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Visit-to-Visit HbA1c Variability Is Associated With Cardiovascular Disease and Microvascular Complications in Patients With Newly Diagnosed Type 2 Diabetes

OBJECTIVE

To investigate the association between visit-to-visit HbA1c variability and cardiovascular events and microvascular complications in patients with newly diagnosed type 2 diabetes.

RESEARCH DESIGN AND METHODS

This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA1c measurements before the outcomes were evaluated. We used the previously reported HbA1c variability score (HVS), calculated as the percentage of the number of changes in HbA1c >0.5% (5.5 mmol/mol) among all HbA1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models.

RESULTS

We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, HVS >80 to ≤100 vs. HVS ≥0 to ≤20, hazard ratio 2.38 [95% CI 1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA1c, confirmed the robustness of the results.

CONCLUSIONS

Our study shows that higher HbA1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA1c.




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Genetic Susceptibility Determines {beta}-Cell Function and Fasting Glycemia Trajectories Throughout Childhood: A 12-Year Cohort Study (EarlyBird 76)

OBJECTIVE

Previous studies suggested that childhood prediabetes may develop prior to obesity and be associated with relative insulin deficiency. We proposed that the insulin-deficient phenotype is genetically determined and tested this hypothesis by longitudinal modeling of insulin and glucose traits with diabetes risk genotypes in the EarlyBird cohort.

RESEARCH DESIGN AND METHODS

EarlyBird is a nonintervention prospective cohort study that recruited 307 healthy U.K. children at 5 years of age and followed them throughout childhood. We genotyped 121 single nucleotide polymorphisms (SNPs) previously associated with diabetes risk, identified in the adult population. Association of SNPs with fasting insulin and glucose and HOMA indices of insulin resistance and β-cell function, available from 5 to 16 years of age, were tested. Association analysis with hormones was performed on selected SNPs.

RESULTS

Several candidate loci influenced the course of glycemic and insulin traits, including rs780094 (GCKR), rs4457053 (ZBED3), rs11257655 (CDC123), rs12779790 (CDC123 and CAMK1D), rs1111875 (HHEX), rs7178572 (HMG20A), rs9787485 (NRG3), and rs1535500 (KCNK16). Some of these SNPs interacted with age, the growth hormone–IGF-1 axis, and adrenal and sex steroid activity.

CONCLUSIONS

The findings that genetic markers influence both elevated and average courses of glycemic traits and β-cell function in children during puberty independently of BMI are a significant step toward early identification of children at risk for diabetes. These findings build on our previous observations that pancreatic β-cell defects predate insulin resistance in the onset of prediabetes. Understanding the mechanisms of interactions among genetic factors, puberty, and weight gain would allow the development of new and earlier disease-management strategies in children.




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Inoreader mobile apps updated to support Automatic Night Mode, Microblogs, Sort by Magic and popularity indicators.

Hey, it’s been quite some time without updates on this front, but our latest updates to our Android and iOS…




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Autologous Umbilical Cord Blood Transfusion in Young Children With Type 1 Diabetes Fails to Preserve C-Peptide

OBJECTIVE

We conducted an open-label, phase I study using autologous umbilical cord blood (UCB) infusion to ameliorate type 1 diabetes (T1D). Having previously reported on the first 15 patients reaching 1 year of follow-up, herein we report on the complete cohort after 2 years of follow-up.

RESEARCH DESIGN AND METHODS

A total of 24 T1D patients (median age 5.1 years) received a single intravenous infusion of autologous UCB cells and underwent metabolic and immunologic assessments.

RESULTS

No infusion-related adverse events were observed. β-Cell function declined after UCB infusion. Area under the curve C-peptide was 24.3% of baseline 1 year postinfusion (P < 0.001) and 2% of baseline 2 years after infusion (P < 0.001). Flow cytometry revealed increased regulatory T cells (Tregs) (P = 0.04) and naive Tregs (P = 0.001) 6 and 9 months after infusion, respectively.

CONCLUSIONS

Autologous UCB infusion in children with T1D is safe and induces changes in Treg frequency but fails to preserve C-peptide.




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Turning the Tide: Addressing the Long-Term Challenges of EU Mobility for Sending Countries

Amid ongoing debates about the costs and benefits of free movement, this MPI webinar examines evidence from the EU-funded REMINDER project on different types of East-West mobility. Speakers examine big-picture trends of East-West migration; consider possible policy responses at regional, national, and EU levels to alleviate some of the challenges; and reflect on realistic actions that could be taken under a new European Commission.




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Application of Adult-Learning Principles to Patient Instructions: A Usability Study for an Exenatide Once-Weekly Injection Device

Gayle Lorenzi
Sep 1, 2010; 28:157-162
Bridges to Excellence




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Squirrels and Stock Brokers, Or: Innovation Dilemmas, Robustness and Probability

Decisions are made in order to achieve desirable outcomes. An innovation dilemma arises when a seemingly more attractive option is also more uncertain than other options. In this essay we explore the relation between the innovation dilemma and the robustness of a decision, and the relation between robustness and probability. A decision is robust to uncertainty if it achieves required outcomes despite adverse surprises. A robust decision may differ from the seemingly best option. Furthermore, robust decisions are not based on knowledge of probabilities, but can still be the most likely to succeed.

Squirrels, Stock-Brokers and Their Dilemmas




Decision problems.
Imagine a squirrel nibbling acorns under an oak tree. They're pretty good acorns, though a bit dry. The good ones have already been taken. Over in the distance is a large stand of fine oaks. The acorns there are probably better. But then, other squirrels can also see those trees, and predators can too. The squirrel doesn't need to get fat, but a critical caloric intake is necessary before moving on to other activities. How long should the squirrel forage at this patch before moving to the more promising patch, if at all?

Imagine a hedge fund manager investing in South African diamonds, Australian Uranium, Norwegian Kroners and Singapore semi-conductors. The returns have been steady and good, but not very exciting. A new hi-tech start-up venture has just turned up. It looks promising, has solid backing, and could be very interesting. The manager doesn't need to earn boundless returns, but it is necessary to earn at least a tad more than the competition (who are also prowling around). How long should the manager hold the current portfolio before changing at least some of its components?

These are decision problems, and like many other examples, they share three traits: critical needs must be met; the current situation may or may not be adequate; other alternatives look much better but are much more uncertain. To change, or not to change? What strategy to use in making a decision? What choice is the best bet? Betting is a surprising concept, as we have seen before; can we bet without knowing probabilities?

Solution strategies.
The decision is easy in either of two extreme situations, and their analysis will reveal general conclusions.

One extreme is that the status quo is clearly insufficient. For the squirrel this means that these crinkled rotten acorns won't fill anybody's belly even if one nibbled here all day long. Survival requires trying the other patch regardless of the fact that there may be many other squirrels already there and predators just waiting to swoop down. Similarly, for the hedge fund manager, if other funds are making fantastic profits, then something has to change or the competition will attract all the business.

The other extreme is that the status quo is just fine, thank you. For the squirrel, just a little more nibbling and these acorns will get us through the night, so why run over to unfamiliar oak trees? For the hedge fund manager, profits are better than those of any credible competitor, so uncertain change is not called for.

From these two extremes we draw an important general conclusion: the right answer depends on what you need. To change, or not to change, depends on what is critical for survival. There is no universal answer, like, "Always try to improve" or "If it's working, don't fix it". This is a very general property of decisions under uncertainty, and we will call it preference reversal. The agent's preference between alternatives depends on what the agent needs in order to "survive".

The decision strategy that we have described is attuned to the needs of the agent. The strategy attempts to satisfy the agent's critical requirements. If the status quo would reliably do that, then stay put; if not, then move. Following the work of Nobel Laureate Herbert Simon, we will call this a satisficing decision strategy: one which satisfies a critical requirement.

"Prediction is always difficult, especially of the future." - Robert Storm Petersen

Now let's consider a different decision strategy that squirrels and hedge fund managers might be tempted to use. The agent has obtained information about the two alternatives by signals from the environment. (The squirrel sees grand verdant oaks in the distance, the fund manager hears of a new start up.) Given this information, a prediction can be made (though the squirrel may make this prediction based on instincts and without being aware of making it). Given the best available information, the agent predicts which alternative would yield the better outcome. Using this prediction, the decision strategy is to choose the alternative whose predicted outcome is best. We will call this decision strategy best-model optimization. Note that this decision strategy yields a single universal answer to the question facing the agent. This strategy uses the best information to find the choice that - if that information is correct - will yield the best outcome. Best-model optimization (usually) gives a single "best" decision, unlike the satisficing strategy that returns different answers depending on the agent's needs.

There is an attractive logic - and even perhaps a moral imperative - to use the best information to make the best choice. One should always try to do one's best. But the catch in the argument for best-model optimization is that the best information may actually be grievously wrong. Those fine oak trees might be swarming with insects who've devoured the acorns. Best-model optimization ignores the agent's central dilemma: stay with the relatively well known but modest alternative, or go for the more promising but more uncertain alternative.

"Tsk, tsk, tsk" says our hedge fund manager. "My information already accounts for the uncertainty. I have used a probabilistic asset pricing model to predict the likelihood that my profits will beat the competition for each of the two alternatives."

Probabilistic asset pricing models are good to have. And the squirrel similarly has evolved instincts that reflect likelihoods. But a best-probabilistic-model optimization is simply one type of best-model optimization, and is subject to the same vulnerability to error. The world is full of surprises. The probability functions that are used are quite likely wrong, especially in predicting the rare events that the manager is most concerned to avoid.

Robustness and Probability

Now we come to the truly amazing part of the story. The satisficing strategy does not use any probabilistic information. Nonetheless, in many situations, the satisficing strategy is actually a better bet (or at least not a worse bet), probabilistically speaking, than any other strategy, including best-probabilistic-model optimization. We have no probabilistic information in these situations, but we can still maximize the probability of success (though we won't know the value of this maximum).

When the satisficing decision strategy is the best bet, this is, in part, because it is more robust to uncertainty than another other strategy. A decision is robust to uncertainty if it achieves required outcomes even if adverse surprises occur. In many important situations (though not invariably), more robustness to uncertainty is equivalent to being more likely to succeed or survive. When this is true we say that robustness is a proxy for probability.

A thorough analysis of the proxy property is rather technical. However, we can understand the gist of the idea by considering a simple special case.

Let's continue with the squirrel and hedge fund examples. Suppose we are completely confident about the future value (in calories or dollars) of not making any change (staying put). In contrast, the future value of moving is apparently better though uncertain. If staying put would satisfy our critical requirement, then we are absolutely certain of survival if we do not change. Staying put is completely robust to surprises so the probability of success equals 1 if we stay put, regardless of what happens with the other option. Likewise, if staying put would not satisfy our critical requirement, then we are absolutely certain of failure if we do not change; the probability of success equals 0 if we stay, and moving cannot be worse. Regardless of what probability distribution describes future outcomes if we move, we can always choose the option whose likelihood of success is greater (or at least not worse). This is because staying put is either sure to succeed or sure to fail, and we know which.

This argument can be extended to the more realistic case where the outcome of staying put is uncertain and the outcome of moving, while seemingly better than staying, is much more uncertain. The agent can know which option is more robust to uncertainty, without having to know probability distributions. This implies, in many situations, that the agent can choose the option that is a better bet for survival.

Wrapping Up

The skillful decision maker not only knows a lot, but is also able to deal with conflicting information. We have discussed the innovation dilemma: When choosing between two alternatives, the seemingly better one is also more uncertain.

Animals, people, organizations and societies have developed mechanisms for dealing with the innovation dilemma. The response hinges on tuning the decision to the agent's needs, and robustifying the choice against uncertainty. This choice may or may not coincide with the putative best choice. But what seems best depends on the available - though uncertain - information.

The commendable tendency to do one's best - and to demand the same of others - can lead to putatively optimal decisions that may be more vulnerable to surprise than other decisions that would have been satisfactory. In contrast, the strategy of robustly satisfying critical needs can be a better bet for survival. Consider the design of critical infrastructure: flood protection, nuclear power, communication networks, and so on. The design of such systems is based on vast knowledge and understanding, but also confronts bewildering uncertainties and endless surprises. We must continue to improve our knowledge and understanding, while also improving our ability to manage the uncertainties resulting from the expanding horizon of our efforts. We must identify the critical goals and seek responses that are immune to surprise. 




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How we must respond to the coronavirus pandemic | Bill Gates

Philanthropist and Microsoft cofounder Bill Gates offers insights into the COVID-19 pandemic, discussing why testing and self-isolation are essential, which medical advancements show promise and what it will take for the world to endure this crisis. (This virtual conversation is part of the TED Connects series, hosted by head of TED Chris Anderson and current affairs curator Whitney Pennington Rodgers. Recorded March 24, 2020)




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Eligibility for Federal School Improvement Grants Helped Ohio Students, Study Says

Academic achievement at Ohio schools eligible for School Improvement Grants during the Obama administration increased for a few years, a new study says, but SIG's legacy remains complicated.




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Bill Protecting Ohio E-School Heads to Governor

A bill shielding what is now Ohio's largest online school and its sponsor from the negative consequences of accepting thousands of former Electronic Classroom of Tomorrow students is headed to Gov. John Kasich for his signature.




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Murphy tells Trump at White House NJ will need billions




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How to Teach Math to Students With Disabilities, English Language Learners

Experts recommend emphasizing language skills, avoiding assumptions about ability based on broad student labels, and focusing on students’ strengths rather than their weaknesses.




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California doom: Staggering $54 billion budget deficit looms




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Hogan vetoes major education bill, cites virus budget impact




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North Dakota Bill Targets Common Core in Both Substance and Name

North Dakota lawmakers fended off an effort to ensure that the state's new standards, and any tests that might be used with them, won't mirror the common core.




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Trump Taps a Nebraska Education Official for Rehabilitative Services Post

President Donald Trump has tapped Mark Schultz, a deputy commissioner of education in Nebraska, to serve as commissioner of the rehabilitation services administration at the Education Department.




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Civics-Test Bills Hit State Legislatures Again in 2016

A bill in Nebraska would require high school students to take a civics examination before graduating.




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Heavy Response to Nebraska Restraint Bill Illuminates Teachers' Frustrations

A Nebraska senator introduced a bill that would give teachers legal cover to physically restraint disruptive students, prompting a strong positive response from members of the state teachers' union.




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Hogan vetoes major education bill, cites virus budget impact




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New York Proposes Increased Flexibility to Teacher Certification Process

To give districts more flexibility in the face of teacher shortages, New York's education department is proposing to modify its regulations on teacher certifications.




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'Open Algorithms' Bill Would Jolt New York City Schools, Public Agencies

The proposed legislation would require the 1.1-million student district to publish the source code behind algorithms used to assign students to high schools, evaluate teachers, and more.




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Yonkers, N.Y., District Commits to More Inclusion of Students with Disabilities

The U.S. Department of Education's office for civil rights said that some students were placed in self-contained special education settings without an individualized justification for doing so.




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New York Denied ESSA Waiver to Test Students With Disabilities Off Grade Level

The state will be required to test all students using grade level tests, except for those with significant cognitive disabilities.




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School Accessibility Gets $150 Million Boost in N.Y.C. Budget

The money, which will be allocated over three years, is expected to make major and minor improvements to schools throughout the city.




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Colorado Lawmakers Pass Pension Reform Bill in Late-Night Deal

The final version of the bill reduces the cost-of-living raises and increases employee contributions to their retirement, among other changes.




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Murphy tells Trump at White House NJ will need billions




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How to Teach Math to Students With Disabilities, English Language Learners

Experts recommend emphasizing language skills, avoiding assumptions about ability based on broad student labels, and focusing on students’ strengths rather than their weaknesses.




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California doom: Staggering $54 billion budget deficit looms




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Hogan vetoes major education bill, cites virus budget impact




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California Reforms Accountability

California just made school accountability much more complicated. And that's good.




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Incoming California Governor to Seek Nearly $2 Billion in Early-Childhood Funding

Democrat Gavin Newsom, who takes office Jan. 7, plans to expand full-day kindergarten and child-care offerings in the state, according to media reports.




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He's Fighting for Details on How Hawaii Spent $2 Billion on Its Schools

An activist's lawsuit is an example of how many states, because of outdated software, have trouble answering the public's demand to detail how billions of K-12 dollars are spent.




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Murphy tells Trump at White House NJ will need billions




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With Waiver Denial, Utah Mulls Second Accountability System

Utah is one of four states where state laws conflict with components of the federal Every Student Succeeds Act meaning districts may have to answer to two separate accountability systems this fall.




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Utah to reconsider bill funding special needs scholarships




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Child-Care Challenges Cost Georgia Nearly $2 Billion Annually, Study Finds

A new study says that problems surrounding child-care hurt Georgia parents economically in many ways including in turned down promotions and having to cut back on work and school hours.




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West Virginia signs deal with brand consultant ahead of college athletes' potential ability for endorsements

The NCAA is expected to formally approve rules changes that will allow athletes to get endorsement income in 2021.




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The billionaire’s dirty little secret / L.J. Diva.

Originally published as "Her Secret Island of Sex and Torment" in 2014. Rereleased as "Her Secret Island" in 2016.




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Building confidence in enrolling learners with disability for providers of education and training / ACPET, NDCO.




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Don't worry about the rent : choosing new office space to boost business performance / Darren Bilsborough.




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The new costs adjudication rules / presented by Bill Ericson, Finlaysons.




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Costs in estate matters : the practical implications of the return of the loser pays rule / presented by Bill Ericson, Finlaysons Lawyers.




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Costs and persons under a disability : the potential for a conflict of interest / presented by Master Norman, District Court of South Australia.




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CTP Update - Claims for Loss of Dependency under part 5 of the Civil Liability Act 1936.




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Common costs problems / paper presented by Bill Ericson, Ericson Legal.




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Mobile elevating work platforms (MEWP) guidelines.




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Big data, big responsibilities : a guide to privacy & data security for Australian business / Nick Abrahams and Jim Lennon.

Data protection -- Law and legislation -- Australia.




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Macquarie atlas of Indigenous Australia / general editors, Bill Arthur & Frances Morphy ; [foreword by Patrick Dodson].

Aboriginal Australians -- Names.




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Global meat : social and environmental consequences of the expanding meat industry / edited by Bill Winders and Elizabeth Ransom.

Meat industry and trade -- Environmental aspects.




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Controversial Science Education Bill Defeated by South Dakota Panel

Critics said the bill would have allowed teachers to bring in alternative theories about climate change and evolution.