Risk Factors for Hyperosmolar Hyperglycemic State in Pediatric Type 2 Diabetes.

BACKGROUND: There is a paucity of data on the risk factors for the hyperosmolar hyperglycemic state (HHS) compared with diabetic ketoacidosis (DKA) in pediatric type 2 diabetes (T2D). METHODS: We used the national Kids Inpatient Database to identify pediatric admissions for DKA and HHS among those with T2D in the years 2006, 2009, 2012, and 2019. Admissions were identified using ICD codes. Those aged <9yo were excluded. We used descriptive statistics to summarize baseline characteristics and Chi-squared test and logistic regression to evaluate factors associated with admission for HHS compared with DKA in unadjusted and adjusted models. RESULTS: We found 8,961 admissions for hyperglycemic emergencies in youth with T2D, of which 6% were due to HHS and 94% were for DKA. These admissions occurred mostly in youth 17-20 years old (64%) who were non-White (Black 31%, Hispanic 20%), with public insurance (49%) and from the lowest income quartile (42%). In adjusted models, there were increased odds for HHS compared to DKA in males (OR 1.77, 95% CI 1.42-2.21) and those of Black race compared to those of White race (OR 1.81, 95% CI 1.34-2.44). Admissions for HHS had 11.3-fold higher odds for major or extreme severity of illness and 5.0-fold higher odds for mortality. CONCLUSION: While DKA represents the most admissions for hyperglycemic emergencies among pediatric T2D, those admitted for HHS had higher severity of illness and mortality. Male gender and Black race were associated with HHS admission compared to DKA. Additional studies are needed to understand the drivers of these risk factors

An Empirical Comparison of Consumer Innovation Adoption Models: Implications for Subsistence Marketplaces

So called “pro-poor” innovations may improve consumer wellbeing in subsistence marketplaces. However, there is little research that integrates the area with the vast literature on innovation adoption. Using a questionnaire where respondents were asked to provide their evaluations about a mobile banking innovation, this research fills this gap by providing empirical evidence of the applicability of existing innovation adoption models in subsistence marketplaces. The study was conducted in Bangladesh among a geographically dispersed sample. The data collected allowed an empirical comparison of models in a subsistence context. The research reveals the most useful models in this context to be the Value Based Adoption Model and the Consumer Acceptance of Technology model. In light of these findings and further examination of the model comparison results the research also shows that consumers in subsistence marketplaces are not just motivated by functionality and economic needs. If organizations cannot enhance the hedonic attributes of a pro-poor innovation, and reduce the internal/external constraints related to adoption of that pro-poor innovation, then adoption intention by consumers will be lower

Bostonia: The Boston University Alumni Magazine. Volume 16

Founded in 1900, Bostonia magazine is Boston University's main alumni publication, which covers alumni and student life, as well as university activities, events, and programs

Geographical migration and fitness dynamics of Streptococcus pneumoniae

Streptococcus pneumoniae is a leading cause of pneumonia and meningitis worldwide. Many different serotypes co-circulate endemically in any one location1,2. The extent and mechanisms of spread and vaccine-driven changes in fitness and antimicrobial resistance remain largely unquantified. Here using geolocated genome sequences from South Africa (n = 6,910, collected from 2000 to 2014), we developed models to reconstruct spread, pairing detailed human mobility data and genomic data. Separately, we estimated the population-level changes in fitness of strains that are included (vaccine type (VT)) and not included (non-vaccine type (NVT)) in pneumococcal conjugate vaccines, first implemented in South Africa in 2009. Differences in strain fitness between those that are and are not resistant to penicillin were also evaluated. We found that pneumococci only become homogenously mixed across South Africa after 50 years of transmission, with the slow spread driven by the focal nature of human mobility. Furthermore, in the years following vaccine implementation, the relative fitness of NVT compared with VT strains increased (relative risk of 1.68; 95% confidence interval of 1.59–1.77), with an increasing proportion of these NVT strains becoming resistant to penicillin. Our findings point to highly entrenched, slow transmission and indicate that initial vaccine-linked decreases in antimicrobial resistance may be transient

Relationships Between Socioeconomic Status, Insurance Coverage for Diabetes Technology and Adverse Health in Patients With Type 1 Diabetes.

IntroductionInsulin pumps and continuous glucose monitors (CGM) have many benefits in the management of type 1 diabetes. Unfortunately disparities in technology access occur in groups with increased risk for adverse effects (eg, low socioeconomic status [SES], public insurance).Research design & methodsUsing 2015 to 2016 data from 4,895 participants from the T1D Exchange Registry, a structural equation model (SEM) was fit to explore the hypothesized direct and indirect relationships between SES, insurance features, access to diabetes technology, and adverse clinical outcomes (diabetic ketoacidosis, hypoglycemia). SEM was estimated using the maximum likelihood method and standardized path coefficients are presented.ResultsHigher SES and more generous insurance coverage were directly associated with CGM use (β = 1.52, SE = 0.12, P < .0001 and β = 1.21, SE = 0.14, P < .0001, respectively). Though SES displayed a small inverse association with pump use (β = -0.11, SE = 0.04, P = .0097), more generous insurance coverage displayed a stronger direct association with pump use (β = 0.88, SE = 0.10, P < .0001). CGM use and pump use were both directly associated with fewer adverse outcomes (β = -0.23, SE = 0.06, P = .0002 and β = -0.15, SE = 0.04, P = .0002, respectively). Both SES and insurance coverage demonstrated significant indirect effects on adverse outcomes that operated through access to diabetes technology (β = -0.33, SE = 0.09, P = .0002 and β = -0.40, SE = 0.09, P < .0001, respectively).ConclusionsThe association between SES and insurance coverage and adverse outcomes was primarily mediated through diabetes technology use, suggesting that disparities in diabetes outcomes have the potential to be mitigated by addressing the upstream disparities in technology use

Czynniki ryzyka stanu hiperglikemiczno-hiperosmolalnego w cukrzycy typu 2 u dzieci i młodzieży

Wprowadzenie. Niewiele jest danych porównawczych dotyczących czynników ryzyka stanu hiperglikemiczno-hiperosmolalnego (HHS, hyperosmolar hyperglycemic state) i cukrzycowej kwasicy ketonowej (DKA, diabetic ketoacidosis) u dzieci z cukrzycą typu 2. Metody. W badaniu wykorzystano amerykańską krajową bazę danych dotyczących hospitalizacji pacjentów pediatrycznych Kids’ Inpatient Database, aby zidentyfikować przyjęcia z powodu DKA i HHS u dzieci i młodzieży z cukrzycą typu 2 w latach 2006, 2009, 2012 i 2019. Hospitalizacje identyfikowano za pomocą kodów ICD. Wykluczono osoby w wieku poniżej 9 lat. Wykorzystano statystyki opisowe do podsumowania charakterystyki wyjściowej oraz test chi-kwadrat i regresji logistycznej do oceny czynników związanych z przyjęciem do szpitala z powodu HHS w porównaniu z DKA w modelach nieskorygowanych i skorygowanych. Wyniki. Odnotowano 8961 przyjęć w trybie nagłym młodzieży z cukrzycą typu 2 z powodu hiperglikemii, z czego 6% było spowodowanych HHS, a 94% — DKA. Te hospitalizacje dotyczyły głównie młodzieży w wieku 17–20 lat (64%), która nie była rasy białej (31% rasy czarnej, 20% Latynosów), posiadała ubezpieczenie społeczne (49%) i pochodziła z kwartyla najniższych dochodów (42%). W skorygowanych modelach szanse wystąpienia HHS było większe w porównaniu z DKA u mężczyzn (OR 1,77; 95% CI 1,42–2,21) oraz u osób rasy czarnej w porównaniu z rasą białą (OR 1,81, 95% CI 1,34–2,44). Przyjęcia do szpitala z powodu HHS charakteryzowały się 11,3-krotnie większą szansą, że stan pacjenta będzie ciężki lub skrajnie ciężki, i 5-krotnie większą szansą zgonu. Wnioski. Chociaż wśród dzieci i młodzieży z cukrzycą typu 2 najczęstszą przyczyną przyjęć w trybie nagłym pacjentów z hiperglikemią była DKA, hospitalizacje pacjentów z powodu HHS charakteryzowały się większą ciężkością choroby i wyższą śmiertelnością. Płeć męska i rasa czarna były powiązane z przyjęciem z powodu HHS (w porównaniu z DKA). Potrzebne są dodatkowe badania, aby zrozumieć mechanizmy wpływające na te czynniki ryzyka

A Longitudinal View of Disparities in Insulin Pump Use Among Youth with Type 1 Diabetes: The SEARCH for Diabetes in Youth Study.

Objective: To evaluate changes in insulin pump use over two decades in a national U.S. sample. Research Design and Methods: We used data from the SEARCH for Diabetes in Youth study to perform a serial cross-sectional analysis to evaluate changes in insulin pump use in participants <20 years old with type 1 diabetes by race/ethnicity and markers of socioeconomic status across four time periods between 2001 and 2019. Multivariable generalized estimating equations were used to assess insulin pump use. Temporal changes by subgroup were assessed through interactions. Results: Insulin pump use increased from 31.7% to 58.8%, but the disparities seen in pump use persisted and were unchanged across subgroups over time. Odds ratio for insulin pump use in Hispanic (0.57, confidence interval [95% CI] 0.45-0.73), Black (0.28, 95% CI 0.22-0.37), and Other race (0.49, 95% CI 0.32-0.76) participants were significantly lower than White participants. Those with ≤high school degree (0.39, 95% CI 0.31-0.47) and some college (0.68, 95% CI 0.58-0.79) had lower use compared to those with ≥bachelors degree. Those with public insurance (0.84, 95% CI 0.70-1.00) had lower use than those with private insurance. Those with an annual household income <$25K (0.43, 95$25K-$49K (0.52, 95$50K-$74K (0.79, 95$75,000. Conclusion: Over the past two decades, there was no improvement in the racial, ethnic, and socioeconomic inequities in insulin pump use, despite an overall increase in use. Studies that evaluate barriers or test interventions to improve technology access are needed to address these persistent inequities

Racial Disparities in Access and Use of Diabetes Technology Among Adult Patients with Type 1 Diabetes in a U.S. Academic Medical Center

   Objective: Recent studies highlight racial disparities in insulin pump (PUMP) and continuous glucose monitor (CGM) use in children and adolescents with type 1 diabetes (T1D). This study explored racial disparities in diabetes technology among adult patients with T1D. Research Design and Methods: Retrospective clinic-based cohort study of adult patients with T1D seen consecutively from April 2013 to January 2020. Race was categorized into non-Black (reference group) and Black. The primary outcomes were baseline and prevalent technology use, rates of diabetes technology discussions (CGMdiscn, PUMPdiscn), and prescribing (CGMrx, PUMPrx). Multivariable logistic regression analysis evaluated the association of technology discussions and prescribing with race, adjusting for social determinants of health and diabetes outcomes.  Results:  Among 1,528 adults with T1D, baseline technology use was significantly lower for Black compared to non-Black patients (7.9% vs. 30.3% for CGM; 18.7% vs. 49.6% for pump), as was prevalent use (43.6% vs. 72.1% for CGM; 30.7% vs. 64.2% for pump). Black patients had adjusted odds ratios (aORs) of 0.51 (95% CI, 0.29, 0.90) and 0.61 (95% CI, 0.41, 0.93) for CGMdiscn and CGMrx, respectively. Black patients had aORs of 0.74 (95% CI, 0.44, 1.25) and 0.40 (95% CI, 0.22, 0.70), for PUMPdiscn and PUMPrx, respectively. Neighborhood context, insurance, marital and employment status, and number of clinic visits were also associated with the outcomes. Conclusions and Relevance: Significant racial disparities were observed in discussions, prescribing, and use of diabetes technology. Further research is needed to identify the causes behind these disparities and develop and evaluate strategies to reduce them.</p