Browsing by Subject "Medication"

Sort by: Order: Results:

Now showing items 1-4 of 4
  • Nicoletti, Paola; Aithal, Guruprasad P.; Bjornsson, Einar S.; Andrade, Raul J.; Sawle, Ashley; Arrese, Marco; Barnhart, Huiman X.; Bondon-Guitton, Emmanuelle; Hayashi, Paul H.; Bessone, Fernando; Carvajal, Alfonso; Cascorbi, Ingolf; Cirulli, Elizabeth T.; Chalasani, Naga; Conforti, Anita; Coulthard, Sally A.; Daly, Mark J.; Day, Christopher P.; Dillon, John F.; Fontana, Robert J.; Grove, Jane I.; Hallberg, Par; Hernandez, Nelia; Ibanez, Luisa; Kullak-Ublick, Gerd A.; Laitinen, Tarja; Larrey, Dominique; Lucena, M. Isabel; Maitland-van der Zee, Anke H.; Martin, Jennifer H.; Molokhia, Mariam; Pirmohamed, Munir; Powell, Elizabeth E.; Qin, Shengying; Serrano, Jose; Stephens, Camilla; Stolz, Andrew; Wadelius, Mia; Watkins, Paul B.; Floratos, Aris; Shen, Yufeng; Nelson, Matthew R.; Urban, Thomas J.; Daly, Ann K.; Int Drug-Induced Liver Injury Cons; Drug-Induced Liver Injury Network; Int Serious Adverse Events Consort (2017)
    BACKGROUND & AIMS: We performed a genome-wide association study (GWAS) to identify genetic risk factors for druginduced liver injury (DILI) from licensed drugs without previously reported genetic risk factors. METHODS: We performed a GWAS of 862 persons with DILI and 10,588 population-matched controls. The first set of cases was recruited before May 2009 in Europe (n = 137) and the United States (n = 274). The second set of cases were identified from May 2009 through May 2013 from international collaborative studies performed in Europe, the United States, and South America. For the GWAS, we included only cases with patients of European ancestry associated with a particular drug (but not flucloxacillin or amoxicillin-clavulanate). We used DNA samples from all subjects to analyze HLA genes and single nucleotide polymorphisms. After the discovery analysis was concluded, we validated our findings using data from 283 European patients with diagnosis of DILI associated with various drugs. RESULTS: We associated DILI with rs114577328 (a proxy for A* 33: 01 a HLA class I allele; odds ratio [OR], 2.7; 95% confidence interval [CI], 1.9 - 3.8; P = 2.4 x 10(-8)) and with rs72631567 on chromosome 2 (OR, 2.0; 95% CI, 1.6 - 2.5; P = 9.7 x 10(-9)). The association with A* 33: 01 was mediated by large effects for terbinafine-, fenofibrate-, and ticlopidine-related DILI. The variant on chromosome 2 was associated with DILI from a variety of drugs. Further phenotypic analysis indicated that the association between DILI and A* 33: 01 was significant genome wide for cholestatic and mixed DILI, but not for hepatocellular DILI; the polymorphism on chromosome 2 was associated with cholestatic and mixed DILI as well as hepatocellular DILI. We identified an association between rs28521457 (within the lipopolysaccharide-responsive vesicle trafficking, beach and anchor containing gene) and only hepatocellular DILI (OR, 2.1; 95% CI, 1.6 - 2.7; P = 4.8 x 10(-9)). We did not associate any specific drug classes with genetic polymorphisms, except for statin-associated DILI, which was associated with rs116561224 on chromosome 18 (OR, 5.4; 95% CI, 3.0 - 9.5; P = 7.1 x 10(-9)). We validated the association between A* 33: 01 terbinafine-and sertraline-induced DILI. We could not validate the association between DILI and rs72631567, rs28521457, or rs116561224. CONCLUSIONS: In a GWAS of persons of European descent with DILI, we associated HLA-A* 33: 01 with DILI due to terbinafine and possibly fenofibrate and ticlopidine. We identified polymorphisms that appear to be associated with DILI from statins, as well as 2 non-drug-specific risk factors.
  • Laine, M. K.; Kujala, R.; Eriksson, J. G.; Kautiainen, H.; Sarna, S.; Kujala, U. M. (2017)
    Aims Regular physical activity plays a major role, in both prevention and treatment of type 2 diabetes. Less is known whether vigorous physical activity during young adulthood is associated with costs of diabetes medication in later life. The aim of this study is to evaluate this question. Methods The study population consisted of 1314 former elite-class athletes and 860 matched controls. The former athletes were divided into three groups based on their active career sport: endurance, mixed and power sports. Information on purchases of diabetes medication between 1995 and 2009 was obtained from the drug purchase register of the Finnish Social Insurance Institution. Results The total cost of diabetes medication per person year was significantly lower among the former endurance (mean 81 theta [95% CI 33-151 theta ]) and mixed group athletes (mean 272 theta [95% CI 181- 388 theta]) compared with the controls (mean 376 theta [95% CI 284- 485 theta]), (p <0.001 and p = 0.045, respectively). Of the former endurance athletes, 0.4% used insulin, while 5.2% of the controls used insulin (p = 0.018). Conclusions A career as former endurance, sprint, jumper or team game athlete seems to reduce the costs of diabetes medication in later life.
  • Michalcova, Jana; Vasut, Karel; Airaksinen, Marja; Bielakova, Katarina (2020)
    Background Falls are common undesirable events for older adults in institutions. Even though the patient's fall risk may be scored on admission, the medication-induced fall risk may be ignored. This study developed a preliminary categorization of fall-risk-increasing drugs (FRIDs) to be added as a risk factor to the existing fall risk assessment tool routinely used in geriatric care units. Methods Medication use data of older adults who had experienced at least one fall during a hospital ward or a nursing home stay within a 2-year study period were retrospectively collected from patient records. Medicines used were classified into three risk categories (high, moderate and none) according to the fall risk information in statutory summaries of product characteristics (SmPCs). The fall risk categorization incorporated the relative frequency of such adverse drug effects (ADEs) in SmPCs that were known to be connected to fall risk (sedation, orthostatic hypotension, syncope, dizziness, drowsiness, changes in blood pressure or impaired balance). Also, distribution of fall risk scores assessed on admission without considering medications was counted. Results The fall-experienced patients (n = 188, 128 from the hospital and 60 from nursing home records) used altogether 1748 medicaments, including 216 different active substances. Of the active substances, 102 (47%) were categorized as high risk (category A) for increasing fall risk. Fall-experienced patients (n = 188) received a mean of 3.8 category A medicines (n = 710), 53% (n = 375) of which affected the nervous and 40% (n = 281) the cardiovascular system. Without considering medication-related fall risk, 53% (n = 100) of the patients were scored having a high fall risk (3 or 4 risk scores). Conclusion It was possible to develop a preliminary categorization of FRIDs basing on their adverse drug effect profile in SmPCs and frequency of use in older patients who had experienced at least one documented fall in a geriatric care unit. Even though more than half of the fall-experienced study participants had high fall risk scores on admission, their fall risk might have been underestimated as use of high fall risk medicines was common, even concomitant use. Further studies are needed to develop the FRID categorization and assess its impact on fall risk.
  • Michalcova, Jana; Vasut, Karel; Airaksinen, Marja; Bielakova, Katarina (BioMed Central, 2020)
    Abstract Background Falls are common undesirable events for older adults in institutions. Even though the patient’s fall risk may be scored on admission, the medication-induced fall risk may be ignored. This study developed a preliminary categorization of fall-risk-increasing drugs (FRIDs) to be added as a risk factor to the existing fall risk assessment tool routinely used in geriatric care units. Methods Medication use data of older adults who had experienced at least one fall during a hospital ward or a nursing home stay within a 2-year study period were retrospectively collected from patient records. Medicines used were classified into three risk categories (high, moderate and none) according to the fall risk information in statutory summaries of product characteristics (SmPCs). The fall risk categorization incorporated the relative frequency of such adverse drug effects (ADEs) in SmPCs that were known to be connected to fall risk (sedation, orthostatic hypotension, syncope, dizziness, drowsiness, changes in blood pressure or impaired balance). Also, distribution of fall risk scores assessed on admission without considering medications was counted. Results The fall-experienced patients (n = 188, 128 from the hospital and 60 from nursing home records) used altogether 1748 medicaments, including 216 different active substances. Of the active substances, 102 (47%) were categorized as high risk (category A) for increasing fall risk. Fall-experienced patients (n = 188) received a mean of 3.8 category A medicines (n = 710), 53% (n = 375) of which affected the nervous and 40% (n = 281) the cardiovascular system. Without considering medication-related fall risk, 53% (n = 100) of the patients were scored having a high fall risk (3 or 4 risk scores). Conclusion It was possible to develop a preliminary categorization of FRIDs basing on their adverse drug effect profile in SmPCs and frequency of use in older patients who had experienced at least one documented fall in a geriatric care unit. Even though more than half of the fall-experienced study participants had high fall risk scores on admission, their fall risk might have been underestimated as use of high fall risk medicines was common, even concomitant use. Further studies are needed to develop the FRID categorization and assess its impact on fall risk.