Baseline epidemiologic and physiologic data.

Baseline epidemiologic and physiologic data.</p

Correlation (R- value) between test-retest using 4 different variables to express hypoxic ventilatory response and 2 different variables to express hypercapnic ventilatory response.

<p>Correlation (R- value) between test-retest using 4 different variables to express hypoxic ventilatory response and 2 different variables to express hypercapnic ventilatory response.</p

Hypoxic (HVR) and hypercapnic (HCVR) ventilatory responses in males vs females.

<p>Hypoxic (HVR) and hypercapnic (HCVR) ventilatory responses in males vs females.</p

Analysis of Hypoxic and Hypercapnic Ventilatory Response in Healthy Volunteers

<div><p>Introduction</p><p>A previous study has suggested that the Human Leukocyte Antigen (HLA) allele DQB1*06:02 affects hypoxic ventilatory response (HVR) but not hypercapnic ventilatory response (HCVR) in an Asian population. The current study evaluated the relationship in Caucasians and Asians. In addition we assessed whether gender or polymorphisms in genes participating in the control of breathing affect HVR and HCVR.</p><p>Methods</p><p>A re-breathing system was used to measure HVR and HCVR in 551 young adults (56.8% Caucasians, 30% Asians). HLA-DQB1*06:02 and tagged polymorphisms and coding variants in genes participating in breathing (PHOX2B, GPR4 and TASK2/KCNK5) were analyzed. The associations between HVR/HCVR and HLA-DQB1*06:02, genetic polymorphisms, and gender were evaluated using ANOVA or frequentist association testing with SNPTEST.</p><p>Results</p><p>HVR and gender are strongly correlated. HCVR and gender are not. Mean HVR in women was 0.276±0.168 (liter/minute/%SpO2) compared to 0.429±0.266 (liter/minute/%SpO2) in men, p<0.001 (55.4% higher HVR in men). Women had lower baseline minute ventilation (8.08±2.36 l/m vs. 10.00±3.43l/m, p<0.001), higher SpO2 (98.0±1.3% vs. 96.6±1.7%, p<0.001), and lower EtCO2 (4.65±0.68% vs. 4.82±1.02%, p = 0.025). One hundred and two (18.5%) of the participants had HLA-DQB1*06:02. No association was seen between HLA-DQB1*06:02 and HVR or HCVR. Genetic analysis revealed point wise, uncorrected significant associations between two TASK2/KCNK5 variants (rs2815118 and rs150380866) and HCVR.</p><p>Conclusions</p><p>This is the largest study to date reporting the relationship between gender and HVR/ HCVR and the first study assessing the association between genetic polymorphisms in humans and HVR/HCVR. The data suggest that gender has a large effect on hypoxic breathing response.</p></div

Measurement of ventilatory response to hypercapnia.

<p>Illustration of 2 different methods to calculate the ventilatory response to hypercapnia (HCVR) using the following 2 variables: Hypercapnia-all and Regression _{(Hypercapnia-all)}. Hypercapnia-all is the change in V_e (ΔV_e) between baseline and the end of the study, divided by the reciprocal change in EtCO₂ (ΔEtCO₂) in the following form: HCVR = ΔV_e/ΔCO₂. Regression _{(Hypercapnia-all)} is the slope of regression line of all measurements.</p

Measurement of ventilatory response to hypoxemia.

<p>Illustration of 4 metrics to calculate ventilatory response to hypoxemia (HVR): Hypoxia-all, Hypoxia-90, Regression _(Hypoxia-all) and Regression _(Hypoxia-90). The first two variables were calculated by taking the increase in minute ventilation (ΔV_e) between baseline and maximal hypoxemia (mh) and dividing it by the corresponding change in SpO₂ (ΔSpO₂). Baseline minute ventilation differed for Hypoxia-all and Hypoxia-90. In Hypoxia-all baseline minute ventilation was the minute ventilation at the beginning of the study (bl). In Hypoxia-90 baseline minute ventilation was the minute ventilation measured at 90% saturation (90%SpO₂). Hypoxia-all was calculated using the equation </p><p></p> Whereas, Hypoxia-90 was calculated using the equation <p></p> Linear regression was applied to the measurements. Regression _(Hypoxia-all) used the regression line of all measurements. Regression _(Hypoxia-90) used only measurements done when SpO₂ was 90% or lower.<p></p

Association between Hypoxic and Hypercapnic Ventilatory Responses.

<p>R = 0.392, p<0.001.</p

Correlation between test and re-test of hypoxic (N = 28 participants) and hypercapnic (N = 16 participants) responses.

<p>Correlation between test and re-test of hypoxic (N = 28 participants) and hypercapnic (N = 16 participants) responses.</p

Image_1_Myalgic Encephalomyelitis/Chronic Fatigue Syndrome is common in post-acute sequelae of SARS-CoV-2 infection (PASC): Results from a post-COVID-19 multidisciplinary clinic.JPEG

BackgroundThe global prevalence of PASC is estimated to be present in 0·43 and based on the WHO estimation of 470 million worldwide COVID-19 infections, corresponds to around 200 million people experiencing long COVID symptoms. Despite this, its clinical features are not well-defined.MethodsWe collected retrospective data from 140 patients with PASC in a post-COVID-19 clinic on demographics, risk factors, illness severity (graded as one-mild to five-severe), functional status, and 29 symptoms and principal component symptoms cluster analysis. The Institute of Medicine (IOM) 2015 criteria were used to determine the Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) phenotype.FindingsThe median age was 47 years, 59.0% were female; 49.3% White, 17.2% Hispanic, 14.9% Asian, and 6.7% Black. Only 12.7% required hospitalization. Seventy-two (53.5%) patients had no known comorbid conditions. Forty-five (33.9%) were significantly debilitated. The median duration of symptoms was 285.5 days, and the number of symptoms was 12. The most common symptoms were fatigue (86.5%), post-exertional malaise (82.8%), brain fog (81.2%), unrefreshing sleep (76.7%), and lethargy (74.6%). Forty-three percent fit the criteria for ME/CFS, majority were female, and obesity (BMI > 30 Kg/m2) (P = 0.00377895) and worse functional status (P = 0.0110474) were significantly associated with ME/CFS.InterpretationsMost PASC patients evaluated at our clinic had no comorbid condition and were not hospitalized for acute COVID-19. One-third of patients experienced a severe decline in their functional status. About 43% had the ME/CFS subtype.</p

Data_Sheet_1_Myalgic Encephalomyelitis/Chronic Fatigue Syndrome is common in post-acute sequelae of SARS-CoV-2 infection (PASC): Results from a post-COVID-19 multidisciplinary clinic.PDF

BackgroundThe global prevalence of PASC is estimated to be present in 0·43 and based on the WHO estimation of 470 million worldwide COVID-19 infections, corresponds to around 200 million people experiencing long COVID symptoms. Despite this, its clinical features are not well-defined.MethodsWe collected retrospective data from 140 patients with PASC in a post-COVID-19 clinic on demographics, risk factors, illness severity (graded as one-mild to five-severe), functional status, and 29 symptoms and principal component symptoms cluster analysis. The Institute of Medicine (IOM) 2015 criteria were used to determine the Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) phenotype.FindingsThe median age was 47 years, 59.0% were female; 49.3% White, 17.2% Hispanic, 14.9% Asian, and 6.7% Black. Only 12.7% required hospitalization. Seventy-two (53.5%) patients had no known comorbid conditions. Forty-five (33.9%) were significantly debilitated. The median duration of symptoms was 285.5 days, and the number of symptoms was 12. The most common symptoms were fatigue (86.5%), post-exertional malaise (82.8%), brain fog (81.2%), unrefreshing sleep (76.7%), and lethargy (74.6%). Forty-three percent fit the criteria for ME/CFS, majority were female, and obesity (BMI > 30 Kg/m2) (P = 0.00377895) and worse functional status (P = 0.0110474) were significantly associated with ME/CFS.InterpretationsMost PASC patients evaluated at our clinic had no comorbid condition and were not hospitalized for acute COVID-19. One-third of patients experienced a severe decline in their functional status. About 43% had the ME/CFS subtype.</p