To assess the efficacy of abatacept (ABA) in RA patients with interstitial lung disease (ILD) (RA-ILD).
This was an observational, multicentre study of RA-ILD patients treated with at least one dose ...of ABA. ILD was diagnosed by high-resolution CT (HRCT). We analysed the following variables at baseline (ABA initiation), 12 months and at the end of the follow-up: Modified Medical Research Council (MMRC) scale (1-point change), forced vital capacity (FVC) or diffusion lung capacity for carbon monoxide (DLCO) (improvement or worsening ≥10%), HRCT, DAS on 28 joints evaluated using the ESR (DAS28ESR) and CS-sparing effect.
We studied 263 RA-ILD patients 150 women/113 men; mean (s.d.) age 64.6 (10) years. At baseline, they had a median duration of ILD of 1 (interquartile range 0.25-3.44) years, moderate or severe degree of dyspnoea (MMRC grade 2, 3 or 4) (40.3%), FVC (% of the predicted) mean (s.d.) 85.9 (21.8)%, DLCO (% of the predicted) 65.7 (18.3) and DAS28ESR 4.5 (1.5). The ILD patterns were: usual interstitial pneumonia (UIP) (40.3%), non-specific interstitial pneumonia (NSIP) (31.9%) and others (27.8%). ABA was prescribed at standard dose, i.v. (25.5%) or s.c. (74.5%). After a median follow-up of 12 (6-36) months the following variables did not show worsening: dyspnoea (MMRC) (91.9%); FVC (87.7%); DLCO (90.6%); and chest HRCT (76.6%). A significant improvement of DAS28ESR from 4.5 (1.5) to 3.1 (1.3) at the end of follow-up (P < 0.001) and a CS-sparing effect from a median 7.5 (5-10) to 5 (2.5-7.5) mg/day at the end of follow-up (P < 0.001) was also observed. ABA was withdrawn in 62 (23.6%) patients due to adverse events (n = 30), articular inefficacy (n = 27), ILD worsening (n = 3) and other causes (n = 2).
ABA may be an effective and safe treatment for patients with RA-ILD.
Abstract
Background
The effects of cardiometabolic drugs on the prognosis of diabetic patients with COVID-19, especially very old patients, are not well known. This work was aimed to analyze the ...association between preadmission cardiometabolic therapy (antidiabetic, antiaggregant, antihypertensive, and lipid-lowering drugs) and in-hospital mortality among patients ≥80 years with type 2 diabetes mellitus (T2DM) hospitalized for COVID-19.
Method
We conducted a nationwide, multicenter, observational study in patients ≥80 years with T2DM hospitalized for COVID-19 between March 1 and May 29, 2020. The primary outcome measure was in-hospital mortality. A multivariate logistic regression analysis was performed to assess the association between preadmission cardiometabolic therapy and in-hospital mortality.
Results
Of the 2 763 patients ≥80 years old hospitalized due to COVID-19, 790 (28.6%) had T2DM. Of these patients, 385 (48.7%) died during admission. On the multivariate analysis, the use of dipeptidyl peptidase-4 inhibitors (adjusted odds ratio AOR 0.502, 95% confidence interval CI: 0.309–0.815, p = .005) and angiotensin receptor blockers (AOR 0.454, 95% CI: 0.274–0.759, p = .003) were independent protectors against in-hospital mortality, whereas the use of acetylsalicylic acid was associated with higher in-hospital mortality (AOR 1.761, 95% CI: 1.092–2.842, p = .020). Other antidiabetic drugs, angiotensin-converting enzyme inhibitors, and statins showed neutral association with in-hospital mortality.
Conclusions
We found important differences between cardiometabolic drugs and in-hospital mortality in older patients with T2DM hospitalized for COVID-19. Preadmission treatment with dipeptidyl peptidase-4 inhibitors and angiotensin receptor blockers could reduce in-hospital mortality; other antidiabetic drugs, angiotensin-converting enzyme inhibitors, and statins seem to have a neutral effect; and acetylsalicylic acid could be associated with excess mortality.
We aimed to develop and validate a prediction model, based on clinical history and examination findings on initial diagnosis of coronavirus disease 2019 (COVID-19), to identify patients at risk of ...critical outcomes.
We used data from the SEMI-COVID-19 Registry, a cohort of consecutive patients hospitalized for COVID-19 from 132 centres in Spain (23rd March to 21st May 2020). For the development cohort, tertiary referral hospitals were selected, while the validation cohort included smaller hospitals. The primary outcome was a composite of in-hospital death, mechanical ventilation, or admission to intensive care unit. Clinical signs and symptoms, demographics, and medical history ascertained at presentation were screened using least absolute shrinkage and selection operator, and logistic regression was used to construct the predictive model.
There were 10 433 patients, 7850 in the development cohort (primary outcome 25.1%, 1967/7850) and 2583 in the validation cohort (outcome 27.0%, 698/2583). The PRIORITY model included: age, dependency, cardiovascular disease, chronic kidney disease, dyspnoea, tachypnoea, confusion, systolic blood pressure, and SpO2 ≤93% or oxygen requirement. The model showed high discrimination for critical illness in both the development (C-statistic 0.823; 95% confidence interval (CI) 0.813, 0.834) and validation (C-statistic 0.794; 95%CI 0.775, 0.813) cohorts. A freely available web-based calculator was developed based on this model (https://www.evidencio.com/models/show/2344).
The PRIORITY model, based on easily obtained clinical information, had good discrimination and generalizability for identifying COVID-19 patients at risk of critical outcomes.
Behavioral strategies are a primary focus in the study of Middle Paleolithic assemblages. Since the emergence of the processual paradigma, this research has been partly based on the use of ...interpretive frameworks derived from ethnoarcheological sources. However, this approach is flawed by the lack of correspondence between the time scale of the ethnographic information and the time scale of the archeological record. This paper presents the lithic assemblage from level J (ca. 50 ka BP), one of the Middle Paleolithic layers excavated in the Abric Romaní (Capellades, Spain). The study of this assemblage has been carried out from a spatio-temporal perspective, trying to discern two different time scales involved in the formation of the archeological record: the geological time scale of the assemblage-as-a-whole and the ethnographic time scale of the individual events. The results suggest that several domains of lithic variability, like raw material provisioning, artifact transport and spatial patterns, are time-dependent and should be approached taking into account the temporal depth of the archeological assemblages.
Celiac disease (CeD) is an autoimmune condition triggered by gluten in genetically predisposed individuals, affecting all ages. Intestinal permeability (IP) is crucial in the pathogenesis of CeD and ...it is primarily governed by tight junctions (TJs) that uphold the intestinal barrier's integrity. The protein zonulin plays a critical role in modulating the permeability of TJs having emerged as a potential non-invasive biomarker to study IP. The importance of this study lies in providing evidence for the usefulness of a non-invasive tool in the study of IP both at baseline and in the follow-up of paediatric patients with CeD. In this single-centre prospective observational study, we explored the correlation between faecal zonulin levels and others faecal and serum biomarkers for monitoring IP in CeD within the paediatric population. We also aimed to establish reference values for faecal zonulin in the paediatric population. We found that faecal zonulin and calprotectin values are higher at the onset of CeD compared with the control population. Specifically, the zonulin levels were 347.5 ng/mL as opposed to 177.7 ng/mL in the control population (
= 0.001), while calprotectin levels were 29.8 μg/g stool compared to 13.9 μg/g stool (
= 0.029). As the duration without gluten consumption increased, a significant reduction in faecal zonulin levels was observed in patients with CeD (348.5 ng/mL vs. 157.1 ng/mL;
= 0.002), along with a decrease in the prevalence of patients with vitamin D insufficiency (88.9% vs. 77.8%). We conclude that faecal zonulin concentrations were higher in the patients with active CeD compared with healthy individuals or those following a gluten-free diet (GFD). The significant decrease in their values over the duration of the GFD suggests the potential use of zonulin as an additional tool in monitoring adherence to a GFD.
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local ...areas, hyperspectral technology of small dimensions is the ideal solution. This research explores the use of encoded hyperspectral signatures to develop automated classifiers capable of discriminating between polluted and clean water and distinguishing between various types of oil. The overall objective is to leverage these classifiers to be able to improve the performance of conventional systems that rely solely on hyperspectral imagery. The acquisition of the hyperspectral signatures of water and hydrocarbons was carried out with a spectroradiometer. The range of the spectroradiometer used in this study covers the ranges between 350–1000 (visible near-infrared) and 1000–2500 (short-wavelength infrared). This gives detailed information regarding the targets of interest. Different neural autoencoders (AEs) have been developed to reduce inputs into different dimensions, from 1 to 15. Each of these encoded sets was used to train decision tree (DT) classifiers. The results are very promising, as they show that the AE models encoded data with correlation coefficients above 0.95. The classifiers trained with the different sets provide accuracies close to 1.
Abstract
Background
Advanced age is a well-known risk factor for poor prognosis in COVID-19. However, few studies have specifically focused on very old inpatients with COVID-19. This study aims to ...describe the clinical characteristics of very old inpatients with COVID-19 and identify risk factors for in-hospital mortality at admission.
Methods
We conducted a nationwide, multicenter, retrospective, observational study in patients ≥ 80 years hospitalized with COVID-19 in 150 Spanish hospitals (SEMI-COVID-19) Registry (March 1–May 29, 2020). The primary outcome was in-hospital mortality. A uni- and multivariate logistic regression was performed to assess predictors of mortality at admission.
Results
A total of 2772 consecutive patients (49.4% men, median age 86.3 years) were analyzed. Rates of atherosclerotic cardiovascular disease, diabetes mellitus, dementia, and Barthel Index < 60 were 30.8%, 25.6%, 30.5%, and 21.0%, respectively. The overall case-fatality rate was 46.9% (n: 1301) and increased with age (80–84 years: 41.6%; 85–90 years: 47.3%; 90–94 years: 52.7%; ≥95 years: 54.2%). After analysis, male sex and moderate-to-severe dependence were independently associated with in-hospital mortality; comorbidities were not predictive. At admission, independent risk factors for death were: oxygen saturation < 90%; temperature ≥ 37.8°C; quick sequential organ failure assessment (qSOFA) score ≥ 2; and unilateral–bilateral infiltrates on chest x-rays. Some analytical findings were independent risk factors for death, including estimated glomerular filtration rate < 45 mL/min/1.73 m2; lactate dehydrogenase ≥ 500 U/L; C-reactive protein ≥ 80 mg/L; neutrophils ≥ 7.5 × 103/μL; lymphocytes < 0.8 × 103/μL; and monocytes < 0.5 × 103/μL.
Conclusions
This first large, multicenter cohort of very old inpatients with COVID-19 shows that age, male sex, and poor preadmission functional status—not comorbidities—are independently associated with in-hospital mortality. Severe COVID-19 at admission is related to poor prognosis.
Predicting the levels of a pollutant in a given area is an open problem, mainly because historical data are typically available at certain locations, where monitoring stations are located, but not at ...all locations in the area. This work presents an approach based on developing predictions at each of the points where an immission station is available; in this case, based on shallow Artificial Neural Networks, ANNs, and then using a simple geostatistical interpolation algorithm (Inverse Distance Weighted, IDW), a pollutant map is constructed over the entire study area, thus providing predictions at each point in the plane. The ANN models are designed to make 1 h ahead and 4 h ahead predictions, using an autoregressive scheme as inputs (in the case of 4 h ahead as a jumping strategy). The results are then compared using the Friedman and Bonferroni tests to select the best model at each location, and predictions are made with all the best models. In general, to the 1 h ahead prediction models, the optimal models typically have fewer neurons and require minimal historical data. For instance, the best model in Algeciras has an R of almost 0.89 and consists of 1 hidden neuron and 3 to 5 lags, similar to Colegio Los Barrios. In the case of 4h ahead prediction, Colegio Carteya station shows the best model, with an R of almost 0.89 and a MSE of less than 240, including 5 hidden neurons and different lags from the past. The results are sufficiently adequate, especially in the case of predictions 4 h into the future. The aim is to integrate the models into a tool for citizens and administrations to make decisions.
Patients with systemic sclerosis (SSc) are at increased risk of cancer, a growing cause of non–SSc-related death among these patients. We analyzed the increased cancer risk among Spanish patients ...with SSc using standardized incidence ratios (SIRs) and identified independent cancer risk factors in this population.
Spanish Scleroderma Registry data were analyzed to determine the demographic characteristics of patients with SSc, and logistic regression was used to identify cancer risk factors. SIRs with 95% confidence intervals (CIs) relative to the general Spanish population were calculated.
Of 1930 patients with SSc, 206 had cancer, most commonly breast, lung, hematological, and colorectal cancers. Patients with SSc had increased risks of overall cancer (SIR 1.48, 95% CI 1.36–1.60; P < 0.001), and of lung (SIR 2.22, 95% CI 1.77–2.73; P < 0.001), breast (SIR 1.31, 95% CI 1.10–1.54; P = 0.003), and hematological (SIR 2.03, 95% CI 1.52–2.62; P < 0.001) cancers. Cancer was associated with older age at SSc onset (odds ratio OR 1.22, 95% CI 1.01–1.03; P < 0.001), the presence of primary biliary cholangitis (OR 2.35, 95% CI 1.18–4.68; P = 0.015) and forced vital capacity <70% (OR 1.8, 95% CI 1.24–2.70; P = 0.002). The presence of anticentromere antibodies lowered the risk of cancer (OR 0.66, 95% CI 0.45–0.97; P = 0.036).
Spanish patients with SSc had an increased cancer risk compared with the general population. Some characteristics, including specific autoantibodies, may be related to this increased risk.
•Systemic sclerosis patients have increased risk of lung, breast, and blood cancer.•Primary biliary cholangitis is linked to a 6-fold greater risk of breast cancer.•Moderate or severe interstitial lung disease is linked to a higher risk of cancer.•Anti-centromere antibodies are associated with a lower risk of cancer.
Smoking can play a key role in SARS-CoV-2 infection and in the course of the disease. Previous studies have conflicting or inconclusive results on the prevalence of smoking and the severity of the ...coronavirus disease (COVID-19).
Observational, multicenter, retrospective cohort study of 14,260 patients admitted for COVID-19 in Spanish hospitals between February and September 2020. Their clinical characteristics were recorded and the patients were classified into a smoking group (active or former smokers) or a non-smoking group (never smokers). The patients were followed up to one month after discharge. Differences between groups were analyzed. A multivariate logistic regression and Kapplan Meier curves analyzed the relationship between smoking and in-hospital mortality.
The median age was 68.6 (55.8-79.1) years, with 57.7% of males. Smoking patients were older (69.9 59.6-78.0 years), more frequently male (80.3%) and with higher Charlson index (4 2-6) than non-smoking patients. Smoking patients presented a worse evolution, with a higher rate of admission to the intensive care unit (ICU) (10.4 vs 8.1%), higher in-hospital mortality (22.5 vs. 16.4%) and readmission at one month (5.8 vs. 4.0%) than in non-smoking patients. After multivariate analysis, smoking remained associated with these events.
Active or past smoking is an independent predictor of poor prognosis in patients with COVID-19. It is associated with higher ICU admissions and in-hospital mortality.
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