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There is a genetic component to the risk of severe COVID-19, but the genetic effects are difficult to separate from social constructs that covary with genetic ancestry. To address this, the authors identify determinants of COVID-19 severity using admixture mapping, viral phylodynamics, and host immune and metagenomic sequencing.

Abstract Background Hypertriglyceridemia has emerged as a critical coronary artery disease (CAD) risk factor. Rare loss-of-function (LoF) variants in apolipoprotein C-III have been reported to reduce triglycerides (TG) and are cardioprotective in American Indians and Europeans. However, there is a lack of data in other Europeans and non-Europeans. Also, whether genetically increased plasma TG due to ApoC-III is causally associated with increased CAD risk is still unclear and inconsistent. The objectives of this study were to verify the cardioprotective role of earlier reported six LoF variants of APOC3 in South Asians and other multi-ethnic cohorts and to evaluate the causal association of TG raising common variants for increasing CAD risk. Methods We performed gene-centric and Mendelian randomization analyses and evaluated the role of genetic variation encompassing APOC3 for affecting circulating TG and the risk for developing CAD. Results One rare LoF variant (rs138326449) with a 37% reduction in TG was associated with lowered risk for CAD in Europeans (p = 0.007), but we could not confirm this association in Asian Indians (p = 0.641). Our data could not validate the cardioprotective role of other five LoF variants analysed. A common variant rs5128 in the APOC3 was strongly associated with elevated TG levels showing a p-value 2.8 × 10− 424. Measures of plasma ApoC-III in a small subset of Sikhs revealed a 37% increase in ApoC-III concentrations among homozygous mutant carriers than the wild-type carriers of rs5128. A genetically instrumented per 1SD increment of plasma TG level of 15 mg/dL would cause a mild increase (3%) in the risk for CAD (p = 0.042). Conclusions Our results highlight the challenges of inclusion of rare variant information in clinical risk assessment and the generalizability of implementation of ApoC-III inhibition for treating atherosclerotic disease. More studies would be needed to confirm whether genetically raised TG and ApoC-III concentrations would increase CAD risk.

Regular exercise promotes overall health and prevents non-communicable diseases, but the adaptation mechanisms are unclear. Here, the authors perform a meta-analysis to reveal time-specific patterns of the acute and long-term exercise response in human skeletal muscle, and identify sex- and age-specific changes.

Mendelian randomization is a popular method to detect causal relationships between traits, but can be confounded by instances of horizontal pleiotropy. Here, the authors present a Mendelian randomization workflow which includes causal discovery analysis and filtering of genetic instruments based on their conditional independencies.

Abstract Preliminary reports suggest that the Coronavirus Disease 2019 (COVID− 19) pandemic has led to disproportionate morbidity and mortality among historically disadvantaged populations. We investigate the racial and socioeconomic associations of COVID− 19 hospitalization among 418,794 participants of the UK Biobank, of whom 549 (0.13%) had been hospitalized. Both Black participants (odds ratio 3.7; 95%CI 2.5–5.3) and Asian participants (odds ratio 2.2; 95%CI 1.5–3.2) were at substantially increased risk as compared to White participants. We further observed a striking gradient in COVID− 19 hospitalization rates according to the Townsend Deprivation Index − a composite measure of socioeconomic deprivation − and household income. Adjusting for socioeconomic factors and cardiorespiratory comorbidities led to only modest attenuation of the increased risk in Black participants, adjusted odds ratio 2.4 (95%CI 1.5–3.7). These observations confirm and extend earlier preliminary and lay press reports of higher morbidity in non-White individuals in the context of a large population of participants in a national biobank. The extent to which this increased risk relates to variation in pre-existing comorbidities, differences in testing or hospitalization patterns, or additional disparities in social determinants of health warrants further study.

While many pleiotropic genetic loci have been identified, how they contribute to phenotypes across traits and diseases is unclear. Here, the authors propose decomposition of genetic associations (DeGAs), which uses singular value decomposition, to characterize the underlying latent structure of genetic associations of 2,138 phenotypes.

Protein-truncating variants (PTVs) are predicted to significantly affect a gene’s function and, thus, human traits. Here, DeBoever et al. systematically analyze PTVs in more than 300,000 individuals across 135 phenotypes and identify 27 associations between PTVs and medical conditions.

Cancer: Blood mutations linked to solid tumor risk Increased risk for solid tumors linked to mutations detected in blood samples that shorten the coding sequence of their genes. Mark Daly and colleagues from the Broad Institute in Cambridge, Massachusetts, USA, used large genomic databases to test whether having blood cells both with and without genetic variants predicted to shorten the encoded protein—a phenomenon known as mosaic protein-truncating variants (PTVs)—was associated with developing a range of solid-tumor cancers. They studied DNA from around 8,000 people with cancer and 6,000 healthy controls. Other studies have shown that mosaic PTVs precede and predict the development of leukemia. In this study, the scientists not only confirmed previous reports linking these variants to breast and ovarian cancer but also extended the association to include tumors of the brain, skin and lungs. These results broadly connect cancer to blood DNA changes.

Hand grip strength as a proxy of muscular fitness is a clinical predictor of mortality and morbidity. In a large-scale GWA study, the authors find 16 robustly associated genetic loci that highlight roles in muscle fibre structure and function, neuronal maintenance and nervous system signal transduction.

While hundreds of loci are linked with inflammatory bowel diseases (IBDs), the functional consequences of the associated variants remain unclear. Here, the authors screened in ulcerative colitis (UC) patients’ genomes for protein-truncating variants near IBD loci, and identify a protein truncating variant in RNF186to be protective against UC.

La implementación y generalización de la modalidad de Educación a Distancia durante el período de la pandemia Covid 19, demostró su incuestionable importancia en todos los niveles educativos, con énfasis en la Educación Superior, tanto en la formación de pregrado como de posgrado. En cambio, una de las problemáticas que se revela, entre los docentes al emplear esta modalidad, se relaciona con la diversidad de criterios en cómo evaluar el diseño y la calidad de los cursos a distancia. El presente estudio tiene como objetivo, fundamentar un modelo de diseño y evaluación de la calidad de la educación a distancia para contribuir a perfeccionar la calidad del proceso formativo en la Universidad de Oriente. Este modelo contiene los indicadores para evaluar la calidad de los cursos en línea y las aulas virtuales soportados en la plataforma Moodle, cuya pertinencia fue constatada mediante la inducción-deducción, la observación, el análisis estadístico presentado en una escala valorativa, talleres de reflexión metodológica y técnicas de la estadística descriptiva. Se propone un modelo que constituye una herramienta metodológica para la autoevaluación y evaluación del proceso de montaje de los cursos y de su gestión pedagógica en la plataforma Moodle. Su implementación da cuenta de la efectividad de sus resultados, evidentes en la superioridad de los niveles del contenido alcanzados por los estudiantes en las diferentes disciplinas y el desarrollo de habilidades por los docentes en el empleo de la metodología y recursos tecnológicos que impone esta modalidad con el uso de las aulas virtuales.

# Background Patients with chronic lung disease (CLD), such as asthma or chronic obstructive pulmonary disease, were expected to have an increased risk of clinical manifestations and severity of COVID-19. However, these comorbidities have been reported less frequently than expected. Chronic treatment with inhaled corticosteroids (ICS) may impact the clinical course of COVID-19. The main objective of this study is to know the influence of chronic treatment with ICS on the prognosis of COVID-19 hospitalized patients with CLD. # Methods A multicenter retrospective cohort study was designed, including patients hospitalized with COVID-19. Epidemiological and clinical data were collected at admission and at seven days, and clinical outcomes were collected. Patients with CLD with and without chronic treatment with ICS were compared. # Results Two thousand five hundred ninety-eight patients were included, of which 1,171 patients had a diagnosis of asthma and 1,427 of COPD (53.37% and 41.41% with ICS, respectively). No differences were found in mortality, transfer to ICU, or development of moderate-severe ARDS. Patients with chronic ICS had a longer hospital stay in both asthma and COPD patients (9 vs. 8 days, *p =* 0.031 in asthma patients), (11 vs. 9 days, *p =* 0.018 in COPD patients); although they also had more comorbidity burden. # Conclusions Patients with chronic inhaled corticosteroids had longer hospital stays and more chronic comorbidities, measured by the Charlson comorbidity index, but they did not have more severe disease at admission, evaluated with qSOFA and PSI scores. Chronic treatment with inhaled corticosteroids had no influence on the prognosis of patients with chronic lung disease and COVID-19.

Abstract In 2020, the COVID-19 pandemic followed a two-wave pattern in most countries. Hospital admission for COVID-19 in one wave or another could have affected mortality, especially among the older persons. The objective of this study was to evaluate whether the admission of older patients during the different waves, before SARS-CoV-2 vaccination was available, was associated with a different mortality. We compared the mortality rates of patients hospitalized during 2020 before (first wave) and after (second wave) July 7, 2020, included in the SEMI-COVID-19 Registry, a large, multicenter, retrospective cohort of patients admitted to 126 Spanish hospitals for COVID-19. A multivariate logistic regression analysis was performed to control for changes in either the patient or disease profile. As of December 26, 2022, 22,494 patients had been included (17,784 from the first wave and 4710 from the second one). Overall mortality was 20.4% in the first wave and 17.2% in the second wave (risk difference (RD) − 3.2%; 95% confidence interval (95% CI) − 4.4 to − 2.0). Only patients aged 70 and older (10,973 patients: 8571 in the first wave and 2386 in the second wave) had a significant reduction in mortality (RD − 7.6%; 95% CI − 9.7 to − 5.5) (unadjusted relative risk reduction: 21.6%). After adjusting for age, comorbidities, variables related to the severity of the disease, and treatment received, admission during the second wave remained a protective factor. In Spain, patients aged 70 years and older admitted during the second wave of the COVID-19 pandemic had a significantly lower risk of mortality, except in severely dependent persons in need of corticosteroid treatment. This effect is independent of patient characteristics, disease severity, or treatment received. This suggests a protective effect of a better standard of care, greater clinical expertise, or a lesser degree of healthcare system overload.

Nature Communications 7 Article number: 12342 (2016); Published 9 August 2016; Updated 13 September 2016 The HTML version of this Article incorrectly listed the authors of the UK IBD Genetics Consortium and the NIDDK IBD Genetics Consortium individually in the main author list. This has now been corrected in the HTML; the PDF version of the paper was correct from the time of publication.

IntroductionThis study aims to discuss and assess the impact of three prevalent methodological biases: competing risks, immortal-time bias, and confounding bias in real-world observational studies evaluating treatment effectiveness. We use a demonstrative observational data example of COVID-19 patients to assess the impact of these biases and propose potential solutions.MethodsWe describe competing risks, immortal-time bias, and time-fixed confounding bias by evaluating treatment effectiveness in hospitalized patients with COVID-19. For our demonstrative analysis, we use observational data from the registry of patients with COVID-19 who were admitted to the Bellvitge University Hospital in Spain from March 2020 to February 2021 and met our predefined inclusion criteria. We compare estimates of a single-dose, time-dependent treatment with the standard of care. We analyze the treatment effectiveness using common statistical approaches, either by ignoring or only partially accounting for the methodological biases. To address these challenges, we emulate a target trial through the clone-censor-weight approach.ResultsOverlooking competing risk bias and employing the naïve Kaplan-Meier estimator led to increased in-hospital death probabilities in patients with COVID-19. Specifically, in the treatment effectiveness analysis, the Kaplan-Meier estimator resulted in an in-hospital mortality of 45.6% for treated patients and 59.0% for untreated patients. In contrast, employing an emulated trial framework with the weighted Aalen-Johansen estimator, we observed that in-hospital death probabilities were reduced to 27.9% in the “X”-treated arm and 40.1% in the non-“X”-treated arm. Immortal-time bias led to an underestimated hazard ratio of treatment.ConclusionOverlooking competing risks, immortal-time bias, and confounding bias leads to shifted estimates of treatment effects. Applying the naïve Kaplan-Meier method resulted in the most biased results and overestimated probabilities for the primary outcome in analyses of hospital data from COVID-19 patients. This overestimation could mislead clinical decision-making. Both immortal-time bias and confounding bias must be addressed in assessments of treatment effectiveness. The trial emulation framework offers a potential solution to address all three methodological biases.

Desde hace tiempo vemos cómo en cualquier bar peninsular se salda el menor desencuentro entre contertulios desenfundando el telefonito, para invocar a san Google y zanjar la discusión tomando al pie de la letra el bulo mejor situado que circule por allí. Hemos pasado de la docta ignorancia practicada por Nicolás de Cusa, muy consciente de los límites del conocer, al alarde de ese analfabetismo tan estimado por el José Bergamín de La decadencia del analfabetismo. Y no podemos disculpar el asunto recurriendo al missreading auspiciado por Harold Bloom, ya que este exige una cultura libresca y el afán de continuar una tradición; frente a ella, ahora nos enfrentamos con el desprecio y el temor a esa arma de doble filo que es la letra porque, al menos en español, con sangre entra. Como indicaba Erasmo de Rotterdam en su Elogio de la locura, la gente solo espera oír aquello de más fácil deglución, por eso las entradas en INTERnet deben gozar de la mayor futilidad para cobrar seguidores, algo que nos obliga a la restauración de las competencias del conocer para fijar la distinción entre qué sea el conocimiento y qué el cacareo útil solo para el apareamiento. Esta ponencia continúa mis investigaciones en la esfera de las artes y cultura digitales, para insistir en la persistente decadencia cultural desde la aparición de la web 2.0 en 2004, fecha de inicio del ocaso de los ídolos. Nota bene: El título está tomado del artículo de Jean Dulck «Du gentleman au hooligan». El subtítulo, obvia decirlo, hace referencia al tópico de Nietzsche sobre El ocaso de los ídolos, y al conocido grabado de Francisco de Goya y Lucientes «El sueño de la razón produce monstruos», nº 43 de la serie de Los Caprichos (1797-1799).

Abstract Background Real-world observational data are an important source of evidence on the treatment effectiveness for patients hospitalized with coronavirus disease 2019 (COVID-19). However, observational studies evaluating treatment effectiveness based on longitudinal data are often prone to methodological biases such as immortal time bias, confounding bias, and competing risks. Methods For exemplary target trial emulation, we used a cohort of patients hospitalized with COVID-19 (n = 501) in a single centre. We described the methodology for evaluating the effectiveness of a single-dose treatment, emulated a trial using real-world data, and drafted a hypothetical study protocol describing the main components. To avoid immortal time and time-fixed confounding biases, we applied the clone-censor-weight technique. We set a 5-day grace period as a period of time when treatment could be initiated. We used the inverse probability of censoring weights to account for the selection bias introduced by artificial censoring. To estimate the treatment effects, we took the multi-state model approach. We considered a multi-state model with five states. The primary endpoint was defined as clinical severity status, assessed by a 5-point ordinal scale on day 30. Differences between the treatment group and standard of care treatment group were calculated using a proportional odds model and shown as odds ratios. Additionally, the weighted cause-specific hazards and transition probabilities for each treatment arm were presented. Results Our study demonstrates that trial emulation with a multi-state model analysis is a suitable approach to address observational data limitations, evaluate treatment effects on clinically heterogeneous in-hospital death and discharge alive endpoints, and consider the intermediate state of admission to ICU. The multi-state model analysis allows us to summarize results using stacked probability plots that make it easier to interpret results. Conclusions Extending the emulated target trial approach to multi-state model analysis complements treatment effectiveness analysis by gaining information on competing events. Combining two methodologies offers an option to address immortal time bias, confounding bias, and competing risk events. This methodological approach can provide additional insight for decision-making, particularly when data from randomized controlled trials (RCTs) are unavailable.

Background: This study aimed to validate the role of the D-dimer to lymphocyte ratio (DLR) for mortality prediction in a large national cohort of hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: A retrospective, multicenter, observational study that included hospitalized patients due to SARS-CoV-2 infection in Spain was conducted from March 2020 to March 2022. All biomarkers and laboratory indices analyzed were measured once at admission. Results: A total of 10,575 COVID-19 patients were included in this study. The mean age of participants was 66.9 (±16) years, and 58.6% (6202 patients) of them were male. The overall mortality rate was 16.3% (n = 1726 patients). Intensive care unit admission was needed in 10.5% (n = 1106 patients), non-invasive mechanical ventilation was required in 8.8% (n = 923 patients), and orotracheal intubation was required in 7.5% (789 patients). DLR presented a c-statistic of 0.69 (95% CI, 0.68–0.71) for in-hospital mortality with an optimal cut-off above 1. Multivariate analysis showed an independent association for in-hospital mortality for DLR > 1 (adjusted OR 2.09, 95% CI 1.09–4.04; p = 0.03); in the same way, survival analysis showed a higher mortality risk for DLR > 1 (HR 2.24; 95% CI 2.03–2.47; p < 0.01). Further, no other laboratory indices showed an independent association for mortality in multivariate analysis. Conclusions: This study confirmed the usefulness of DLR as a prognostic biomarker for mortality associated with SARS-CoV-2 infection, being an accessible, cost-effective, and easy-to-use biomarker in daily clinical practice.

Tourism worldwide is one of the most important sectors of the economy, taking into account the sources of employment it generates, as well as the growth of world GDP, which is why it occupies one of the main measures of sustainable development in the countries. Ecuador is one of the countries with the greatest biodiversity on the planet, and it has kept an increase in the arrival of tourists in recent years due to its natural wonders, which include visits to beaches, snow-capped mountains, and even excursions to jungle areas. It is worth mentioning that in all destinations you can appreciate biodiversity in all its splendor. The objective of this scientific paper is to carry out a study of the main factors that influence the development of Ecuador as a tourist destination. Two neutrosophic methods were used for this: (Neutrosophic AHP and DEMATEL) due to their versatility in decision-making and expert criteria processing. The conclusions reached indicate that the factors that need more attention are the prices in the tourist packages and the security of the tourist destination, its correct treatment will guarantee to turn Ecuador into a sustainable tourist destination.

Acquired hemophilia A (AHA) is a rare bleeding disorder caused by the presence of autoantibodies against factor VIII (FVIII). As with other autoimmune diseases, its etiology is complex and its genetic basis is unknown. The aim of this study was to identify the immunogenetic background that predisposes individuals to AHA. HLA and KIR gene clusters, as well as KLRK1, were sequenced using next-generation sequencing in 49 AHA patients. Associations between candidate genes involved in innate and adaptive immune responses and AHA were addressed by comparing the alleles, genotypes, haplotypes, and gene frequencies in the AHA cohort with those in the donors’ samples or Spanish population cohort. Two genes of the HLA cluster, as well as rs1049174 in KLRK1, which tags the natural killer (NK) cytotoxic activity haplotype, were found to be linked to AHA. Specifically, A*03:01 (p = 0.024; odds ratio (OR) = 0.26[0.06–0.85]) and DRB1*13:03 (p = 6.8 × 103, OR = 7.56[1.64–51.40]), as well as rs1049174 (p = 0.012), were significantly associated with AHA. In addition, two AHA patients were found to carry one copy each of the low-frequency allele DQB1*03:09 (nallele = 2, 2.04%), which was completely absent in the donors. To the best of our knowledge, this is the first time that the involvement of these specific alleles in the predisposition to AHA has been proposed. Further molecular and functional studies will be needed to unravel their specific contributions. We believe our findings expand the current knowledge on the genetic factors involved in susceptibility to AHA, which will contribute to improving the diagnosis and prognosis of AHA patients.

We evaluated the association between T. gondii seropositivity and violent behavior in a sample of inmates in Durango, Mexico. Through a cross-sectional study design, we studied 128 inmates (mean age: 35.89 ± 10.51; range: 19-65 years). Sera of participants were analyzed for anti-T. gondii IgG antibodies using a commercially available enzyme-linked immunosorbent assay. Violence was assessed by 1) the Historical, Clinical and Risk Management-20 (HCR-20) tool; 2) the type of the crime for which inmates were convicted; and 3) the Buss-Perry Aggression Questionnaire (AGQ). Of the 128 inmates, 17 (13.3%) had high risk of violence by the HCR-20 criteria, 72 (56.3%) were considered violent by the type of the crime committed, and 59 (46.1%) were considered violent by the AGQ. Depending on the evaluation method of violence, the seroprevalence of T. gondii infection in violent inmates varied from 0% to 6.9%. No statistically significant difference in anti-T. gondii IgG seroprevalence between violent and non-violent inmates was found (for instance by AGQ, OR: 1.17; 95% CI: 0.22-6.07; P = 1.00). Mean scores of the AGQ in T. gondii seropositive inmates (73.67 ± 29.09; 95% CI: 50.00-99.31) were similar to those (79.84 ± 25.00; 95% CI: 75.46-84.27) found in T. gondii seronegative inmates (P = 0.55). Mean scores of anger, psychical aggression, verbal aggression, and hostility in T. gondii seropositive inmates were similar to those found in T. gondii seronegative inmates. Results of this study suggest that infection with T. gondii is not associated with violence in inmates in Durango, Mexico. Further studies with larger sample sizes and in several correctional facilities to determine the association between T. gondii infection and violence in inmates are needed.

Introduction: Since the beginning of the COVID-19 pandemic in March 2020, an intimate relationship between this disease and cardiovascular diseases has been seen. However, few studies assess the development of heart failure during this infection. This study aims to determine the predisposing factors for the development of heart failure (HF) during hospital admission of COVID-19 patients. Methodology: A retrospective and multicenter study of patients with HF admitted for COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry). A bivariate analysis was performed to relate the different variables evaluated in patients developing heart failure during hospital admission. A multivariate analysis including the most relevant clinical variables obtained in bivariate analyses to predict the outcome of heart failure was performed. Results: A total of 16.474 patients hospitalized for COVID-19 were included (57.5% men, mean age 67 years), 958 of them (5.8%) developed HF during hospitalization. The risk factors for HF development were: age (odds ratio [OR]): 1.042; confidence interval 95% (CI 95%): 1.035–1.050; p < 0.001), atrial fibrillation (OR: 2.022; CI 95%: 1.697–2.410; p < 0.001), BMI > 30 kg/m2 (OR: 1.460 CI 95%: 1.230–1.733; p < 0001), and peripheral vascular disease (OR: 1.564; CI 95%: 1.217–2.201; p < 0.001). Patients who developed HF had a higher rate of mortality (54.1% vs. 19.1%, p < 0.001), intubation rate (OR: 2,36; p < 0.001), and ICU admissions (OR: 2.38; p < 0001). Conclusions: Patients who presented a higher risk of developing HF were older with cardiovascular risk factors. The risk factors for HF development were age, atrial fibrillation, obesity, and peripheral vascular disease. In addition, patients who developed HF more frequently required to be intubated or admitted to the ICU.

We present a systematic assessment of polygenic risk score (PRS) prediction across more than 1,500 traits using genetic and phenotype data in the UK Biobank. We report 813 sparse PRS models with significant (p < 2.5 x 10-5) incremental predictive performance when compared against the covariate-only model that considers age, sex, types of genotyping arrays, and the principal component loadings of genotypes. We report a significant correlation between the number of genetic variants selected in the sparse PRS model and the incremental predictive performance (Spearman's ⍴ = 0.61, p = 2.2 x 10-59 for quantitative traits, ⍴ = 0.21, p = 9.6 x 10-4 for binary traits). The sparse PRS model trained on European individuals showed limited transferability when evaluated on non-European individuals in the UK Biobank. We provide the PRS model weights on the Global Biobank Engine (https://biobankengine.stanford.edu/prs).

ABSTRACT: Objectives: The aim of this study was to analyze whether subgroups of immunosuppressive (IS) medications conferred different outcomes in COVID-19. Methods: The study involved a multicenter retrospective cohort of consecutive immunosuppressed patients (ISPs) hospitalized with COVID-19 from March to July, 2020. The primary outcome was in-hospital mortality. A propensity score-matched (PSM) model comparing ISP and non-ISP was planned, as well as specific PSM models comparing individual IS medications associated with mortality. Results: Out of 16 647 patients, 868 (5.2%) were on chronic IS therapy prior to admission and were considered ISPs. In the PSM model, ISPs had greater in-hospital mortality (OR 1.25, 95% CI 0.99–1.62), which was related to a worse outcome associated with chronic corticoids (OR 1.89, 95% CI 1.43–2.49). Other IS drugs had no repercussions with regard to mortality risk (including calcineurin inhibitors (CNI); OR 1.19, 95% CI 0.65–2.20). In the pre-planned specific PSM model involving patients on chronic IS treatment before admission, corticosteroids were associated with an increased risk of mortality (OR 2.34, 95% CI 1.43–3.82). Conclusions: Chronic IS therapies comprise a heterogeneous group of drugs with different risk profiles for severe COVID-19 and death. Chronic systemic corticosteroid therapy is associated with increased mortality. On the contrary, CNI and other IS treatments prior to admission do not seem to convey different outcomes.

Abstract To assess severity markers and outcomes of patients with systemic sclerosis (SSc) with or without pulmonary arterial hypertension (PAH-SSc/non-PAH-SSc), and the impact of interstitial lung disease (ILD) on PAH-SSc. Non-PAH-SSc patients from the Spanish SSc registry and PAH-SSc patients from the Spanish PAH registry were included. A total of 364 PAH-SSc and 1589 non-PAH-SSc patients were included. PAH-SSc patients had worse NYHA-functional class (NYHA-FC), worse forced vital capacity (FVC) (81.2 ± 20.6% vs 93.6 ± 20.6%, P

Abstract Background Since December 2019, the COVID-19 pandemic has changed the concept of medicine. This work aims to analyze the use of antibiotics in patients admitted to the hospital due to SARS-CoV-2 infection. Methods This work analyzes the use and effectiveness of antibiotics in hospitalized patients with COVID-19 based on data from the SEMI-COVID-19 registry, an initiative to generate knowledge about this disease using data from electronic medical records. Our primary endpoint was all-cause in-hospital mortality according to antibiotic use. The secondary endpoint was the effect of macrolides on mortality. Results Of 13,932 patients, antibiotics were used in 12,238. The overall death rate was 20.7% and higher among those taking antibiotics (87.8%). Higher mortality was observed with use of all antibiotics (OR 1.40, 95% CI 1.21–1.62; p

Abstract To determine the proportion of patients with COVID-19 who were readmitted to the hospital and the most common causes and the factors associated with readmission. Multicenter nationwide cohort study in Spain. Patients included in the study were admitted to 147 hospitals from March 1 to April 30, 2020. Readmission was defined as a new hospital admission during the 30 days after discharge. Emergency department visits after discharge were not considered readmission. During the study period 8392 patients were admitted to hospitals participating in the SEMI-COVID-19 network. 298 patients (4.2%) out of 7137 patients were readmitted after being discharged. 1541 (17.7%) died during the index admission and 35 died during hospital readmission (11.7%, p = 0.007). The median time from discharge to readmission was 7 days (IQR 3–15 days). The most frequent causes of hospital readmission were worsening of previous pneumonia (54%), bacterial infection (13%), venous thromboembolism (5%), and heart failure (5%). Age [odds ratio (OR): 1.02; 95% confident interval (95% CI): 1.01–1.03], age-adjusted Charlson comorbidity index score (OR: 1.13; 95% CI: 1.06–1.21), chronic obstructive pulmonary disease (OR: 1.84; 95% CI: 1.26–2.69), asthma (OR: 1.52; 95% CI: 1.04–2.22), hemoglobin level at admission (OR: 0.92; 95% CI: 0.86–0.99), ground-glass opacification at admission (OR: 0.86; 95% CI:0.76–0.98) and glucocorticoid treatment (OR: 1.29; 95% CI: 1.00–1.66) were independently associated with hospital readmission. The rate of readmission after hospital discharge for COVID-19 was low. Advanced age and comorbidity were associated with increased risk of readmission.

Objectives: To assess the characteristics and risk factors for mortality in patients with severe coronavirus disease-2019 (COVID-19) treated with tocilizumab (TCZ), alone or in combination with corticosteroids (CS). Methods: From March 17 to April 7, 2020, a real-world observational retrospective analysis of consecutive hospitalized adult patients receiving TCZ to treat severe COVID-19 was conducted at our 750-bed university hospital. The main outcome was all-cause in-hospital mortality. Results: A total of 1,092 patients with COVID-19 were admitted during the study period. Of them, 186 (17%) were treated with TCZ, of which 129 (87.8%) in combination with CS. Of the total 186 patients, 155 (83.3 %) patients were receiving noninvasive ventilation when TCZ was initiated. Mean time from symptoms onset and hospital admission to TCZ use was 12 (±4.3) and 4.3 days (±3.4), respectively. Overall, 147 (79%) survived and 39 (21%) died. By multivariate analysis, mortality was associated with older age (HR = 1.09, p < 0.001), chronic heart failure (HR = 4.4, p = 0.003), and chronic liver disease (HR = 4.69, p = 0.004). The use of CS, in combination with TCZ, was identified as a protective factor against mortality (HR = 0.26, p < 0.001) in such severe COVID-19 patients receiving TCZ. No serious superinfections were observed after a 30-day follow-up. Conclusions: In patients with severe COVID-19 receiving TCZ due to systemic host-immune inflammatory response syndrome, the use of CS in addition to TCZ therapy, showed a beneficial effect in preventing in-hospital mortality.

Abstract Background Limited evidence exists on the role of glucose-lowering drugs in patients with COVID-19. Our main objective was to examine the association between in-hospital death and each routine at-home glucose-lowering drug both individually and in combination with metformin in patients with type 2 diabetes mellitus admitted for COVID-19. We also evaluated their association with the composite outcome of the need for ICU admission, invasive and non-invasive mechanical ventilation, or in-hospital death as well as on the development of in-hospital complications and a long-time hospital stay. Methods We selected all patients with type 2 diabetes mellitus in the Spanish Society of Internal Medicine’s registry of COVID-19 patients (SEMI-COVID-19 Registry). It is an ongoing, observational, multicenter, nationwide cohort of patients admitted for COVID-19 in Spain from March 1, 2020. Each glucose-lowering drug user was matched with a user of other glucose-lowering drugs in a 1:1 manner by propensity scores. In order to assess the adequacy of propensity score matching, we used the standardized mean difference found in patient characteristics after matching. There was considered to be a significant imbalance in the group if a standardized mean difference > 10% was found. To evaluate the association between treatment and study outcomes, both conditional logit and mixed effect logistic regressions were used when the sample size was ≥ 100. Results A total of 2666 patients were found in the SEMI-COVID-19 Registry, 1297 on glucose-lowering drugs in monotherapy and 465 in combination with metformin. After propensity matching, 249 patients on metformin, 105 on dipeptidyl peptidase-4 inhibitors, 129 on insulin, 127 on metformin/dipeptidyl peptidase-4 inhibitors, 34 on metformin/sodium-glucose cotransporter 2 inhibitor, and 67 on metformin/insulin were selected. No at-home glucose-lowering drugs showed a significant association with in-hospital death; the composite outcome of the need of intensive care unit admission, mechanical ventilation, or in-hospital death; in-hospital complications; or long-time hospital stays. Conclusions In patients with type 2 diabetes mellitus admitted for COVID-19, at-home glucose-lowering drugs showed no significant association with mortality and adverse outcomes. Given the close relationship between diabetes and COVID-19 and the limited evidence on the role of glucose-lowering drugs, prospective studies are needed.

Este trabajo realiza un análisis del estado de la adopción de las aulas virtuales de la Universidad de Oriente para acercarse a las posibles causas de sus limitaciones. Se tienen en cuenta indicadores como: el soporte tecnológico, la organización de la preparación de los docentes, lo usuarios registrados, las aulas vacías, las actividades y los recursos que se emplean, la actitud hacia las tecnologías y las creencias tecnológicas. El análisis reveló algunos de los retos que tiene la institución frente a la digitalización de sus procesos.

Objective To describe the impact of different doses of corticosteroids on the evolution of patients with COVID-19 pneumonia, based on the potential benefit of the non-genomic mechanism of these drugs at higher doses. Methods Observational study using data collected from the SEMI-COVID-19 Registry. We evaluated the epidemiological, radiological and analytical scenario between patients treated with megadoses therapy of corticosteroids vs low-dose of corticosteroids and the development of complications. The primary endpoint was all-cause in-hospital mortality according to use of corticosteroids megadoses. Results Of a total of 14,921 patients, corticosteroids were used in 5,262 (35.3%). Of them, 2,216 (46%) specifically received megadoses. Age was a factor that differed between those who received megadoses therapy versus those who did not in a significant manner (69 years [IQR 59–79] vs 73 years [IQR 61–83]; p < .001). Radiological and analytical findings showed a higher use of megadoses therapy among patients with an interstitial infiltrate and elevated inflammatory markers associated with COVID-19. In the univariate study it appears that steroid use is associated with increased mortality (OR 2.07 95% CI 1.91–2.24 p < .001) and megadose use with increased survival (OR 0.84 95% CI 0.75–0.96, p 0.011), but when adjusting for possible confounding factors, it is observed that the use of megadoses is also associated with higher mortality (OR 1.54, 95% CI 1.32–1.80; p < .001). There is no difference between megadoses and low-dose (p .298). Although, there are differences in the use of megadoses versus low-dose in terms of complications, mainly infectious, with fewer pneumonias and sepsis in the megadoses group (OR 0.82 95% CI 0.71–0.95; p < .001 and OR 0.80 95% CI 0.65–0.97; p < .001) respectively. Conclusion There is no difference in mortality with megadoses versus low-dose, but there is a lower incidence of infectious complications with glucocorticoid megadoses.

ObjectiveTo describe the impact of different doses of corticosteroids on the evolution of patients with COVID-19 pneumonia, based on the potential benefit of the non-genomic mechanism of these drugs at higher doses.MethodsObservational study using data collected from the SEMI-COVID-19 Registry. We evaluated the epidemiological, radiological and analytical scenario between patients treated with megadoses therapy of corticosteroids vs low-dose of corticosteroids and the development of complications. The primary endpoint was all-cause in-hospital mortality according to use of corticosteroids megadoses.ResultsOf a total of 14,921 patients, corticosteroids were used in 5,262 (35.3%). Of them, 2,216 (46%) specifically received megadoses. Age was a factor that differed between those who received megadoses therapy versus those who did not in a significant manner (69 years [IQR 59-79] vs 73 years [IQR 61-83]; p < .001). Radiological and analytical findings showed a higher use of megadoses therapy among patients with an interstitial infiltrate and elevated inflammatory markers associated with COVID-19. In the univariate study it appears that steroid use is associated with increased mortality (OR 2.07 95% CI 1.91-2.24 p < .001) and megadose use with increased survival (OR 0.84 95% CI 0.75-0.96, p 0.011), but when adjusting for possible confounding factors, it is observed that the use of megadoses is also associated with higher mortality (OR 1.54, 95% CI 1.32-1.80; p < .001). There is no difference between megadoses and low-dose (p .298). Although, there are differences in the use of megadoses versus low-dose in terms of complications, mainly infectious, with fewer pneumonias and sepsis in the megadoses group (OR 0.82 95% CI 0.71-0.95; p < .001 and OR 0.80 95% CI 0.65-0.97; p < .001) respectively.ConclusionThere is no difference in mortality with megadoses versus low-dose, but there is a lower incidence of infectious complications with glucocorticoid megadoses.

BackgroundSleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort.Methods and findingsIn this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures-bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration-were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = -0.11 (95% confidence interval -0.13 to -0.10, p = 3 × 10-56, FDR = 6 × 10-55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry.ConclusionsIn this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals.

Systemic sclerosis (SSc) is a low-incidence autoimmune disease that requires collaborative work through national or international registries to advance scientifically. The present systematic review aims to be an update of all national and international registries to date. In total, 7 first-world countries have SSc registries. In addition, there are also 3 international SSc registries plus 2 other registries focused on SSc-related pulmonary arterial hypertension. These registries not only carry out clinical research but also allow the collection of serum, DNA and tissue samples, as well as collaborative work to carry out randomized clinical trials and collaboration with other registries not directly focused on SSc.

La motivación para la publicación del artículo, radica en la necesidad de pensar, analizar y debatir frente a los alcances sociales que realmente tiene la Política Pública de Educación Superior en el Municipio de Buenaventura, como unidad de complejidad social que requiere ser vista desde sus potencialidades. El objetivo consistió en identificar la pertinencia social actual de la educación superior en Buenaventura, en relación con los criterios de formulación de política pública de educación superior en Colombia. Como metodología, el proceso se realizó mediante una mirada hermenéutica que condujo a la triangulación metodológica (entrevista, encuesta, revisión documental) tomando como muestra poblacional a 160 estudiantes y 56 docentes de la Universidad del Pacifico y de la Universidad del Valle, sedes de Buenaventura, ambas públicas. Una conclusión relevante fue que se deben considerar las características culturales como ejes fundamentales en la planificación e implementación de la Política Pública de Educación Superior en el Distrito Especial de Buenaventura, con el fin de obtener mayores opciones de apropiación de la población y pertinencia de la misma en el contexto social, económico y educativo.

(1) Background: C-reactive protein (CRP) and albumin are inflammatory markers. We analyzed the prognostic capacity of serum albumin (SA) and CRP for an outcome comprising mortality, length of stay, ICU admission, and non-invasive mechanical ventilation in hospitalized COVID-19 patients. (2) Methods: We conducted a retrospective cohort study based on the Spanish national SEMI-COVID-19 Registry. Two multivariate logistic models were adjusted for SA, CRP, and their combination. Training and testing samples were used to validate the models. (3) Results: The outcome was present in 41.1% of the 3471 participants, who had lower SA (mean [SD], 3.5 [0.6] g/dL vs. 3.8 [0.5] g/dL; p < 0.001) and higher CRP (108.9 [96.5] mg/L vs. 70.6 [70.3] mg/L; p < 0.001). In the adjusted multivariate model, both were associated with poorer evolution: SA, OR 0.674 (95% CI, 0.551–0.826; p < 0.001); CRP, OR 1.002 (95% CI, 1.001–1.004; p = 0.003). The CRP/SA model had a similar predictive capacity (honest AUC, 0.8135 [0.7865–0.8405]), with a continuously increasing risk and cutoff value of 25 showing the highest predictive capacity (OR, 1.470; 95% CI, 1.188–1.819; p < 0.001). (4) Conclusions: SA and CRP are good independent predictors of patients hospitalized with COVID-19. For the CRP/SA ratio value, 25 is the cutoff for poor clinical course.

(1) Background: Large cohort studies of patients with COVID-19 treated with remdesivir have reported improved clinical outcomes, but data on older patients are scarce. Objective: This work aims to assess the potential benefit of remdesivir in unvaccinated very old patients hospitalized with COVID-19; (2) Methods: This is a retrospective analysis of patients ≥ 80 years hospitalized in Spain between 15 July and 31 December 2020 (SEMI-COVID-19 Registry). Differences in 30-day all-cause mortality were adjusted using a multivariable regression analysis. (3) Results: Of the 4331 patients admitted, 1312 (30.3%) were ≥80 years. Very old patients treated with remdesivir (n: 140, 10.7%) had a lower mortality rate than those not treated with remdesivir (OR (95% CI): 0.45 (0.29–0.69)). After multivariable adjustment by age, sex, and variables associated with lower mortality (place of COVID-19 acquisition; degree of dependence; comorbidities; dementia; duration of symptoms; admission qSOFA; chest X-ray; D-dimer; and treatment with corticosteroids, tocilizumab, beta-lactams, macrolides, and high-flow nasal canula oxygen), the use of remdesivir remained associated with a lower 30-day all-cause mortality rate (adjusted OR (95% CI): 0.40 (0.22–0.61) (p < 0.001)). (4) Conclusions: Remdesivir may reduce mortality in very old patients hospitalized with COVID-19.

BackgroundMost patients with COVID-19 receive antibiotics despite the fact that bacterial co-infections are rare. This can lead to increased complications, including antibacterial resistance. We aim to analyze risk factors for inappropriate antibiotic prescription in these patients and describe possible complications arising from their use.MethodsThe SEMI-COVID-19 Registry is a multicenter, retrospective patient cohort. Patients with antibiotic were divided into two groups according to appropriate or inappropriate prescription, depending on whether the patient fulfill any criteria for its use. Comparison was made by means of multilevel logistic regression analysis. Possible complications of antibiotic use were also identified.ResultsOut of 13,932 patients, 3047 (21.6%) were prescribed no antibiotics, 6116 (43.9%) were appropriately prescribed antibiotics, and 4769 (34.2%) were inappropriately prescribed antibiotics. The following were independent factors of inappropriate prescription: February-March 2020 admission (OR 1.54, 95%CI 1.18-2.00), age (OR 0.98, 95%CI 0.97-0.99), absence of comorbidity (OR 1.43, 95%CI 1.05-1.94), dry cough (OR 2.51, 95%CI 1.94-3.26), fever (OR 1.33, 95%CI 1.13-1.56), dyspnea (OR 1.31, 95%CI 1.04-1.69), flu-like symptoms (OR 2.70, 95%CI 1.75-4.17), and elevated C-reactive protein levels (OR 1.01 for each mg/L increase, 95% CI 1.00-1.01). Adverse drug reactions were more frequent in patients who received ANTIBIOTIC (4.9% vs 2.7%, p < .001).ConclusionThe inappropriate use of antibiotics was very frequent in COVID-19 patients and entailed an increased risk of adverse reactions. It is crucial to define criteria for their use in these patients. Knowledge of the factors associated with inappropriate prescribing can be helpful.

The clinical evaluation of a genetic syndrome relies upon recognition of a characteristic pattern of signs or symptoms to guide targeted genetic testing for confirmation of the diagnosis. However, individuals displaying a single phenotype of a complex syndrome may not meet criteria for clinical diagnosis or genetic testing. Here, we present a phenome-wide association study (PheWAS) approach to systematically explore the phenotypic expressivity of common and rare alleles in genes associated with four well-described syndromic diseases (Alagille (AS), Marfan (MS), DiGeorge (DS), and Noonan (NS) syndromes) in the general population. Using human phenotype ontology (HPO) terms, we systematically mapped 60 phenotypes related to AS, MS, DS and NS in 337,198 unrelated white British from the UK Biobank (UKBB) based on their hospital admission records, self-administrated questionnaires, and physiological measurements. We performed logistic regression adjusting for age, sex, and the first 5 genetic principal components, for each phenotype and each variant in the target genes (JAG1, NOTCH2 FBN1, PTPN1 and RAS-opathy genes, and genes in the 22q11.2 locus) and performed a gene burden test. Overall, we observed multiple phenotype-genotype correlations, such as the association between variation in JAG1, FBN1, PTPN11 and SOS2 with diastolic and systolic blood pressure; and pleiotropy among multiple variants in syndromic genes. For example, rs11066309 in PTPN11 was significantly associated with a lower body mass index, an increased risk of hypothyroidism and a smaller size for gestational age, all in concordance with NS-related phenotypes. Similarly, rs589668 in FBN1 was associated with an increase in body height and blood pressure, and a reduced body fat percentage as observed in Marfan syndrome. Our findings suggest that the spectrum of associations of common and rare variants in genes involved in syndromic diseases can be extended to individual phenotypes within the general population.

The UK Biobank is a very large, prospective population-based cohort study across the United Kingdom. It provides unprecedented opportunities for researchers to investigate the relationship between genotypic information and phenotypes of interest. Multiple regression methods, compared with genome-wide association studies (GWAS), have already been showed to greatly improve the prediction performance for a variety of phenotypes. In the high-dimensional settings, the lasso, since its first proposal in statistics, has been proved to be an effective method for simultaneous variable selection and estimation. However, the large-scale and ultrahigh dimension seen in the UK Biobank pose new challenges for applying the lasso method, as many existing algorithms and their implementations are not scalable to large applications. In this paper, we propose a computational framework called batch screening iterative lasso (BASIL) that can take advantage of any existing lasso solver and easily build a scalable solution for very large data, including those that are larger than the memory size. We introduce snpnet, an R package that implements the proposed algorithm on top of glmnet and optimizes for single nucleotide polymorphism (SNP) datasets. It currently supports ℓ1-penalized linear model, logistic regression, Cox model, and also extends to the elastic net with ℓ1/ℓ2 penalty. We demonstrate results on the UK Biobank dataset, where we achieve competitive predictive performance for all four phenotypes considered (height, body mass index, asthma, high cholesterol) using only a small fraction of the variants compared with other established polygenic risk score methods.

(1) Background: This work aims to analyze clinical outcomes according to ethnic groups in patients hospitalized for COVID-19 in Spain. (2) Methods: This nationwide, retrospective, multicenter, observational study analyzed hospitalized patients with confirmed COVID-19 in 150 Spanish hospitals (SEMI-COVID-19 Registry) from 1 March 2020 to 31 December 2021. Clinical outcomes were assessed according to ethnicity (Latin Americans, Sub-Saharan Africans, Asians, North Africans, Europeans). The outcomes were in-hospital mortality (IHM), intensive care unit (ICU) admission, and the use of invasive mechanical ventilation (IMV). Associations between ethnic groups and clinical outcomes adjusted for patient characteristics and baseline Charlson Comorbidity Index values and wave were evaluated using logistic regression. (3) Results: Of 23,953 patients (median age 69.5 years, 42.9% women), 7.0% were Latin American, 1.2% were North African, 0.5% were Asian, 0.5% were Sub-Saharan African, and 89.7% were European. Ethnic minority patients were significantly younger than European patients (median (IQR) age 49.1 (40.5–58.9) to 57.1 (44.1–67.1) vs. 71.5 (59.5–81.4) years, p < 0.001). The unadjusted IHM was higher in European (21.6%) versus North African (11.4%), Asian (10.9%), Latin American (7.1%), and Sub-Saharan African (3.2%) patients. After further adjustment, the IHM was lower in Sub-Saharan African (OR 0.28 (0.10–0.79), p = 0.017) versus European patients, while ICU admission rates were higher in Latin American and North African versus European patients (OR (95%CI) 1.37 (1.17–1.60), p < 0.001) and (OR (95%CI) 1.74 (1.26–2.41), p < 0.001). Moreover, Latin American patients were 39% more likely than European patients to use IMV (OR (95%CI) 1.43 (1.21–1.71), p < 0.001). (4) Conclusion: The adjusted IHM was similar in all groups except for Sub-Saharan Africans, who had lower IHM. Latin American patients were admitted to the ICU and required IMV more often.

Protein-altering variants that are protective against human disease provide in vivo validation of therapeutic targets. Here we use genotyping data from UK Biobank (n = 337,151 unrelated White British individuals) and FinnGen (n = 176,899) to conduct a search for protein-altering variants conferring lower intraocular pressure (IOP) and protection against glaucoma. Through rare protein-altering variant association analysis, we find a missense variant in ANGPTL7 in UK Biobank (rs28991009, p.Gln175His, MAF = 0.8%, genotyped in 82,253 individuals with measured IOP and an independent set of 4,238 glaucoma patients and 250,660 controls) that significantly lowers IOP (β = -0.53 and -0.67 mmHg for heterozygotes, -3.40 and -2.37 mmHg for homozygotes, P = 5.96 x 10-9 and 1.07 x 10-13 for corneal compensated and Goldman-correlated IOP, respectively) and is associated with 34% reduced risk of glaucoma (P = 0.0062). In FinnGen, we identify an ANGPTL7 missense variant at a greater than 50-fold increased frequency in Finland compared with other populations (rs147660927, p.Arg220Cys, MAF Finland = 4.3%), which was genotyped in 6,537 glaucoma patients and 170,362 controls and is associated with a 29% lower glaucoma risk (P = 1.9 x 10-12 for all glaucoma types and also protection against its subtypes including exfoliation, primary open-angle, and primary angle-closure). We further find three rarer variants in UK Biobank, including a protein-truncating variant, which confer a strong composite lowering of IOP (P = 0.0012 and 0.24 for Goldman-correlated and corneal compensated IOP, respectively), suggesting the protective mechanism likely resides in the loss of interaction or function. Our results support inhibition or down-regulation of ANGPTL7 as a therapeutic strategy for glaucoma.

Unstructured clinical narratives are continuously being recorded as part of delivery of care in electronic health records, and dedicated tagging staff spend considerable effort manually assigning clinical codes for billing purposes. Despite these efforts, however, label availability and accuracy are both suboptimal. In this retrospective study, we aimed to automate the assignment of top-level International Classification of Diseases version 9 (ICD-9) codes to clinical records from human and veterinary data stores using minimal manual labor and feature curation. Automating top-level annotations could in turn enable rapid cohort identification, especially in a veterinary setting. To this end, we trained long short-term memory (LSTM) recurrent neural networks (RNNs) on 52,722 human and 89,591 veterinary records. We investigated the accuracy of both separate-domain and combined-domain models and probed model portability. We established relevant baseline classification performances by training Decision Trees (DT) and Random Forests (RF). We also investigated whether transforming the data using MetaMap Lite, a clinical natural language processing tool, affected classification performance. We showed that the LSTM-RNNs accurately classify veterinary and human text narratives into top-level categories with an average weighted macro F1 score of 0.74 and 0.68 respectively. In the "neoplasia" category, the model trained on veterinary data had a high validation accuracy in veterinary data and moderate accuracy in human data, with F1 scores of 0.91 and 0.70 respectively. Our LSTM method scored slightly higher than that of the DT and RF models. The use of LSTM-RNN models represents a scalable structure that could prove useful in cohort identification for comparative oncology studies. Digitization of human and veterinary health information will continue to be a reality, particularly in the form of unstructured narratives. Our approach is a step forward for these two domains to learn from and inform one another.

BackgroundLifestyle interventions to reduce body mass index (BMI) are critical public health strategies for type 2 diabetes prevention. While weight loss interventions have shown demonstrable benefit for high-risk and prediabetic individuals, we aimed to determine whether the same benefits apply to those at lower risk.Methods and findingsWe performed a multi-stratum Mendelian randomization study of the effect size of BMI on diabetes odds in 287,394 unrelated individuals of self-reported white British ancestry in the UK Biobank, who were recruited from across the United Kingdom from 2006 to 2010 when they were between the ages of 40 and 69 years. Individuals were stratified on the following diabetes risk factors: BMI, diabetes family history, and genome-wide diabetes polygenic risk score. The main outcome measure was the odds ratio of diabetes per 1-kg/m2 BMI reduction, in the full cohort and in each stratum. Diabetes prevalence increased sharply with BMI, family history of diabetes, and genetic risk. Conversely, predicted risk reduction from weight loss was strikingly similar across BMI and genetic risk categories. Weight loss was predicted to substantially reduce diabetes odds even among lower-risk individuals: for instance, a 1-kg/m2 BMI reduction was associated with a 1.37-fold reduction (95% CI 1.12-1.68) in diabetes odds among non-overweight individuals (BMI < 25 kg/m2) without a family history of diabetes, similar to that in obese individuals (BMI ≥ 30 kg/m2) with a family history (1.21-fold reduction, 95% CI 1.13-1.29). A key limitation of this analysis is that the BMI-altering DNA sequence polymorphisms it studies represent cumulative predisposition over an individual's entire lifetime, and may consequently incorrectly estimate the risk modification potential of weight loss interventions later in life.ConclusionsIn a population-scale cohort, lower BMI was consistently associated with reduced diabetes risk across BMI, family history, and genetic risk categories, suggesting all individuals can substantially reduce their diabetes risk through weight loss. Our results support the broad deployment of weight loss interventions to individuals at all levels of diabetes risk.

Objectives: Since the results of the RECOVERY trial, WHO recommendations about the use of corticosteroids (CTs) in COVID-19 have changed. The aim of the study is to analyse the evolutive use of CTs in Spain during the pandemic to assess the potential influence of new recommendations. Material and methods: A retrospective, descriptive, and observational study was conducted on adults hospitalised due to COVID-19 in Spain who were included in the SEMI-COVID-19 Registry from March to November 2020. Results: CTs were used in 6053 (36.21%) of the included patients. The patients were older (mean (SD)) (69.6 (14.6) vs. 66.0 (16.8) years; p < 0.001), with hypertension (57.0% vs. 47.7%; p < 0.001), obesity (26.4% vs. 19.3%; p < 0.0001), and multimorbidity prevalence (20.6% vs. 16.1%; p < 0.001). These patients had higher values (mean (95% CI)) of C-reactive protein (CRP) (86 (32.7–160) vs. 49.3 (16–109) mg/dL; p < 0.001), ferritin (791 (393–1534) vs. 470 (236–996) µg/dL; p < 0.001), D dimer (750 (430–1400) vs. 617 (345–1180) µg/dL; p < 0.001), and lower Sp02/Fi02 (266 (91.1) vs. 301 (101); p < 0.001). Since June 2020, there was an increment in the use of CTs (March vs. September; p < 0.001). Overall, 20% did not receive steroids, and 40% received less than 200 mg accumulated prednisone equivalent dose (APED). Severe patients are treated with higher doses. The mortality benefit was observed in patients with oxygen saturation

We aimed to determine the impact of steroid use in COVID-19 in-hospital mortality, in a retrospective cohort study of the SEMICOVID19 database of admitted patients with SARS-CoV-2 laboratory-confirmed pneumonia from 131 Spanish hospitals. Patients treated with corticosteroids were compared to patients not treated with corticosteroids; and adjusted using a propensity-score for steroid treatment. From March–July 2020, 5.262 (35.26%) were treated with corticosteroids and 9.659 (64.73%) were not. In-hospital mortality overall was 20.50%; it was higher in patients treated with corticosteroids than in controls (28.5% versus 16.2%, OR 2.068 [95% confidence interval; 1.908 to 2.242]; p = 0.0001); however, when adjusting by occurrence of ARDS, mortality was significantly lower in the steroid group (43.4% versus 57.6%; OR 0.564 [95% confidence interval; 0.503 to 0.633]; p = 0.0001). Moreover, the greater the respiratory failure, the greater the impact on mortality of the steroid treatment. When adjusting these results including the propensity score as a covariate, in-hospital mortality remained significantly lower in the steroid group (OR 0.774 [0.660 to 0.907], p = 0.002). Steroid treatment reduced mortality by 24% relative to no steroid treatment (RRR 0.24). These results support the use of glucocorticoids in COVID-19 in this subgroup of patients.

Corticosteroids are largely recommended in patients with severe COVID-19. However, evidence to support high-dose methylprednisolone (MP) pulses is not as robust as that demonstrated for low-dose dexamethasone (DXM) in the RECOVERY trial. This is a retrospective cohort study on severe, non-critically ill patients with COVID-19, comparing 3-day MP pulses ≥ 100 mg/day vs. DXM 6 mg/day for 10 days. The primary outcome was in-hospital mortality, and the secondary outcomes were need of intensive care unit (ICU) admission or invasive mechanical ventilation (IMV). Propensity-score matching (PSM) analysis was applied. From March 2020 to April 2021, a total of 2,284 patients were admitted to our hospital due to severe, non-critically ill COVID-19, and of these, 189 (8.3%) were treated with MP, and 493 (21.6%) with DXM. The results showed that patients receiving MP showed higher in-hospital mortality (31.2% vs. 17.8%, p < 0.001), need of ICU admission (29.1% vs. 20.5%, p = 0.017), need of IMV (25.9% vs. 13.8, p < 0.001), and median hospital length of stay (14 days vs. 11 days, p < 0.001). Our results suggest that treatment with low-dose DXM for 10 days is superior to 3 days of high-dose MP pulses in preventing in-hospital mortality and need for ICU admission or IMV in severe, non-critically ill patients with COVID-19.

Our main aim was to describe the effect on the severity of ACEI (angiotensin-converting enzyme inhibitor) and ARB (angiotensin II receptor blocker) during COVID-19 hospitalization. A retrospective, observational, multicenter study evaluating hospitalized patients with COVID-19 treated with ACEI/ARB. The primary endpoint was the incidence of the composite outcome of prognosis (IMV (invasive mechanical ventilation), NIMV (non-invasive mechanical ventilation), ICU admission (intensive care unit), and/or all-cause mortality). We evaluated both outcomes in patients whose treatment with ACEI/ARB was continued or withdrawn. Between February and June 2020, 11,205 patients were included, mean age 67 years (SD = 16.3) and 43.1% female; 2162 patients received ACEI/ARB treatment. ACEI/ARB treatment showed lower all-cause mortality (p < 0.0001). Hypertensive patients in the ACEI/ARB group had better results in IMV, ICU admission, and the composite outcome of prognosis (p < 0.0001 for all). No differences were found in the incidence of major adverse cardiovascular events. Patients previously treated with ACEI/ARB continuing treatment during hospitalization had a lower incidence of the composite outcome of prognosis than those whose treatment was withdrawn (RR 0.67, 95%CI 0.63–0.76). ARB was associated with better survival than ACEI (HR 0.77, 95%CI 0.62–0.96). ACEI/ARB treatment during COVID-19 hospitalization was associated with protection on mortality. The benefits were greater in hypertensive, those who continued treatment, and those taking ARB.