[Serum biomarkers in acute low back pain and sciatica]. / Szérumbiomarkerek akut lumbalis-lumbosacralis fájdalomban.

Inflammation contributes to the pathogenesis of low back pain and sciatica. Growing evidence suggests that elevated levels of some inflammatory biomarkers are associated with these conditions. Much of the research evaluating the association between pro- and anti-inflammatory cytokines, chemokines, other regulatory molecules, and low back pain and sciatica, focused on patients with chronic low back pain, while fewer studies addressed the issue of detectable biomarkers in the acute phase. Previous studies suggest that pro-inflammatory cytokines such as TNF-α, IL-6, and IL-8 and anti-inflammatory IL-4 and IL-10 play an important role in the inflammatory response following intervertebral disc herniation. According to the approach of personalized medicine it is important to identify subsets of patients within the acute patient group regarding etiology, prognosis and treatment. In addition, if we can identify subgroups based on levels of pro-inflammatory biomarkers, where inflammation may be the leading cause of pain, we assume that this subgroup would likely be effectively treated with anti-inflammatory medication. The efficacy of TNF-α inhibitors and IL-6 inhibitors in treating low back pain and sciatica has already been tested in clinical trials, but further studies are required. Overall, identification of circulating biomarkers of acute low back pain and sciatica may assist in refining personalized diagnosis and treatment. Further research is needed to evaluate the role of inflammation in acute low back pain and sciatica, to identify what methods are appropriate for evaluation in clinical practice, and whether there are biomarkers of prognostic value in these patients. Orv Hetil. 2020; 161(13): 483-490.

[Databases in neurological diseases: overview of international examples in multiple sclerosis]. / Nagy adatbázisok neurológiai kórképekben: nemzetközi áttekintés a sclerosis multiplex példáján.

Vast amounts of data are created during routine patient care which are stored in unstructured digital and hardcopy formats in healthcare institutions. Analysis of large databases help to define the healthcare needs of the population and to organize healthcare services for specific diseases. As a model, we selected multiple sclerosis (MS), a disease with well-defined diagnostic criteria, a usually inpatient initial diagnosis, and a need for regular outpatient check-up. Using multiple sclerosis as an example, we set forth to screen and analyze international and Hungarian databases. In the framework of the initiation of the data lake system of Semmelweis University, we aim to define features of the data system needed for disease-specific databases for future applications. To determine essential data-entry criteria for such a database, we review the most important multiple sclerosis registries. We evaluate the type of registered data, structure of database, privacy issues, the availability and ways of application of the databases. Initially, the MS databases were created locally, aiming for better care of patients. As a further step, data were collected for scientific research by national and international co-operations. Disease-specific databases have become of high priority for national healthcare providers, and long-term information on a population ("real-world" data) is extremely important to assess the effectivity and safety of a treatment at the population level. Our analysis contributes to a project which focuses on the aspects of developing a data lake at a service provider level including clinical, diagnostic and digital healthcare departments of Semmelweis University, Budapest, Hungary. Orv Hetil. 2019; 160(4): 123-130.

[Multiple sclerosis in central Hungary: experiences and future possibilities of developing a local database]. / Sclerosis multiplex a közép-magyarországi régióban: a helyi adatbázisfejlesztés tapasztalatai és jövobeli lehetoségei.

INTRODUCTION: Data during routine patient care are created in multiple digital and paper-based hardcopy systems, therefore their retrieval is cumbersome in the follow-up of patients. Multiple sclerosis is the most prevalent neurological disorder in the young age, with major consequences on health and socio-economic status. AIM: We set forth to create a user-friendly, detailed local database where it is easy to access, register and analyze data. Based on our experiences during building this registry, we develop the model of a modern type of database. METHOD: First we established a local registry in Excel, then data were transferred to the worldwide used iMed system. Separate pages were used to register basic data, follow-up visits, relapses, accompanying diseases, results of neuroimaging, cerebrospinal fluid, evoked response and other tests, pharmacological and non-pharmacological treatments. RESULTS: The database currently contains data of 316 patients. MRI was performed in 96%, cerebrospinal fluid examination in 45% of the patients. The rate of primary progressive disease at disease onset is 9%. Disease modifying treatments were applied in 82% of the patients. CONCLUSION: The traditional manual data entry and data export in PDF format is obsolete and time-consuming. The development of local disease-specific databases appropriate for clinical and research purposes requires continuous and mostly automatic data entry. In future local registries the establishment of uniform documentational language and structure, and automatic transfer of information among different digital systems are required. We present the model of such a registry, which is based on a healthcare data lake. Orv Hetil. 2019; 160(4): 131-137.