COVID-19-related hospitalization. Our findings suggest that males and females with COVID-19 have pathologically larger conducting airway luminal areas than healthy, sex- and height-matched controls.

Occult hemorrhages after trauma can be present insidiously, and if not detected early enough can result in patient death. This study evaluated a hemorrhage model on 18 human subjects, comparing the performance of traditional vital signs to multiple off-the-shelf non-invasive biomarkers. A validated lower body negative pressure (LBNP) model was used to induce progression towards hypovolemic cardiovascular instability. Traditional vital signs included mean arterial pressure (MAP), electrocardiography (ECG), plethysmography (Pleth), and the test systems utilized electrical impedance via commercial electrical impedance tomography (EIT) and multifrequency electrical impedance spectroscopy (EIS) devices. Absolute and relative metrics were used to evaluate the performance in addition to machine learning-based modeling. Relative EIT-based metrics measured on the thorax outperformed vital sign metrics (MAP, ECG, and Pleth) achieving an area-under-the-curve (AUC) of 0.99 (CI 0.95–1.00, 100% sensitivity, 87.5% specificity) at the smallest LBNP change (0–15 mmHg). The best vital sign metric (MAP) at this LBNP change yielded an AUC of 0.6 (CI 0.38–0.79, 100% sensitivity, 25% specificity). Out-of-sample predictive performance from machine learning models were strong, especially when combining signals from multiple technologies simultaneously. EIT, alone or in machine learning-based combination, appears promising as a technology for early detection of progression toward hemodynamic instability.

Convalescent plasma has been used worldwide to treat patients hospitalized with coronavirus disease 2019 (COVID-19) and prevent disease progression. Despite global usage, uncertainty remains regarding plasma efficacy, as randomized controlled trials (RCTs) have provided divergent evidence regarding the survival benefit of convalescent plasma. Here, we argue that during a global health emergency, the mosaic of evidence originating from multiple levels of the epistemic hierarchy should inform contemporary policy and healthcare decisions. Indeed, worldwide matched-control studies have generally found convalescent plasma to improve COVID-19 patient survival, and RCTs have demonstrated a survival benefit when transfused early in the disease course but limited or no benefit later in the disease course when patients required greater supportive therapies. RCTs have also revealed that convalescent plasma transfusion contributes to improved symptomatology and viral clearance. To further investigate the effect of convalescent plasma on patient mortality, we performed a meta-analytical approach to pool daily survival data from all controlled studies that reported Kaplan–Meier survival plots. Qualitative inspection of all available Kaplan–Meier survival data and an aggregate Kaplan–Meier survival plot revealed a directionally consistent pattern among studies arising from multiple levels of the epistemic hierarchy, whereby convalescent plasma transfusion was generally associated with greater patient survival. Given that convalescent plasma has a similar safety profile as standard plasma, convalescent plasma should be implemented within weeks of the onset of future infectious disease outbreaks.

Introduction It is unknown if there are limb differences in vascular function during prolonged sitting. Purpose This study was designed to test whether the effects of prolonged sitting on brachial artery (BA) and the superficial femoral artery (SFA) are similar. Methods Twelve men (24.2 ± 4 yrs.) participated in a 3 hr prolonged sitting trial (SIT). SFA and BA flow mediated dilation (FMD) and respective flow patterns were measured at baseline, 1 hr, 2 hr and 3 hr. Results By a one-way ANOVA there was a significant decline in SFA FMD during 3 hrs of SIT (p < 0.001). Simultaneously, there was a significant decline in antegrade (p = 0.04) and mean (0.037) shear rates. By a one way ANOVA there were no significant differences in BA FMD during 3 hrs of sitting. There were no changes in the shear rates in the BA except for a significant decrease in antegrade shear rate (p = 0.029) and a significant increase in oscillatory shear index (p = 0.034) during 3 hrs of sitting. Furthermore, there was no correlation between BA and SFA FMD measurements. Conclusion Three hours of sitting resulted in impaired SFA FMD but not BA FMD. Although 3 hours of sitting did not impair BA FMD, it impaired shear patterns in the BA.

Oxygen transport from the lungs to peripheral tissue is dependent on the affinity of hemoglobin for oxygen. Recent experimental data have suggested that the maximum human capacity for oxygen uptake and utilization (V̇O2max) at sea level and altitude (~3000 m) is sensitive to alterations in hemoglobin‐oxygen affinity. However, the effect of such alterations on V̇O2max at extreme altitudes remains largely unknown due to the rarity of mutations affecting hemoglobin‐oxygen affinity. This work uses a mathematical model that couples pulmonary oxygen uptake with systemic oxygen utilization under conditions of high metabolic demand to investigate the effect of hemoglobin‐oxygen affinity on V̇O2max as a function of altitude. The model includes the effects of both diffusive and convective limitations on oxygen transport. Pulmonary oxygen uptake is calculated using a spatially‐distributed model that accounts for the effects of hematocrit and hemoglobin‐oxygen affinity. Systemic oxygen utilization is calculated assuming Michaelis–Menten kinetics. The pulmonary and systemic model components are solved iteratively to compute predicted arterial and venous oxygen levels. Values of V̇O2max are predicted for several values of hemoglobin‐oxygen affinity and hemoglobin concentration based on data from humans with hemoglobin mutations. The model predicts that increased hemoglobin‐oxygen affinity leads to increased V̇O2max at altitudes above ~4500 m.

Interstitial lung disease (ILD) encompasses pulmonary disorders characterized by chronic inflammation and fibrosis that disrupt pulmonary gas exchange. While ILD‐related changes in the lung parenchyma are well‐documented, less is known about how ILD affects luminal area within the large conducting airways. This retrospective, case–control study tested the hypothesis that patients with ILD would have greater large conducting airway luminal areas than healthy matched controls. Three‐dimensional reconstructions of computed tomography images were used to quantify airway luminal areas in patients with ILD (n = 82; 54% female) and healthy controls matched for age, sex, and height. Patients with ILD had 16%–22% greater airway luminal areas across all seven measured large conducting airways compared to controls (all p < 0.001). Among patients with ILD, males had 17%–34% greater height‐normalized airway luminal areas than females (all p < 0.05). These data provide evidence that ILD is associated with greater large conducting airway luminal area, even when matched for key demographic factors. Consistent with observations in health, males with ILD exhibited greater height‐normalized airway size than females. These findings offer new insight into airway remodeling in ILD and highlight potential sex differences in airway luminal area.

Treatment of patients with COVID-19 using convalescent plasma from recently recovered patients has been shown to be safe, but the time course of change in clinical status following plasma transfusion in relation to baseline disease severity has not yet been described. We analyzed short, descriptive daily reports of patient status in 7,180 hospitalized recipients of COVID-19 convalescent plasma in the Mayo Clinic Expanded Access Program. We assessed, from the day following transfusion, whether the patient was categorized by his or her physician as better, worse or unchanged compared to the day before, and whether, on the reporting day, the patient received mechanical ventilation, was in the ICU, had died or had been discharged. Most patients improved following transfusion, but clinical improvement was most notable in mild to moderately ill patients. Patients classified as severely ill upon enrollment improved, but not as rapidly, while patients classified as critically ill/end-stage and patients on ventilators showed worsening of disease status even after treatment with convalescent plasma. Patients age 80 and over showed little or no clinical improvement following transfusion. Clinical status at the time of convalescent plasma treatment and age appear to be the primary factors in determining the therapeutic effectiveness of COVID-19 convalescent plasma among hospitalized patients.