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79 results on '"Berglund, G"'

2. SIDE-EFFECTS IN LONG-TERM TREATMENT WITH HYDRALAZINE

Author

O. K. Andersson, Berglund G, and Bengt R. Widgren

Subjects
Male, medicine.medical_specialty, Long term treatment, Lupus erythematosus, business.industry, MEDLINE, Retrospective cohort study, Middle Aged, Hydralazine, medicine.disease, Glomerulonephritis, Internal medicine, Hypertension, Internal Medicine, medicine, Humans, Lupus Erythematosus, Systemic, Female, business, Aged, Retrospective Studies, medicine.drug
Published
2009

3. Intraerythrocyte sodium content and transmembrane sodium flux in hypertensive patients treated with diuretics or β-adrenoceptorblockers

Author

Jacob Nauclér, Olof Jonsson, Dag Elmfeldt, Berglund G, and Hans Herlitz

Subjects
Adult, Male, medicine.medical_specialty, Erythrocytes, Potassium, medicine.medical_treatment, Sodium, Adrenergic beta-Antagonists, chemistry.chemical_element, Spironolactone, Pharmacology, Toxicology, Essential hypertension, chemistry.chemical_compound, Hydrochlorothiazide, Internal medicine, medicine, Humans, Diuretics, Metoprolol, Erythrocyte Membrane, Middle Aged, Hydralazine, medicine.disease, Endocrinology, chemistry, Hypertension, Diuretic, medicine.drug
Abstract

Forty-seven male patients with essential hypertension were randomized to treatment with either a beta-adrenoceptorblocker (metoprolol), (n = 24), or a diuretic (hydrochlorothiazide), (n = 23). If their diastolic blood pressure was not lowered below 95 mm Hg by the maximum dose of either drug, hydralazine (15 patients) and in a few cases (6 patients) spironolactone was given. After five years of treatment all the patients were examined with respect to intraerythrocyte sodium (IeNa) and potassium (IeK), sodium influx and sodium efflux. Patients treated with the diuretic (D) tended to have a higher IeNa (9.8 +/- 0.4 mmol/l red cells) and sodium influx (0.044 +/- 0.002 mmol Na/l X min) compared with those taking the beta-adrenoceptorblocker (B) (8.9 +/- 0.3 mmol/l and 0.041 +/- 0.002 mmol Na/l X min), but neither of these differences was statistically significant. Sodium efflux, however, was significantly increased in D (0.073 +/- 0.003 mmol Na/l X min vs 0.061 +/- 0.003 mmol/l X min). No difference in IeK was noted between the two groups. Six patients taking spironolactone had a low IeNa (7.3 +/- 0.4 mmol/l), sodium influx (0.039 +/- 0.001 mmol Na/l X min) and sodium efflux (0.050 +/- 0.006 mmol Na/l X min).

Published
2009

4. The Swedish CArdioPulmonary BioImage Study: objectives and design

Author

Bergström, G., primary, Berglund, G., additional, Blomberg, A., additional, Brandberg, J., additional, Engström, G., additional, Engvall, J., additional, Eriksson, M., additional, Faire, U., additional, Flinck, A., additional, Hansson, M. G., additional, Hedblad, B., additional, Hjelmgren, O., additional, Janson, C., additional, Jernberg, T., additional, Johnsson, Å., additional, Johansson, L., additional, Lind, L., additional, Löfdahl, C.‐G., additional, Melander, O., additional, Östgren, C. J., additional, Persson, A., additional, Persson, M., additional, Sandström, A., additional, Schmidt, C., additional, Söderberg, S., additional, Sundström, J., additional, Toren, K., additional, Waldenström, A., additional, Wedel, H., additional, Vikgren, J., additional, Fagerberg, B., additional, and Rosengren, A., additional

Published
2015
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5. Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables

Author

Burgess, Stephen, Thompson, Simon G, CRP CHD Genetics Collaboration, Burgess, S, Thompson, SG, Andrews, G, Samani, NJ, Hall, A, Whincup, P, Morris, R, Lawlor, DA, Davey Smith, G, Timpson, N, Ebrahim, S, Ben-Shlomo, Y, Brown, M, Ricketts, S, Sandhu, M, Reiner, A, Psaty, B, Lange, L, Cushman, M, Hung, J, Thompson, P, Beilby, J, Warrington, N, Palmer, LJ, Nordestgaard, BG, Tybjaerg-Hansen, A, Zacho, J, Wu, C, Lowe, G, Tzoulaki, I, Kumari, M, Yamamoto, JF, Chiodini, B, Franzosi, M, Hankey, GJ, Jamrozik, K, Palmer, L, Rimm, E, Pai, J, Heckbert, S, Bis, J, Anand, S, Engert, J, Collins, R, Clarke, R, Melander, O, Berglund, G, Ladenvall, P, Johansson, L, Jansson, J-H, Hallmans, G, Hingorani, A, Humphries, S, Manson, J, Watkins, H, Hopewell, J, Saleheen, D, Frossard, R, Danesh, J, Sattar, N, Robertson, M, Shepherd, J, Schaefer, E, Hofman, A, Witteman, JCM, Kardys, I, de Faire, U, Bennet, A, Ford, I, Packard, C, Lawlor, Debbie A, Davey Smith, George, Casas, JP, Smeeth, L, Wensley, F, Bowden, J, Di Angelantonio, E, Gao, P, Shah, T, Verzilli, C, Walker, M, Whittaker, J, Danesh, John [0000-0003-1158-6791], Sandhu, Manjinder [0000-0002-2725-142X], Burgess, Stephen [0000-0001-5365-8760], Di Angelantonio, Emanuele [0000-0001-8776-6719], Thompson, Simon [0000-0002-5274-7814], and Apollo - University of Cambridge Repository

Subjects
Genetic Markers, C-Reactive Protein, Models, Statistical, Phenotype, Meta-Analysis as Topic, Fibrinogen, Humans, Bayes Theorem, Biostatistics, Polymorphism, Single Nucleotide
Abstract

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.

Published
2010

6. Systematically missing confounders in individual participant data meta-analysis of observational cohort studies

Author

Fibrinogen Studies Collaboration, Jackson, D, White, I, Kostis, JB, Wilson, AC, Folsom, AR, Wu, K, Chambless, L, Benderly, M, Goldbourt, U, Willeit, J, Kiechl, S, Yarnell, JW, Sweetnam, PM, Elwood, PC, Cushman, M, Psaty, BM, Tracy, RP, Tybjaerg-Hansen, A, Haverkate, F, de Maat, MP, Thompson, SG, Fowkes, FG, Lee, AJ, Smith, FB, Salomaa, V, Harald, K, Rasi, V, Vahtera, E, Jousilahti, P, D'Agostino, R, Kannel, WB, Wilson, PW, Tofler, G, Levy, D, Marchioli, R, Valagussa, F, Rosengren, A, Wilhelmsen, L, Lappas, G, Eriksson, H, Cremer, P, Nagel, D, Curb, JD, Rodriguez, B, Yano, K, Salonen, J, Nyyssönen, K, Tuomainen, TP, Hedblad, B, Engström, G, Berglund, G, Loewel, H, Koenig, W, Hense, HW, Meade, TW, Cooper, JA, De Stavola, B, Knottenbelt, C, Miller, GJ, Bauer, KA, Rosenberg, RD, Sato, S, Kitamura, A, Naito, Y, Iso, H, Palosuo, T, Ducimetiere, P, Amouyel, P, Arveiler, D, Evans, AE, Ferrieres, J, Juhan-Vague, I, Bingham, A, Schulte, H, Assmann, G, Cantin, B, Lamarche, B, Despres, JP, Dagenais, GR, Tunstall-Pedoe, H, Lowe, GD, Woodward, M, Ben-Shlomo, Y, Davey Smith, G, Palmieri, V, Yeh, JL, Rudnicka, A, Brennan, P, Ridker, P, Rodeghiero, F, Tosetto, A, Shepherd, J, Ford, I, Robertson, M, Brunner, E, Shipley, M, Feskens, EJ, Di Angelantonio, E, Kaptoge, S, Lewington, S, Sarwar, N, Walker, M, Watson, S, White, IR, Wood, AM, and Danesh, J

Abstract

One difficulty in performing meta-analyses of observational cohort studies is that the availability of confounders may vary between cohorts, so that some cohorts provide fully adjusted analyses while others only provide partially adjusted analyses. Commonly, analyses of the association between an exposure and disease either are restricted to cohorts with full confounder information, or use all cohorts but do not fully adjust for confounding. We propose using a bivariate random-effects meta-analysis model to use information from all available cohorts while still adjusting for all the potential confounders. Our method uses both the fully adjusted and the partially adjusted estimated effects in the cohorts with full confounder information, together with an estimate of their within-cohort correlation. The method is applied to estimate the association between fibrinogen level and coronary heart disease incidence using data from 154,012 participants in 31 cohorts

Published
2009

50. The Malmö biological bank

Author

PERO, R. W., primary, OLSSON, A., additional, BERGLUND, G., additional, JANZON, L., additional, LARSSON, S. A., additional, and ELMSTÅHL, S., additional

Published
1993
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