Influenza vaccination and cardiovascular risk in patients with recent TIA and stroke

OBJECTIVES: To determine whether current influenza vaccination is associated with reduced risk of major vascular events in patients with recent ischemic stroke or TIA of mainly atherothrombotic origin. METHODS: Data were pooled from 2 prospective cohort studies, the OPTIC Registry (n = 3,635) and the AMISTAD Study (n = 618), and from the randomized PERFORM Trial (n = 19,120), all of which included patients with recent ischemic stroke or TIA. Influenza vaccination status was determined in 23,110 patients. The primary outcome was a composite of nonfatal myocardial infarction, nonfatal stroke, or vascular death up to 2 years. Secondary outcomes were myocardial infarction and stroke separately. RESULTS: Influenza vaccination had no association with the primary outcome in the propensity score-matched cohort (hazard ratio 0.97, 95% confidence interval [CI] 0.85-1.11; p = 0.67) or in the propensity score-adjusted cohort (hazard ratio 1.00, 95% CI 0.89-1.12; p = 0.99). Similarly, the risk of stroke and myocardial infarction did not differ between the vaccinated group and the unvaccinated group; in the matched cohort, the hazard ratio was 1.01 (95% CI 0.88-1.17; p = 0.89) for stroke and 0.84 (95% CI 0.59-1.18; p = 0.30) for myocardial infarction. CONCLUSIONS: Influenza vaccination was not associated with reduced outcome events in patients with recent atherothrombotic ischemic stroke after considering all baseline characteristics (including concomitant medications) associated with influenza vaccination.

CD41 T cell recovery during suppression of HIV replication: an international comparison of the immunological efficacy of antiretroviral therapy in North America, Asia and Africa.

BACKGROUND Even among HIV-infected patients who fully suppress plasma HIV RNA replication on antiretroviral therapy, genetic (e.g. CCL3L1 copy number), viral (e.g. tropism) and environmental (e.g. chronic exposure to microbial antigens) factors influence CD4 recovery. These factors differ markedly around the world and therefore the expected CD4 recovery during HIV RNA suppression may differ globally. METHODS We evaluated HIV-infected adults from North America, West Africa, East Africa, Southern Africa and Asia starting non-nucleoside reverse transcriptase inhibitorbased regimens containing efavirenz or nevirapine, who achieved at least one HIV RNA level <500/ml in the first year of therapy and observed CD4 changes during HIV RNA suppression. We used a piecewise linear regression to estimate the influence of region of residence on CD4 recovery, adjusting for socio-demographic and clinical characteristics. We observed 28 217 patients from 105 cohorts over 37 825 person-years. RESULTS After adjustment, patients from East Africa showed diminished CD4 recovery as compared with other regions. Three years after antiretroviral therapy initiation, the mean CD4 count for a prototypical patient with a pre-therapy CD4 count of 150/ml was 529/ml [95% confidence interval (CI): 517–541] in North America, 494/ml (95% CI: 429–559) in West Africa, 515/ml (95% CI: 508–522) in Southern Africa, 503/ml (95% CI: 478–528) in Asia and 437/ml (95% CI: 425–449) in East Africa. CONCLUSIONS CD4 recovery during HIV RNA suppression is diminished in East Africa as compared with other regions of the world, and observed differences are large enough to potentially influence clinical outcomes. Epidemiological analyses on a global scale can identify macroscopic effects unobservable at the clinical, national or individual regional level.

Computer Vision-Based Carbohydrate Estimation for Type 1 Diabetic Patients Using Smartphones

Background: Individuals with type 1 diabetes (T1D) have to count the carbohydrates (CHOs) of their meal to estimate the prandial insulin dose needed to compensate for the meal’s effect on blood glucose levels. CHO counting is very challenging but also crucial, since an error of 20 grams can substantially impair postprandial control. Method: The GoCARB system is a smartphone application designed to support T1D patients with CHO counting of nonpacked foods. In a typical scenario, the user places a reference card next to the dish and acquires 2 images with his/her smartphone. From these images, the plate is detected and the different food items on the plate are automatically segmented and recognized, while their 3D shape is reconstructed. Finally, the food volumes are calculated and the CHO content is estimated by combining the previous results and using the USDA nutritional database. Results: To evaluate the proposed system, a set of 24 multi-food dishes was used. For each dish, 3 pairs of images were taken and for each pair, the system was applied 4 times. The mean absolute percentage error in CHO estimation was 10 ± 12%, which led to a mean absolute error of 6 ± 8 CHO grams for normal-sized dishes. Conclusion: The laboratory experiments demonstrated the feasibility of the GoCARB prototype system since the error was below the initial goal of 20 grams. However, further improvements and evaluation are needed prior launching a system able to meet the inter- and intracultural eating habits.

Carbohydrate Estimation by a Mobile Phone-Based System Versus Self-Estimations of Individuals With Type 1 Diabetes Mellitus: A Comparative Study

Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.

Na 1 Nachlass Max Horkheimer, 600 - Korrespondenzen u.a. mit Friedrich Pollock (p. VI 42, 211-386)

Briefwechsel zwischen Max Horkheimer, Frederick Pollock und Karl August und Olga Wittfogel; 2 Briefe zwischen Edith B. Bernett und Max Horkheimer, April 1940; 2 Briefe zwischen Max Horkheimer und Philip Vaudrin, Juli 1939; 3 Briefe an David H. Stevens von Max Horkheimer, 26.03.1938; 1 Brief von A. Radcliffe an Frederick Pollock, 18.11.1937; 3 Briefe an Max Horkheimer von der Columbia University Faculty of Political Science (New York), November 1937; 2 Briefe von der Columbia University Department of History (New York) an Max Horkheimer, November 1937; 1 Brief an Max Horkheimer von Sharon Beard, 27.11.1937; 1 Brief von Ruth Benedict an Max Horkheimer, 19.11.1937; 1 Brief an Max Horkheimer von Franz Boas, 19.11.1937; 1 Brief von R. E. Chaddock an Max Horkheimer, 21.11.1937; 1 Brief an Max Horkheimer von Ch'ao-ting Chi, 19.11.1937; 1 Brief von J. M. Clark an Max Horkheimer, 22.11.1937; 1 Brief an Dr. Wertheimer von Morris R. Cohen, 29.11.1937; 1 Brief von Alfred E. Cohn an Max Horkheimer, 26.11.1937; 1 Brief an Max Horkheimer von John J. Coss, 22.11.1937; 1 Brief von George S. Counts an Max Horkheimer, 24.11.1937; 1 Brief an Max Horkheimer von A. P. Evans, 22.11.1937; 3 Briefe von Gertrude Stewart an Max Horkheimer, 20. - 24.11.1937; 1 Brief an Max Horkheimer von L. C. Goodrich, 22.11.1937; 1 Brief von John W. Innes an Max Horkheimer, 20.11.1937; 1 Brief an Max Horkheimer von Philip C. Jessup, 24.11.1937; 1 Brief von John A. Krout an Max Horkheimer, 23.11.1937; 1 Brief an Max Horkheimer von Bruno Lasker, 20.11.1937; 1 Brief von Samuel McCune Lindsay an Max Horkheimer, 24.11.1937; 1 Brief an Max Horkheimer von K. N. Llewellyn, 26.11.1937; 1 Brief von R. S. Lynd an Max Horkheimer, [November 1937]; 1 Brief an Max Horkheimer von R. M. MacIver, 19.11.1937; 1 Brief von Julian W. Mack an Max Horkheimer, 24.11.1937; 1 Brief an Max Horkheimer von Arthur Maxmahon, 20.11.1937; 1 Brief von Jerome Michael an Max Horkheimer, 26.11.1937; 1 Brief an Max Horkheimer von Wesley C. Mitchell, 22.11.1937; 1 Brief von der Columbia University School of Business (New York) an Max Horkheimer, 22.11.1937; 2 Briefe zwischen Max Horkheimer und der John Simon Guggenheim Memorial Foundation (New York), November 1937; 2 Briefe von der Columbia University Department of Psychology (New York) an Max Horkheimer, November 1937; 1 Brief an Max Horkheimer von Goodwin Watson, 23.11.1937; 1 Brief von Otto Nathan an Max Horkheimer, 26.11.937; 1 Brief an Max Horkheimer von John K. Norton, 23.11.1937; 1 Brief von der Columbia University Department of Chinese (New York) an Max Horkheimer, 23.11.1937; 1 Brief an Max Horkheimer von Gerold Tanquary Robinson, 19.11.1937; 1 Brief von der Columbia University Department of Public Law and Government (New York) an Max Horkheimer, 22.11.1937; 1 Brief an Max Horkheimer von R. C. Sailer, 20.11.1937; 1 Brief von Herbert W. Schneider an Max Horkheimer, 22.11.1937; 1 Brief an Max Horkheimer von R. L. Schuyler, 20.11.1937; 1 Brief von Pauline Steorns an Max Horkheimer, 22.11.1937; 1 Brief an Max Horkheimer von Frank Tannenbaum, 19.11.1937; 1 Brief von Alfred Vagés an Max Horkheimer, 26.11.1937;