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INTRODUCTION: Arterial spin labeling (ASL) is a functional neuroimaging technique that has been frequently used to investigate acute pain states. A major advantage of ASL as opposed to blood-oxygen-level-dependent functional neuroimaging is its applicability for low-frequency designs. As such, ASL represents an interesting option for studies in which repeating an experimental event would reduce its ecological validity. Whereas most ASL pain studies so far have used thermal stimuli, to our knowledge, no ASL study so far has investigated pain responses to sharp mechanical pain. METHODS: As a proof of concept, we investigated whether ASL has the sensitivity to detect brain activation within core areas of the nociceptive network in healthy controls following a single stimulation block based on 96 s of mechanical painful stimulation using a blunt blade. RESULTS: We found significant increases in perfusion across many regions of the nociceptive network such as primary and secondary somatosensory cortices, premotor cortex, posterior insula, inferior parietal cortex, parietal operculum, temporal gyrus, temporo-occipital lobe, putamen, and the cerebellum. Contrary to our hypothesis, we did not find any significant increase within ACC, thalamus, or PFC. Moreover, we were able to detect a significant positive correlation between pain intensity ratings and pain-induced perfusion increase in the posterior insula. CONCLUSION: We demonstrate that ASL is suited to investigate acute pain in a single event paradigm, although to detect activation within some regions of the nociceptive network, the sensitivity of our paradigm seemed to be limited. Regarding the posterior insula, our paradigm was sensitive enough to detect a correlation between pain intensity ratings and pain-induced perfusion increase. Previous experimental pain studies have proposed that intensity coding in this region may be restricted to thermal stimulation. Our result demonstrates that the posterior insula encodes intensity information for mechanical stimuli as well.
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Circulación Cerebrovascular , Dolor , Encéfalo/fisiología , Circulación Cerebrovascular/fisiología , Humanos , Imagen por Resonancia Magnética/métodos , Dolor/diagnóstico por imagen , Lóbulo Parietal/fisiología , Marcadores de SpinRESUMEN
Objectives: To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions. Design: Retrospective cohort study. Setting: The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe. Participants: Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2. Primary and secondary outcome measures: Patients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction. Results: Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites. Conclusions: Laboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.
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Ventilation heterogeneity is frequent in bronchial asthma and can be assessed using multiple breath wash-out testing (MBW). Most data is available in paediatric patients and using nitrogen as a tracer gas. We aimed to evaluate sulphur hexafluoride (SF6) MBW in adult asthmatics. Spirometry, whole-body plethysmography, impulse oscillometry and SF6-MBW were prospectively performed. MBW parameters reflecting global (lung clearance index, LCI), acinar (Sacin) and conductive (Scond) ventilation heterogeneity were derived from three consecutive wash-outs. LCI was calculated for the traditional 2.5% and an earlier 5% stopping point that has the potential to reduce wash-out times. 91 asthmatics (66%) and 47 non-asthmatic controls (34%) were included in final analysis. LCI2.5 and LCI5 were higher in asthmatics (p < 0.001). Likewise, Sacin and Scond were elevated (p < 0.001 and p < 0.01). Coefficient of variation was 3.4% for LCI2.5 and 3.5% for LCI5 in asthmatics. Forty-one asthmatic patients had normal spirometry. ROC analysis revealed an AUC of 0.906 for the differentiation from non-asthmatic controls exceeding diagnostic performance of individual and conventional parameters (AUC = 0.819, p < 0.05). SF6-MBW is feasible and reproducible in adult asthmatics. Ventilation heterogeneity is increased as compared to non-asthmatic controls persisting in asthmatic patients with normal spirometry. Diagnostic performance is not affected using an earlier LCI stopping point while reducing wash-out duration considerably.
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Ventilación Pulmonar/fisiología , Pruebas de Función Respiratoria/métodos , Hexafluoruro de Azufre/metabolismo , Adulto , Anciano , Asma/diagnóstico , Asma/metabolismo , Asma/fisiopatología , Pruebas Respiratorias/métodos , Estudios de Factibilidad , Femenino , Humanos , Pulmón/metabolismo , Masculino , Persona de Mediana Edad , Respiración , Espirometría/métodosRESUMEN
This study aimed to investigate whether the differences in pain perception between patients with borderline personality disorder (BPD) and healthy subjects (HCs) can be explained by differences in the glutamate/GABA ratio in the posterior insula. In total, 29 BPD patients and 31 HCs were included in the statistical analysis. Mechanical pain sensitivity was experimentally assessed with pinprick stimuli between 32 and 512 mN on a numeric rating scale. The metabolites were measured in the right posterior insula using the MEshcher-GArwood Point-RESolved Spectroscopy sequence for single-voxel magnetic resonance spectroscopy (1H-MRS). The 256- and the 512-mN pinprick stimuli were perceived as significantly less painful by the BPD patient group compared with HCs. No differences were found between groups for the glutamate/GABA ratios. A positive correlation between the glutamate/GABA ratio and the pain intensity ratings to 256- and 512-mN pinpricks could be found in the combined and in the HC group. In the BPD patient group, the correlations between the glutamate/GABA ratio and the pain intensity ratings to 256- and 512-mN pinpricks did not reach significance. In conclusion, the study showed that individual differences in pain perception may in part be explained by the individual glutamate/GABA ratio in the posterior insula. However, this possible mechanism does not explain the differences in pain perception between BPD patients and HCs.
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Trastorno de Personalidad Limítrofe/metabolismo , Ácido Glutámico/metabolismo , Percepción del Dolor/fisiología , Dolor/metabolismo , Ácido gamma-Aminobutírico/metabolismo , Adolescente , Adulto , Trastorno de Personalidad Limítrofe/complicaciones , Mapeo Encefálico , Femenino , Humanos , Persona de Mediana Edad , Umbral del Dolor/fisiología , Salud de la Mujer , Adulto JovenRESUMEN
The Demonstrator study aims to analyse comorbidities and rare diseases among patients from German university hospitals within the German Medical Informatics Initiative. This work aimed to design and determine the feasibility of a model to assess the quality of the claims data used in the study. Several data quality issues were identified affecting small amounts of cases in one of the participating sites. As a next step an extension to all participating sites is planned.
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Exactitud de los Datos , Informática Médica , Hospitales Universitarios , HumanosRESUMEN
INTRODUCTION: Data quality (DQ) is an important prerequisite for secondary use of electronic health record (EHR) data in clinical research, particularly with regards to progressing towards a learning health system, one of the MIRACUM consortium's goals. Following the successful integration of the i2b2 research data repository in MIRACUM, we present a standardized and generic DQ framework. STATE OF THE ART: Already established DQ evaluation methods do not cover all of MIRACUM's requirements. CONCEPT: A data quality analysis plan was developed to assess common data quality dimensions for demographic-, condition-, procedure- and department-related variables of MIRACUM's research data repository. IMPLEMENTATION: A data quality analysis (DQA) tool was developed using R scripts packaged in a Docker image with all the necessary dependencies and R libraries for easy distribution. It integrates with the i2b2 data repository at each MIRACUM site, executes an analysis on the data and generates a DQ report. LESSONS LEARNED: Our DQA tool brings the analysis to the data and thus meets the MIRACUM data protection requirements. It evaluates established DQ dimensions of data repositories in a standardized and easily distributable way. This analysis allowed us to reveal and revise inconsistencies in earlier versions of the ETL jobs. The framework is portable, easy to deploy across different sites and even further adaptable to other database schemes. CONCLUSION: The presented framework provides the first step towards a unified, standardized and harmonized EHR DQ assessment in MIRACUM. DQ issues can now be systematically identified by individual hospitals to subsequently implement site- or consortium-wide feedback loops to increase data quality.