Nash Social Welfare in Selfish and Online Load Balancing (Short Paper)

In load balancing problems there is a set of clients, each wishing to select a resource from a set of permissible ones, in order to execute a certain task. Each resource has a latency function, which depends on its workload, and a client's cost is the completion time of her chosen resource. Two fundamental variants of load balancing problems are selfish load balancing (aka. load balancing games), where clients are non-cooperative selfish players aimed at minimizing their own cost solely, and online load balancing, where clients appear online and have to be irrevocably assigned to a resource without any knowledge about future requests. We revisit both problems under the objective of minimizing the Nash Social Welfare, i.e., the geometric mean of the clients' costs. To the best of our knowledge, despite being a celebrated welfare estimator in many social contexts, the Nash Social Welfare has not been considered so far as a benchmarking quality measure in load balancing problems. We provide tight bounds on the price of anarchy of pure Nash equilibria and on the competitive ratio of the greedy algorithm under very general latency functions, including polynomial ones. For this particular class, we also prove that the greedy strategy is optimal, as it matches the performance of any possible online algorithm

Statin Use and Cognitive Function:Population-Based Observational Study with Long-Term Follow-Up

We aimed to evaluate the association between statin use and cognitive function. Cognitive function was measured with the Ruff Figural Fluency Test (RFFT; worst score, 0; best score, 175 points) and the Visual Association Test (VAT; low performance, 0-10; high performance, 11-12 points) in an observational study that included 4,095 community-dwelling participants aged 35-82 years. Data on statin use were obtained from a computerized pharmacy database. Analysis were done for the total cohort and subsamples matched on cardiovascular risk (N=1232) or propensity score for statin use (N=3609). We found that a total of 904 participants (10%) used a statin. Statin users were older than non-users: mean age (SD) 61 (10) vs. 52 (11) years (p</p

Course of body weight before and after the initiation of insulin therapy in type 2 diabetes mellitus:Retrospective inception cohort study (ZODIAC 58)

Aims: The aim of this study was to explore the effect of insulin treatment initiation on weight by taking weight change prior to initiation into account. Materials and methods: We performed an observational retrospective inception cohort study, concerning Dutch primary care. We identified all patients that initiated insulin treatment (n = 7967) and individually matched patients with a reference patient (n = 5213 pairs). We obtained estimated mean weight changes in the five years prior to five years post insulin therapy. We applied linear regression analysis on weight change in the first year after insulin therapy (T0 to T+1), with matched group as primary determinant adjusted for pre-insulin weight change and additional covariates. Results: Estimated mean weight increased in the five consecutive years prior to insulin therapy (-0.23 kg in year T-5 to T-4, 0.01 kg in year T-4 to T-3, 0.07 kg in year T-3 to T-2, 0.24 kg in year T-2 to T-1, and 0.46 kg in year T-1 to T0) and continued to increase in the first year after, that is T0 to T+1, at a slightly lower rate (0.31 ± 3.9 kg). Pre-insulin weight change had the highest explained variance and was inversely and independently associated with weight change (p < .001). Starting insulin was associated with weight increase, independent of pre-insulin weight change (β-adjusted 1.228, p < .001). Stratification revealed that despite having a more or less similar baseline BMI, patients with substantial weight increase showed higher estimated mean BMI's followed by weight loss pre-insulin. In matched references, estimated mean weight changes were negative in all years concerning the study period, indicating consistent weight loss. Conclusions: Initiation of insulin therapy was independently associated with weight increase; however, overall effect on weight was small and subject to substantial variation. Pre-insulin weight change is identified as a relatively strong inverse determinant of weight change after insulin initiation

Determinants of excessive weight gain after the initiation of insulin therapy in type 2 diabetes mellitus:Retrospective inception cohort study (ZODIAC 60)

AIMS: To explore determinants of excessive weight gain after initiation of insulin therapy in type 2 diabetes mellitus (T2DM), in particular variables identified in the pre-insulin phase.METHODS: We performed a retrospective observational intervention cohort study, by means of a new user design/ inception cohort concerning n = 5086 patients. We studied determinants of excessive weight gain (5 kg or more) in the first year after initiation of insulin therapy, using both visualization and logistic regression analysis with subsequent receiver operation characteristic (ROC) analyses. Potential determinants pre-, at- and post-insulin initiation were included.RESULTS: One out of 10 patients (10.0%) gained 5 kg weight or more. The earliest determinants of excessive weight gain were weight change (inversely) and HbA1c change in the two years prior to insulin therapy (p &lt; 0.001). Patients that lost weight parallel with HbA1c rise in the two-years pre-insulin, showed the most pronounced weight gain. Of these patients, roughly one out of five (20.3%) gained 5 kg weight or more.CONCLUSIONS: Clinicians and patients should be alert for excessive weight gain after initiation of insulin, in the case of weight loss prior to insulin therapy initiation, particularly with increasing and prolonged high HbA1c at (and after) insulin initiation.</p

Alpha Lipoic Acid for Symptomatic Peripheral Neuropathy in Patients with Diabetes: A Meta-Analysis of Randomized Controlled Trials

Objective. We performed a systematic review of the literature to evaluate the effects of alpha lipoic acid for symptomatic peripheral neuropathy in patients with diabetes mellitus. Research design and methods. The databases MEDLINE and EMBASE were searched using the key words “lipoic acid”, “thioctic acid”, “diabet∗”, and the MeSH-terms “thioctic acid” and “diabetes mellitus”. Randomised controlled trials using the TSS score as the outcome measure were selected and assessed for their methodological quality. Study selection and quality assessment were performed independently by three observers. Results. Overall, the pooled standardized mean difference estimated from all trials revealed a reduction in TSS scores of −2.26 (CI: −3.12 to −1.41; P = 0.00001) in favour of alpha lipoic acid administration. Subgroup analyses of oral administration (−1.78 CI: −2.45 to −1.10; P = 0.00001) and intravenous administration (−2.81 CI: −4.16 to −1.46; P = 0.0001) confirmed the robustness of the overall result. Conclusions. When given intravenously at a dosage of 600 mg/day over a period of 3 weeks, alpha lipoic acid leads to a significant and clinically relevant reduction in neuropathic pain (grade of recommendation A). It is unclear if the significant improvements seen after 3–5 weeks of oral administration at a dosage of >600 mg/day are clinically relevant

Health related quality of life in patients with type I diabetes mellitus:generic &amp; disease-specific measurement

Background & objectives: An ideal instrument for the assessment of health related quality of life (HRQOL) in patients with diabetes mellitus type I (T1DM) should incorporate the benefits of both generic and disease-specific instruments. The objective of this study was to investigate the responsiveness and the ability to provide information about diabetes-specific associations with HRQOL, of two generic instruments, in comparison with two diabetes-specific instruments, in patients with T1DM. Methods: In a Dutch cohort of 234 patients with T1DM we longitudinally assessed HRQOL using both generic and diabetes-specific instruments. We investigated the responsiveness, the associations with diabetes-specific variables and the Identification of specific patients by the Instruments used. Results: The generic RAND-36 was able to detect statistically significant and clinically relevant changes in HRQOL over time. Moreover, the RAND-36 was associated with (changes In) diabetes. specific variables. The generic and diabetes-specific Instruments partly Identified different patients with lowest HRQOL. Interpretation & conclusion: The RAND-36 was highly responsive to changes in HRQOL in patients with T1DM and revealed diabetes-specific associations with HRQOL. A low correlation between the generic and diabetes-specific instruments and partly different identification of patients with lower HRQOL support the complementary use of these instruments In patients with T1DM