Knowledge-based best of breed approach for automated detection of clinical events based on German free text digital hospital discharge letters

OBJECTIVES: The secondary use of medical data contained in electronic medical records, such as hospital discharge letters, is a valuable resource for the improvement of clinical care (e.g. in terms of medication safety) or for research purposes. However, the automated processing and analysis of medical free text still poses a huge challenge to available natural language processing (NLP) systems. The aim of this study was to implement a knowledge-based best of breed approach, combining a terminology server with integrated ontology, a NLP pipeline and a rules engine. METHODS: We tested the performance of this approach in a use case. The clinical event of interest was the particular drug-disease interaction "proton-pump inhibitor [PPI] use and osteoporosis". Cases were to be identified based on free text digital discharge letters as source of information. Automated detection was validated against a gold standard. RESULTS: Precision of recognition of osteoporosis was 94.19%, and recall was 97.45%. PPIs were detected with 100% precision and 97.97% recall. The F-score for the detection of the given drug-disease-interaction was 96,13%. CONCLUSION: We could show that our approach of combining a NLP pipeline, a terminology server, and a rules engine for the purpose of automated detection of clinical events such as drug-disease interactions from free text digital hospital discharge letters was effective. There is huge potential for the implementation in clinical and research contexts, as this approach enables analyses of very high numbers of medical free text documents within a short time period

Low-density lipoprotein cholesterol goal attainment in patients with clinical evidence of familial hypercholesterolemia and elevated Lp(a)

Background: Although potent lipid-lowering therapies are available, patients commonly fall short of recommended low-density lipoprotein cholesterol (LDL-C) levels. The aim of this study was to examine the relationship between familial hypercholesterolemia (FH) and elevated lipoprotein(a) [Lp(a)] and LDL-C goal attainment, as well as the prevalence and severity of coronary artery disease (CAD). Moreover, we characterized patients failing to meet recommended LDL-C goals. Methods: We performed a cross-sectional analysis in a cohort of patients undergoing cardiac catheterization. Clinical FH was determined by the Dutch Clinical Lipid Network Score, and Lp(a) >= 50 mg/dL (approximate to 107 nmol/L) was considered elevated. Results: A total of 838 participants were included. Overall, the prevalence of CAD was 72%, and 62% received lipid-lowering treatment. The prevalence of clinical FH (probable and definite FH) was 4%, and 19% had elevated Lp(a) levels. With 35%, LDL-C goal attainment was generally poor. Among the participants with clinical FH, none reached their LDL-C target. Among patients with elevated Lp(a), LDL-C target achievement was only 28%. The prevalence and severity of CAD were higher in participants with clinical FH (86% prevalence) and elevated Lp(a) (80% prevalence). Conclusion: Most participants failed to meet their individual LDL-C goals according to the ESC 2016 and 2019 guidelines. In particular, high-risk patients with clinical FH or elevated Lp(a) rarely met their target for LDL-C. The identification of these patients and more intense treatment approaches are crucial for the improvement of CAD primary and secondary prevention

Hyperlipidemias in elderly patients: results from the Berlin Aging Study II (BASEII), a cross-sectional study

Background: Hyperlipidemias are common and the last decades have seen substantially growing evidence of their causative role in the development of atherosclerosis and subsequent cardiovascular diseases. Since hyperlipidemias usually do not cause direct clinical symptoms, they often remain undiagnosed until a serious cardiovascular event occurs. Especially for LDL-hypercholesteremia, there are well-established treatment options available to prevent the occurrence of atherosclerosis. However, there is a lack of knowledge regarding the proper treatment of elderly patients. The goal of this study was to assess the prevalence of hyperlipidemia in a group of young and a group of elderly community-dwelling participants and to determine to what extent treatment of hyperlipidemia should be initiated or required. Methods: Crossectional data from a total of 2151 subjects (1657 in the elderly group, mean age 69, and 494 in the young group (control group), mean age 29) of the Berlin Aging Study II (BASE-II) were available. Medical history was assessed and recorded by trained physicians and prevalence of lipid disorders was determined with laboratory tests, including a lipid-profile. Results: A large proportion of subjects (39%) were unaware of an existing lipid disorder. The prevalence of hyperlipidemia was more frequent in the elderly group (76%) compared to the young group (41%). Hypercholesterolemia was the most common diagnosed disorder (64%), followed by hyperlipoproteinemia(a) (18%), hypertriglyceridemia (7%) and combined hyperlipoproteinaemia (5%). Only a minority of this cohort was treated with lipid-lowering medication (17%) and of those treatment targets according to ESC guidelines were reached only in 16.5 %. Conclusions: Hyperlipidemias appear underdiagnosed and undertreated. As the prevalence of these disorders increases with age and with regard to their role as a major modifiable risk factor for cardiovascular disease it seems to be advisable to aim for more consistent and sustainable screening and treatment of these common disorders. Trial registration: BASE-II registered with the clinical trial registry Deutsches Register Klinischer Studien (DRKS00009277)

Duplicate Table Detection with Xash

Data lakes are typically lightly curated and as such prone to data quality problems and inconsistencies. In particular, duplicate tables are common in most repositories. The goal of duplicate table detection is to identify those tables that display the same data. Comparing tables is generally quite expensive as the order of rows and columns might differ for otherwise identical tables. In this paper, we explore the application of Xash, a hash function previously proposed for the discovery of multi-column join candidates, for the use case of duplicate table detection. With Xash, it is possible to generate a so-called super key, which serves like a bloom filter and instantly identifies the existence of particular cell values. We show that using Xash it is possible to speed up the duplicate table detection process significantly. In comparison to SimHash and other competing hash functions, Xash results in fewer false positive candidates

Development Of An Adaptive Augmented Reality Qualification System For Manual Assembly And Maintenance

The manufacturing industry is facing various challenges today - globalization, fast-moving sales markets, short product life cycles, individualization, mass production and diversity of variants are trends that will continue or even increase in the future. Speed and flexibility in production are thus becoming important success factors for companies. To meet the demands of the market, there is a growing necessity to deploy employees flexibly within the production process. This increases the need for additional qualification of workers. By overlaying reality with virtual cues, Head-mounted displays (HMD) can present information in a situation-specific and location-linked manner. Data glasses also offer a high and convertible degree of support through the possibility of providing different media forms while both hands are available at the same time. Augmented Reality (AR) guidance systems are already available on the market and are suitable as permanent assistance systems, but only to a limited extent for qualification aspects. An industrially applicable qualification software that collects expert knowledge from skilled workers and then makes it available to new or inexperienced employees in an adaptive way that promotes learning is currently not available. This paper therefore presents the development of the software AQUA, which taps internal expertise with low effort and creates training courses that convey learning content to learners without over- or under-challenging them

Potentially inappropriate medication in older participants of the Berlin Aging Study II (BASE-II) - Sex differences and associations with morbidity and medication use

INTRODUCTION: Multimorbidity in advanced age and the need for drug treatment may lead to polypharmacy, while pharmacokinetic and pharmacodynamic changes may increase the risk of adverse drug events (ADEs). OBJECTIVE: The aim of this study was to determine the proportion of subjects using potentially inappropriate medication (PIM) in a cohort of older and predominantly healthy adults in relation to polypharmacy and morbidity. METHODS: Cross-sectional data were available from 1,382 study participants (median age 69 years, IQR 67-71, 51.3% females) of the Berlin Aging Study II (BASE-II). PIM was classified according to the EU(7)-PIM and German PRISCUS (representing a subset of the former) list. Polypharmacy was defined as the concomitant use of at least five drugs. A morbidity index (MI) largely based on the Charlson Index was applied to evaluate the morbidity burden. RESULTS: Overall, 24.1% of the participants were affected by polypharmacy. On average, men used 2 (IQR 1-4) and women 3 drugs (IQR 1-5). According to PRISCUS and EU(7)-PIM, 5.9% and 22.6% of participants received at least one PIM, while use was significantly more prevalent in females (25.5%) compared to males (19.6%) considering EU(7)-PIM (p = 0.01). In addition, morbidity in males receiving PIM according to EU(7)-PIM was higher (median MI 1, IQR 1-3) compared to males without PIM use (median MI 1, IQR 0-2, p<0.001). CONCLUSION: PIM use occurred more frequently in women than in men, while it was associated with higher morbidity in males. As expected, EU(7)-PIM identifies more subjects as PIM users than the PRISCUS list but further studies are needed to investigate the differential impact of both lists on ADEs and outcome. KEY POINTS: We found PIM use to be associated with a higher number of regular medications and with increased morbidity. Additionally, we detected a higher prevalence of PIM use in females compared to males, suggesting that women and people needing intensive drug treatment are patient groups, who are particularly affected by PIM use

Methods for non-proportional hazards in clinical trials: A systematic review

For the analysis of time-to-event data, frequently used methods such as the log-rank test or the Cox proportional hazards model are based on the proportional hazards assumption, which is often debatable. Although a wide range of parametric and non-parametric methods for non-proportional hazards (NPH) has been proposed, there is no consensus on the best approaches. To close this gap, we conducted a systematic literature search to identify statistical methods and software appropriate under NPH. Our literature search identified 907 abstracts, out of which we included 211 articles, mostly methodological ones. Review articles and applications were less frequently identified. The articles discuss effect measures, effect estimation and regression approaches, hypothesis tests, and sample size calculation approaches, which are often tailored to specific NPH situations. Using a unified notation, we provide an overview of methods available. Furthermore, we derive some guidance from the identified articles. We summarized the contents from the literature review in a concise way in the main text and provide more detailed explanations in the supplement (page 29)