TY - JOUR A1 - Wagner, Martin A1 - Wanner, Christoph A1 - Schich, Martin A1 - Kotseva, Kornelia A1 - Wood, David A1 - Hartmann, Katrin A1 - Fette, Georg A1 - Rücker, Viktoria A1 - Oezkur, Mehmet A1 - Störk, Stefan A1 - Heuschmann, Peter U. T1 - Patient’s and physician’s awareness of kidney disease in coronary heart disease patients – a cross-sectional analysis of the German subset of the EUROASPIRE IV survey JF - BMC Nephrology N2 - Background Chronic kidney disease (CKD) is a common comorbid condition in coronary heart disease (CHD). CKD predisposes the patient to acute kidney injury (AKI) during hospitalization. Data on awareness of kidney dysfunction among CHD patients and their treating physicians are lacking. In the current cross-sectional analysis of the German EUROASPIRE IV sample we aimed to investigate the physician’s awareness of kidney disease of patients hospitalized for CHD and also the patient’s awareness of CKD in a study visit following hospital discharge. Methods All serum creatinine (SCr) values measured during the hospital stay were used to describe impaired kidney function (eGFR\(_{CKD-EPI}\) < 60 ml/min/1.73m2) at admission, discharge and episodes of AKI (KDIGO definition). Information extracted from hospital discharge letters and correct ICD coding for kidney disease was studied as a surrogate of physician’s awareness of kidney disease. All patients were interrogated 0.5 to 3 years after hospital discharge, whether they had ever been told about kidney disease by a physician. Results Of the 536 patients, 32% had evidence for acute or chronic kidney disease during the index hospital stay. Either condition was mentioned in the discharge letter in 22%, and 72% were correctly coded according to ICD-10. At the study visit in the outpatient setting 35% had impaired kidney function. Of 158 patients with kidney disease, 54 (34%) were aware of CKD. Determinants of patient’s awareness were severity of CKD (OR\(_{eGFR}\) 0.94; 95%CI 0.92–0.96), obesity (OR 1.97; 1.07–3.64), history of heart failure (OR 1.99; 1.00–3.97), and mentioning of kidney disease in the index event’s hospital discharge letter (OR 5.51; 2.35–12.9). Conclusions Although CKD is frequent in CHD, only one third of patients is aware of this condition. Patient’s awareness was associated with kidney disease being mentioned in the hospital discharge letter. Future studies should examine how raising physician’s awareness for kidney dysfunction may improve patient’s awareness of CKD. KW - coronary heart disease KW - ICD-coding of CKD KW - chronic kidney disease KW - patients’ awareness KW - physicians’ awareness KW - EUROASPIRE survey Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-158387 VL - 18 IS - 321 ER - TY - JOUR A1 - Traub, Jan A1 - Grondey, Katja A1 - Gassenmaier, Tobias A1 - Schmitt, Dominik A1 - Fette, Georg A1 - Frantz, Stefan A1 - Boivin-Jahns, Valérie A1 - Jahns, Roland A1 - Störk, Stefan A1 - Stoll, Guido A1 - Reiter, Theresa A1 - Hofmann, Ulrich A1 - Weber, Martin S. A1 - Frey, Anna T1 - Sustained increase in serum glial fibrillary acidic protein after first ST-elevation myocardial infarction JF - International Journal of Molecular Sciences N2 - Acute ischemic cardiac injury predisposes one to cognitive impairment, dementia, and depression. Pathophysiologically, recent positron emission tomography data suggest astroglial activation after experimental myocardial infarction (MI). We analyzed peripheral surrogate markers of glial (and neuronal) damage serially within 12 months after the first ST-elevation MI (STEMI). Serum levels of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) were quantified using ultra-sensitive molecular immunoassays. Sufficient biomaterial was available from 45 STEMI patients (aged 28 to 78 years, median 56 years, 11% female). The median (quartiles) of GFAP was 63.8 (47.0, 89.9) pg/mL and of NfL 10.6 (7.2, 14.8) pg/mL at study entry 0–4 days after STEMI. GFAP after STEMI increased in the first 3 months, with a median change of +7.8 (0.4, 19.4) pg/mL (p = 0.007). It remained elevated without further relevant increases after 6 months (+11.7 (0.6, 23.5) pg/mL; p = 0.015), and 12 months (+10.3 (1.5, 22.7) pg/mL; p = 0.010) compared to the baseline. Larger relative infarction size was associated with a higher increase in GFAP (ρ = 0.41; p = 0.009). In contrast, NfL remained unaltered in the course of one year. Our findings support the idea of central nervous system involvement after MI, with GFAP as a potential peripheral biomarker of chronic glial damage as one pathophysiologic pathway. KW - myocardial infarction KW - STEMI KW - glial fibrillary acidic protein KW - GFAP KW - neurofilament light chain KW - NfL KW - glial damage KW - cardiac magnetic resonance imaging KW - MRI KW - infarction size Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-288261 SN - 1422-0067 VL - 23 IS - 18 ER - TY - JOUR A1 - Toepfer, Martin A1 - Corovic, Hamo A1 - Fette, Georg A1 - Klügl, Peter A1 - Störk, Stefan A1 - Puppe, Frank T1 - Fine-grained information extraction from German transthoracic echocardiography reports JF - BMC Medical Informatics and Decision Making N2 - Background Information extraction techniques that get structured representations out of unstructured data make a large amount of clinically relevant information about patients accessible for semantic applications. These methods typically rely on standardized terminologies that guide this process. Many languages and clinical domains, however, lack appropriate resources and tools, as well as evaluations of their applications, especially if detailed conceptualizations of the domain are required. For instance, German transthoracic echocardiography reports have not been targeted sufficiently before, despite of their importance for clinical trials. This work therefore aimed at development and evaluation of an information extraction component with a fine-grained terminology that enables to recognize almost all relevant information stated in German transthoracic echocardiography reports at the University Hospital of Würzburg. Methods A domain expert validated and iteratively refined an automatically inferred base terminology. The terminology was used by an ontology-driven information extraction system that outputs attribute value pairs. The final component has been mapped to the central elements of a standardized terminology, and it has been evaluated according to documents with different layouts. Results The final system achieved state-of-the-art precision (micro average.996) and recall (micro average.961) on 100 test documents that represent more than 90 % of all reports. In particular, principal aspects as defined in a standardized external terminology were recognized with f 1=.989 (micro average) and f 1=.963 (macro average). As a result of keyword matching and restraint concept extraction, the system obtained high precision also on unstructured or exceptionally short documents, and documents with uncommon layout. Conclusions The developed terminology and the proposed information extraction system allow to extract fine-grained information from German semi-structured transthoracic echocardiography reports with very high precision and high recall on the majority of documents at the University Hospital of Würzburg. Extracted results populate a clinical data warehouse which supports clinical research. Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-125509 VL - 15 IS - 91 ER - TY - JOUR A1 - Sommer, Kim K. A1 - Amr, Ali A1 - Bavendiek, Udo A1 - Beierle, Felix A1 - Brunecker, Peter A1 - Dathe, Henning A1 - Eils, Jürgen A1 - Ertl, Maximilian A1 - Fette, Georg A1 - Gietzelt, Matthias A1 - Heidecker, Bettina A1 - Hellenkamp, Kristian A1 - Heuschmann, Peter A1 - Hoos, Jennifer D. E. A1 - Kesztyüs, Tibor A1 - Kerwagen, Fabian A1 - Kindermann, Aljoscha A1 - Krefting, Dagmar A1 - Landmesser, Ulf A1 - Marschollek, Michael A1 - Meder, Benjamin A1 - Merzweiler, Angela A1 - Prasser, Fabian A1 - Pryss, Rüdiger A1 - Richter, Jendrik A1 - Schneider, Philipp A1 - Störk, Stefan A1 - Dieterich, Christoph T1 - Structured, harmonized, and interoperable integration of clinical routine data to compute heart failure risk scores JF - Life N2 - Risk prediction in patients with heart failure (HF) is essential to improve the tailoring of preventive, diagnostic, and therapeutic strategies for the individual patient, and effectively use health care resources. Risk scores derived from controlled clinical studies can be used to calculate the risk of mortality and HF hospitalizations. However, these scores are poorly implemented into routine care, predominantly because their calculation requires considerable efforts in practice and necessary data often are not available in an interoperable format. In this work, we demonstrate the feasibility of a multi-site solution to derive and calculate two exemplary HF scores from clinical routine data (MAGGIC score with six continuous and eight categorical variables; Barcelona Bio-HF score with five continuous and six categorical variables). Within HiGHmed, a German Medical Informatics Initiative consortium, we implemented an interoperable solution, collecting a harmonized HF-phenotypic core data set (CDS) within the openEHR framework. Our approach minimizes the need for manual data entry by automatically retrieving data from primary systems. We show, across five participating medical centers, that the implemented structures to execute dedicated data queries, followed by harmonized data processing and score calculation, work well in practice. In summary, we demonstrated the feasibility of clinical routine data usage across multiple partner sites to compute HF risk scores. This solution can be extended to a large spectrum of applications in clinical care. KW - medical informatics initiative KW - HiGHmed KW - medical data integration center KW - clinical routine data KW - heart failure KW - risk prediction scores KW - semantic interoperability KW - openEHR Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-275239 SN - 2075-1729 VL - 12 IS - 5 ER - TY - JOUR A1 - Liman, Leon A1 - May, Bernd A1 - Fette, Georg A1 - Krebs, Jonathan A1 - Puppe, Frank T1 - Using a clinical data warehouse to calculate and present key metrics for the radiology department: implementation and performance evaluation JF - JMIR Medical Informatics N2 - Background: Due to the importance of radiologic examinations, such as X-rays or computed tomography scans, for many clinical diagnoses, the optimal use of the radiology department is 1 of the primary goals of many hospitals. Objective: This study aims to calculate the key metrics of this use by creating a radiology data warehouse solution, where data from radiology information systems (RISs) can be imported and then queried using a query language as well as a graphical user interface (GUI). Methods: Using a simple configuration file, the developed system allowed for the processing of radiology data exported from any kind of RIS into a Microsoft Excel, comma-separated value (CSV), or JavaScript Object Notation (JSON) file. These data were then imported into a clinical data warehouse. Additional values based on the radiology data were calculated during this import process by implementing 1 of several provided interfaces. Afterward, the query language and GUI of the data warehouse were used to configure and calculate reports on these data. For the most common types of requested reports, a web interface was created to view their numbers as graphics. Results: The tool was successfully tested with the data of 4 different German hospitals from 2018 to 2021, with a total of 1,436,111 examinations. The user feedback was good, since all their queries could be answered if the available data were sufficient. The initial processing of the radiology data for using them with the clinical data warehouse took (depending on the amount of data provided by each hospital) between 7 minutes and 1 hour 11 minutes. Calculating 3 reports of different complexities on the data of each hospital was possible in 1-3 seconds for reports with up to 200 individual calculations and in up to 1.5 minutes for reports with up to 8200 individual calculations. Conclusions: A system was developed with the main advantage of being generic concerning the export of different RISs as well as concerning the configuration of queries for various reports. The queries could be configured easily using the GUI of the data warehouse, and their results could be exported into the standard formats Excel and CSV for further processing. KW - data warehouse KW - eHealth KW - hospital data KW - electronic health records KW - radiology KW - statistics and numerical data KW - medical records Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-349411 SN - 2291-9694 VL - 11 ER - TY - JOUR A1 - Kerwagen, Fabian A1 - Fuchs, Konrad F. A1 - Ullrich, Melanie A1 - Schulze, Andres A1 - Straka, Samantha A1 - Krop, Philipp A1 - Latoschik, Marc E. A1 - Gilbert, Fabian A1 - Kunz, Andreas A1 - Fette, Georg A1 - Störk, Stefan A1 - Ertl, Maximilian T1 - Usability of a mHealth solution using speech recognition for point-of-care diagnostic management JF - Journal of Medical Systems N2 - The administrative burden for physicians in the hospital can affect the quality of patient care. The Service Center Medical Informatics (SMI) of the University Hospital Würzburg developed and implemented the smartphone-based mobile application (MA) ukw.mobile1 that uses speech recognition for the point-of-care ordering of radiological examinations. The aim of this study was to examine the usability of the MA workflow for the point-of-care ordering of radiological examinations. All physicians at the Department of Trauma and Plastic Surgery at the University Hospital Würzburg, Germany, were asked to participate in a survey including the short version of the User Experience Questionnaire (UEQ-S) and the Unified Theory of Acceptance and Use of Technology (UTAUT). For the analysis of the different domains of user experience (overall attractiveness, pragmatic quality and hedonic quality), we used a two-sided dependent sample t-test. For the determinants of the acceptance model, we employed regression analysis. Twenty-one of 30 physicians (mean age 34 ± 8 years, 62% male) completed the questionnaire. Compared to the conventional desktop application (DA) workflow, the new MA workflow showed superior overall attractiveness (mean difference 2.15 ± 1.33), pragmatic quality (mean difference 1.90 ± 1.16), and hedonic quality (mean difference 2.41 ± 1.62; all p < .001). The user acceptance measured by the UTAUT (mean 4.49 ± 0.41; min. 1, max. 5) was also high. Performance expectancy (beta = 0.57, p = .02) and effort expectancy (beta = 0.36, p = .04) were identified as predictors of acceptance, the full predictive model explained 65.4% of its variance. Point-of-care mHealth solutions using innovative technology such as speech-recognition seem to address the users’ needs and to offer higher usability in comparison to conventional technology. Implementation of user-centered mHealth innovations might therefore help to facilitate physicians’ daily work. KW - mHealth KW - digital Health KW - speech recognition KW - usability KW - user-centered design KW - clinical systems Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-324002 VL - 47 IS - 1 ER - TY - JOUR A1 - Kaspar, Mathias A1 - Fette, Georg A1 - Hanke, Monika A1 - Ertl, Maximilian A1 - Puppe, Frank A1 - Störk, Stefan T1 - Automated provision of clinical routine data for a complex clinical follow-up study: A data warehouse solution JF - Health Informatics Journal N2 - A deep integration of routine care and research remains challenging in many respects. We aimed to show the feasibility of an automated transformation and transfer process feeding deeply structured data with a high level of granularity collected for a clinical prospective cohort study from our hospital information system to the study's electronic data capture system, while accounting for study-specific data and visits. We developed a system integrating all necessary software and organizational processes then used in the study. The process and key system components are described together with descriptive statistics to show its feasibility in general and to identify individual challenges in particular. Data of 2051 patients enrolled between 2014 and 2020 was transferred. We were able to automate the transfer of approximately 11 million individual data values, representing 95% of all entered study data. These were recorded in n = 314 variables (28% of all variables), with some variables being used multiple times for follow-up visits. Our validation approach allowed for constant good data quality over the course of the study. In conclusion, the automated transfer of multi-dimensional routine medical data from HIS to study databases using specific study data and visit structures is complex, yet viable. KW - clinical data warehouse KW - clinical study KW - electronic data capture KW - electronic health records KW - secondary data usage Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-260828 VL - 28 IS - 1 ER - TY - JOUR A1 - Frey, Anna A1 - Gassenmaier, Tobias A1 - Hofmann, Ulrich A1 - Schmitt, Dominik A1 - Fette, Georg A1 - Marx, Almuth A1 - Heterich, Sabine A1 - Boivin-Jahns, Valérie A1 - Ertl, Georg A1 - Bley, Thorsten A1 - Frantz, Stefan A1 - Jahns, Roland A1 - Störk, Stefan T1 - Coagulation factor XIII activity predicts left ventricular remodelling after acute myocardial infarction JF - ESC Heart Failure N2 - Aims Acute myocardial infarction (MI) is the major cause of chronic heart failure. The activity of blood coagulation factor XIII (FXIIIa) plays an important role in rodents as a healing factor after MI, whereas its role in healing and remodelling processes in humans remains unclear. We prospectively evaluated the relevance of FXIIIa after acute MI as a potential early prognostic marker for adequate healing. Methods and results This monocentric prospective cohort study investigated cardiac remodelling in patients with ST-elevation MI and followed them up for 1 year. Serum FXIIIa was serially assessed during the first 9 days after MI and after 2, 6, and 12 months. Cardiac magnetic resonance imaging was performed within 4 days after MI (Scan 1), after 7 to 9 days (Scan 2), and after 12 months (Scan 3). The FXIII valine-to-leucine (V34L) single-nucleotide polymorphism rs5985 was genotyped. One hundred forty-six patients were investigated (mean age 58 ± 11 years, 13% women). Median FXIIIa was 118 % (quartiles, 102–132%) and dropped to a trough on the second day after MI: 109%(98–109%; P < 0.001). FXIIIa recovered slowly over time, reaching the baseline level after 2 to 6 months and surpassed baseline levels only after 12 months: 124 % (110–142%). The development of FXIIIa after MI was independent of the genotype. FXIIIa on Day 2 was strongly and inversely associated with the relative size of MI in Scan 1 (Spearman’s ρ = –0.31; P = 0.01) and Scan 3 (ρ = –0.39; P < 0.01) and positively associated with left ventricular ejection fraction: ρ = 0.32 (P < 0.01) and ρ = 0.24 (P = 0.04), respectively. Conclusions FXIII activity after MI is highly dynamic, exhibiting a significant decline in the early healing period, with reconstitution 6 months later. Depressed FXIIIa early after MI predicted a greater size of MI and lower left ventricular ejection fraction after 1 year. The clinical relevance of these findings awaits to be tested in a randomized trial. KW - blood coagulation factor XIII KW - ST-elevation myocardial infarction KW - healing and remodelling processes KW - cardiac magnetic resonance imaging Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-236013 VL - 7 IS - 5 ER - TY - JOUR A1 - Dietrich, Georg A1 - Krebs, Jonathan A1 - Liman, Leon A1 - Fette, Georg A1 - Ertl, Maximilian A1 - Kaspar, Mathias A1 - Störk, Stefan A1 - Puppe, Frank T1 - Replicating medication trend studies using ad hoc information extraction in a clinical data warehouse JF - BMC Medical Informatics and Decision Making N2 - Background Medication trend studies show the changes of medication over the years and may be replicated using a clinical Data Warehouse (CDW). Even nowadays, a lot of the patient information, like medication data, in the EHR is stored in the format of free text. As the conventional approach of information extraction (IE) demands a high developmental effort, we used ad hoc IE instead. This technique queries information and extracts it on the fly from texts contained in the CDW. Methods We present a generalizable approach of ad hoc IE for pharmacotherapy (medications and their daily dosage) presented in hospital discharge letters. We added import and query features to the CDW system, like error tolerant queries to deal with misspellings and proximity search for the extraction of the daily dosage. During the data integration process in the CDW, negated, historical and non-patient context data are filtered. For the replication studies, we used a drug list grouped by ATC (Anatomical Therapeutic Chemical Classification System) codes as input for queries to the CDW. Results We achieve an F1 score of 0.983 (precision 0.997, recall 0.970) for extracting medication from discharge letters and an F1 score of 0.974 (precision 0.977, recall 0.972) for extracting the dosage. We replicated three published medical trend studies for hypertension, atrial fibrillation and chronic kidney disease. Overall, 93% of the main findings could be replicated, 68% of sub-findings, and 75% of all findings. One study could be completely replicated with all main and sub-findings. Conclusion A novel approach for ad hoc IE is presented. It is very suitable for basic medical texts like discharge letters and finding reports. Ad hoc IE is by definition more limited than conventional IE and does not claim to replace it, but it substantially exceeds the search capabilities of many CDWs and it is convenient to conduct replication studies fast and with high quality. KW - data warehouse KW - medication extraction KW - information extraction Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-200409 VL - 19 ER -