scholarly journals Generalizable EHR-R-REDCap pipeline for a national multi-institutional rare tumor patient registry

JAMIA Open ◽  
2022 ◽  
Vol 5 (1) ◽  
Author(s):  
Sophia Z Shalhout ◽  
Farees Saqlain ◽  
Kayla Wright ◽  
Oladayo Akinyemi ◽  
David M Miller
Keyword(s):  
Large Scale ◽  
Clinical Laboratory ◽  
Laboratory Data ◽  
National Registry ◽  
Clinical Informatics ◽  
Patient Registry ◽  
Real World Data ◽  
Tumor Patient ◽  
Data Quality Assessment ◽  
National Patient

Abstract Objective To develop a clinical informatics pipeline designed to capture large-scale structured Electronic Health Record (EHR) data for a national patient registry. Materials and Methods The EHR-R-REDCap pipeline is implemented using R statistical software to remap and import structured EHR data into the Research Electronic Data Capture (REDCap)-based multi-institutional Merkel Cell Carcinoma (MCC) Patient Registry using an adaptable data dictionary. Results Clinical laboratory data were extracted from EPIC Clarity across several participating institutions. Laboratory values (Labs) were transformed, remapped, and imported into the MCC registry using the EHR labs abstraction (eLAB) pipeline. Forty-nine clinical tests encompassing 482 450 results were imported into the registry for 1109 enrolled MCC patients. Data-quality assessment revealed highly accurate, valid labs. Univariate modeling was performed for labs at baseline on overall survival (N = 176) using this clinical informatics pipeline. Conclusion We demonstrate feasibility of the facile eLAB workflow. EHR data are successfully transformed and bulk-loaded/imported into a REDCap-based national registry to execute real-world data analysis and interoperability.

scholarly journals Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

2021 ◽  
Vol 10 (21) ◽  
pp. 5160
Author(s):  
Egesta Lopci
Keyword(s):  
Large Scale ◽  
Clinical Laboratory ◽  
Scale Validation ◽  
Checkpoint Inhibitors ◽  
Laboratory Data ◽  
Major Change ◽  
New Drugs ◽  
Response Criteria ◽  
Clinical Implementation ◽  
Pet Ct

Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

scholarly journals Characteristics of patients infected with SARS COVID-19 admitted at COVID health facilities in one of the aspirational district of India: a retrospective study

2020 ◽  
Vol 7 (11) ◽  
pp. 4435
Author(s):  
Ekta Sharma ◽  
Gurmeet Katoch ◽  
Rajesh Guleri ◽  
Jalam Bhardwaj
Keyword(s):  
Large Scale ◽  
Clinical Laboratory ◽  
Descriptive Analysis ◽  
Laboratory Data ◽  
Age Groups ◽  
The Elderly ◽  
Categorical Variables ◽  
Close Monitoring ◽  
Continuous Variables ◽  
Wide Range

Background: COVID-19 is the third corona virus that has emerged among the human population in the last two decades. The main aim of this study was to describe the epidemiologic features, clinical presentation of first 52 patients diagnosed with polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection admitted at COVID health facilities.Methods: A retrospective descriptive study was conducted over a period of three months from 1st April 2020 to 30th June 2020. We obtained demographic, epidemiological, clinical, laboratory data from the medical records of patients infected with SARS-Cov-2. The categorical variables were expressed in terms of frequency and percentages and the continuous variables were expressed as mean and standard deviation. In addition to descriptive analysis, Pearson’s chi- square test was applied to ascertain the associations between certain variables.Results: The mean age of participants was 29±11.67 years with a male preponderance. Forty three (83%) patients had travel history within India in the previous 30 days i.e. from Delhi (35%), Haryana (15%), Tamilnadu (11%), Himachal Pradesh (8%), Maharashtra (1.9%), Punjab (8%), and Uttar Pradesh (4%). Majority of the patients (90%) were asymptomatic. The age group of 21-30 years was the most affected group (44%) as comparison to the other age groups. No mortality was reported and 100% recovery rate was found.Conclusions: In conclusion, COVID-19 affects a wide-range of patients, from youth to the elderly.  In this study, all the COVID-19 infected patients were classified as mild as most were asymptomatic. Close monitoring and large-scale control strategies will be needed to prevent widespread transmission within the community.

PP119 How Much Evidence Is Enough For Action – ‘Adaptive Approach’ Helps?

2018 ◽  
Vol 34 (S1) ◽  
pp. 111-112
Author(s):  
Raoh-Fang Pwu ◽  
Grace Wu ◽  
Wen-Wen Yang
Keyword(s):  
Hepatitis C ◽  
Large Scale ◽  
Care Program ◽  
National Registry ◽  
Published Data ◽  
Real World Data ◽  
Target Number ◽  
Prevalence Survey ◽  
Adaptive Approach ◽  
Number Of Patients

Introduction:Aiming for hepatitis C elimination by 2030, Taiwan has set up a mid-term goal of “over 50 percent of patients treated by 2025.” Among various aspects of evidence that are needed, the target number to be treated is difficult to estimate with certainty due to great geographical heterogeneity of hepatitis C prevalence, and the absence of a nation-wide large scale prevalence survey.Methods:A broad estimate of the number of patients to be treated with high uncertainty was calculated, and reimbursement criteria were set for year 2017 given limited data and treatment budget. In the meanwhile, various sources and approaches to estimate the target number to be treated, and to identify the high prevalence areas, were collected and synthesized for future planning through a systematic review of published data and consulting experts for unpublished data. An expert panel was consulted for the level of confidence and completeness of the evidence. A plan for using real-world data to reduce the uncertainty after initial actions of national program was also in place.Results:Eight thousand patients who fulfilled the reimbursement criteria were treated in 2017 as planned. Strategic steps were identified based on the collected data, and the treatment target, namely 200,000 patients to be treated during 2018 to 2025, was then set for appropriate action plans. National registry infrastructure is planned for supporting future policy modification.Conclusions:Hepatitis C elimination is an important public health task and it requires immediate actions. The expected expenses are high, yet the number of patients is difficult to estimate with precision. How to deal with this uncertainty (financially and in care program design) will be the most challenging part. An adaptive approach (“evidence”-”action”-”more evidence”-”modified action”) could be the pragmatic way to move forward without sacrificing the quality of decision-making.

A STUDY OF HEPATITIS B VIRUS GENOTYPES IN CHRONIC HEPATITIS B PATIENTS

2011 ◽  
pp. 25-29
Author(s):  
Keyword(s):  
Chronic Hepatitis ◽  
Hepatitis B ◽  
Chronic Hepatitis B ◽  
Clinical Laboratory ◽  
Laboratory Data ◽  
Hbv Dna ◽  
Hbv Genotypes ◽  
B Virus ◽  
Virus Genotypes ◽  
Genotype C

Aims: To measure the prevalence of HBV genotypes in chronic hepatitis B patients and their relation to HBeAg and HBV DNA level. Methods: 81 patients were enrolled in this study from January 2009 to December 2010. Clinical, laboratory data were collected during the patient’s hospitalization. Sera were quantitatively tested for HBeAg and HBV DNA. HBV genotyping was made by real-time PCR. Results: Among the 81 patients, 60.5% had genotype B, 26.7% had genotype C and 8.6% had mixed genotype B-C. Prevalence of symptoms (fatigue, anorexia, insomnia...) was higher in genotype C than in genotype B. Genotype C patients had positivity higher HBeAg than genotype B patients (56% vs. 38,8%, p <0.05). The rate of HBV DNA > 107 copies/mL was higher in genotype C group than in genotype B group (36% vs. 28,6%, p > 0.05). Conclusions: Most of the patients had genotypes B or C. Patients with genotype C had positive HBeAg and may be related to higher serological HBV DNA level than in genotype B.

scholarly journals Analyses of longitudinal, hospital clinical laboratory data with application to blood glucose concentrations

2011 ◽  
Vol 30 (27) ◽  
pp. 3208-3220 ◽  
Author(s):  
Jonathan S. Schildcrout ◽  
Sebastien Haneuse ◽  
Josh F. Peterson ◽  
Joshua C. Denny ◽  
Michael E. Matheny ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Clinical Laboratory ◽  
Laboratory Data ◽  
Blood Glucose Concentrations

scholarly journals The association between clinical laboratory data and chest CT findings explains disease severity in a large Italian cohort of COVID-19 patients

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Simone Canovi ◽  
◽  
Giulia Besutti ◽  
Efrem Bonelli ◽  
Valentina Iotti ◽  
...  
Keyword(s):  
Clinical Laboratory ◽  
Laboratory Data ◽  
Organ Damage ◽  
Cross Sectional Study ◽  
Chest Ct ◽  
Arterial Oxygen ◽  
Emergency Rooms ◽  
Cross Sectional ◽  
Ct Findings ◽  
Patient Prognosis

Abstract Background Laboratory data and computed tomography (CT) have been used during the COVID-19 pandemic, mainly to determine patient prognosis and guide clinical management. The aim of this study was to evaluate the association between CT findings and laboratory data in a cohort of COVID-19 patients. Methods This was an observational cross-sectional study including consecutive patients presenting to the Reggio Emilia (Italy) province emergency rooms for suspected COVID-19 for one month during the outbreak peak, who underwent chest CT scan and laboratory testing at presentation and resulted positive for SARS-CoV-2. Results Included were 866 patients. Total leukocytes, neutrophils, C-reactive protein (CRP), creatinine, AST, ALT and LDH increase with worsening parenchymal involvement; an increase in platelets was appreciable with the highest burden of lung involvement. A decrease in lymphocyte counts paralleled worsening parenchymal extension, along with reduced arterial oxygen partial pressure and saturation. After correcting for parenchymal extension, ground-glass opacities were associated with reduced platelets and increased procalcitonin, consolidation with increased CRP and reduced oxygen saturation. Conclusions Pulmonary lesions induced by SARS-CoV-2 infection were associated with raised inflammatory response, impaired gas exchange and end-organ damage. These data suggest that lung lesions probably exert a central role in COVID-19 pathogenesis and clinical presentation.

Tiered Sampling

2021 ◽  
Vol 15 (5) ◽  
pp. 1-52
Author(s):  
Lorenzo De Stefani ◽  
Erisa Terolli ◽  
Eli Upfal
Keyword(s):  
Large Scale ◽  
Analysis Of Algorithms ◽  
Base Layer ◽  
Single Edge ◽  
Real World Data ◽  
High Quality ◽  
Large Graphs ◽  
Massive Graphs ◽  
Variance Estimate ◽  
Low Probability

We introduce Tiered Sampling , a novel technique for estimating the count of sparse motifs in massive graphs whose edges are observed in a stream. Our technique requires only a single pass on the data and uses a memory of fixed size M , which can be magnitudes smaller than the number of edges. Our methods address the challenging task of counting sparse motifs—sub-graph patterns—that have a low probability of appearing in a sample of M edges in the graph, which is the maximum amount of data available to the algorithms in each step. To obtain an unbiased and low variance estimate of the count, we partition the available memory into tiers (layers) of reservoir samples. While the base layer is a standard reservoir sample of edges, other layers are reservoir samples of sub-structures of the desired motif. By storing more frequent sub-structures of the motif, we increase the probability of detecting an occurrence of the sparse motif we are counting, thus decreasing the variance and error of the estimate. While we focus on the designing and analysis of algorithms for counting 4-cliques, we present a method which allows generalizing Tiered Sampling to obtain high-quality estimates for the number of occurrence of any sub-graph of interest, while reducing the analysis effort due to specific properties of the pattern of interest. We present a complete analytical analysis and extensive experimental evaluation of our proposed method using both synthetic and real-world data. Our results demonstrate the advantage of our method in obtaining high-quality approximations for the number of 4 and 5-cliques for large graphs using a very limited amount of memory, significantly outperforming the single edge sample approach for counting sparse motifs in large scale graphs.

scholarly journals Dynamic Loads and Response of a Spar Buoy Wind Turbine with Pitch-Controlled Rotating Blades: An Experimental Study

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3598
Author(s):  
Sara Russo ◽  
Pasquale Contestabile ◽  
Andrea Bardazzi ◽  
Elisa Leone ◽  
Gregorio Iglesias ◽  
...  
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Degrees Of Freedom ◽  
Large Scale ◽  
Laboratory Data ◽  
Nonlinear Behavior ◽  
Offshore Wind ◽  
Small Scale ◽  
Wave Steepness ◽  
Design Factor

New large-scale laboratory data are presented on a physical model of a spar buoy wind turbine with angular motion of control surfaces implemented (pitch control). The peculiarity of this type of rotating blade represents an essential aspect when studying floating offshore wind structures. Experiments were designed specifically to compare different operational environmental conditions in terms of wave steepness and wind speed. Results discussed here were derived from an analysis of only a part of the whole dataset. Consistent with recent small-scale experiments, data clearly show that the waves contributed to most of the model motions and mooring loads. A significant nonlinear behavior for sway, roll and yaw has been detected, whereas an increase in the wave period makes the wind speed less influential for surge, heave and pitch. In general, as the steepness increases, the oscillations decrease. However, higher wind speed does not mean greater platform motions. Data also indicate a significant role of the blade rotation in the turbine thrust, nacelle dynamic forces and power in six degrees of freedom. Certain pairs of wind speed-wave steepness are particularly unfavorable, since the first harmonic of the rotor (coupled to the first wave harmonic) causes the thrust force to be larger than that in more energetic sea states. The experiments suggest that the inclusion of pitch-controlled, variable-speed blades in physical (and numerical) tests on such types of structures is crucial, highlighting the importance of pitch motion as an important design factor.

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