117 research outputs found

    Model type II regression for lagrangian validation of HF radar velocities in the NW Iberian Peninsula

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    Two designs of lagrangian low-cost drifting buoys have been developed in order to monitor the ocean surface dynamics in the North-west Iberian Peninsula and provide ground-truth observations that can be used to assess the performance of High Frequency (HF) Radars of RAIA observatory from 2020 to 2022. Since regression model type I, which is typically used in buoy-HF radar antennas validations, does not consider the presence of errors in the observations from both instruments, regression model type II was proposed to instrument intercomparison. Furthermore, a new metric was developed to better assess both model types regressions in lagrangian validations.Peer Reviewe

    Older Adult Patients in the Emergency Department: Which Patients should be Selected for a Different Approach?

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    Background: While multidimensional and interdisciplinary assessment of older adult patients improves their short-term outcomes after evaluation in the emergency department (ED), this assessment is time-consuming and ill-suited for the busy environment. Thus, identifying patients who will benefit from this strategy is challenging. Therefore, this study aimed to identify older adult patients suitable for a different ED approach as well as independent variables associated with poor short-term clinical outcomes. Methods: We included all patients >= 65 years attending 52 EDs in Spain over 7 days. Sociodemographic, comorbidity, and baseline functional status data were collected. The outcomes were 30 -day mortality, re -presentation, hospital readmission, and the composite of all outcomes. Results: During the study among 96,014 patients evaluated in the ED, we included 23,338 patients >= 65 years-mean age, 78.4 +/- 8.1 years; 12,626 (54.1%) women. During follow-up, 5,776 patients (24.75%) had poor outcomes after evaluation in the ED: 1,140 (4.88%) died, 4,640 (20.51) returned to the ED, and 1,739 (7.69%) were readmitted 30 days after discharge following the index visit. A model including male sex, age >= 75 years, arrival by ambulance, Charlson Comorbidity Index >= 3, and functional impairment had a C -index of 0.81 (95% confidence interval, 0.80-0.82) for 30 -day mortality. Conclusion: Male sex, age >= 75 years, arrival by ambulance, functional impairment, or severe comorbidity are features of patients who could benefit from approaches in the ED different from the common triage to improve the poor short-term outcomes of this population

    Clinical validation of risk scoring systems to predict risk of delayed bleeding after EMR of large colorectal lesions

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    [Background and Aims]: The Endoscopic Resection Group of the Spanish Society of Endoscopy (GSEED-RE) model and the Australian Colonic Endoscopic Resection (ACER) model were proposed to predict delayed bleeding (DB) after EMR of large superficial colorectal lesions, but neither has been validated. We validated and updated these models.[Methods]: A multicenter cohort study was performed in patients with nonpedunculated lesions ≥20 mm removed by EMR. We assessed the discrimination and calibration of the GSEED-RE and ACER models. Difficulty performing EMR was subjectively categorized as low, medium, or high. We created a new model, including factors associated with DB in 3 cohort studies.[Results]: DB occurred in 45 of 1034 EMRs (4.5%); it was associated with proximal location (odds ratio [OR], 2.84; 95% confidence interval [CI], 1.31-6.16), antiplatelet agents (OR, 2.51; 95% CI, .99-6.34) or anticoagulants (OR, 4.54; 95% CI, 2.14-9.63), difficulty of EMR (OR, 3.23; 95% CI, 1.41-7.40), and comorbidity (OR, 2.11; 95% CI, .99-4.47). The GSEED-RE and ACER models did not accurately predict DB. Re-estimation and recalibration yielded acceptable results (GSEED-RE area under the curve [AUC], .64 [95% CI, .54-.74]; ACER AUC, .65 [95% CI, .57-.73]). We used lesion size, proximal location, comorbidity, and antiplatelet or anticoagulant therapy to generate a new model, the GSEED-RE2, which achieved higher AUC values (.69-.73; 95% CI, .59-.80) and exhibited lower susceptibility to changes among datasets.[Conclusions]: The updated GSEED-RE and ACER models achieved acceptable prediction levels of DB. The GSEED-RE2 model may achieve better prediction results and could be used to guide the management of patients after validation by other external groups. (Clinical trial registration number: NCT 03050333.)Research support for this study was received from “La Caixa/Caja Navarra” Foundation (ID 100010434;project PR15/11100006)

    Role of age and comorbidities in mortality of patients with infective endocarditis

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    [Purpose]: The aim of this study was to analyse the characteristics of patients with IE in three groups of age and to assess the ability of age and the Charlson Comorbidity Index (CCI) to predict mortality. [Methods]: Prospective cohort study of all patients with IE included in the GAMES Spanish database between 2008 and 2015.Patients were stratified into three age groups:<65 years,65 to 80 years,and ≥ 80 years.The area under the receiver-operating characteristic (AUROC) curve was calculated to quantify the diagnostic accuracy of the CCI to predict mortality risk. [Results]: A total of 3120 patients with IE (1327 < 65 years;1291 65-80 years;502 ≥ 80 years) were enrolled.Fever and heart failure were the most common presentations of IE, with no differences among age groups.Patients ≥80 years who underwent surgery were significantly lower compared with other age groups (14.3%,65 years; 20.5%,65-79 years; 31.3%,≥80 years). In-hospital mortality was lower in the <65-year group (20.3%,<65 years;30.1%,65-79 years;34.7%,≥80 years;p < 0.001) as well as 1-year mortality (3.2%, <65 years; 5.5%, 65-80 years;7.6%,≥80 years; p = 0.003).Independent predictors of mortality were age ≥ 80 years (hazard ratio [HR]:2.78;95% confidence interval [CI]:2.32–3.34), CCI ≥ 3 (HR:1.62; 95% CI:1.39–1.88),and non-performed surgery (HR:1.64;95% CI:11.16–1.58).When the three age groups were compared,the AUROC curve for CCI was significantly larger for patients aged <65 years(p < 0.001) for both in-hospital and 1-year mortality. [Conclusion]: There were no differences in the clinical presentation of IE between the groups. Age ≥ 80 years, high comorbidity (measured by CCI),and non-performance of surgery were independent predictors of mortality in patients with IE.CCI could help to identify those patients with IE and surgical indication who present a lower risk of in-hospital and 1-year mortality after surgery, especially in the <65-year group

    Treatment with tocilizumab or corticosteroids for COVID-19 patients with hyperinflammatory state: a multicentre cohort study (SAM-COVID-19)

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    Objectives: The objective of this study was to estimate the association between tocilizumab or corticosteroids and the risk of intubation or death in patients with coronavirus disease 19 (COVID-19) with a hyperinflammatory state according to clinical and laboratory parameters. Methods: A cohort study was performed in 60 Spanish hospitals including 778 patients with COVID-19 and clinical and laboratory data indicative of a hyperinflammatory state. Treatment was mainly with tocilizumab, an intermediate-high dose of corticosteroids (IHDC), a pulse dose of corticosteroids (PDC), combination therapy, or no treatment. Primary outcome was intubation or death; follow-up was 21 days. Propensity score-adjusted estimations using Cox regression (logistic regression if needed) were calculated. Propensity scores were used as confounders, matching variables and for the inverse probability of treatment weights (IPTWs). Results: In all, 88, 117, 78 and 151 patients treated with tocilizumab, IHDC, PDC, and combination therapy, respectively, were compared with 344 untreated patients. The primary endpoint occurred in 10 (11.4%), 27 (23.1%), 12 (15.4%), 40 (25.6%) and 69 (21.1%), respectively. The IPTW-based hazard ratios (odds ratio for combination therapy) for the primary endpoint were 0.32 (95%CI 0.22-0.47; p < 0.001) for tocilizumab, 0.82 (0.71-1.30; p 0.82) for IHDC, 0.61 (0.43-0.86; p 0.006) for PDC, and 1.17 (0.86-1.58; p 0.30) for combination therapy. Other applications of the propensity score provided similar results, but were not significant for PDC. Tocilizumab was also associated with lower hazard of death alone in IPTW analysis (0.07; 0.02-0.17; p < 0.001). Conclusions: Tocilizumab might be useful in COVID-19 patients with a hyperinflammatory state and should be prioritized for randomized trials in this situatio

    The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the Extended Baryon Oscillation Spectroscopic Survey and from the Second Phase of the Apache Point Observatory Galactic Evolution Experiment

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    The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since 2014 July. This paper describes the second data release from this phase, and the 14th from SDSS overall (making this Data Release Fourteen or DR14). This release makes the data taken by SDSS-IV in its first two years of operation (2014–2016 July) public. Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey; the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data-driven machine-learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from the SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS web site (www.sdss.org) has been updated for this release and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020 and will be followed by SDSS-V
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