Is glycaemic control associated with dietary patterns independent of weight change in people newly diagnosed with type 2 diabetes? Prospective analysis of the Early-ACTivity-In-Diabetes trial.

BACKGROUND: It is unclear whether diet affects glycaemic control in type 2 diabetes (T2D), over and above its effects on bodyweight. We aimed to assess whether changes in dietary patterns altered glycaemic control independently of effects on bodyweight in newly diagnosed T2D. METHODS: We used data from 4-day food diaries, HbA1c and potential confounders in participants of the Early-ACTivity-In-Diabetes trial measured at 0, 6 and 12 months. At baseline, a 'carb/fat balance' dietary pattern and an 'obesogenic' dietary pattern were derived using reduced-rank regression, based on hypothesised nutrient-mediated mechanisms linking dietary intake to glycaemia directly or via obesity. Relationships between 0 and 6 month change in dietary pattern scores and baseline-adjusted HbA1c at 6 months (n = 242; primary outcome) were assessed using multivariable linear regression. Models were repeated for periods 6-12 months and 0-12 months (n = 194 and n = 214 respectively; secondary outcomes). RESULTS: Reductions over 0-6 months were observed in mean bodyweight (- 2.3 (95% CI: - 2.7, - 1.8) kg), body mass index (- 0.8 (- 0.9, - 0.6) kg/m2), energy intake (- 788 (- 953, - 624) kJ/day), and HbA1c (- 1.6 (- 2.6, -0.6) mmol/mol). Weight loss strongly associated with lower HbA1c at 0-6 months (ß = - 0.70 [95% CI - 0.95, - 0.45] mmol/mol/kg lost). Average fat and carbohydrate intakes changed to be more in-line with UK healthy eating guidelines between 0 and 6 months. Dietary patterns shifting carbohydrate intakes higher and fat intakes lower were characterised by greater consumption of fresh fruit, low-fat milk and boiled/baked potatoes and eating less of higher-fat processed meats, butter/animal fats and red meat. Increases in standardised 'carb/fat balance' dietary pattern score associated with improvements in HbA1c at 6 months independent of weight loss (ß = - 1.54 [- 2.96, - 0.13] mmol/mol/SD). No evidence of association with HbA1c was found for this dietary pattern at other time-periods. Decreases in 'obesogenic' dietary pattern score were associated with weight loss (ß = - 0.77 [- 1.31, - 0.23] kg/SD) but not independently with HbA1c during any period. CONCLUSIONS: Promoting weight loss should remain the primary nutritional strategy for improving glycaemic control in early T2D. However, improving dietary patterns to bring carbohydrate and fat intakes closer to UK guidelines may provide small, additional improvements in glycaemic control. TRIAL REGISTRATION: ISRCTN92162869 . Retrospectively registered on 25 July 2005.

A longitudinal study investigating change in BMI z-score in primary school-aged children and the association of child BMI z-score with parent BMI.

BACKGROUND: This paper aims to explore change in BMI z-score through childhood and the association between parent BMI and child BMI z-score. This is important to understand for the development of effective obesity interventions. METHODS: Data from the longitudinal B-ProAct1v study (1837 participants) were analysed. A paired sample t-test examined changes in child BMI z-score between Year 1 and 4. Multivariable linear regression models examined the cross-sectional associations between child BMI z-score and parent BMI in Year 1 and 4. The influence of change in parental BMI between Year 1 and Year 4 on child BMI z-score in Year 4 was explored through regression analyses, adjusted for baseline BMI z-score. RESULTS: There was a strong association between child BMI z-score at Year 1 and 4. Child mean BMI z-score score increased from 0.198 to 0.330 (p = < 0.005) between these timepoints. For every unit increase in parent BMI, there was an increase in child BMI z-score of 0.047 in Year 1 (p = < 0.005) and of 0.059 in Year 4 (p = < 0.005). Parental BMI change was not significantly associated with Year 4 child BMI z-score. CONCLUSION: The key indicator of higher child BMI at Year 4 is high BMI at Year 1. Further studies are needed to explore the impact of parental weight change on child BMI z-score and whether interventions targeted at overweight or obese parents, can improve their child's BMI z-score.

Using Information Technology To Improve COVID-19 Care At New York City Health + Hospitals.

As the coronavirus disease 2019 (COVID-19) pandemic surged in New York City, the city's public hospital system, New York City Health + Hospitals, recognized that innovative technological solutions were needed to respond to the crisis. Our health system recently transitioned to a unified enterprisewide electronic medical record across all of our hospitals. This accelerated our ability to implement a series of technological solutions to the crisis. We engaged in focused efforts to improve staff efficiency, including rapid medical screening exams for low-acuity patients, use of "SmartNotes," and improved vital sign monitoring. We standardized patient workup using specialty-specific order sets, created dashboards to give insight into enterprisewide bed availability and facilitate transfers from the hardest-hit hospitals, and improved the patient experience by using tablets to connect patients with loved ones. The technology bridged divides between different hospital systems across New York City to encourage the sharing of data and improve patient care. By rapidly expanding its use of information technology, NYC Health + Hospitals was able to respond to the COVID-19 surge and is now better positioned to work in a more integrated fashion in the future.

Staffing Up For The Surge: Expanding The New York City Public Hospital Workforce During The COVID-19 Pandemic.

Confronted with the coronavirus disease 2019 (COVID-19) pandemic, New York City Health + Hospitals, the city's public health care system, rapidly expanded capacity across its eleven acute care hospitals and three new field hospitals. To meet the unprecedented demand for patient care, NYC Health + Hospitals redeployed staff to the areas of greatest need and redesigned recruiting, onboarding, and training processes. The hospital system engaged private staffing agencies, partnered with the Department of Defense, and recruited volunteers throughout the country. A centralized onboarding team created a single-source portal for medical care providers requiring credentialing and established new staff positions to increase efficiency. Using new educational tools focused on COVID-19 content, the hospital system trained twenty thousand staff members, including nearly nine thousand nurses, within a two-month period. Creation of multidisciplinary teams, frequent enterprisewide communication, willingness to shift direction in response to changing needs, and innovative use of technology were the key factors that enabled the hospital system to meet its goals.

Critical Care And Emergency Department Response At The Epicenter Of The COVID-19 Pandemic.

New York City has emerged as the global epicenter for the coronavirus disease 2019 (COVID-19) pandemic. The city's public health system, New York City Health + Hospitals, has been key to the city's response because its vulnerable patient population is disproportionately affected by the disease. As the number of cases rose in the city, NYC Health + Hospitals carried out plans to greatly expand critical care capacity. Primary intensive care unit (ICU) spaces were identified and upgraded as needed, and new ICU spaces were created in emergency departments, procedural areas, and other inpatient units. Patients were transferred between hospitals to reduce strain. Critical care staffing was supplemented by temporary recruits, volunteers, and Department of Defense medical personnel. Supplies needed to deliver critical care were monitored closely and replenished to prevent interruptions. An emergency department action team was formed to ensure that the experience of front-line providers was informing network-level decisions. The steps taken by NYC Health + Hospitals greatly expanded its capacity to provide critical care during an unprecedented surge of COVID-19 cases in NYC. These steps, along with lessons learned, could inform preparations for other health systems during a primary or secondary surge of cases.

Tuberculoma-Induced Seizures.

Seizures in human immunodeficiency virus (HIV) patients can be caused by a wide variety of opportunistic infections, and, especially in developing countries, tuberculosis (TB) should be high on the differential. In India, TB is the most common opportunistic infection in HIV and it can have several different central nervous system manifestations, including intracranial tuberculomas. In this case, an HIV patient presenting with new-onset seizure and fever was diagnosed with tuberculous meningitis and multiple intracranial tuberculomas. The patient received standard TB medications, steroids, and anticonvulsants in the emergency department and was admitted for further care.