Deintensification in older patients with type 2 diabetes: a systematic review of approaches, rates and outcomes.

BACKGROUND: Guideline bodies recommend less strict glycaemic targets in older people with diabetes. It is uncertain whether the benefits of deintensification or de-prescribing, commonly employed by clinicians to achieve the less strict targets, outweighs the harms in these patients. We conducted a systematic review of published evidence, to assess deintensification approaches and rates and evaluate the harms and benefits of deintensification with antidiabetic medication and other therapies amongst older people (≥ 65 years) with type 2 diabetes with or without cardiometabolic conditions. METHODS: We identified relevant studies in a literature search of MEDLINE, Embase, Web of Science, and Cochrane databases to 30 October 2018. Data was extracted on baseline characteristics, details on deintensification, and outcomes and was synthesized using a narrative approach. RESULTS: Ten studies (observational cohorts and interventional studies) with data on 26,558 patients with comorbidities were eligible. Deintensification approaches included complete withdrawal, discontinuation, reducing dosage, conversion, or substitution of at least one medication, but majority of studies were based on complete withdrawal or discontinuation of antihyperglycaemic medication. Rates of deintensification approaches ranged from 13.4% to 75%. Majority of studies reported no deterioration in HbA1c levels, hypoglycaemic episodes falls or hospitalisation on deintensification. On adverse events and mortality, no significant differences were observed between the comparison groups in the majority of studies. CONCLUSION: Available but limited evidence suggests that the benefits of deintensification outweighs the harms in older people with type 2 diabetes with or without comorbidities. Given the heterogeneity of patients with diabetes, further research is warranted on which deintensification approaches are appropriate and beneficial for each specific patient population

Risk factors for severe outcomes in people with diabetes hospitalised for COVID-19: a cross-sectional database study

AIM: This study's objective was to assess the risk of severe in-hospital complications of patients admitted for COVID-19 and diabetes mellitus (DM). DESIGN: This was a cross-sectional study. SETTINGS: We used pseudonymised medical record data provided by six general hospitals from the HM Hospitales group in Spain. OUTCOME MEASURES: Multiple logistic regression analyses were used to identify variables associated with mortality and the composite of mortality or invasive mechanical ventilation (IMV) in the overall population, and stratified for the presence or absence of DM. Spline analysis was conducted on the entire population to investigate the relationship between glucose levels at admission and outcomes. RESULTS: Overall, 1621 individuals without DM and 448 with DM were identified in the database. Patients with DM were on average 5.1 years older than those without. The overall in-hospital mortality was 18.6% (N=301), and was higher among patients with DM than those without (26.3% vs 11.3%; p65 years, male sex and pre-existing chronic kidney disease. We observed a non-linear relationship between blood glucose levels at admission and risk of in-hospital mortality and death or IMV. The highest probability for each outcome (around 50%) was at random glucose of around 550 mg/dL (30.6 mmol/L), and the risks flattened above this value. CONCLUSION: The results confirm the high burden associated with DM in patients hospitalised with COVID-19 infection, particularly among men, the elderly and those with impaired kidney function. Moreover, hyperglycaemia on admission was strongly associated with poor outcomes, suggesting that personalised optimisation could help to improve outcome during the hospital stay

Evolving mortality and clinical outcomes of hospitalized subjects during successive COVID-19 waves in Catalonia, Spain.

BACKGROUND: The changes in shield strategies, treatments, emergence variants, and healthcare pathways might shift the profile and outcome of patients hospitalized with COVID-19 in successive waves of the outbreak. METHODS: We retrospectively analysed the characteristics and in-hospital outcomes of all patients admitted with COVID-19 in eight university hospitals of Catalonia (North-East Spain) between Feb 28, 2020 and Feb 28, 2021. Using a 7-joinpoint regression analysis, we split admissions into four waves. The main hospital outcomes included 30-day mortality and admission to intensive care unit (ICU). FINDINGS: The analysis included 17,027 subjects admitted during the first wave (6800; 39.9%), summer wave (1807; 10.6%), second wave (3804; 22.3%), and third wave (4616; 27.1%). The highest 30-day mortality rate was reported during the first wave (17%) and decreased afterwards, remaining stable at 13% in the second and third waves (overall 30% reduction); the lowest mortality was reported during the summer wave (8%, 50% reduction). ICU admission became progressively more frequent during successive waves. In Cox regression analysis, the main factors contributing to differences in 30-day mortality were the epidemic wave, followed by gender, age, diabetes, chronic kidney disease, and neoplasms. INTERPRETATION: Although in-hospital COVID-19 mortality remains high, it decreased substantially after the first wave and is highly dependent of patient's characteristics and ICU availability. Highest mortality reductions occurred during a wave characterized by younger individuals, an increasingly frequent scenario as vaccination campaigns progress. FUNDING: This work did not receive specific funding