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101. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions

Author

Kaptoge, S, Pennells, L, De Bacquer, D, Cooney, MT, Kavousi, M, Stevens, G, Riley, LM, Savin, S, Khan, T, Altay, S, Amouyel, P, Assmann, G, Bell, S, Ben-Shlomo, Y, Berkman, L, Beulens, JW, Björkelund, C, Blaha, M, Blazer, DG, Bolton, T, Bonita Beaglehole, R, Brenner, H, Brunner, EJ, Casiglia, E, Chamnan, P, Choi, YH, Chowdry, R, Coady, S, Crespo, CJ, Cushman, M, Dagenais, GR, D'Agostino, RB, Daimon, M, Davidson, KW, Engström, G, Ford, I, Gallacher, J, Gansevoort, RT, Gaziano, TA, Giampaoli, S, Grandits, G, Grimsgaard, S, Grobbee, DE, Gudnason, V, Guo, Q, Tolonen, H, Humphries, S, Iso, H, Jukema, JW, Kauhanen, J, Kengne, AP, Khalili, D, Koenig, W, Kromhout, D, Krumholz, H, Lam, TH, Laughlin, G, Marín Ibañez, A, Meade, TW, Moons, KGM, Nietert, PJ, Ninomiya, T, Nordestgaard, BG, O'Donnell, C, Palmieri, L, Patel, A, Perel, P, Price, JF, Providencia, R, Ridker, PM, Rodriguez, B, Rosengren, A, Roussel, R, Sakurai, M, Salomaa, V, Sato, S, Schöttker, B, Shara, N, Shaw, JE, Shin, HC, Simons, LA, Sofianopoulou, E, Sundström, J, Völzke, H, Wallace, RB, Wareham, NJ, Willeit, P, Wood, D, Wood, A, Zhao, D, Woodward, M, Danaei, G, Roth, G, Mendis, S, Onuma, O, Varghese, C, Ezzati, M, Graham, I, Jackson, R, Danesh, J, Kaptoge, S, Pennells, L, De Bacquer, D, Cooney, MT, Kavousi, M, Stevens, G, Riley, LM, Savin, S, Khan, T, Altay, S, Amouyel, P, Assmann, G, Bell, S, Ben-Shlomo, Y, Berkman, L, Beulens, JW, Björkelund, C, Blaha, M, Blazer, DG, Bolton, T, Bonita Beaglehole, R, Brenner, H, Brunner, EJ, Casiglia, E, Chamnan, P, Choi, YH, Chowdry, R, Coady, S, Crespo, CJ, Cushman, M, Dagenais, GR, D'Agostino, RB, Daimon, M, Davidson, KW, Engström, G, Ford, I, Gallacher, J, Gansevoort, RT, Gaziano, TA, Giampaoli, S, Grandits, G, Grimsgaard, S, Grobbee, DE, Gudnason, V, Guo, Q, Tolonen, H, Humphries, S, Iso, H, Jukema, JW, Kauhanen, J, Kengne, AP, Khalili, D, Koenig, W, Kromhout, D, Krumholz, H, Lam, TH, Laughlin, G, Marín Ibañez, A, Meade, TW, Moons, KGM, Nietert, PJ, Ninomiya, T, Nordestgaard, BG, O'Donnell, C, Palmieri, L, Patel, A, Perel, P, Price, JF, Providencia, R, Ridker, PM, Rodriguez, B, Rosengren, A, Roussel, R, Sakurai, M, Salomaa, V, Sato, S, Schöttker, B, Shara, N, Shaw, JE, Shin, HC, Simons, LA, Sofianopoulou, E, Sundström, J, Völzke, H, Wallace, RB, Wareham, NJ, Willeit, P, Wood, D, Wood, A, Zhao, D, Woodward, M, Danaei, G, Roth, G, Mendis, S, Onuma, O, Varghese, C, Ezzati, M, Graham, I, Jackson, R, and Danesh, J

Abstract

Background: To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods: In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40–80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings: Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0·685 (95% CI 0·629–0·741) to 0·833 (0·783–0·882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a

Published
2019

102. Comparing different definitions of prediabetes with subsequent risk of diabetes: An individual participant data meta-analysis involving 76 513 individuals and 8208 cases of incident diabetes

Author

Lee, Crystal, Colagiuri, S., Woodward, M., Gregg, E.W., Adams, R., Azizi, F., Gabriel, R., Gill, T.K., Gonzalez, C., Hodge, A., Jacobs, D.R., Joseph, J.J., Khalili, D., Magliano, D.J., Mehlig, K., Milne, R., Mishra, G., Mongraw-Chaffin, M., Pasco, J.A., Sakurai, M., Schreiner, P.J., Selvin, E., Shaw, J.E., Wittert, G., Yatsuya, H., Huxley, Rachel, Lee, Crystal, Colagiuri, S., Woodward, M., Gregg, E.W., Adams, R., Azizi, F., Gabriel, R., Gill, T.K., Gonzalez, C., Hodge, A., Jacobs, D.R., Joseph, J.J., Khalili, D., Magliano, D.J., Mehlig, K., Milne, R., Mishra, G., Mongraw-Chaffin, M., Pasco, J.A., Sakurai, M., Schreiner, P.J., Selvin, E., Shaw, J.E., Wittert, G., Yatsuya, H., and Huxley, Rachel

Abstract

Objective: There are currently five widely used definition of prediabetes. We compared the ability of these to predict 5-year conversion to diabetes and investigated whether there were other cut-points identifying risk of progression to diabetes that may be more useful. Research design and methods: We conducted an individual participant meta-analysis using longitudinal data included in the Obesity, Diabetes and Cardiovascular Disease Collaboration. Cox regression models were used to obtain study-specific HRs for incident diabetes associated with each prediabetes definition. Harrell's C-statistics were used to estimate how well each prediabetes definition discriminated 5-year risk of diabetes. Spline and receiver operating characteristic curve (ROC) analyses were used to identify alternative cut-points. Results: Sixteen studies, with 76 513 participants and 8208 incident diabetes cases, were available. Compared with normoglycemia, current prediabetes definitions were associated with four to eight times higher diabetes risk (HRs (95% CIs): 3.78 (3.11 to 4.60) to 8.36 (4.88 to 14.33)) and all definitions discriminated 5-year diabetes risk with good accuracy (C-statistics 0.79-0.81). Cut-points identified through spline analysis were fasting plasma glucose (FPG) 5.1 mmol/L and glycated hemoglobin (HbA1c) 5.0% (31 mmol/mol) and cut-points identified through ROC analysis were FPG 5.6 mmol/L, 2-hour postload glucose 7.0 mmol/L and HbA1c 5.6% (38 mmol/mol). Conclusions: In terms of identifying individuals at greatest risk of developing diabetes within 5 years, using prediabetes definitions that have lower values produced non-significant gain. Therefore, deciding which definition to use will ultimately depend on the goal for identifying individuals at risk of diabetes.

Published
2019

108. A study on secure wireless networks consisting of home appliances

Author

Nakakita, H., Yamaguchi, K., Hashimoto, M., Saito, T., and Sakurai, M.

Subjects
Wireless local area networks (Computer networks) -- Research, Bluetooth technology, Wireless network, Wireless LAN/WAN system, Business, Electronics and electrical industries, Engineering and manufacturing industries
Abstract

We propose a security system for a wireless home network, regarding which consumers need not be aware of configuration of IP address or wireless LAN protocol type. This system assumes that a server manages a connectivity of each appliance to the wireless home network. The server uses two kinds of keys. First is a master key which is unique to each appliance. Second is a shared network key, which is securely distributed to each appliance with encryption by the master key. The periodic distribution of the new shared network key through the application layer ensures the timely update of the key, and prevents unknown appliances from joining the home network. The distributed data on the home network are protected by the encryption function in the data link layer of, for example, IEEE802.11 and Bluetooth protocols. This system ensures higher security for the wireless home network with small implementation cost. Index Terms--Security, Home Network, Wireless Network, IEEE802.11, Bluetooth

Published
2003

122. Global Citizenship Education (Foster the Science Literacy)

Author

SAKURAI, M., NAGASE, K., SATO, A., SANKODA, H., HARA, J., and NAKAMURA, A.

Abstract

スーパーサイエンスハイスクール（SSH）の取り組み Practices of Super Science High School (SSH) Programs

Published
2016

123. Risk thresholds for alcohol consumption: combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies

Author

Wood, A.M. Kaptoge, S. Butterworth, A.S. Willeit, P. Warnakula, S. Bolton, T. Paige, E. Paul, D.S. Sweeting, M. Burgess, S. Bell, S. Astle, W. Stevens, D. Koulman, A. Selmer, R.M. Verschuren, W.M.M. Sato, S. Njølstad, I. Woodward, M. Salomaa, V. Nordestgaard, B.G. Yeap, B.B. Fletcher, A. Melander, O. Kuller, L.H. Balkau, B. Marmot, M. Koenig, W. Casiglia, E. Cooper, C. Arndt, V. Franco, O.H. Wennberg, P. Gallacher, J. de la Cámara, A.G. Völzke, H. Dahm, C.C. Dale, C.E. Bergmann, M.M. Crespo, C.J. van der Schouw, Y.T. Kaaks, R. Simons, L.A. Lagiou, P. Schoufour, J.D. Boer, J.M.A. Key, T.J. Rodriguez, B. Moreno-Iribas, C. Davidson, K.W. Taylor, J.O. Sacerdote, C. Wallace, R.B. Quiros, J.R. Tumino, R. Blazer, D.G., II Linneberg, A. Daimon, M. Panico, S. Howard, B. Skeie, G. Strandberg, T. Weiderpass, E. Psaty, B.M. Kromhout, D. Salamanca-Fernandez, E. Kiechl, S. Krumholz, H.M. Grioni, S. Palli, D. Huerta, J.M. Price, J. Sundström, J. Arriola, L. Arima, H. Travis, R.C. Panagiotakos, D.B. Karakatsani, A. Trichopoulou, A. Kühn, T. Grobbee, D.E. Barrett-Connor, E. van Schoor, N. Boeing, H. Overvad, K. Kauhanen, J. Wareham, N. Langenberg, C. Forouhi, N. Wennberg, M. Després, J.-P. Cushman, M. Cooper, J.A. Rodriguez, C.J. Sakurai, M. Shaw, J.E. Knuiman, M. Voortman, T. Meisinger, C. Tjønneland, A. Brenner, H. Palmieri, L. Dallongeville, J. Brunner, E.J. Assmann, G. Trevisan, M. Gillum, R.F. Ford, I.F. Sattar, N. Lazo, M. Thompson, S.G. Ferrari, P. Leon, D.A. Davey Smith, G. Peto, R. Jackson, R. Banks, E. Di Angelantonio, E. Danesh, J. Veikko, S. Gómez de la Cámara, A. Rimm, E.B. Dallongeville, J.-P. Gillumn, R.F. Thompson, S. Emerging Risk Factors Collaboration/EPIC-CVD/UK Biobank Alcohol Study Group

Abstract

Background: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. Methods: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose–response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th–95th percentile 1·04–13·5]) from 71 011 participants from 37 studies. Findings: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality risk around or below 100 g per week. Alcohol consumption was roughly linearly associated with a higher risk of stroke (HR per 100 g per week higher consumption 1·14, 95% CI, 1·10–1·17), coronary disease excluding myocardial infarction (1·06, 1·00–1·11), heart failure (1·09, 1·03–1·15), fatal hypertensive disease (1·24, 1·15–1·33); and fatal aortic aneurysm (1·15, 1·03–1·28). By contrast, increased alcohol consumption was log-linearly associated with a lower risk of myocardial infarction (HR 0·94, 0·91–0·97). In comparison to those who reported drinking >0–≤100 g per week, those who reported drinking >100–≤200 g per week, >200–≤350 g per week, or >350 g per week had lower life expectancy at age 40 years of approximately 6 months, 1–2 years, or 4–5 years, respectively. Interpretation: In current drinkers of alcohol in high-income countries, the threshold for lowest risk of all-cause mortality was about 100 g/week. For cardiovascular disease subtypes other than myocardial infarction, there were no clear risk thresholds below which lower alcohol consumption stopped being associated with lower disease risk. These data support limits for alcohol consumption that are lower than those recommended in most current guidelines. Funding: UK Medical Research Council, British Heart Foundation, National Institute for Health Research, European Union Framework 7, and European Research Council. © 2018 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.

Published
2018

127. Successful Steroid Therapy for Lipoid Pneumonia Developing After Allogeneic Hematopoietic Stem Cell Transplant: A Case Report

Author

Sakurai, M., primary, Kato, J., additional, Toyama, T., additional, Hashida, R., additional, Yamane, Y., additional, Abe, R., additional, Koda, Y., additional, Kohashi, S., additional, Kikuchi, T., additional, Hayashi, Y., additional, Nukaga, S., additional, Ueda, S., additional, Fukunaga, K., additional, Okamoto, S., additional, and Mori, T., additional

Published
2018
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137. Covariate-adjusted measures of discrimination for survival data

Author

White, Ian R, Rapsomaniki, Eleni, Wannamethee, S. G., Morris, R. W., Willeit, J., Willeit, P., Santer, P., Kiechl, S., Wald, N., Ebrahim, S., Lawlor, D. A., Gallacher, J., Yarnell, J. W. G., Ben Shlomo, Y., Casiglia, Edoardo, Tikhonoff, V., Sutherland, S. E., Nietert, P. J., Keil, J. E., Bachman, D. L., Psaty, B. M., Cushman, M., Nordestgaard, B. G., Tybjærg Hansen, A., Frikke Schmidt, R., Giampaoli, S., Palmieri, L., Panico, S., Pilotto, L., Vanuzzo, D., Simons, L. A., Friedlander, Y., Mccallum, J., Price, J. F., Mclachlan, S., Taylor, J. O., Guralnik, J. M., Wallace, R. B., Kohout, F. J., Cornoni Huntley, J. C., Blazer, D. G., Phillips, C. L., Wareham, N. J., Khaw, K. T., Brenner, H., Schöttker, B., Müller, H. T., Rothenbacher, D., Nissinen, A., Donfrancesco, C., Harald, K., Jousilahti, P. R., Vartiainen, E., Salomaa, V., D'Agostino, R. B., Wolf, P. A., Vasan, R. S., Daimon, M., Oizumi, T., Kayama, T., Kato, T., Chetrit, A., Dankner, R., Lubin, F., Welin, L., Svärdsudd, K., Eriksson, H., Lappas, G., Lissner, L., Mehlig, K., Björkelund, C., Nagel, D., Kiyohara, Y., Arima, H., Ninomiya, T., Hata, J., Rodriguez, B., Dekker, J. M., Nijpels, G., Stehouwer, C. D. A., Iso, H., Kitamura, A., Yamagishi, K., Noda, H., Goldbourt, U., Kauhanen, J., Salonen, J. T., Tuomainen, T. P., Meade, T. W., Destavola, B. L., Blokstra, A., Verschuren, W. M. M., de Boer, I. H., Folsom, A. R., Koenig, W., Meisinger, C., Peters, A., Bueno de Mesquita, H. B., Rosengren, A., Wilhelmsen, L., Kuller, L. H., Grandits, G., Cooper, J. A., Bauer, K. A., Davidson, K. W., Kirkland, S., Shaffer, J. A., Shimbo, D., Sato, S., Dullaart, R. P. F., Bakker, S. J. L., Gansevoort, R. T., Ducimetiere, P., Amouyel, P., Arveiler, D., Evans, A., Ferrières, J., Schulte, H., Assmann, G., Jukema, J. W., Westendorp, R. G. J., Sattar, N., Cantin, B., Lamarche, B., Després, J. P., Null, E. Barrett Connor, Wingard, D. L., Daniels, L. B., Gudnason, V., Aspelund, T., Trevisan, M., Hofman, A., Franco, O. H., Tunstall Pedoe, H., Tavendale, R., Lowe, G. D. O., Woodward, M., Howard, W. J., Howard, B. V., Zhang, Y., Best, L. G., Umans, J., Davey Smith, G., Onat, A., Nakagawa, H., Sakurai, M., Nakamura, K., Morikawa, Y., Njølstad, I., Mathiesen, E. B., Wilsgaard, T., Sundström, J., Gaziano, J. M., Ridker, P. M., Marmot, M., Clarke, R., Collins, R., Fletcher, A., Brunner, E., Shipley, M., Kivimaki, M., Buring, J., Rifai, N., Cook, N., Ford, I., Robertson, M., Marín Ibañez, A., Feskens, E. J. M., Geleijnse, J. M., MUMC+: HVC Pieken Maastricht Studie (9), Interne Geneeskunde, MUMC+: MA Interne Geneeskunde (3), RS: FHML non-thematic output, Apollo - University of Cambridge Repository, White, Ian R, Rapsomaniki, Eleni, and Panico, Salvatore

Subjects
Statistics and Probability, Male, Biometry, C-index, D-index, Discrimination, Analysis of Variance, Cardiovascular Diseases, Clinical Trials as Topic, Discriminant Analysis, Female, Humans, Middle Aged, Risk Factors, Survival Analysis, Medicine (all), Statistics, Probability and Uncertainty, 01 natural sciences, Article, Unit (housing), 010104 statistics & probability, 03 medical and health sciences, 0302 clinical medicine, Survival data, Cardiovascular Disease, Covariate, Statistics, 030212 general & internal medicine, 0101 mathematics, 10. No inequality, Prognostic models, Survival analysis, Medicine(all), Proportional hazards model, Risk Factor, General Medicine, Probability and Uncertainty, Discriminant Analysi, Demography, Human
Abstract

Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data.To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s).We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration.The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices.The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.? 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Published
2015

140. Site occupancy of Ga and Nb in Nd12.5Fe(sub bal)Ga0.3Nb0.2B6.2 during the hydrogenation, disproportionation, desorption, and recombination process

Author

Konno, K., Matsuura, M., Ikuta, N., Sakurai, M., and Mishima, C.

Subjects
Niobium -- Chemical properties, Gallium compounds -- Chemical properties, Disproportionation -- Analysis, Hydrogenation -- Analysis, Physics
Abstract

The effect of small additives of Ga and Nb in Nd12.5Fe(sub bal)Ga0.3Nb0.2B6.2 on their local structure during homogenization, disproportionation, desorption and recombination (HDDR) process is examined. The Fe(4c) sites of the recombined Nd2Fe14B crystal are occupied by Ga in the recombined state whereas a stable NdFeB compound is formed by Nb that remains undecomposed throughout the HDDR process

Published
2002

141. Risk thresholds for alcohol consumption:combined analysis of individual-participant data for 599 912 current drinkers in 83 prospective studies

Author

Wood, A. M. (Angela M.), Kaptoge, S. (Stephen), Butterworth, A. S. (Adam S.), Willeit, P. (Peter), Warnakula, S. (Samantha), Bolton, T. (Thomas), Paige, E. (Ellie), Paul, D. S. (Dirk S.), Sweeting, M. (Michael), Burgess, S. (Stephen), Bell, S. (Steven), Astle, W. (William), Stevens, D. (David), Koulman, A. (Albert), Selmer, R. M. (Randi M.), Verschuren, W. M. (W. M. Monique), Sato, S. (Shinichi), Njolstad, I. (Inger), Woodward, M. (Mark), Salomaa, V. (Veikko), Nordestgaard, B. G. (Borge G.), Yeap, B. B. (Bu B.), Fletcher, A. (Astrid), Melander, O. (Olle), Kuller, L. H. (Lewis H.), Balkau, B. (Beverley), Marmot, M. (Michael), Koenig, W. (Wolfgang), Casiglia, E. (Edoardo), Cooper, C. (Cyrus), Arndt, V. (Volker), Franco, O. H. (Oscar H.), Wennberg, P. (Patrik), Gallacher, J. (John), de la Camara, A. G. (Agustin Gomez), Volzke, H. (Henry), Dahm, C. C. (Christina C.), Dale, C. E. (Caroline E.), Bergmann, M. M. (Manuela M.), Crespo, C. J. (Carlos J.), van der Schouw, Y. T. (Yvonne T.), Kaaks, R. (Rudolf), Simons, L. A. (Leon A.), Lagiou, P. (Pagona), Schoufour, J. D. (Josje D.), Boer, J. M. (Jolanda M. A.), Key, T. J. (Timothy J.), Rodriguez, B. (Beatriz), Moreno-Iribas, C. (Conchi), Davidson, K. W. (Karina W.), Taylor, J. O. (James O.), Sacerdote, C. (Carlotta), Wallace, R. B. (Robert B.), Quiros, J. R. (J. Ramon), Tumino, R. (Rosario), Blazer, D. G. (Dan G., II), Linneberg, A. (Allan), Daimon, M. (Makoto), Panico, S. (Salvatore), Howard, B. (Barbara), Skeie, G. (Guri), Strandberg, T. (Timo), Weiderpass, E. (Elisabete), Nietert, P. J. (Paul J.), Psaty, B. M. (Bruce M.), Kromhout, D. (Daan), Salamanca-Fernandez, E. (Elena), Kiechl, S. (Stefan), Krumholz, H. M. (Harlan M.), Grioni, S. (Sara), Palli, D. (Domenico), Huerta, J. M. (Jose M.), Price, J. (Jackie), Sundstrom, J. (Johan), Arriola, L. (Larraitz), Arima, H. (Hisatomi), Travis, R. C. (Ruth C.), Panagiotakos, D. B. (Demosthenes B.), Karakatsani, A. (Anna), Trichopoulou, A. (Antonia), Kuhn, T. (Tilman), Grobbee, D. E. (Diederick E.), Barrett-Connor, E. (Elizabeth), van Schoor, N. (Natasja), Boeing, H. (Heiner), Overvad, K. (Kim), Kauhanen, J. (Jussi), Wareham, N. (Nick), Langenberg, C. (Claudia), Forouhi, N. (Nita), Wennberg, M. (Maria), Despres, J.-P. (Jean-Pierre), Cushman, M. (Mary), Cooper, J. A. (Jackie A.), Rodriguez, C. J. (Carlos J.), Sakurai, M. (Masaru), Shaw, J. E. (Jonathan E.), Knuiman, M. (Matthew), Voortman, T. (Trudy), Meisinger, C. (Christa), Tjonneland, A. (Anne), Brenner, H. (Hermann), Palmieri, L. (Luigi), Dallongeville, J. (Jean), Brunner, E. J. (Eric J.), Assmann, G. (Gerd), Trevisan, M. (Maurizio), Gillum, R. F. (Richard F.), Ford, I. (Ian), Sattar, N. (Naveed), Lazo, M. (Mariana), Thompson, S. G. (Simon G.), Ferrari, P. (Pietro), Leon, D. A. (David A.), Smith, G. D. (George Davey), Peto, R. (Richard), Jackson, R. (Rod), Banks, E. (Emily), Di Angelantonio, E. (Emanuele), Danesh, J. (John), Wood, A. M. (Angela M.), Kaptoge, S. (Stephen), Butterworth, A. S. (Adam S.), Willeit, P. (Peter), Warnakula, S. (Samantha), Bolton, T. (Thomas), Paige, E. (Ellie), Paul, D. S. (Dirk S.), Sweeting, M. (Michael), Burgess, S. (Stephen), Bell, S. (Steven), Astle, W. (William), Stevens, D. (David), Koulman, A. (Albert), Selmer, R. M. (Randi M.), Verschuren, W. M. (W. M. Monique), Sato, S. (Shinichi), Njolstad, I. (Inger), Woodward, M. (Mark), Salomaa, V. (Veikko), Nordestgaard, B. G. (Borge G.), Yeap, B. B. (Bu B.), Fletcher, A. (Astrid), Melander, O. (Olle), Kuller, L. H. (Lewis H.), Balkau, B. (Beverley), Marmot, M. (Michael), Koenig, W. (Wolfgang), Casiglia, E. (Edoardo), Cooper, C. (Cyrus), Arndt, V. (Volker), Franco, O. H. (Oscar H.), Wennberg, P. (Patrik), Gallacher, J. (John), de la Camara, A. G. (Agustin Gomez), Volzke, H. (Henry), Dahm, C. C. (Christina C.), Dale, C. E. (Caroline E.), Bergmann, M. M. (Manuela M.), Crespo, C. J. (Carlos J.), van der Schouw, Y. T. (Yvonne T.), Kaaks, R. (Rudolf), Simons, L. A. (Leon A.), Lagiou, P. (Pagona), Schoufour, J. D. (Josje D.), Boer, J. M. (Jolanda M. A.), Key, T. J. (Timothy J.), Rodriguez, B. (Beatriz), Moreno-Iribas, C. (Conchi), Davidson, K. W. (Karina W.), Taylor, J. O. (James O.), Sacerdote, C. (Carlotta), Wallace, R. B. (Robert B.), Quiros, J. R. (J. Ramon), Tumino, R. (Rosario), Blazer, D. G. (Dan G., II), Linneberg, A. (Allan), Daimon, M. (Makoto), Panico, S. (Salvatore), Howard, B. (Barbara), Skeie, G. (Guri), Strandberg, T. (Timo), Weiderpass, E. (Elisabete), Nietert, P. J. (Paul J.), Psaty, B. M. (Bruce M.), Kromhout, D. (Daan), Salamanca-Fernandez, E. (Elena), Kiechl, S. (Stefan), Krumholz, H. M. (Harlan M.), Grioni, S. (Sara), Palli, D. (Domenico), Huerta, J. M. (Jose M.), Price, J. (Jackie), Sundstrom, J. (Johan), Arriola, L. (Larraitz), Arima, H. (Hisatomi), Travis, R. C. (Ruth C.), Panagiotakos, D. B. (Demosthenes B.), Karakatsani, A. (Anna), Trichopoulou, A. (Antonia), Kuhn, T. (Tilman), Grobbee, D. E. (Diederick E.), Barrett-Connor, E. (Elizabeth), van Schoor, N. (Natasja), Boeing, H. (Heiner), Overvad, K. (Kim), Kauhanen, J. (Jussi), Wareham, N. (Nick), Langenberg, C. (Claudia), Forouhi, N. (Nita), Wennberg, M. (Maria), Despres, J.-P. (Jean-Pierre), Cushman, M. (Mary), Cooper, J. A. (Jackie A.), Rodriguez, C. J. (Carlos J.), Sakurai, M. (Masaru), Shaw, J. E. (Jonathan E.), Knuiman, M. (Matthew), Voortman, T. (Trudy), Meisinger, C. (Christa), Tjonneland, A. (Anne), Brenner, H. (Hermann), Palmieri, L. (Luigi), Dallongeville, J. (Jean), Brunner, E. J. (Eric J.), Assmann, G. (Gerd), Trevisan, M. (Maurizio), Gillum, R. F. (Richard F.), Ford, I. (Ian), Sattar, N. (Naveed), Lazo, M. (Mariana), Thompson, S. G. (Simon G.), Ferrari, P. (Pietro), Leon, D. A. (David A.), Smith, G. D. (George Davey), Peto, R. (Richard), Jackson, R. (Rod), Banks, E. (Emily), Di Angelantonio, E. (Emanuele), and Danesh, J. (John)

Abstract

Background: Low-risk limits recommended for alcohol consumption vary substantially across different national guidelines. To define thresholds associated with lowest risk for all-cause mortality and cardiovascular disease, we studied individual-participant data from 599 912 current drinkers without previous cardiovascular disease. Methods: We did a combined analysis of individual-participant data from three large-scale data sources in 19 high-income countries (the Emerging Risk Factors Collaboration, EPIC-CVD, and the UK Biobank). We characterised dose–response associations and calculated hazard ratios (HRs) per 100 g per week of alcohol (12·5 units per week) across 83 prospective studies, adjusting at least for study or centre, age, sex, smoking, and diabetes. To be eligible for the analysis, participants had to have information recorded about their alcohol consumption amount and status (ie, non-drinker vs current drinker), plus age, sex, history of diabetes and smoking status, at least 1 year of follow-up after baseline, and no baseline history of cardiovascular disease. The main analyses focused on current drinkers, whose baseline alcohol consumption was categorised into eight predefined groups according to the amount in grams consumed per week. We assessed alcohol consumption in relation to all-cause mortality, total cardiovascular disease, and several cardiovascular disease subtypes. We corrected HRs for estimated long-term variability in alcohol consumption using 152 640 serial alcohol assessments obtained some years apart (median interval 5·6 years [5th–95th percentile 1·04–13·5]) from 71 011 participants from 37 studies. Findings: In the 599 912 current drinkers included in the analysis, we recorded 40 310 deaths and 39 018 incident cardiovascular disease events during 5·4 million person-years of follow-up. For all-cause mortality, we recorded a positive and curvilinear association with the level of alcohol consumption, with the minimum mortality ris

Published
2018

147. Redistribution of Zr and Ga in Nd2Fe14B-based magnets during the hydrogen disproportionation desorption recombination process: an x-ray absorption fine structure study

Author

Ashfaq, A., Matsuura, M., Ikuta, N., and Sakurai, M.

Subjects
Magnets, Permanent -- Research, Physics
Abstract

The effects of the hydrogen disproportionation desorption recombination process on the distribution behaviors of Zr and Ga are studied using x-ray absorption fine structure (XAFS) measurements. Results show that Zr occupies an Fe(j2) site for the as-cast state while Ga occupies an Fe(c2) site in the Nd2Fw14B structure for the homogenized state. Small changes in Zr XAFS spectra following disproportionation also indicate that locally the Nd2Fe14B phase with Zr at an Fe(j2) site is stabilized against disproportionation.

Published
1999

148. Central Retinal Artery Occlusion during Cisplatin and Etoposide Chemotherapy for Small Cell Lung Cancer

Author

Oshitari T, Shirato S, Ryota Kurimoto, Ikuo Sekine, Yoshino I, Kitamura Y, Sakurai M, Tawada A, Yamamoto S, Kato F, Baba T, Shunichiro Iwasawa, and Takiguchi T

Subjects
Cisplatin, Chemotherapy, genetic structures, business.industry, medicine.medical_treatment, medicine.disease, eye diseases, medicine, Cancer research, Central retinal artery occlusion, Non small cell, Central Retinal Artery Occlusion, sense organs, business, Etoposide, medicine.drug, Cancer
Abstract

We present our findings in a case of central retinal artery occlusion (CRAO) that developed in a patient while being treatedwith intravenous cisplatin (CDDP) and etoposide (VP16) for small cell lung cancer. The patient was a 67-year-old womanwho had lung lobectomy for small cell lung cancer. She began adjuvant chemotherapy with CDDP and VP16 after thesurgery, and after 13 days of chemotherapy, she developed a sudden painless decrease of vision in her left eye. She wasreferred to Department of Ophthalmology, and our examination found that her decimal visual acuities were 1.0 OD andlight perception OS. Fluorescein angiography showed a CRAO in her left eye. Two months later, she had a sharp pain inthe left eye because of neovascular glaucoma, and cyclophotocoagulation was immediately performed. Although her visual function did not recover completely (light perception OS), the pain was alleviated after the cyclophotocoagulation. Physicalexaminations showed no additional abnormalities of the cardiovascular system. Although a CRAO during chemotherapyis extremely rare, ophthalmologists and internists should remember that a CRAO can develop in patients undergoing combined chemotherapy even though other cardiovascular events may not be present.

Published
2017
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