Analysis of immunization time, amplitude, and adverse events of seven different vaccines against SARS-CoV-2 across four different countries

BackgroundScarce information exists in relation to the comparison of seroconversion and adverse events following immunization (AEFI) with different SARS-CoV-2 vaccines. Our aim was to correlate the magnitude of the antibody response to vaccination with previous clinical conditions and AEFI.MethodsA multicentric comparative study where SARS-CoV-2 spike 1-2 IgG antibodies IgG titers were measured at baseline, 21-28 days after the first and second dose (when applicable) of the following vaccines: BNT162b2 mRNA, mRNA-1273, Gam-COVID-Vac, Coronavac, ChAdOx1-S, Ad5-nCoV and Ad26.COV2. Mixed model and Poisson generalized linear models were performed.ResultsWe recruited 1867 individuals [52 (SD 16.8) years old, 52% men]. All vaccines enhanced anti-S1 and anti-S2 IgG antibodies over time (p<0.01). The highest increase after the first and second dose was observed in mRNA-1273 (p<0.001). There was an effect of previous SARS-CoV-2 infection; and an interaction of age with previous SARS-CoV-2 infection, Gam-COVID-Vac and ChAdOx1-S (p<0.01). There was a negative correlation of Severe or Systemic AEFI (AEs) of naïve SARS-CoV-2 subjects with age and sex (p<0.001); a positive interaction between the delta of antibodies with Gam-COVID-Vac (p=0.002). Coronavac, Gam-COVID-Vac and ChAdOx1-S had less AEs compared to BNT162b (p<0.01). mRNA-1273 had the highest number of AEFIs. The delta of the antibodies showed an association with AEFIs in previously infected individuals (p<0.001).ConclusionsThe magnitude of seroconversion is predicted by age, vaccine type and SARS-CoV-2 exposure. AEs are correlated with age, sex, and vaccine type. The delta of the antibody response only correlates with AEs in patients previously exposed to SARS-CoV-2.Registration numberClinicalTrials.gov, identifier NCT05228912

Effect of Heterologous Vaccination Regimen with Ad5-nCoV CanSinoBio and BNT162b2 Pfizer in SARS-CoV-2 IgG Antibodies Titers

The efficacy of one dose Ad5-nCoV has been concerning. This study aimed to evaluate the effect of a single dose BNT162b2 in individuals after a completed Ad5-nCoV vaccination regiment compared to a group without this boost measuring SARS-CoV-2 Spike 1–2 IgG antibodies in plasma. This observational study included a subgroup analysis of patients who were immunized with Ad5-nCoV in a northern city of Mexico. During follow-up, some patients self-reported having received a BNT162b2 booster. We report baseline IgG levels, 21–28 days after the Ad5-nCoV dose, three months, and an additional 21–28 days after BNT162b2 (four months after Ad5-nCoV). Seventeen patients, age 40 (16), 52.9% men, were analyzed. We created four groups: G1 and G2 refer to patients without a history of SARS-CoV-2 infection, vaccinated with Ad5-nCoV and Ad5-nCoV/BNT162b2 (n = 4 and n = 6), respectively; G3 and G4 included patients with a history of SARS-CoV-2 infection and immunized with Ad5-nCoV and Ad5-nCoV/BNT162b2 (n = 5 and n = 2), respectively. The Ad5-nCoV/BNT162b2 protocol reported higher antibody titers after 21–28 days. Median (IQR) values were: G1 46.7 (-), G2 1077.5 (1901), G3 1158.5 (2673.5), and G4 2090 (-) (p < 0.05). Headache and pain at injection site were the most frequent adverse reactions associated with Ad5-nCoV (n = 10, 83%) and BNT162b2 (n = 5, 83.3%), respectively. Patients receiving BNT162b2 after Ad5-nCoV had higher SARS-CoV-2 spike 1–2 IgG antibody titers and had no severe adverse reactions

Risk of positive screening for anorexia nervosa, bulimia nervosa and night eating syndrome and associated risk factors in medical fellows in Northeastern Mexico: a multicenter study

Abstract Background Eating disorders and food ingestion (EDs) are serious mental illnesses with a higher prevalence in young adults, with difficult diagnoses that cause serious morbidity and mortality problems. There is not much information about the risk of positive screening for EDs, specifically, anorexia nervosa (AN) and bulimia nervosa (BN) and night eating syndrome (NES) in undergraduate medical interns (UMI) and medical residents (MR) in Mexico. Aim To determine the risk of AN, BN and NES and to determine the risk factors of such conditions such as age, body mass index (BMI) and gender of MR and UMI with AN/BN and NES at four private hospitals in northeastern Mexico. Methods A cross-sectional, descriptive, non-randomized survey in MR and UMI in four hospitals in Northeastern Mexico was conducted using an electronic questionnaire that included: informed consent signature, SCOFF questionnaire for AN and BN screening, NES questionnaire. Also, a survey on general sociodemographic data of each participant was included. Chi-square test and a logistic regression model were computed for analyses. Results The population included a total of 129 MR and UMI. It was observed that 48.8% were positive for AN or BN and 32.6% were positive for the NES. There was no difference between age, sex, BMI, or medical specialty (if they were MR); however, MR from the first year had a higher risk of AN or BN (OR 23.7, 95% CI 1.181–475.266). Conclusions There was a higher risk of positive screening for AN or BN and NES in UMI and MR in our population. In the case of MR, those in first year have a higher risk of AN and BN. Timely diagnosis and treatment are mandatory in this population

Effect of Vitamin D3 Supplementation vs. Dietary–Hygienic Measures on SARS-CoV-2 Infection Rates in Hospital Workers with 25-Hydroxyvitamin D3 [25(OH)D3] Levels ≥20 ng/mL

Background: There is scant information on the effect of supplementation with vitamin D3 in SARS-CoV-2 infection cases when patient 25-hydroxyvitamin D3 [25(OH)D3] levels are between 20–100 ng/mL. We aimed to evaluate the effect of supplementation with vitamin D3 vs. dietary–hygienic measures on the SARS-CoV-2 infection rate in participants with serum 25(OH)D3 levels ≥20 ng/mL. Methods: This study was quasi-experimental. We invited hospital workers with 25(OH)D3 levels between 20–100 ng/mL and no previous SARS-CoV-2 infection. They were randomized as follows: treatment options were a) vitamin D3 supplementation (52,000 IU monthly, G1) or b) dietary–hygienic measures (G2). We conducted a 3- to 6-month follow-up of SARS-CoV-2 infections. Participants with 25(OH)D3 levels <20 ng/mL were also analyzed. We divided these latter participants depending on whether they were supplemented (G3) or not (G4). Results: We analyzed 198 participants, with an average age of 44.4 (SD 9) years, and 130 (65.7%) were women. G1 had fewer cases of SARS-CoV-2 infection than G2 after a follow-up of 3- to 6-months (p < 0.05). There were no differences between G3 and G4 at the 3- and 6-month follow-up cutoff points (p > 0.05). Using a mixed effect Cox regression analysis in the 164 participants that completed six months of follow-up, vitamin D3 supplementation appeared to act as a protective factor against SARS-CoV-2 infection (HR 0.21, p = 0.008) in G1 and G2. None of the participants treated with the supplementation doses had serum 25(OH)D3 levels >100 ng/mL. Conclusions: Vitamin D3 supplementation in participants with 25(OH)D3 levels between 20–100 ng/mL have a lower rate of SARS-CoV-2 infection compared with the use of dietary–hygienic measures at six months follow-up

Effect of Vitamin D₃ Supplementation vs. Dietary–Hygienic Measures on SARS-CoV-2 Infection Rates in Hospital Workers with 25-Hydroxyvitamin D3 [25(OH)D3] Levels ≥20 ng/mL

Background: There is scant information on the effect of supplementation with vitamin D3 in SARS-CoV-2 infection cases when patient 25-hydroxyvitamin D3 [25(OH)D3] levels are between 20–100 ng/mL. We aimed to evaluate the effect of supplementation with vitamin D3 vs. dietary–hygienic measures on the SARS-CoV-2 infection rate in participants with serum 25(OH)D3 levels ≥20 ng/mL. Methods: This study was quasi-experimental. We invited hospital workers with 25(OH)D3 levels between 20–100 ng/mL and no previous SARS-CoV-2 infection. They were randomized as follows: treatment options were a) vitamin D3 supplementation (52,000 IU monthly, G1) or b) dietary–hygienic measures (G2). We conducted a 3- to 6-month follow-up of SARS-CoV-2 infections. Participants with 25(OH)D3 levels Results: We analyzed 198 participants, with an average age of 44.4 (SD 9) years, and 130 (65.7%) were women. G1 had fewer cases of SARS-CoV-2 infection than G2 after a follow-up of 3- to 6-months (p p > 0.05). Using a mixed effect Cox regression analysis in the 164 participants that completed six months of follow-up, vitamin D3 supplementation appeared to act as a protective factor against SARS-CoV-2 infection (HR 0.21, p = 0.008) in G1 and G2. None of the participants treated with the supplementation doses had serum 25(OH)D3 levels >100 ng/mL. Conclusions: Vitamin D3 supplementation in participants with 25(OH)D3 levels between 20–100 ng/mL have a lower rate of SARS-CoV-2 infection compared with the use of dietary–hygienic measures at six months follow-up

Improvement of electrocardiographic diagnostic accuracy of left ventricular hypertrophy using a Machine Learning approach.

The electrocardiogram (ECG) is the most common tool used to predict left ventricular hypertrophy (LVH). However, it is limited by its low accuracy (<60%) and sensitivity (30%). We set forth the hypothesis that the Machine Learning (ML) C5.0 algorithm could optimize the ECG in the prediction of LVH by echocardiography (Echo) while also establishing ECG-LVH phenotypes. We used Echo as the standard diagnostic tool to detect LVH and measured the ECG abnormalities found in Echo-LVH. We included 432 patients (power = 99%). Of these, 202 patients (46.7%) had Echo-LVH and 240 (55.6%) were males. We included a wide range of ventricular masses and Echo-LVH severities which were classified as mild (n = 77, 38.1%), moderate (n = 50, 24.7%) and severe (n = 75, 37.1%). Data was divided into a training/testing set (80%/20%) and we applied logistic regression analysis on the ECG measurements. The logistic regression model with the best ability to identify Echo-LVH was introduced into the C5.0 ML algorithm. We created multiple decision trees and selected the tree with the highest performance. The resultant five-level binary decision tree used only six predictive variables and had an accuracy of 71.4% (95%CI, 65.5-80.2), a sensitivity of 79.6%, specificity of 53%, positive predictive value of 66.6% and a negative predictive value of 69.3%. Internal validation reached a mean accuracy of 71.4% (64.4-78.5). Our results were reproduced in a second validation group and a similar diagnostic accuracy was obtained, 73.3% (95%CI, 65.5-80.2), sensitivity (81.6%), specificity (69.3%), positive predictive value (56.3%) and negative predictive value (88.6%). We calculated the Romhilt-Estes multilevel score and compared it to our model. The accuracy of the Romhilt-Estes system had an accuracy of 61.3% (CI95%, 56.5-65.9), a sensitivity of 23.2% and a specificity of 94.8% with similar results in the external validation group. In conclusion, the C5.0 ML algorithm surpassed the accuracy of current ECG criteria in the detection of Echo-LVH. Our new criteria hinge on ECG abnormalities that identify high-risk patients and provide some insight on electrogenesis in Echo-LVH

Development, validation and measurement of patient satisfaction questionnaire in Spanish in drive thru services adapted to hospital pharmacies during COVID-19 pandemic

Background: There are no validation studies on patient satisfaction surveys in Spanish that can evaluate a hospital pharmacy drive-thru service. Objective: To develop and apply a pharmacy drive-thru satisfaction survey in Spanish during the COVID-19 pandemic with an analysis of the instrument validation. Methods: This was a qualitative study for developing, validating, and measuring patient satisfaction who used the drive-thru pharmacy during the COVID-19 pandemic. Content validity was obtained by a two-round Delphi and patient interview for apparent validity. The questionnaire was administered to 110 patients. The researchers made an item reduction by inter-item and item-total correlation analysis, stability validation by a test–retest, a test of reliability by Cronbach's alpha, and extraction of factors by an exploratory factorial analysis. Likewise, confirmatory factor analysis was developed to obtain a structural equation model based on generating an instrument of two sub-models of latent factors (service and place) with ten observed variables (items). Results: A questionnaire was developed that relates six observable variables to the latent factor service and four observable variables to the latent factor place which are ten items based on a Likert scale from 1 to 5, obtaining a Cronbach's alpha = 0.901. The mean population satisfaction score was 4.523. The model presented a Root Mean Square Error of Approximation (RMSEA) of 0.026 (0.000–0.098), and standardized beta values greater than 0.2 according to the confirmatory factor analysis. Therefore, the goodness-of-fit of our model is consistent and the instrument of patient satisfaction with the use of drive-thru has been validated. Patient satisfaction had a mean of 4.9 points. Conclusions: This study developed and validated a reliable scale that evaluates satisfaction in a hospital pharmacy drive-thru service during COVID-19 pandemic that can be applied in other Spanish speaking countries. A great percentage of the patients that were evaluated had good satisfaction

Analysis of Immunization, Adverse Events, and Efficacy of a Fourth Dose of BNT162b2 Vaccine in Health Workers in Mexico, a Pilot Study

There is scarce information on seroconversion and adverse events after immunization (AEFI) with the fourth dose of BNT162b2. Our aim was to correlate the magnitude of the antibody response to this vaccination regimen in terms of clinical conditions and AEFI. This was an observational pilot study in which SARS-CoV-2 S1&ndash;S2 IgG antibodies titers were measured 21&ndash;28 days after the first and second dose, three months after the second dose, 1&ndash;7 and 21&ndash;28 days after the third dose, before the fourth dose, and 21&ndash;28 days after the fourth dose. We recruited 112 subjects in a hospital in Mexico, 74% women, with an average age of 43 (SD 9) years. After the first dose, subjects had a median IgG AU/mL (IQR) of 122 (1904) that increased to 1875 (2095), 3020 (2330), and 4230 (3393) 21&ndash;28 days after the second, third, and fourth doses, respectively (p &lt; 0.01). The number (%) who experienced any AEFI between the first and fourth doses was 90 (80.4), 89 (79), 65 (58), and 69 (61.5), respectively (p &lt; 0.001). After the fourth dose, the most frequent of AEFI was pain at the injection site (87%). There was a correlation between AEFI and gender after the fourth dose, as well as with antibody levels (p &lt; 0.05). During the Omicron outbreak, six (5.3%) had mild COVID-19 for 8&ndash;28 days after the fourth dose. The median increase in S1/S2 IgG was 30.8-fold after the fourth BNT162b2 dose when compared with the first dose and caused mild AEFI

Analyzing the Interplay between COVID-19 Viral Load, Inflammatory Markers, and Lymphocyte Subpopulations on the Development of Long COVID

The global impact of the SARS-CoV-2 infection has been substantial, affecting millions of people. Long COVID, characterized by persistent or recurrent symptoms after acute infection, has been reported in over 40% of patients. Risk factors include age and female gender, and various mechanisms, including chronic inflammation and viral persistence, have been implicated in long COVID’s pathogenesis. However, there are scarce studies in which multiple inflammatory markers and viral load are analyzed simultaneously in acute infection to determine how they predict for long COVID at long-term follow-up. This study explores the association between long COVID and inflammatory markers, viral load, and lymphocyte subpopulation during acute infection in hospitalized patients to better understand the risk factors of this disease. This longitudinal retrospective study was conducted in patients hospitalized with COVID-19 in northern Mexico. Inflammatory parameters, viral load, and lymphocyte subpopulation during the acute infection phase were analyzed, and long COVID symptoms were followed up depending on severity and persistence (weekly or monthly) and assessed 1.5 years after the acute infection. This study analyzed 79 patients, among them, 41.8% presented long COVID symptoms, with fatigue being the most common (45.5%). Patients with long COVID had higher lymphocyte levels during hospitalization, and NK cell subpopulation levels were also associated with long COVID. ICU admission during acute COVID-19 was also linked to the development of long COVID symptoms

Family history and obesity in youth, their effect on acylcarnitine/aminoacids metabolomics and non-alcoholic fatty liver disease (NAFLD). Structural equation modeling approach

Background: Structural equation modeling (SEM) can help understanding complex functional relationships among obesity, non-alcoholic fatty liver disease (NAFLD), family history of obesity, targeted metabolomics and pro-inflammatory markers. We tested two hypotheses: 1) If obesity precedes an excess of free fatty acids that increase oxidative stress and mitochondrial dysfunction, there would be an increase of serum acylcarnitines, amino acids and cytokines in obese subjects. Acylcarnitines would be related to non-alcoholic fatty disease that will induce insulin resistance. 2) If a positive family history of obesity and type 2 diabetes are the major determinants of the metabolomic profile, there would be higher concentration of amino acids and acylcarnitines in patients with this background that will induce obesity and NAFLD which in turn will induce insulin resistance. Methods/Results 137 normoglycemic subjects, mean age (SD) of 30.61 (8.6) years divided in three groups: BMI30 with absence of NAFLD (G2), n = 24; and BMI>30 with NAFLD (G3), n = 31. Family history of obesity (any) was present in 53%. Both models were adjusted in SEM. Family history of obesity predicted obesity but could not predict acylcarnitines and amino acid concentrations (effect size <0.2), but did predict obesity phenotype. Conclusion: Family history of obesity is the major predictor of obesity, and the metabolic abnormalities on amino acids, acylcarnitines, inflammation, insulin resistance, and NAFLD