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Pregled bibliografske jedinice broj: 1054081

Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records


Šabanović, Šefket; Ljiljana, Majnarić; Babič, František; Vadovský, Michal; Paralič, Ján; Včev, Aleksandar; Holzinger, Andreas
Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records // Bmc medical informatics and decision making, 18 (2018), 1; 24-43 doi:10.1186/s12911-018-0601-2 (međunarodna recenzija, članak, znanstveni)


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Naslov
Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records
(Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records)

Autori
Šabanović, Šefket ; Ljiljana, Majnarić ; Babič, František ; Vadovský, Michal ; Paralič, Ján ; Včev, Aleksandar ; Holzinger, Andreas

Izvornik
Bmc medical informatics and decision making (1472-6947) 18 (2018), 1; 24-43

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
General practice, Research, Routine data, Electronic health records, Computer methods for data anlysis, Menopausal women, Hypertension, Metabolic syndrome

Sažetak
Background: There is potential for medical research on the basis of routine data used from general practice electronic health records (GP eHRs), even in areas where there is no common GP research platform. We present a case study on menopausal women with hypertension and metabolic syndrome (MS). The aims were to explore the appropriateness of the standard definition of MS to apply to this specific, narrowly defined population group and to improve recognition of women at high CV risk. Methods: We investigated the possible uses offered by available data from GP eHRs, completed with patients interview, in goal of the study, using a combination of methods. For the sample of 202 hypertensive women, 47–59 years old, a data set was performed, consisted of a total number of 62 parameters, 50 parameters used from GP eHRs. It was analysed by using a mixture of methods: analysis of differences, cutoff values, graphical presentations, logistic regression and decision trees. Results: The age range found to best match the emergency of MS was 51–55 years. Deviations from the definition of MS were identified: a larger cut-off value of the waist circumference measure (89 vs 80 cm) and parameters BMI and total serum cholesterol perform better as components of MS than the standard parameters waist circumference and HDL-cholesterol. The threshold value of BMI at which it is expected that most of hypertensive menopausal women have MS, was found to be 25.5. The other best means for recognision of women with MS include triglycerides above the threshold of 1.7 mmol/L and information on statins use. Prevention of CVD should focus on women with a new onset diabetes and comorbidities of a long-term hypertension with anxiety/depression. Conclusions: The added value of this study goes beyond the current paradigm on MS. Results indicate characteristics of MS in a narrowly defined, specific population group. A comprehensive view has been enabled by using heterogenoeus data and a smart combination of various methods for data analysis. The paper shows the feasibility of this research approach in routine practice, to make use of data which would otherwise not be used for research.

Izvorni jezik
Engleski



POVEZANOST RADA


Ustanove:
Medicinski fakultet, Osijek,
Fakultet za dentalnu medicinu i zdravstvo, Osijek

Profili:

Avatar Url Ljiljana Majnarić (autor)

Avatar Url Aleksandar Včev (autor)

Poveznice na cjeloviti tekst rada:

doi

Citiraj ovu publikaciju:

Šabanović, Šefket; Ljiljana, Majnarić; Babič, František; Vadovský, Michal; Paralič, Ján; Včev, Aleksandar; Holzinger, Andreas
Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records // Bmc medical informatics and decision making, 18 (2018), 1; 24-43 doi:10.1186/s12911-018-0601-2 (međunarodna recenzija, članak, znanstveni)
Šabanović, Š., Ljiljana, M., Babič, F., Vadovský, M., Paralič, J., Včev, A. & Holzinger, A. (2018) Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records. Bmc medical informatics and decision making, 18 (1), 24-43 doi:10.1186/s12911-018-0601-2.
@article{article, author = {\v{S}abanovi\'{c}, \v{S}efket and Ljiljana, Majnari\'{c} and Babi\v{c}, Franti\v{s}ek and Vadovsk\'{y}, Michal and Parali\v{c}, J\'{a}n and V\v{c}ev, Aleksandar and Holzinger, Andreas}, year = {2018}, pages = {24-43}, DOI = {10.1186/s12911-018-0601-2}, keywords = {General practice, Research, Routine data, Electronic health records, Computer methods for data anlysis, Menopausal women, Hypertension, Metabolic syndrome}, journal = {Bmc medical informatics and decision making}, doi = {10.1186/s12911-018-0601-2}, volume = {18}, number = {1}, issn = {1472-6947}, title = {Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records}, keyword = {General practice, Research, Routine data, Electronic health records, Computer methods for data anlysis, Menopausal women, Hypertension, Metabolic syndrome} }
@article{article, author = {\v{S}abanovi\'{c}, \v{S}efket and Ljiljana, Majnari\'{c} and Babi\v{c}, Franti\v{s}ek and Vadovsk\'{y}, Michal and Parali\v{c}, J\'{a}n and V\v{c}ev, Aleksandar and Holzinger, Andreas}, year = {2018}, pages = {24-43}, DOI = {10.1186/s12911-018-0601-2}, keywords = {General practice, Research, Routine data, Electronic health records, Computer methods for data anlysis, Menopausal women, Hypertension, Metabolic syndrome}, journal = {Bmc medical informatics and decision making}, doi = {10.1186/s12911-018-0601-2}, volume = {18}, number = {1}, issn = {1472-6947}, title = {Metabolic syndrome in hypertensive women in the age of menopause: a case study on data from general practice electronic health records}, keyword = {General practice, Research, Routine data, Electronic health records, Computer methods for data anlysis, Menopausal women, Hypertension, Metabolic syndrome} }

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