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001-es BibID:BIBFORM103908
Első szerző:Nádró Bíborka (általános orvos)
Cím:Serum progranulin level in patients with newly diagnosed untreated familial hypercholesterolemia / Nádró B., Lőrincz H., Juhász L., Szentpéteri A., Sztanek F., Seres I., Páll D., Fülöp P., Paragh G., Harangi M.
Dátum:2022
ISSN:0021-9150
Megjegyzések:Background and Aims : Familial hypercholesterolemia (FH) is a monogenic form of severe hypercholesterolemia, characterized by elevated total cholesterol and low-density lipoprotein-cholesterol concentrations that, if left untreated, is associated with early onset of atherosclerosis. Progranulin (PGRN) is a recently discovered growth factor with many biological functions. PGRN has anti-inflammatory properties because it inhibits neutrophil degranulation and blocks tumor necrosis factor ? transmission, therefore, might be anti-atherogenic. To date, serum level of PGRN in patients with FH has not been studied. Methods: Eighty-one newly diagnosed, untreated patients with FH and 32 healthy control subjects were involved in our study. Serum PGRN levels were determined by ELISA. We diagnosed FH using the Dutch Lipid Clinic Network criteria. Results: We could not find significant difference in serum PGRN levels between FH patients and healthy controls (37.66?9.75 vs. 38.43?7.74 ng/mL, ns.). However, we found significant positive correlations between triglyceride, C-reactive protein (CRP), and PGRN levels (p<0.01 and p<0.01, respectively), while significant negative correlation was found between high-density lipoprotein cholesterol (HDL-C) and PGRN levels (p<0.05) both in the whole study population and in FH patients. Conclusions: Strong correlations between HDL-C, CRP and PGRN levels suggest that PGRN may exerts its anti-atherogenic effect in FH patients by alteration in HDL-C level by amelioration of inflammatory processes. Further studies on larger study populations are needed to clarify the underlying mechanisms. Funding: This presentation was supported by the Bridging Fund (Faculty of Medicine, University of Debrecen) and PD124126 project.
Tárgyszavak:Orvostudományok Egészségtudományok idézhető absztrakt
folyóiratcikk
atherosclerosis
familial hypercholesterolemia
progranulin
lipoprotein
inflammation
Megjelenés:Atherosclerosis. - 355 (2022), p. e248. -
További szerzők:Lőrincz Hajnalka (1986-) (biológus) Juhász Lilla (1990-) (általános orvos) Szentpéteri Anita (1988-) (biológus) Sztanek Ferenc (1982-) (orvos) Seres Ildikó (1954-) (biokémikus) Páll Dénes (1967-) (belgyógyász, kardiológus) Fülöp Péter (1974-) (belgyógyász, endokrinológus, lipidológus) Paragh György (1953-) (belgyógyász) Harangi Mariann (1974-) (belgyógyász, endokrinológus)
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001-es BibID:BIBFORM102878
035-os BibID:(cikkazonosító)4311 (Wos)000839128300001 (Scopus)85136936484
Első szerző:Németh Ákos (vegyész)
Cím:Identifying Patients with Familial Chylomicronemia Syndrome Using FCS Score-Based Data Mining Methods / Németh Ákos, Harangi Mariann, Daróczy Bálint, Juhász Lilla, Paragh György, Fülöp Péter
Dátum:2022
ISSN:2077-0383
Megjegyzések:Background: There are no exact data about the prevalence of familial chylomicronemia syndrome (FCS) in Central Europe. We aimed to identify FCS patients using either the FCS score proposed by Moulin et al. or with data mining, and assessed the diagnostic applicability of the FCS score. Methods: Analyzing medical records of 1,342,124 patients, the FCS score of each patient was calculated. Based on the data of previously diagnosed FCS patients, we trained machine learning models to identify other features that may improve FCS score calculation. Results: We identified 26 patients with an FCS score of ?10. From the trained models, boosting tree models and support vector machines performed the best for patient recognition with overall AUC above 0.95, while artificial neural networks accomplished above 0.8, indicating less efficacy. We identified laboratory features that can be considered as additions to the FCS score calculation. Conclusions: The estimated prevalence of FCS was 19.4 per million in our region, which exceeds the prevalence data of other European countries. Analysis of larger regional and country-wide data might increase the number of FCS cases. Although FCS score is an excellent tool in identifying potential FCS patients, consideration of some other features may improve its accuracy.
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
data mining
familial chylomicronemia syndrome
FCS score
machine learning
screening
Megjelenés:Journal of Clinical Medicine. - 11 (2022), p. 1-14. -
További szerzők:Harangi Mariann (1974-) (belgyógyász, endokrinológus) Daróczy Bálint (1984-) (informatikus, matematikus) Juhász Lilla (1990-) (általános orvos) Paragh György (1953-) (belgyógyász) Fülöp Péter (1974-) (belgyógyász, endokrinológus, lipidológus)
Pályázati támogatás:GINOP-2.3.2-15-2016-00005
GINOP
Bridging Fund
Egyéb
MTA Premium Postdoctoral Grant 2018
MTA
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3.

001-es BibID:BIBFORM100171
Első szerző:Németh Ákos (vegyész)
Cím:Assessment of associations between serum lipoprotein (a) levels and atherosclerotic vascular diseases in Hungarian patients with familial hypercholesterolemia using data mining and machine learning / Németh Ákos, Daróczy Bálint, Juhász Lilla, Fülöp Péter, Harangi Mariann, Paragh György
Dátum:2022
ISSN:1664-8021
Megjegyzések:Background and aims: Premature mortality due to atherosclerotic vascular disease is very high in Hungary in comparison with international prevalence rates, though the estimated prevalence of familial hypercholesterolemia (FH) is in line with the data of other European countries. Previous studies have shown that high lipoprotein(a)- Lp(a) levels are associated with an increased risk of atherosclerotic vascular diseases in patients with FH. We aimed to assess the associations of serum Lp(a) levels and such vascular diseases in FH using data mining methods and machine learning techniques in the Northern Great Plain region of Hungary. Methods: Medical records of 590,500 patients were included in our study. Based on the data from previously diagnosed FH patients using the Dutch Lipid Clinic Network scores (?7 was evaluated as probable or definite FH), we trained machine learning models to identify FH patients. Results: We identified 459 patients with FH and 221 of them had data available on Lp(a). Patients with FH had significantly higher Lp(a) levels compared to non-FH subjects (236 (92.5; 698.5) vs. 167 (80.2; 431.5) mg/L, p<0.01). Also 35.3% of FH patients had Lp(a) levels >500 mg/L. Atherosclerotic complications were significantly more frequent in FH patients compared to patients without FH (46.6% vs. 13.9%). However, contrary to several other previous studies, we could not find significant associations between serum Lp(a) levels and atherosclerotic vascular diseases in the studied Hungarian FH patient group. Conclusions: The extremely high burden of vascular disease is mainly explained by the unhealthy lifestyle of our patients (i.e. high prevalence of smoking, unhealthy diet and physical inactivity resulting in obesity and hypertension). The lack of associations between serum Lp(a) levels and atherosclerotic vascular diseases in Hungarian FH patients may be due to the high prevalence of these risk factors, that mask the deleterious effect of Lp(a).
Tárgyszavak:Orvostudományok Klinikai orvostudományok idegen nyelvű folyóiratközlemény külföldi lapban
folyóiratcikk
Lipoprotein(a)
Familial Hypercholesterolemia
cardiovascular risk
Data Mining
Atherosclerosis
Megjelenés:Frontiers in Genetics. - 13 (2022), p. 849197. -
További szerzők:Daróczy Bálint (1984-) (informatikus, matematikus) Juhász Lilla (1990-) (általános orvos) Fülöp Péter (1974-) (belgyógyász, endokrinológus, lipidológus) Harangi Mariann (1974-) (belgyógyász, endokrinológus) Paragh György (1953-) (belgyógyász)
Pályázati támogatás:GINOP-2.3.2-15-2016-00005
GINOP
Bridging Fund
Egyéb
Premium Postdoctoral Fund
MTA
Internet cím:Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
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