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101. Empagliflozin effectively reduces liver fat content in type 2 diabetes

Author

Kahl, S, additional, Gancheva, S, additional, Straßburger, K, additional, Herder, C, additional, Machann, J, additional, Katsuyama, H, additional, Kabisch, S, additional, Henkel, E, additional, Kopf, S, additional, Kantartzis, K, additional, Kuß, O, additional, Kupriyanova, Y, additional, Hwang, JH, additional, Kasperk, C, additional, Stefan, N, additional, Pfeiffer, AFH, additional, Birkenfeld, A, additional, and Roden, M, additional

Published
2019
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103. Subphenotypen neu diagnostizierter Patienten mit Diabetes entwickeln unterschiedliche Risikoprofile für Diabetes-assoziierte Erkrankungen

Author

Zaharia, OP, additional, Strassburger, K, additional, Strom, A, additional, Kupriyanova, Y, additional, Bönhof, G, additional, Karusheva, Y, additional, Antoniou, S, additional, Bódis, K, additional, Markgraf, D, additional, Burkart, V, additional, Müssig, K, additional, Hwang, JH, additional, Asplund, O, additional, Groop, L, additional, Ahlqvist, E, additional, Seissler, J, additional, Nawroth, P, additional, Kopf, S, additional, Schmid, SM, additional, Stumvoll, M, additional, Pfeiffer, AFH, additional, Kabisch, S, additional, Tselmin, S, additional, Fritsche, A, additional, Ziegler, D, additional, Kuss, O, additional, Szendroedi, J, additional, and Roden, M, additional

Published
2019
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104. Association of CD69 Up-Regulation on CD4+ CLA+ T cells versus patch test, strip patch test and clinical history in nickel sensitization

Author

Dickel H, Kuss O, Kamphowe J, Altmeyer P, and Höxtermann S

Subjects
Allergic contact dermatitis, nickel sulfate, flow cytometric assay, CD69 up-regulation, patch test, strip patch test, clinical history, receiver operating characteristic, Medicine
Abstract

Abstract Objective The patch test (PT) with its modification - the strip patch test (SPT) - is the standard in vivo procedure to diagnose an allergic contact dermatitis (ACD). To date, none of the in vitro tests for the diagnosis of ACD fulfils the requirements of an easy, valid and reliable test. To investigate the prediction ability of a flow cytometric assay of CD69 up-regulation on CD4+ CLA+ T cells in nickel-sensitive and non-nickel-sensitive patients. Methods In a prospective, investigator-blinded, clinical study a total of 85 nickel-sensitive (n = 44; 51.8%) and non-nickel-sensitive patients (n = 41; 48.2%) were enrolled. The association between CD69 up-regulation on CD4+ CLA+ T cells on the one hand and PT, SPT, and clinical history on the other hand was measured. Association is expressed with c statistic values (receiver operating characteristic analysis) and corresponding 95% CIs. Results The associations were c = 0.57 (95% CI: 0.42-0.72) between CD69 up-regulation and PT, c = 0.49 (95% CI: 0.36-0.62) between CD69 up-regulation and SPT, and c = 0.51 (95% CI: 0.37-0.64) between CD69 up-regulation and clinical history. Conclusions CD69 up-regulation on CD4+ CLA+ T cells in vitro could not predict neither a positive PT or SPT result nor a positive clinical history to nickel sulfate. The combination of clinical history and patch testing still remains the basis for diagnosing ACD.

Published
2010
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106. Die Propensity Score-Analyse – Eine innovative Methode zur Auswertung von nichtrandomisierten Interventionsstudien

Author

Kuß, O

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund: Es besteht weitgehende Einigkeit in der empirischen Forschung darüber, dass Interventionen primär in randomisierten Studien geprüft werden sollen. In manchen Fällen sind diese jedoch „unnötig, ungeeignet, unmöglich oder ungenügend“ und werden[zum vollständigen Text gelangen Sie über die oben angegebene URL], 51. Kongress für Allgemeinmedizin und Familienmedizin

Published
2017
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107. Erratum to:Methods for evaluating medical tests and biomarkers

Author

Gopalakrishna, G, Langendam, M, Scholten, R, Bossuyt, P, Leeflang, M, Noel-Storr, A, Thomas, J, Marshall, I, Wallace, B, Whiting, P, Davenport, C, GopalaKrishna, G, De Salis, I, Mallett, S, Wolff, R, Riley, R, Westwood, M, Kleinen, J, Collins, G, Reitsma, H, Moons, K, Zapf, A, Hoyer, A, Kramer, K, Kuss, O, Ensor, J, Deeks, JJ, Martin, EC, Riley, RD, Rücker, G, Steinhauser, S, Schumacher, M, Snell, K, Willis, B, Debray, T, Deeks, J, Di Ruffano, LF, Taylor-Phillips, S, Hyde, C, Taylor, SA, Batnagar, G, STREAMLINE COLON Investigators, STREAMLINE LUNG Investigators, METRIC Investigators, Seedat, F, Clarke, A, Byron, S, Nixon, F, Albrow, R, Walker, T, Deakin, C, Zhelev, Z, Hunt, H, Yang, Y, Abel, L, Buchanan, J, Fanshawe, T, Shinkins, B, Wynants, L, Verbakel, J, Van Huffel, S, Timmerman, D, Van Calster, B, Zwinderman, A, Oke, J, O'Sullivan, J, Perera, R, Nicholson, B, Bromley, HL, Roberts, TE, Francis, A, Petrie, D, Mann, GB, Malottki, K, Smith, H, Billingham, L, Sitch, A, Gerke, O, Holm-Vilstrup, M, Segtnan, EA, Halekoh, U, Høilund-Carlsen, PF, Francq, BG, Dinnes, J, Parkes, J, Gregory, W, Hewison, J, Altman, D, Rosenberg, W, Selby, P, Asselineau, J, Perez, P, Paye, A, Bessede, E, Proust-Lima, C, Naaktgeboren, C, De Groot, J, Rutjes, A, Reitsma, J, Ogundimu, E, Cook, J, Le Manach, Y, Vergouwe, Y, Pajouheshnia, R, Groenwold, R, Peelen, L, Nieboer, D, De Cock, B, Pencina, MJ, Steyerberg, EW, Cooper, J, Parsons, N, Stinton, C, Smith, S, Dickens, A, Jordan, R, Enocson, A, Fitzmaurice, D, Adab, P, Boachie, C, Vidmar, G, Freeman, K, Connock, M, Court, R, Moons, C, Harris, J, Mumford, A, Plummer, Z, Lee, K, Reeves, B, Rogers, C, Verheyden, V, Angelini, GD, Murphy, GJ, Huddy, J, Ni, M, Good, K, Cooke, G, Hanna, G, Ma, J, Moons, KGMC, De Groot, JAH, Altman, DG, Reitsma, JB, Collins, GS, Moons, KGM, Kamarudin, AN, Kolamunnage-Dona, R, Cox, T, Borsci, S, Pérez, T, Pardo, MC, Candela-Toha, A, Muriel, A, Zamora, J, Sanghera, S, Mohiuddin, S, Martin, R, Donovan, J, Coast, J, Seo, MK, Cairns, J, Mitchell, E, Smith, A, Wright, J, Hall, P, Messenger, M, Calder, N, Wickramasekera, N, Vinall-Collier, K, Lewington, A, Damen, J, Cairns, D, Hutchinson, M, Sturgeon, C, Mitchel, L, Kift, R, Christakoudi, S, Rungall, M, Mobillo, P, Montero, R, Tsui, T-L, Kon, SP, Tucker, B, Sacks, S, Farmer, C, Strom, T, Chowdhury, P, Rebollo-Mesa, I, Hernandez-Fuentes, M, Damen, JAAG, Debray, TPA, Heus, P, Hooft, L, Scholten, RJPM, Schuit, E, Tzoulaki, I, Lassale, CM, Siontis, GCM, Chiocchia, V, Roberts, C, Schlüssel, MM, Gerry, S, Black, JA, Van der Schouw, YT, Peelen, LM, Spence, G, McCartney, D, Van den Bruel, A, Lasserson, D, Hayward, G, Vach, W, De Jong, A, Burggraaff, C, Hoekstra, O, Zijlstra, J, De Vet, H, Graziadio, S, Allen, J, Johnston, L, O'Leary, R, Power, M, Johnson, L, Waters, R, Simpson, J, Fanshawe, TR, Phillips, P, Plumb, A, Helbren, E, Halligan, S, Gale, A, Sekula, P, Sauerbrei, W, Forman, JR, Dutton, SJ, Takwoingi, Y, Hensor, EM, Nichols, TE, Kempf, E, Porcher, R, De Beyer, J, Hopewell, S, Dennis, J, Shields, B, Jones, A, Henley, W, Pearson, E, Hattersley, A, MASTERMIND consortium, Scheibler, F, Rummer, A, Sturtz, S, Großelfinger, R, Banister, K, Ramsay, C, Azuara-Blanco, A, Burr, J, Kumarasamy, M, Bourne, R, Uchegbu, I, Murphy, J, Carter, A, Marti, J, Eatock, J, Robotham, J, Dudareva, M, Gilchrist, M, Holmes, A, Monaghan, P, Lord, S, StJohn, A, Sandberg, S, Cobbaert, C, Lennartz, L, Verhagen-Kamerbeek, W, Ebert, C, Horvath, A, Test Evaluation Working Group of the European Federation of Clinical Chemistry and Laboratory Medicine, Jenniskens, K, Peters, J, Grigore, B, Ukoumunne, O, Levis, B, Benedetti, A, Levis, AW, Ioannidis, JPA, Shrier, I, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Steele, RJ, Ziegelstein, RC, Bombardier, CH, Osório, FDL, Fann, JR, Gjerdingen, D, Lamers, F, Lotrakul, M, Loureiro, SR, Löwe, B, Shaaban, J, Stafford, L, Van Weert, HCPM, Whooley, MA, Williams, LS, Wittkampf, KA, Yeung, AS, Thombs, BD, Cooper, C, Nieto, T, Smith, C, Tucker, O, Dretzke, J, Beggs, A, Rai, N, Bayliss, S, Stevens, S, Mallet, S, Sundar, S, Hall, E, Porta, N, Estelles, DL, De Bono, J, CTC-STOP protocol development group, and National Institute for Health Research

Subjects
medicine.medical_specialty, Astrophysics::High Energy Astrophysical Phenomena, MEDLINE, 030204 cardiovascular system & hematology, BTC (Bristol Trials Centre), MASTERMIND consortium, 03 medical and health sciences, 0302 clinical medicine, medicine, 030212 general & internal medicine, Intensive care medicine, CTC-STOP protocol development group, lcsh:R5-920, business.industry, Test Evaluation Working Group of the European Federation of Clinical Chemistry and Laboratory Medicine, Published Erratum, STREAMLINE COLON Investigators, 3. Good health, STREAMLINE LUNG Investigators, Centre for Surgical Research, Family medicine, METRIC Investigators, High Energy Physics::Experiment, Erratum, business, lcsh:Medicine (General)
Abstract

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

Published
2017

108. Age at diagnosis of Type 2 diabetes in Germany: a nationwide analysis based on claims data from 69 million people.

Author

Jacobs, E., Rathmann, W., Tönnies, T., Arendt, D., Marchowez, M., Veith, L., Kuss, O., Brinks, R., and Hoyer, A.

Subjects
AGE distribution, AGE factors in disease, CONFIDENCE intervals, MEDICAL informatics, TYPE 2 diabetes, SEX distribution, DESCRIPTIVE statistics
Abstract

Aim: For many European countries, including Germany, no valid estimates are available on age at diagnosis of Type 2 diabetes. Thus, we aimed to estimate the age at diagnosis in Germany. Methods: Age at diagnosis of Type 2 diabetes in Germany was estimated based on Type 2 diabetes prevalence and incidence and the age distribution of the German population. Age‐ and sex‐specific incidence and prevalence in 2014/2015, based on claims data from statutory health insurance (n= 69 000 000, ~85% of the German population), and the age pyramid for Germany in 2015 were used for the calculation. Age at Type 2 diabetes diagnosis was stratified by sex. CIs were estimated using bootstrap methods. In addition, the age range in which 50% of the population received a diagnosis of Type 2 diabetes was calculated (the interquartile range). Results: The mean ± sd age at Type 2 diabetes diagnosis in 2015 was 61.0 ± 13.4 years (95% CI 60.9–61.0) in men. Women were diagnosed ~2 years later than men (mean age 63.4 ± 14.9 years; 95% CI 63.4–63.5). The age range in which 50% of the population was diagnosed with diabetes was 53–72 years for men and 54–76 years for women. Conclusions: The sex differences are mainly attributable to a higher incidence of Type 2 diabetes in men than women during middle age and the higher absolute number of women in the older ages. The early age at diabetes diagnosis compared to average life expectancy means that the risk of diabetes‐related complications is increased. What's new?: In Europe, estimates of age at Type 2 diabetes diagnosis are rarely available and are often not representative of the general population.A high proportion of newly diagnosed Type 2 diabetes cases occur in the age group of 60–80 years.The present study found that the mean age at Type 2 diabetes diagnosis was 61.0 ± 13.4 years in men [median (interquartile range) 62 (53–72) years] and 63.4 ± 14.9 years in women [median (interquartile range) 65 (54–76) years].As a result of increasing life expectancy, a mean age at diagnosis in the early 60s indicates a long diabetes duration, which increases the risk of complications. [ABSTRACT FROM AUTHOR]

Published
2020
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109. Associations between cognitive performance and Mediterranean dietary pattern in patients with type 1 or type 2 diabetes mellitus.

Author

Kössler, Theresa, Weber, Katharina S., Wölwer, Wolfgang, Hoyer, Annika, Strassburger, Klaus, Burkart, Volker, Szendroedi, Julia, Roden, Michael, Müssig, Karsten, for the GDS Group, Roden, M., Al-Hasani, H., Buyken, A. E., Belgardt, B., Geerling, G., Herder, C., Icks, A., Kotzka, J., Kuß, O., and Lammert, E.

Subjects
DIABETES, VERBAL memory, COGNITIVE ability, DIET, TYPE 2 diabetes
Abstract

Diabetes mellitus has been associated with impaired cognitive performance, particularly in verbal memory. Mediterranean diets (MedD) may lead to improvements in overall and single cognitive functions. We hypothesised that adherence to MedD associates with better performance in verbal memory in patients with type 1 or type 2 diabetes. Thus, we performed a cross-sectional analysis including patients with recently diagnosed type 1 (n = 75) or type 2 diabetes (n = 118), metabolically healthy individuals (n = 41) and individuals with type 1 (n = 44) or type 2 diabetes (n = 62) of at least five years after diagnosis. Participants underwent comprehensive metabolic phenotyping and cognitive testing. Adherence to the Modified Mediterranean diet scale (MMDS) was computed from a food frequency questionnaire. Among patients with type 2 diabetes with a known diabetes duration ≥5 years, closer adherence to the MMDS was associated with higher score in verbal memory after adjustment for potential confounders (P = 0.043). Adherence to the MMDS did not relate to verbal memory in recently diagnosed type 2 diabetes (P = 0.275), recently diagnosed or longer-standing type 1 diabetes (P = 0.215 and P = 0.626, respectively) or metabolically healthy individuals (P = 0.666). In conclusion, closer adherence to MedD may exert beneficial effects on cognitive performance in the course of type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2020
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113. Meta-analysis of treatment need for temporomandibular disorders in adult nonpatients.

Author

Al-Jundi MA, John MT, Setz JM, Szentpétery A, and Kuss O

Abstract

AIMS: To determine the prevalence of treatment need for temporomandibular disorders in adult populations by meta-analysis of nonpatient studies and to investigate factors influencing temporomandibular disorder treatment-need estimates. METHODS: Population-based and nonpatient studies of adult subjects with temporomandibular disorders published in the English language prior to July 2006 were systematically reviewed. Electronic databases (MEDLINE, CINAHL, and Science Citation Index Expanded) were searched (n = 641). To combine data, fixed- and random-effects meta-regression models were used. Subgroup analyses were performed to assess factors influencing treatment need estimates. RESULTS: Of 676 articles identified, 17 (9,454 subjects) met the study criteria. The prevalence of treatment need for TMD in adults (95% confidence interval) was estimated to be 15.6% (10.0, 23.6) for the fixed effect model and 16.2% (11.2, 21.1) for the random-effects model. Criteria of estimating treatment need and place of study strongly influenced summary estimates of treatment need (P < .001). Need estimates derived from clinical TMD signs were higher than estimates based on subject-reported symptoms (P = .010). Estimates for younger subjects (19 to 45 years) were higher than for older subjects (46+ years; P = .013). CONCLUSION: The treatment need for TMD in the general adult population is substantial and varies according to definition, criteria, and age. Findings of this meta-analysis can be used for planning and allocating health-care resources. [ABSTRACT FROM AUTHOR]

Published
2008

114. Clinical effectiveness of a strontium chloride -- containing desensitizing agent over 6 months: a randomized, double-blind, placebo-controlled study.

Author

Kobler A, Kuß O, Schaller H, and Gernhardt CR

Abstract

Objective: The aim of this multicenter study was to evaluate the clinical efficacy of a strontium chlorideDScontaining desensitizer, Hyposen (Lege Artis), over 6 months. Method and Materials: A total of 142 patients with hypersensitivity in 9 dental practices and 2 clinical departments were included in the double-blind, randomized, placebo-controlled study. Each patient exhibited at least 2 hypersensitive and caries-free teeth with exposed dentin surfaces. One tooth was treated with strontium chloride (SR) as recommended by the manufacturer, another with a placebo. Levels of hypersensitivity were assessed after 2, 8, 12, and 24 weeks by cold air and tactile stimuli. After 6 months 132 patients could be reexamined. Results: A reduction of discomfort and pain was observed in 95 patients (72%) after treatment with SR. Statistical analysis showed a significant positive effect of SR compared to the placebo group (P < .05, McNemar test). Conclusion: Use of SR for desensitizing hypersensitive dentin is an effective alternative to existing desensitizing agents. [ABSTRACT FROM AUTHOR]

Published
2008

115. Erratum to: Methods for evaluating medical tests and biomarkers.

Author

Gopalakrishna, G, Langendam, M, Scholten, R, Bossuyt, P, Leeflang, M, Noel-Storr, A, Thomas, J, Marshall, I, Wallace, B, Whiting, P, Davenport, C, GopalaKrishna, G, de Salis, I, Mallett, S, Wolff, R, Riley, R, Westwood, M, Kleinen, J, Collins, G, Reitsma, H, Moons, K, Zapf, A, Hoyer, A, Kramer, K, Kuss, O, Ensor, J, Deeks, JJ, Martin, EC, Riley, RD, Rücker, G, Steinhauser, S, Schumacher, M, Snell, K, Willis, B, Debray, T, Deeks, J, di Ruffano, LF, Taylor-Phillips, S, Hyde, C, Taylor, SA, Batnagar, G, STREAMLINE COLON Investigators, STREAMLINE LUNG Investigators, METRIC Investigators, Di Ruffano, LF, Seedat, F, Clarke, A, Byron, S, Nixon, F, Albrow, R, Walker, T, Deakin, C, Zhelev, Z, Hunt, H, Yang, Y, Abel, L, Buchanan, J, Fanshawe, T, Shinkins, B, Wynants, L, Verbakel, J, Van Huffel, S, Timmerman, D, Van Calster, B, Zwinderman, A, Oke, J, O'Sullivan, J, Perera, R, Nicholson, B, Bromley, HL, Roberts, TE, Francis, A, Petrie, D, Mann, GB, Malottki, K, Smith, H, Billingham, L, Sitch, A, Gerke, O, Holm-Vilstrup, M, Segtnan, EA, Halekoh, U, Høilund-Carlsen, PF, Francq, BG, Dinnes, J, Parkes, J, Gregory, W, Hewison, J, Altman, D, Rosenberg, W, Selby, P, Asselineau, J, Perez, P, Paye, A, Bessede, E, Proust-Lima, C, Naaktgeboren, C, de Groot, J, Rutjes, A, Reitsma, J, Ogundimu, E, Cook, J, Le Manach, Y, Vergouwe, Y, Pajouheshnia, R, Groenwold, R, Peelen, L, Nieboer, D, De Cock, B, Pencina, MJ, Steyerberg, EW, Cooper, J, Parsons, N, Stinton, C, Smith, S, Dickens, A, Jordan, R, Enocson, A, Fitzmaurice, D, Adab, P, Boachie, C, Vidmar, G, Freeman, K, Connock, M, Court, R, Moons, C, Harris, J, Mumford, A, Plummer, Z, Lee, K, Reeves, B, Rogers, C, Verheyden, V, Angelini, GD, Murphy, GJ, Huddy, J, Ni, M, Good, K, Cooke, G, Hanna, G, Ma, J, Moons, KGMC, de Groot, JAH, Altman, DG, Reitsma, JB, Collins, GS, Moons, KGM, Kamarudin, AN, Kolamunnage-Dona, R, Cox, T, Borsci, S, Pérez, T, Pardo, MC, Candela-Toha, A, Muriel, A, Zamora, J, Sanghera, S, Mohiuddin, S, Martin, R, Donovan, J, Coast, J, Seo, MK, Cairns, J, Mitchell, E, Smith, A, Wright, J, Hall, P, Messenger, M, Calder, N, Wickramasekera, N, Vinall-Collier, K, Lewington, A, Damen, J, Cairns, D, Hutchinson, M, Sturgeon, C, Mitchel, L, Kift, R, Christakoudi, S, Rungall, M, Mobillo, P, Montero, R, Tsui, T-L, Kon, SP, Tucker, B, Sacks, S, Farmer, C, Strom, T, Chowdhury, P, Rebollo-Mesa, I, Hernandez-Fuentes, M, Damen, JAAG, Debray, TPA, Heus, P, Hooft, L, Scholten, RJPM, Schuit, E, Tzoulaki, I, Lassale, CM, Siontis, GCM, Chiocchia, V, Roberts, C, Schlüssel, MM, Gerry, S, Black, JA, van der Schouw, YT, Peelen, LM, Spence, G, McCartney, D, van den Bruel, A, Lasserson, D, Hayward, G, Vach, W, de Jong, A, Burggraaff, C, Hoekstra, O, Zijlstra, J, de Vet, H, Graziadio, S, Allen, J, Johnston, L, O'Leary, R, Power, M, Johnson, L, Waters, R, Simpson, J, Fanshawe, TR, Phillips, P, Plumb, A, Helbren, E, Halligan, S, Gale, A, Sekula, P, Sauerbrei, W, Forman, JR, Dutton, SJ, Takwoingi, Y, Hensor, EM, Nichols, TE, Kempf, E, Porcher, R, de Beyer, J, Hopewell, S, Dennis, J, Shields, B, Jones, A, Henley, W, Pearson, E, Hattersley, A, MASTERMIND consortium, Scheibler, F, Rummer, A, Sturtz, S, Großelfinger, R, Banister, K, Ramsay, C, Azuara-Blanco, A, Burr, J, Kumarasamy, M, Bourne, R, Uchegbu, I, Murphy, J, Carter, A, Marti, J, Eatock, J, Robotham, J, Dudareva, M, Gilchrist, M, Holmes, A, Monaghan, P, Lord, S, StJohn, A, Sandberg, S, Cobbaert, C, Lennartz, L, Verhagen-Kamerbeek, W, Ebert, C, Horvath, A, Test Evaluation Working Group of the European Federation of Clinical Chemistry and Laboratory Medicine, Jenniskens, K, Peters, J, Grigore, B, Ukoumunne, O, Levis, B, Benedetti, A, Levis, AW, Ioannidis, JPA, Shrier, I, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Steele, RJ, Ziegelstein, RC, Bombardier, CH, Osório, FDL, Fann, JR, Gjerdingen, D, Lamers, F, Lotrakul, M, Loureiro, SR, Löwe, B, Shaaban, J, Stafford, L, van Weert, HCPM, Whooley, MA, Williams, LS, Wittkampf, KA, Yeung, AS, Thombs, BD, Cooper, C, Nieto, T, Smith, C, Tucker, O, Dretzke, J, Beggs, A, Rai, N, Bayliss, S, Stevens, S, Mallet, S, Sundar, S, Hall, E, Porta, N, Estelles, DL, de Bono, J, CTC-STOP protocol development group, Gopalakrishna, G, Langendam, M, Scholten, R, Bossuyt, P, Leeflang, M, Noel-Storr, A, Thomas, J, Marshall, I, Wallace, B, Whiting, P, Davenport, C, GopalaKrishna, G, de Salis, I, Mallett, S, Wolff, R, Riley, R, Westwood, M, Kleinen, J, Collins, G, Reitsma, H, Moons, K, Zapf, A, Hoyer, A, Kramer, K, Kuss, O, Ensor, J, Deeks, JJ, Martin, EC, Riley, RD, Rücker, G, Steinhauser, S, Schumacher, M, Snell, K, Willis, B, Debray, T, Deeks, J, di Ruffano, LF, Taylor-Phillips, S, Hyde, C, Taylor, SA, Batnagar, G, STREAMLINE COLON Investigators, STREAMLINE LUNG Investigators, METRIC Investigators, Di Ruffano, LF, Seedat, F, Clarke, A, Byron, S, Nixon, F, Albrow, R, Walker, T, Deakin, C, Zhelev, Z, Hunt, H, Yang, Y, Abel, L, Buchanan, J, Fanshawe, T, Shinkins, B, Wynants, L, Verbakel, J, Van Huffel, S, Timmerman, D, Van Calster, B, Zwinderman, A, Oke, J, O'Sullivan, J, Perera, R, Nicholson, B, Bromley, HL, Roberts, TE, Francis, A, Petrie, D, Mann, GB, Malottki, K, Smith, H, Billingham, L, Sitch, A, Gerke, O, Holm-Vilstrup, M, Segtnan, EA, Halekoh, U, Høilund-Carlsen, PF, Francq, BG, Dinnes, J, Parkes, J, Gregory, W, Hewison, J, Altman, D, Rosenberg, W, Selby, P, Asselineau, J, Perez, P, Paye, A, Bessede, E, Proust-Lima, C, Naaktgeboren, C, de Groot, J, Rutjes, A, Reitsma, J, Ogundimu, E, Cook, J, Le Manach, Y, Vergouwe, Y, Pajouheshnia, R, Groenwold, R, Peelen, L, Nieboer, D, De Cock, B, Pencina, MJ, Steyerberg, EW, Cooper, J, Parsons, N, Stinton, C, Smith, S, Dickens, A, Jordan, R, Enocson, A, Fitzmaurice, D, Adab, P, Boachie, C, Vidmar, G, Freeman, K, Connock, M, Court, R, Moons, C, Harris, J, Mumford, A, Plummer, Z, Lee, K, Reeves, B, Rogers, C, Verheyden, V, Angelini, GD, Murphy, GJ, Huddy, J, Ni, M, Good, K, Cooke, G, Hanna, G, Ma, J, Moons, KGMC, de Groot, JAH, Altman, DG, Reitsma, JB, Collins, GS, Moons, KGM, Kamarudin, AN, Kolamunnage-Dona, R, Cox, T, Borsci, S, Pérez, T, Pardo, MC, Candela-Toha, A, Muriel, A, Zamora, J, Sanghera, S, Mohiuddin, S, Martin, R, Donovan, J, Coast, J, Seo, MK, Cairns, J, Mitchell, E, Smith, A, Wright, J, Hall, P, Messenger, M, Calder, N, Wickramasekera, N, Vinall-Collier, K, Lewington, A, Damen, J, Cairns, D, Hutchinson, M, Sturgeon, C, Mitchel, L, Kift, R, Christakoudi, S, Rungall, M, Mobillo, P, Montero, R, Tsui, T-L, Kon, SP, Tucker, B, Sacks, S, Farmer, C, Strom, T, Chowdhury, P, Rebollo-Mesa, I, Hernandez-Fuentes, M, Damen, JAAG, Debray, TPA, Heus, P, Hooft, L, Scholten, RJPM, Schuit, E, Tzoulaki, I, Lassale, CM, Siontis, GCM, Chiocchia, V, Roberts, C, Schlüssel, MM, Gerry, S, Black, JA, van der Schouw, YT, Peelen, LM, Spence, G, McCartney, D, van den Bruel, A, Lasserson, D, Hayward, G, Vach, W, de Jong, A, Burggraaff, C, Hoekstra, O, Zijlstra, J, de Vet, H, Graziadio, S, Allen, J, Johnston, L, O'Leary, R, Power, M, Johnson, L, Waters, R, Simpson, J, Fanshawe, TR, Phillips, P, Plumb, A, Helbren, E, Halligan, S, Gale, A, Sekula, P, Sauerbrei, W, Forman, JR, Dutton, SJ, Takwoingi, Y, Hensor, EM, Nichols, TE, Kempf, E, Porcher, R, de Beyer, J, Hopewell, S, Dennis, J, Shields, B, Jones, A, Henley, W, Pearson, E, Hattersley, A, MASTERMIND consortium, Scheibler, F, Rummer, A, Sturtz, S, Großelfinger, R, Banister, K, Ramsay, C, Azuara-Blanco, A, Burr, J, Kumarasamy, M, Bourne, R, Uchegbu, I, Murphy, J, Carter, A, Marti, J, Eatock, J, Robotham, J, Dudareva, M, Gilchrist, M, Holmes, A, Monaghan, P, Lord, S, StJohn, A, Sandberg, S, Cobbaert, C, Lennartz, L, Verhagen-Kamerbeek, W, Ebert, C, Horvath, A, Test Evaluation Working Group of the European Federation of Clinical Chemistry and Laboratory Medicine, Jenniskens, K, Peters, J, Grigore, B, Ukoumunne, O, Levis, B, Benedetti, A, Levis, AW, Ioannidis, JPA, Shrier, I, Cuijpers, P, Gilbody, S, Kloda, LA, McMillan, D, Patten, SB, Steele, RJ, Ziegelstein, RC, Bombardier, CH, Osório, FDL, Fann, JR, Gjerdingen, D, Lamers, F, Lotrakul, M, Loureiro, SR, Löwe, B, Shaaban, J, Stafford, L, van Weert, HCPM, Whooley, MA, Williams, LS, Wittkampf, KA, Yeung, AS, Thombs, BD, Cooper, C, Nieto, T, Smith, C, Tucker, O, Dretzke, J, Beggs, A, Rai, N, Bayliss, S, Stevens, S, Mallet, S, Sundar, S, Hall, E, Porta, N, Estelles, DL, de Bono, J, and CTC-STOP protocol development group

Abstract

[This corrects the article DOI: 10.1186/s41512-016-0001-y.].

Published
2017

116. Frühe diabetische Neurodegeneration – Finden sich im SD-OCT nachweisbare retinale Schichtdickenunterschiede?

Author

Guthoff, R, Schröder, K, Ackermann, P, Steingrube, N, Benthin, A, Völcker, M, Szendrödi, J, Müssig, K, Nowotny, B, Kuß, O, and Roden, M

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund: Die diabetische Retinopathie wurde lange Zeit als mikrovaskuläre Erkrankung angesehen. In den letzten Jahren rückten jedoch zunehmend zusätzliche neurodegenerative Aspekte der Pathogenese in den Fokus. Analog zur Entstehung der diabetischen Polyneuropathie können retinologische[zum vollständigen Text gelangen Sie über die oben angegebene URL], 29. Jahrestagung der Retinologischen Gesellschaft

Published
2016
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122. Pleiotropy among common genetic loci identified for cardiometabolic disorders and C-reactive protein

Author

Ligthart, S, De Vries, PS, Uitterlinden, AG, Hofman, A, Franco, OH, Chasman, DI, Dehghan, A, Dupuis, J, Barbalic, M, Bis, JC, Eiriksdottir, G, Lu, C, Pellikka, N, Wallaschofski, H, Kettunen, J, Henneman, P, Baumert, J, Strachan, DP, Fuchsberger, C, Vitart, V, Wilson, JF, Paré, G, Naitza, S, Rudock, ME, Surakka, I, De Geus, EJC, Alizadeh, BZ, Guralnik, JMD, Shuldiner, A, Tanaka, T, Zee, RYL, Schnabel, RB, Nambi, V, Kavousi, M, Ripatti, S, Nauck, M, Smith, NL, Smith, AV, Sundvall, J, Scheet, P, Liu, Y, Ruokonen, A, Rose, LM, Larson, MG, Hoogeveen, RC, Freimer, NB, Teumer, A, Tracy, RP, Launer, LJ, Buring, JE, Yamamoto, JF, Folsom, AR, Sijbrands, EJG, Pankow, J, Elliott, P, Keaney, JF, Sun, W, Sarin, AP, Fontes, JD, Badola, S, Astor, BC, Pouta, A, Werda, K, Greiser, KH, Kuss, O, Schwabedissen, HEMZ, Thiery, J, Jamshidi, Y, Nolte, IM, Soranzo, N, Spector, TD, Völzke, H, Parker, AN, Aspelund, T, Bates, D, Young, L, Tsui, K, Siscovick, DS, Guo, X, Rotter, JI, Uda, M, Schlessinger, D, Rudan, I, Hicks, AA, Penninx, BW, Thorand, B, Gieger, C, Coresh, J, Willemsen, G, Harris, TB, Järvelin, MR, Rice, K, Radke, D, Salomaa, V, Van Dijk, KW, Boerwinkle, E, Vasan, RS, Ferrucci, L, and Gibson, QD

Abstract

© 2015 Ligthart et al. Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.

Published
2015

123. Distinct trajectories of HbA1c in newly diagnosed Type 2 diabetes from the DPV registry using a longitudinal group‐based modelling approach.

Author

Rathmann, W., Schwandt, A., Hermann, J. M., Kuss, O., Roden, M., Laubner, K., Best, F., Ebner, S., Plaumann, M., and Holl, R. W.

Subjects
TYPE 2 diabetes diagnosis, TYPE 2 diabetes treatment, REPORTING of diseases, DRUGS, GLYCOSYLATED hemoglobin, HYPERGLYCEMIA, LONGITUDINAL method, MEDICAL cooperation, PATIENT compliance, RESEARCH, MULTIPLE regression analysis, BODY mass index, STRUCTURAL equation modeling, GLYCEMIC control
Abstract

Aim: To identify groups of heterogeneous HbA1c trajectories over time in newly diagnosed Type 2 diabetes. Methods: The study comprised 6355 adults with newly diagnosed Type 2 diabetes (55% men, median age 62 years, baseline BMI 31 kg/m2) from the Diabetes Patienten Verlaufsdokumentation (DPV) prospective multicentre diabetes registry (Germany, Austria). Individuals were assessed during the first 5 years after diabetes diagnosis if they had ≥ 3 aggregated HbA1c measurements during follow‐up. Latent class growth modelling was used to determine distinct subgroups that followed similar longitudinal HbA1c patterns (SAS: Proc Traj). Multinomial logistic regression models were used to investigate which variables were associated with the respective HbA1c trajectory groups. Results: Four distinct longitudinal HbA1c trajectory (glycaemic control) groups were found. The largest group (56% of participants) maintained stable good glycaemic control (HbA1c 42–45 mmol/mol). Twenty‐six percent maintained stable moderate glycaemic control (HbA1c 57–62 mmol/mol). A third group (12%) initially showed severe hyperglycaemia (HbA1c 97 mmol/mol) but reached good glycaemic control within 1 year. The smallest group (6%) showed stable poor glycaemic control (HbA1c 79–88 mmol/mol). Younger age at diabetes diagnosis, male sex, and higher BMI were associated with the stable moderate or poor glycaemic control groups. Insulin therapy was strongly associated with the highly improved glycaemic control group. Conclusions: Four subgroups with distinct HbA1c trajectories were determined in newly diagnosed Type 2 diabetes using a group‐based modelling approach. Approximately one‐third of people with newly diagnosed Type 2 diabetes need either better medication adherence or earlier intensification of glucose‐lowering therapy. What's new?: Currently, data on HbA1c trajectories in newly diagnosed Type 2 diabetes are limited.This longitudinal study identified four distinct HbA1c trajectories during the first 5 years after Type 2 diabetes diagnosis. The largest group (56%) showed persistent good glycaemic control, whereas two smaller groups exhibited either stable moderate (26%) or poor (6%) glycaemic control, respectively. Twelve percent of people with Type 2 diabetes showed initial poor glycaemic control, which highly improved during the first year after diabetes diagnosis.A personalized medicine approach in the treatment of newly diagnosed Type 2 diabetes could be supported by identification of subgroups with specific HbA1c trajectories in response to glucose‐lowering therapy. [ABSTRACT FROM AUTHOR]

Published
2019
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124. Korrekter Umgang mit korrelierten Daten in der Rehabilitationsforschung

Author

Watzke S and Kuss O

Subjects
Mixed model, Structure (mathematical logic), Computer science, Clinical study design, Rehabilitation, computer.software_genre, Statistical power, Correlation, Multivariate analysis of variance, Simple (abstract algebra), Statistics, Analysis of variance, Data mining, computer
Abstract

Many study designs in rehabilitation science give rise to correlated data. For example, patients are followed over time, different responses are measured for each patient, or patients are observed in logical units. Standard statistical methods, however, are only valid for independent responses, and careless application of these methods for actually correlated observations might give erroneous results. By means of a simple example, we show how using methods for correlated data can indeed give a gain in statistical power. In the following, different approaches (Summary measures, Repeated Measurement ANOVA, MANOVA, and Mixed Models) to deal with correlated data are presented. We conclude that among these, the Mixed Models approach is the method of choice because it allows flexible modelling of correlation structure and is, meanwhile, also available in standard statistical software packages.

Published
2005

125. The biomechanical properties of an epithelial tissue determine the location of its vasculature.

Author

UCL - SST/ISV - Institut des sciences de la vie, Kragel, M, Schubert, R, Karsjens , H, Otter, S, Bartosinska, B, Jeruschke, K, Weiss, J, Chen, C, Alsteens, David, Kuss, O, Speier, S, Eberhard, D, Müller, Daniel, Lammert, E, UCL - SST/ISV - Institut des sciences de la vie, Kragel, M, Schubert, R, Karsjens , H, Otter, S, Bartosinska, B, Jeruschke, K, Weiss, J, Chen, C, Alsteens, David, Kuss, O, Speier, S, Eberhard, D, Müller, Daniel, and Lammert, E

Abstract

An important question is how growing tissues establish a blood vessel network. Here we study vascular network formation in pancreatic islets, endocrine tissues derived from pancreatic epithelium. We find that depletion of integrin-linked kinase (ILK) in the pancreatic epithelial cells of mice results in glucose intolerance due to a loss of the intra-islet vasculature. In turn, blood vessels accumulate at the islet periphery. Neither alterations in endothelial cell proliferation, apoptosis, morphology, Vegfa expression and VEGF-A secretion nor 'empty sleeves' of vascular basement membrane are found. Instead, biophysical experiments reveal that the biomechanical properties of pancreatic islet cells, such as their actomyosin-mediated cortex tension and adhesive forces to endothelial cells, are significantly changed. These results suggest that a sorting event is driving the segregation of endothelial and epithelial cells and indicate that the epithelial biomechanical properties determine whether the blood vasculature invades or envelops a growing epithelial tissue.

Published
2016

126. Meta-analysis to compare two diagnostic tests to a common gold standard - A new approach using quadrivariate copulas

Author

Hoyer, A. and Kuß, O.

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Introduction: Meta-analysis of diagnostic studies is still a rapidly developing area of biostatistical research. Especially, there is an increasing interest in methods to compare different tests to a common gold standard [ref:1]. Restricting to the case of two diagnostic tests, in these meta-analyses[for full text, please go to the a.m. URL], GMDS 2014; 59. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V. (GMDS)

Published
2014

127. Effekte eines Nachsorgeprogramms für Patienten nach Schlaganfall – Ergebnisse einer randomisierten kontrollierten Studie

Author

Saal, S, Becker, C, Kuß, O, Schubert, M, Stang, A, and Behrens, J

Subjects
ddc: 610, 610 Medical sciences, Medicine
Abstract

Hintergrund und Fragestellung: In der nachstationären Versorgung von Schlaganfallpatienten greifen rehabilitative und tertiärpräventive Aspekte ineinander, um die Auswirkungen des Ereignisses auf die unabhängige Lebensführung zu reduzieren. Dabei wird die nachstationäre[for full text, please go to the a.m. URL], Prävention zwischen Evidenz und Eminenz; 15. Jahrestagung des Deutschen Netzwerks Evidenzbasierte Medizin

Published
2014
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130. Midterm Outcome after Anaortic and Clampless Off-pump and Conventional Coronary Artery Bypass Grafting - Analysis of 5,422 Unselected Patients

Author

Börgermann, J., primary, Preindl, K., additional, Renner, A., additional, Aboud, A., additional, Hakim, K., additional, Benzinger, M., additional, Pühler, T., additional, Ensminger, S., additional, Becker, T., additional, Zittermann, A., additional, Kuss, O., additional, and Gummert, J., additional

Published
2016
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131. Pleiotropy among common genetic loci identified for cardiometabolic disorders and C-reactive protein

Author

Ligthart, S. (Symen), Vries, P.S. (Paul) de, Uitterlinden, A.G. (André), Hofman, A. (Albert), Franco, O.H. (Oscar), Chasman, D.I. (Daniel), Dehghan, A. (Abbas), Dupuis, J. (Josée), Barbalic, M. (maja), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Lu, C. (Chen), Pellikka, N. (Niina), Wallaschofski, H. (Henri), Kettunen, J. (Johannes), Henneman, P. (Peter), Baumert, J. (Jens), Strachan, D.P. (David), Fuchsberger, C. (Christian), Vitart, V. (Veronique), Wilson, J.F. (James F), Paré, G. (Guillaume), Naitza, S. (Silvia), Rudock, M.E. (Megan), Surakka, I. (Ida), Geus, E.J.C. (Eco) de, Alizadeh, B.Z. (Behrooz), Guralnik, J.M. (Jack), Shuldiner, A.R. (Alan), Tanaka, T. (Toshiko), Zee, R.Y.L. (Robert), Schnabel, R.B. (Renate), Nambi, V. (Vijay), Kavousi, M. (Maryam), Ripatti, S. (Samuli), Nauck, M. (Matthias), Smith, N.L. (Nicholas L.), Smith, A.V. (Albert Vernon), Sundvall, J. (Jouko), Scheet, P. (Paul), Liu, Y. (YongMei), Ruokonen, A. (Aimo), Rose, L.M. (Lynda), Larson, M.G. (Martin), Hoogeveen, R.C. (Ron), Freimer, N.B. (Nelson), Teumer, A. (Alexander), Tracy, R.P. (Russell), Launer, L.J. (Lenore), Buring, J.E. (Julie), Yamamoto, J.F. (Jennifer), Folsom, A.R. (Aaron), Sijbrands, E.J.G. (Eric), Pankow, J.S. (James), Elliott, P. (Paul), Keaney, J.F. (John), Sun, W. (Wei), Sarin, A.-P., Fontes, M. (Michel), Badola, S. (Sunita), Astor, B.C. (Brad), Pouta, A. (Anneli), Werda, K. (Karl), Greiser, K.H. (Karin Halina), Kuss, O. (Oliver), Schwabedissen, H.E.M.Z. (Henriette E. Meyer Zu), Thiery, J. (Joachim), Jamshidi, Y. (Yalda), Nolte, I.M. (Ilja M.), Soranzo, N. (Nicole), Spector, T.D. (Timothy), Völzke, H. (Henry), Parker, A.N. (Alex), Aspelund, T. (Thor), Bates, D. (David), Young, L. (Lauren), Tsui, K. (Kim), Siscovick, D.S. (David), Guo, X. (Xiuqing), Rotter, J.I. (Jerome I.), Uda, M. (Manuela), Schlessinger, D., Rudan, I. (Igor), Hicks, A.A. (Andrew), Penninx, B.W.J.H. (Brenda), Thorand, B. (Barbara), Gieger, C. (Christian), Coresh, J. (Josef), Willemsen, G.A.H.M. (Gonneke), Harris, T.B. (Tamara), Jarvelin, M.-R. (Marjo-Riitta), Rice, K.M. (Kenneth), Radke, D. (Dörte), Salomaa, V. (Veikko), Willems van Dijk, J.A.P. (Ko), Boerwinkle, E.A. (Eric), Vasan, R.S. (Ramachandran Srini), Ferrucci, L. (Luigi), Gibson, Q. (Quince), Bandinelli, S. (Stefania), Snieder, H. (Harold), Boomsma, D.I. (Dorret), Xiao, X. (Xiangjun), Campbell, H. (Harry), Hayward, C. (Caroline), Pramstaller, P.P. (Peter Paul), Duijn, C.M. (Cornelia) van, Peltonen, L. (Leena Johanna), Psaty, B.M. (Bruce), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Homuth, G. (Georg), Koenig, W. (Wolfgang), Ballantyne, C. (Christie), Witteman, J.C.M. (Jacqueline), Benjamin, E.J. (Emelia), Perola, M. (Markus), Chasman., D.I. (Daniel I.), Ligthart, S. (Symen), Vries, P.S. (Paul) de, Uitterlinden, A.G. (André), Hofman, A. (Albert), Franco, O.H. (Oscar), Chasman, D.I. (Daniel), Dehghan, A. (Abbas), Dupuis, J. (Josée), Barbalic, M. (maja), Bis, J.C. (Joshua), Eiriksdottir, G. (Gudny), Lu, C. (Chen), Pellikka, N. (Niina), Wallaschofski, H. (Henri), Kettunen, J. (Johannes), Henneman, P. (Peter), Baumert, J. (Jens), Strachan, D.P. (David), Fuchsberger, C. (Christian), Vitart, V. (Veronique), Wilson, J.F. (James F), Paré, G. (Guillaume), Naitza, S. (Silvia), Rudock, M.E. (Megan), Surakka, I. (Ida), Geus, E.J.C. (Eco) de, Alizadeh, B.Z. (Behrooz), Guralnik, J.M. (Jack), Shuldiner, A.R. (Alan), Tanaka, T. (Toshiko), Zee, R.Y.L. (Robert), Schnabel, R.B. (Renate), Nambi, V. (Vijay), Kavousi, M. (Maryam), Ripatti, S. (Samuli), Nauck, M. (Matthias), Smith, N.L. (Nicholas L.), Smith, A.V. (Albert Vernon), Sundvall, J. (Jouko), Scheet, P. (Paul), Liu, Y. (YongMei), Ruokonen, A. (Aimo), Rose, L.M. (Lynda), Larson, M.G. (Martin), Hoogeveen, R.C. (Ron), Freimer, N.B. (Nelson), Teumer, A. (Alexander), Tracy, R.P. (Russell), Launer, L.J. (Lenore), Buring, J.E. (Julie), Yamamoto, J.F. (Jennifer), Folsom, A.R. (Aaron), Sijbrands, E.J.G. (Eric), Pankow, J.S. (James), Elliott, P. (Paul), Keaney, J.F. (John), Sun, W. (Wei), Sarin, A.-P., Fontes, M. (Michel), Badola, S. (Sunita), Astor, B.C. (Brad), Pouta, A. (Anneli), Werda, K. (Karl), Greiser, K.H. (Karin Halina), Kuss, O. (Oliver), Schwabedissen, H.E.M.Z. (Henriette E. Meyer Zu), Thiery, J. (Joachim), Jamshidi, Y. (Yalda), Nolte, I.M. (Ilja M.), Soranzo, N. (Nicole), Spector, T.D. (Timothy), Völzke, H. (Henry), Parker, A.N. (Alex), Aspelund, T. (Thor), Bates, D. (David), Young, L. (Lauren), Tsui, K. (Kim), Siscovick, D.S. (David), Guo, X. (Xiuqing), Rotter, J.I. (Jerome I.), Uda, M. (Manuela), Schlessinger, D., Rudan, I. (Igor), Hicks, A.A. (Andrew), Penninx, B.W.J.H. (Brenda), Thorand, B. (Barbara), Gieger, C. (Christian), Coresh, J. (Josef), Willemsen, G.A.H.M. (Gonneke), Harris, T.B. (Tamara), Jarvelin, M.-R. (Marjo-Riitta), Rice, K.M. (Kenneth), Radke, D. (Dörte), Salomaa, V. (Veikko), Willems van Dijk, J.A.P. (Ko), Boerwinkle, E.A. (Eric), Vasan, R.S. (Ramachandran Srini), Ferrucci, L. (Luigi), Gibson, Q. (Quince), Bandinelli, S. (Stefania), Snieder, H. (Harold), Boomsma, D.I. (Dorret), Xiao, X. (Xiangjun), Campbell, H. (Harry), Hayward, C. (Caroline), Pramstaller, P.P. (Peter Paul), Duijn, C.M. (Cornelia) van, Peltonen, L. (Leena Johanna), Psaty, B.M. (Bruce), Gudnason, V. (Vilmundur), Ridker, P.M. (Paul), Homuth, G. (Georg), Koenig, W. (Wolfgang), Ballantyne, C. (Christie), Witteman, J.C.M. (Jacqueline), Benjamin, E.J. (Emelia), Perola, M. (Markus), and Chasman., D.I. (Daniel I.)

Abstract

Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.

Published
2015
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135. Utility of HbA1c and fasting plasma glucose for screening of Type 2 diabetes: a meta-analysis of full ROC curves.

Author

Hoyer, A., Rathmann, W., and Kuss, O.

Subjects
TYPE 2 diabetes diagnosis, BLOOD sugar, GLYCOSYLATED hemoglobin, META-analysis, SYSTEMATIC reviews, RECEIVER operating characteristic curves
Abstract

Aims There is still debate on the optimal threshold for population-based screening of diabetes (diagnosed by the oral glucose tolerance test) using tests like HbA1c or fasting plasma glucose. Meta-analyses provide meaningful input in such situations. The aim of this article is to perform a meta-analysis that includes the complete information reported in the individual studies of two existing systematic reviews. Methods We screened the individual studies from two systematic reviews and reconstructed the full four-fold tables for every reported threshold. Using a recently proposed meta-analysis model for the comparison of two diagnostic tests, we compared HbA1c with fasting plasma glucose, and estimated meta-analytic receiver operating characteristic curves for both tests using the 11.1 mmol/l threshold of the 2-h post-challenge glucose level (2 h-PG) as the gold standard. Results We included nine studies from two existing systematic reviews in our analysis.Based on our data set, the optimal threshold lies between 42 and 44 mmol/mol (6.0–6.2%) for HbA1c, and 6.2–6.4 mmol/l for fasting plasma glucose choosing the Youden index as the technical criterion. In addition, we found that there is no relevant difference in the performance of HbA1c and fasting plasma glucose. Conclusions In our meta-analysis, we found that the optimal threshold with reference to the 2 h-PG should be chosen between 42 and 44 mmol/mol (6.0–6.2%) for HbA1c, and 6.2–6.4 mmol/l for fasting plasma glucose on the basis of maximal sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Published
2018
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136. Association of neighbourhood socioeconomic status and individual socioeconomic status cardiovascular risk factors in an eastern German population – the CARLA study 2002-2006

Author

Greiser, KH, Tiller, D, Kuss, O, Kluttig, A, Rudge, G, Schumann, B, Werdan, K, and Haerting, J

Subjects
cardiovascular risk factors, ddc: 610, population characteristics, social sciences, 610 Medical sciences, Medicine, neighbourhood SES
Abstract

Background/objectives: Individual socioeconomic status (SES) is a determinant of cardiovascular risk factors (RF). Recent studies suggest an independent association of neighbourhood SES with cardiovascular RF, but the mechanisms have not fully been understood. Our aim was to assess the association[for full text, please go to the a.m. URL], Mainz//2011; 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi)

Published
2011
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137. Etiologic differences between seminoma and nonseminoma of the testis: a systematic review of epidemiological studies

Author

Stang, A and Kuß, O

Subjects
endocrine system, ddc: 610, endocrine system diseases, etiology, seminoma, nonseminoma, incidence, testicular neoplasms, 610 Medical sciences, Medicine, urologic and male genital diseases
Abstract

Introduction: Several descriptive epidemiological features of testicular cancer suggest that the etiologies of seminoma and nonseminoma of the testis may differ. To address this, we conducted a systematic review of case-control and cohort studies of the etiology of testicular cancer. Methods: We [for full text, please go to the a.m. URL], Mainz//2011; 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi)

Published
2011
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138. Log-normal frailty models fitted as Poisson generalized linear mixed models: New evidence from simulations

Author

Hirsch, K, Wienke, A, and Kuss, O

Subjects
Frailty model, ddc: 610, random effect, 610 Medical sciences, Medicine, GLMM
Abstract

The equivalence of a survival model with a piecewise constant baseline hazard function and a Poisson regression model has been known at least since the 1970s. As shown recently by Feng et al., this equivalence carries over to the case of correlated survival data: A frailty model with a log-normal frailty[for full text, please go to the a.m. URL], Mainz//2011; 56. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (gmds), 6. Jahrestagung der Deutschen Gesellschaft für Epidemiologie (DGEpi)

Published
2011
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147. Interdisciplinary care programme to improve self-management for cancer patients undergoing stem cell transplantation: a prospective non-randomised intervention study.

Author

Schmidt, H., Boese, S., Bauer, A., Landenberger, M., Lau, A., Stoll, O., Schmoll, H. ‐ J., Mauz ‐ Koerholz, C., Kuss, O., and Jahn, P.

Subjects
PREVENTION of malnutrition, EVALUATION of medical care, QUALITY of life, CANCER patients, STOMATITIS, PATIENT satisfaction, MUSCLE weakness, ONCOLOGY nursing, CANCER patient medical care, CLINICAL trials, CONFIDENCE intervals, CONTENT analysis, HEALTH care teams, HEMATOPOIETIC stem cell transplantation, LONGITUDINAL method, MULTIVARIATE analysis, NUTRITIONAL assessment, QUESTIONNAIRES, RESEARCH funding, HEALTH self-care, STATISTICS, SAMPLE size (Statistics), DATA analysis, BODY mass index, CONTROL groups, PHYSICAL activity, DESCRIPTIVE statistics, PREVENTION, EDUCATION
Abstract

The purpose of this single-centre prospective non-randomised study was to evaluate the effectiveness of an interdisciplinary care programme to enhance self-management in patients with haematopoietic stem cell transplantation ( HSCT). Patients undergoing HSCT, aged >14 years with informed consent were recruited ( n = 79). Patients in the intervention group ( IG) received standard care plus the SCION- HSCT intervention to counteract three problems after HSCT: muscle weakness, oral mucositis and malnutrition. Control group patients received standard care. Primary endpoint was global health-related quality of life ( HRQoL) at discharge ( EORTC QLQ C30 v. 3.0). Baseline characteristics were balanced between both groups, except physical performance ( ECOG) being significantly lower for patients of the IG. At discharge, no group differences could be seen regarding HRQoL. Non-confirmatory post hoc analyses showed for patients of the IG a shorter duration of hospitalisation ( MD −10.90; 95% CI −18.05 to −3.75) and increased activity during hospitalisation ( MD 2.44; 95% CI 1.27-3.61). In conclusion, clinical effectiveness of the intervention could not be proven with respect to the aspired improvement of HRQoL. However, the nurse-led interdisciplinary caring programme could be carried out in every day ward routine. Further research should focus on working mechanisms of complex interventions aiming to improve HRQoL of patients undergoing HSCT. [ABSTRACT FROM AUTHOR]

Published
2017
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150. Quality of Care of People With Type 2 Diabetes in Eight European Countries: Findings from the Guideline Adherence to Enhance Care (GUIDANCE) study

Author

Stone, MA, Charpentier, G, Doggen, K, Kuss, O, Lindblad, U, Kellner, C, Nolan, J, Pazderska, A, Rutten, G, Trento, M, Khunti, K, Stone, MA, Charpentier, G, Doggen, K, Kuss, O, Lindblad, U, Kellner, C, Nolan, J, Pazderska, A, Rutten, G, Trento, M, and Khunti, K

Abstract

OBJECTIVE: We sought to determine levels of adherence in eight European countries to recommendations for the management of type 2 diabetes and to investigate factors associated with key intermediate outcomes. RESEARCH DESIGN AND METHODS: GUIDANCE was a cross-sectional study including retrospective data extraction from the medical records of people with type 2 diabetes recruited, using a shared protocol, from primary and specialist care sites in the following eight European countries: Belgium, France, Germany, Italy, Ireland, Sweden, the Netherlands, and the United Kingdom. The dataset for analysis comprised 7,597 cases. Proportions meeting process and outcome criteria were determined, including between-country variations. Logistic regression was used to investigate potential predictors of meeting targets for HbA1c, blood pressure, and LDL cholesterol. RESULTS: In the total sample, adherence to process recommendations was high for some measures, for example, HbA1c recorded in past 12 months in 97.6% of cases. Target achievement for intermediate outcome measures was lower, with only 53.6% having HbA1c <7%. Considerable between-country variation was identified for both processes and outcomes. The following characteristics were associated with an increased likelihood of meeting targets for all three measures considered (HbA1c, blood pressure, LDL cholesterol): shorter diagnosis of diabetes; having one or more macrovascular complications; lower BMI; being prescribed lipid-lowering medication; and no current antihypertensive prescribing. CONCLUSIONS: Compared with earlier reports, we have suggested some encouraging positive trends in Europe in relation to meeting targets for the management of people with type 2 diabetes, but there is still scope for further improvement and greater between-country consistency.

Published
2013

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