Papel de la tomografía computerizada multidetector en la estrategia diagnóstica de la hemorragia digestiva baja aguda

Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Medicina. Fecha de lectura: 19 de enero de 200

The Impact of Different Lung Ultrasound Protocols in the Assessment of Lung Lesions in COVID-19 Patients: Is There an Ideal Lung Ultrasound Protocol?.

Background In the past months, several lung ultrasonography (LUS) protocols have been proposed, mainly on previously validated schemes independent of coronavirus disease 2019 (COVID-19). Objectives The main purpose of this study was to determine the impact and accuracy of different LUS protocols proposed in COVID-19. Methods Patients were evaluated with a standard sequence of LUS scans in 72 intercostal spaces along 14 anatomic lines in the chest. A scoring system of LUS findings was reported and then analyzed separately according to each proposed LUS protocol zones. This score was then correlated to a validated Pulmonary Inflammation Index (PII) on chest Computed Tomography (CT). Results Thirty-two patients were enrolled. The most frequent pattern was ground-glass opacities in the chest X-ray (53.1%), chest CT (59.1%) and subpleural or lobar consolidations (40.8%) in the posteroinferior areas (p < 0.001) on LUS. The Interclass Correlation Coefficient (ICC) was significantly correlated with almost every protocol analyzed except the 8-zone (p = 0.119) and the 10-zone protocol that only included one posterior point (p = 0.052). The highest ICC was obtained with a 12-zone protocol (ICC 0.500; p = 0.027) and decreased as more points were included. Conclusions In conclusion, our study results suggest that performing an ultrasound protocol with 12-zone scanning, including the superior and inferior areas of the anterior, lateral and posterior regions of the chest was consistent with higher ICC and higher degree of concordance with CT. We emphasize the need of a more standardization technique to further implement and develop this imaging modality in COVID-19post-print1035 K

Spatiotemporal Characteristics of the Largest HIV-1 CRF02_AG Outbreak in Spain: Evidence for Onward Transmissions

Background and Aim: The circulating recombinant form 02_AG (CRF02_AG) is the predominant clade among the human immunodeficiency virus type-1 (HIV-1) non-Bs with a prevalence of 5.97% (95% Confidence Interval-CI: 5.41–6.57%) across Spain. Our aim was to estimate the levels of regional clustering for CRF02_AG and the spatiotemporal characteristics of the largest CRF02_AG subepidemic in Spain.Methods: We studied 396 CRF02_AG sequences obtained from HIV-1 diagnosed patients during 2000–2014 from 10 autonomous communities of Spain. Phylogenetic analysis was performed on the 391 CRF02_AG sequences along with all globally sampled CRF02_AG sequences (N = 3,302) as references. Phylodynamic and phylogeographic analysis was performed to the largest CRF02_AG monophyletic cluster by a Bayesian method in BEAST v1.8.0 and by reconstructing ancestral states using the criterion of parsimony in Mesquite v3.4, respectively.Results: The HIV-1 CRF02_AG prevalence differed across Spanish autonomous communities we sampled from (p &lt; 0.001). Phylogenetic analysis revealed that 52.7% of the CRF02_AG sequences formed 56 monophyletic clusters, with a range of 2–79 sequences. The CRF02_AG regional dispersal differed across Spain (p = 0.003), as suggested by monophyletic clustering. For the largest monophyletic cluster (subepidemic) (N = 79), 49.4% of the clustered sequences originated from Madrid, while most sequences (51.9%) had been obtained from men having sex with men (MSM). Molecular clock analysis suggested that the origin (tMRCA) of the CRF02_AG subepidemic was in 2002 (median estimate; 95% Highest Posterior Density-HPD interval: 1999–2004). Additionally, we found significant clustering within the CRF02_AG subepidemic according to the ethnic origin.Conclusion: CRF02_AG has been introduced as a result of multiple introductions in Spain, following regional dispersal in several cases. We showed that CRF02_AG transmissions were mostly due to regional dispersal in Spain. The hot-spot for the largest CRF02_AG regional subepidemic in Spain was in Madrid associated with MSM transmission risk group. The existence of subepidemics suggest that several spillovers occurred from Madrid to other areas. CRF02_AG sequences from Hispanics were clustered in a separate subclade suggesting no linkage between the local and Hispanic subepidemics

Quantification of pulmonary opacities using artificial intelligence in chest CT scans during SARS-CoV-2 pandemic: validation and prognostic assessment

Abstract Purpose To assess whether the analysis of pulmonary opacities on chest CT scans by AI-RAD Companion, an artificial intelligence (AI) software, has any prognostic value. Background In December 2019, a new coronavirus named SARS-CoV-2 emerged in Wuhan, China, causing a global pandemic known as COVID-19. The disease initially presents with flu-like symptoms but can progress to severe respiratory distress, organ failure, and high mortality rates. The overwhelming influx of patients strained Emergency Rooms worldwide. To assist in diagnosing and categorizing pneumonia, AI algorithms using deep learning and convolutional neural networks were introduced. However, there is limited research on how applicable these algorithms are in the Emergency Room setting, and their practicality remains uncertain due to most studies focusing on COVID-19-positive patients only. Methods Our study has an observational, analytical, and longitudinal design. The sample consisted of patients who visited our emergency room from August 5, 2021, to September 9, 2021, were suspected of having COVID-19 pneumonia, and underwent a chest CT scan. They were categorized into COVID-19 negative and positive groups based on PCR confirmation. Lung opacities were evaluated separately by a team of radiologists and a commercial AI software called AI-Rad Companion (by Siemens Healthineers). After 5 months we gathered clinical data, such as hospital admission, intensive care unit (ICU) admission, death, and hospital stay. Results The final sample included 304 patients (144 females, 160 males) with a mean age of 68 ± 19 std. Among them, 129 tested negative for COVID-19 and 175 tested positive. We used AI-generated opacity quantification, compared to radiologists' reports, to create receiver operating characteristic curves. The area under the curve ranged from 0.8 to 0.9 with a 95% confidence interval. We then adjusted opacity tests to a sensitivity cut-off of 95%. We found a significant association between these opacity tests and hospital admission and ICU admission (Chi-Squared, P < 0.05), as well as between the percentage of lung opacities and length of hospital stay (Spearman's rho 0.53–0.54, P < 0.05) in both groups. Conclusions During the SARS-CoV-2 pandemic, AI-based opacity tests demonstrated an association with certain prognostic markers in patients with suspected COVID-19 pneumonia, regardless of whether a PCR-confirmed coronavirus infection was ultimately detected

A Cohort of Patients with COVID-19 in a Major Teaching Hospital in Europe

BACKGROUND: Since the confirmation of the first patient infected with SARS-CoV-2 in Spain in January 2020, the epidemic has grown rapidly, with the greatest impact on the region of Madrid. This article describes the first 2226 adult patients with COVID-19, consecutively admitted to La Paz University Hospital in Madrid. METHODS: Our cohort included all patients consecutively hospitalized who had a final outcome (death or discharge) in a 1286-bed hospital of Madrid (Spain) from 25 February (first case admitted) to 19 April 2020. The data were manually entered into an electronic case report form, which was monitored prior to the analysis. RESULTS: We consecutively included 2226 adult patients admitted to the hospital who either died (460) or were discharged (1766). The patients’ median age was 61 years, and 51.8% were women. The most common comorbidity was arterial hypertension (41.3%), and the most common symptom on admission was fever (71.2%). The median time from disease onset to hospital admission was 6 days. The overall mortality was 20.7% and was higher in men (26.6% vs. 15.1%). Seventy-five patients with a final outcome were transferred to the intensive care unit (ICU) (3.4%). Most patients admitted to the ICU were men, and the median age was 64 years. Baseline laboratory values on admission were consistent with an impaired immune-inflammatory profile. CONCLUSIONS: We provide a description of the first large cohort of hospitalized patients with COVID-19 in Europe. Advanced age, male sex, the presence of comorbidities and abnormal laboratory values were more common among the patients with fatal outcomes

Discovering HIV related information by means of association rules and machine learning

Acquired immunodeficiency syndrome (AIDS) is still one of the main health problems worldwide. It is therefore essential to keep making progress in improving the prognosis and quality of life of affected patients. One way to advance along this pathway is to uncover connections between other disorders associated with HIV/AIDS-so that they can be anticipated and possibly mitigated. We propose to achieve this by using Association Rules (ARs). They allow us to represent the dependencies between a number of diseases and other specific diseases. However, classical techniques systematically generate every AR meeting some minimal conditions on data frequency, hence generating a vast amount of uninteresting ARs, which need to be filtered out. The lack of manually annotated ARs has favored unsupervised filtering, even though they produce limited results. In this paper, we propose a semi-supervised system, able to identify relevant ARs among HIV-related diseases with a minimal amount of annotated training data. Our system has been able to extract a good number of relationships between HIV-related diseases that have been previously detected in the literature but are scattered and are often little known. Furthermore, a number of plausible new relationships have shown up which deserve further investigation by qualified medical experts

Delaying surgery for patients with a previous SARS-CoV-2 infection

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