Multimorbidity and adverse outcomes following emergency department attendance: population based cohort study.

Objectives: To describe the effect of multimorbidity on adverse patient centred outcomes in people attending emergency department. Design: Population based cohort study. Setting: Emergency departments in NHS Lothian in Scotland, from 1 January 2012 to 31 December 2019. Participants: Adults (≥18 years) attending emergency departments. Data sources: Linked data from emergency departments, hospital discharges, and cancer registries, and national mortality data. Main outcome measures: Multimorbidity was defined as at least two conditions from the Elixhauser comorbidity index. Multivariable logistic or linear regression was used to assess associations of multimorbidity with 30 day mortality (primary outcome), hospital admission, reattendance at the emergency department within seven days, and time spent in emergency department (secondary outcomes). Primary analysis was stratified by age (<65 v ≥65 years). Results: 451 291 people had 1 273 937 attendances to emergency departments during the study period. 43 504 (9.6%) had multimorbidity, and people with multimorbidity were older (median 73 v 43 years), more likely to arrive by emergency ambulance (57.8% v 23.7%), and more likely to be triaged as very urgent (23.5% v 9.2%) than people who do not have multimorbidity. After adjusting for other prognostic covariates, multimorbidity, compared with no multimorbidity, was associated with higher 30 day mortality (8.2% v 1.2%, adjusted odds ratio 1.81 (95% confidence interval (CI) 1.72 to 1.91)), higher rate of hospital admission (60.1% v 20.5%, 1.81 (1.76 to 1.86)), higher reattendance to an emergency department within seven days (7.8% v 3.5%, 1.41 (1.32 to 1.50)), and longer time spent in the department (adjusted coefficient 0.27 h (95% CI 0.26 to 0.27)). The size of associations between multimorbidity and all outcomes were larger in younger patients: for example, the adjusted odds ratio of 30 day mortality was 3.03 (95% CI 2.68 to 3.42) in people younger than 65 years versus 1.61 (95% CI 1.53 to 1.71) in those 65 years or older. Conclusions: Almost one in ten patients presenting to emergency department had multimorbidity using Elixhauser index conditions. Multimorbidity was strongly associated with adverse outcomes and these associations were stronger in younger people. The increasing prevalence of multimorbidity in the population is likely to exacerbate strain on emergency departments unless practice and policy evolve to meet the growing demand.

Automated Comprehensive CT Assessment of the Risk of Diabetes and Associated Cardiometabolic Conditions.

Background CT performed for various clinical indications has the potential to predict cardiometabolic diseases. However, the predictive ability of individual CT parameters remains underexplored. Purpose To evaluate the ability of automated CT-derived markers to predict diabetes and associated cardiometabolic comorbidities. Materials and Methods This retrospective study included Korean adults (age ≥ 25 years) who underwent health screening with fluorine 18 fluorodeoxyglucose PET/CT between January 2012 and December 2015. Fully automated CT markers included visceral and subcutaneous fat, muscle, bone density, liver fat, all normalized to height (in meters squared), and aortic calcification. Predictive performance was assessed with area under the receiver operating characteristic curve (AUC) and Harrell C-index in the cross-sectional and survival analyses, respectively. Results The cross-sectional and cohort analyses included 32166 (mean age, 45 years ± 6 [SD], 28833 men) and 27 298 adults (mean age, 44 years ± 5 [SD], 24 820 men), respectively. Diabetes prevalence and incidence was 6% at baseline and 9% during the 7.3-year median follow-up, respectively. Visceral fat index showed the highest predictive performance for prevalent and incident diabetes, yielding AUC of 0.70 (95% CI: 0.68, 0.71) for men and 0.82 (95% CI: 0.78, 0.85) for women and C-index of 0.68 (95% CI: 0.67, 0.69) for men and 0.82 (95% CI: 0.77, 0.86) for women, respectively. Combining visceral fat, muscle area, liver fat fraction, and aortic calcification improved predictive performance, yielding C-indexes of 0.69 (95% CI: 0.68, 0.71) for men and 0.83 (95% CI: 0.78, 0.87) for women. The AUC for visceral fat index in identifying metabolic syndrome was 0.81 (95% CI: 0.80, 0.81) for men and 0.90 (95% CI: 0.88, 0.91) for women. CT-derived markers also identified US-diagnosed fatty liver, coronary artery calcium scores greater than 100, sarcopenia, and osteoporosis, with AUCs ranging from 0.80 to 0.95. Conclusion Automated multiorgan CT analysis identified individuals at high risk of diabetes and other cardiometabolic comorbidities. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Pickhardt in this issue.

Antidepressant and antipsychotic prescribing in patients with type 2 diabetes in Scotland: A time-trend analysis from 2004 to 2021.

AIMS: Prescribing of antidepressant and antipsychotic drugs in general populations has increased in the United Kingdom, but prescribing trends in people with type 2 diabetes (T2D) have not previously been investigated. The aim of this study was to describe time trends in annual prevalence of antidepressant and antipsychotic drug prescribing in adult patients with T2D. METHODS: We conducted repeated annual cross-sectional analysesof a population-based diabetes registry with 99% coverage, derived from primary and secondary care data in Scotland, from 2004 to 2021. For each cross-sectional calendar year time period, we calculated the prevalence of antidepressant and antipsychotic drug prescribing, overall and by sociodemographic characteristics and drug subtype. RESULTS: The number of patients with a T2D diagnosis in Scotland increased from 161 915 in 2004 to 309 288 in 2021. Prevalence of antidepressant and antipsychotic prescribing in patients with T2D increased markedly between 2004 and 2021 (from 20.0 per 100 person-years to 33.3 per 100 person-years and from 2.8 per 100 person-years to 4.7 per 100 person-years, respectively). We observed this pattern for all drug subtypes except for first-generation antipsychotics, prescribing of which remained largely stable. The degree of increase, as well as the overall prevalence of prescribing, differed by age, sex, socioeconomic status and subtype of drug class. CONCLUSIONS: There has been a marked increase in the prevalence of antidepressant and antipsychotic prescribing in patients with T2D in Scotland. Further research should identify the reasons for this increase, including indication for use and the extent to which this reflects increases in incident prescribing rather than increased duration.

Estimation of the direct health and indirect societal costs of diabetes in the UK using a cost of illness model.

AIMS: The direct cost of diabetes to the UK health system was estimated at around £10 billion in 2012. This analysis updates that estimate using more recent and accurate data sources. METHODS: A pragmatic review of relevant data sources for UK nations was conducted, including population-level data sets and published literature, to generate estimates of costs separately for Type 1, Type 2 and gestational diabetes. A comprehensive cost framework, developed in collaboration with experts, was used to create a population-based cost of illness model. The key driver of the analysis was prevalence of diabetes and its complications. Estimates were made of the excess costs of diagnosis, treatment and diabetes-related complications compared with the general UK population. Estimates of the indirect costs of diabetes focused on productivity losses due to absenteeism and premature mortality. RESULTS: The direct costs of diabetes in 2021/22 for the UK were estimated at £10.7 billion, of which just over 40% related to diagnosis and treatment, with the rest relating to the excess costs of complications. Indirect costs were estimated at £3.3 billion. CONCLUSIONS: Diabetes remains a considerable cost burden in the UK, and the majority of those costs are still spent on potentially preventable complications. Although rates of some complications are reducing, prevalence continues to increase and effective approaches to primary and secondary prevention continue to be needed. Improvements in data capture, data quality and reporting, and further research on the human and financial implications of increasing incidence of Type 2 diabetes in younger people are recommended.

Glycemic status, insulin resistance, and mortality from lung cancer among individuals with and without diabetes.

BACKGROUND: The effects of glycemic status and insulin resistance on lung cancer remain unclear. We investigated the associations between both glycemic status and insulin resistance, and lung cancer mortality, in a young and middle-aged population with and without diabetes. METHODS: This cohort study involved individuals who participated in routine health examinations. Lung cancer mortality was identified using national death records. Cox proportional hazards models were used to calculate hazard ratios (HRs) with 95% CIs for lung cancer mortality risk. RESULTS: Among 666,888 individuals (mean age 39.9 ± 10.9 years) followed for 8.3 years (interquartile range, 4.6-12.7), 602 lung cancer deaths occurred. Among individuals without diabetes, the multivariable-adjusted HRs (95% CI) for lung cancer mortality comparing hemoglobin A1c categories (5.7-5.9, 6.0-6.4, and ≥ 6.5% or 39-41, 42-46, and ≥ 48 mmol/mol, respectively) with the reference (< 5.7% or < 39 mmol/mol) were 1.39 (1.13-1.71), 1.72 (1.33-2.20), and 2.22 (1.56-3.17), respectively. Lung cancer mortality was associated with fasting blood glucose categories in a dose-response manner (P for trend = 0.001) and with previously diagnosed diabetes. Insulin resistance (HOMA-IR ≥ 2.5) in individuals without diabetes was also associated with lung cancer mortality (multivariable-adjusted HR, 1.41; 95% CI, 1.13-1.75). These associations remained after adjusting for changing status in glucose, hemoglobin A1c, insulin resistance, smoking status, and other confounders during follow-up as time-varying covariates. CONCLUSIONS: Glycemic status within both diabetes and prediabetes ranges and insulin resistance were independently associated with an increased risk of lung cancer mortality.

Impact of COVID-19 and Non-COVID-19 Hospitalized Pneumonia on Longer-Term Cardiovascular Mortality in People With Type 2 Diabetes: A Nationwide Prospective Cohort Study From Scotland.

OBJECTIVE: In this study we examine whether hospitalized coronavirus disease 2019 (COVID-19) pneumonia increases long-term cardiovascular mortality more than other hospitalized pneumonias in people with type 2 diabetes and aim to quantify the relative cardiovascular disease (CVD) mortality risks associated with COVID-19 versus non-COVID-19 pneumonia. RESEARCH DESIGN AND METHODS: With use of the SCI-Diabetes register, two cohorts were identified: individuals with type 2 diabetes in 2016 and at the 2020 pandemic onset. Hospital and death records were linked for determination of pneumonia exposure and CVD deaths. Poisson regression estimated rate ratios (RRs) for CVD death associated with both pneumonia types, with adjustment for confounders. Median follow-up durations were 1,461 days (2016 cohort) and 700 days (2020 cohort). RESULTS: The adjusted RR for CVD death following non-COVID-19 pneumonia was 5.51 (95% CI 5.31-5.71) prepandemic and 7.3 (6.86-7.76) during the pandemic. For COVID-19 pneumonia, the RR was 9.13 (8.55-9.75). Beyond 30 days post pneumonia, the RRs converged, to 4.24 (3.90-4.60) for non-COVID-19 and 3.35 (3.00-3.74) for COVID-19 pneumonia, consistent even with exclusion of prior CVD cases. CONCLUSIONS: Hospitalized pneumonia, irrespective of causal agent, marks an increased risk for CVD death immediately and over the long-term. COVID-19 pneumonia poses a higher CVD death risk than other pneumonias in the short-term, but this distinction diminishes over time. These insights underscore the need for including pneumonia in CVD risk assessments, with particular attention to the acute impact of COVID-19 pneumonia.

Diabetes and risk of hospitalisation due to infection in northeastern Thailand: Retrospective cohort study using population-based healthcare service data.

BACKGROUND: Population-based studies describing the association between diabetes and increased risk of infection have largely been based in high-income countries. There is limited information describing the burden of infectious disease attributable to diabetes in low and middle-income countries. This study aimed to describe the burden and risk of infectious disease hospitalisation in people with diabetes compared to those without diabetes in northeastern Thailand. METHODS: In a retrospective cohort study using electronic health record data for 2012-2018 for 3.8 million people aged ≥20 years in northeastern Thailand, hospitalisation rates for any infectious diseases (ICD-10 codes A00-B99) were estimated and negative binomial regression used to estimate rate ratios (RR) for the association between diabetes and infectious disease hospitalisation adjusted for age, sex and area of residence. RESULTS: In this study, 164,177 people had a diagnosis of diabetes mellitus at any point over the study period. Infectious disease hospitalisation rates per 1000 person-years (95%CI) were 71.8 (70.9, 72.8), 27.7 (27.1, 28.3) and 7.5 (7.5, 7.5) for people with prevalent diabetes, incident diabetes and those without diabetes respectively. Diabetes was associated with a 4.6-fold higher risk of infectious disease hospitalisation (RR (95% CI) 4.59 (4.52, 4.66)). RRs for infectious disease hospitalisation were 3.38 (3.29, 3.47) for people with diabetes managed by lifestyle alone and 5.29 (5.20, 5.39) for people receiving prescriptions for diabetes drugs. CONCLUSIONS: In this Thai population, diabetes was associated with substantially increased risk of hospitalisation due to infectious diseases and people with diabetes who were on pharmacological treatment had a higher risk than those receiving lifestyle modification advice alone.

Ethnic disparities in quality of diabetes care in Scotland: A national cohort study.

AIMS: The aim of this study is to compare quality of diabetes care in people with type 2 diabetes by ethnicity, in Scotland. METHODS: Using a linked national diabetes registry, we included 162,122 people newly diagnosed with type 2 diabetes between 2009 and 2018. We compared receipt of nine guideline indicated processes of care in the first-year post-diabetes diagnosis using logistic regression, comparing eight ethnicity groups to the White group. We compared annual receipt of HbA1c and eye screening during the entire follow-up using generalised linear mixed effects. All analyses adjusted for confounders. RESULTS: Receipt of diabetes care was lower in other ethnic groups compared to White people in the first-year post-diagnosis. Differences were most pronounced for people in the: African, Caribbean or Black; Indian; and other ethnicity groups for almost all processes of care. For example, compared to White people, odds of HbA1c monitoring were: 44% lower in African, Caribbean or Black people (OR 0.56 [95% CI 0.48, 0.66]); 47% lower in Indian people (OR 0.53 [95% CI 0.47, 0.61]); and 50% lower in people in the other ethnicity group (OR 0.50 [95% CI 0.46, 0.58]). Odds of receipt of eye screening were 30%-40% lower in most ethnic groups compared to the White group. During median 5 year follow-up, differences in HbA1c monitoring and eye screening largely persisted, but attenuated slightly for the former. CONCLUSIONS: There are marked ethnic disparities in routine diabetes care in Scotland in the short- and medium-term following diabetes diagnosis. Further investigation is needed to establish and effectively address the underlying reasons.

Participant characteristics and exclusion from phase 3/4 industry funded trials of chronic medical conditions: meta-analysis of individual participant level data.

Objectives: To assess whether age, sex, comorbidity count, and race and ethnic group are associated with the likelihood of trial participants not being enrolled in a trial for any reason (ie, screen failure). Design: Bayesian meta-analysis of individual participant level data. Setting: Industry funded phase 3/4 trials of chronic medical conditions. Participants: Participants were identified using individual participant level data to be in either the enrolled group or screen failure group. Data were available for 52 trials involving 72 178 screened individuals of whom 24 733 (34%) were excluded from the trial at the screening stage. Main outcome measures: For each trial, logistic regression models were constructed to assess likelihood of screen failure in people who had been invited to screening, and were regressed on age (per 10 year increment), sex (male v female), comorbidity count (per one additional comorbidity), and race or ethnic group. Trial level analyses were combined in Bayesian hierarchical models with pooling across condition. Results: In age and sex adjusted models across all trials, neither age nor sex was associated with increased odds of screen failure, although weak associations were detected after additionally adjusting for comorbidity (odds ratio of age, per 10 year increment was 1.02 (95% credibility interval 1.01 to 1.04) and male sex (0.95 (0.91 to 1.00)). Comorbidity count was weakly associated with screen failure, but in an unexpected direction (0.97 per additional comorbidity (0.94 to 1.00), adjusted for age and sex). People who self-reported as black seemed to be slightly more likely to fail screening than people reporting as white (1.04 (0.99 to 1.09)); a weak effect that seemed to persist after adjustment for age, sex, and comorbidity count (1.05 (0.98 to 1.12)). The between-trial heterogeneity was generally low, evidence of heterogeneity by sex was noted across conditions (variation in odds ratios on log scale of 0.01-0.13). Conclusions: Although the conclusions are limited by uncertainty about the completeness or accuracy of data collection among participants who were not randomised, we identified mostly weak associations with an increased likelihood of screen failure for age, sex, comorbidity count, and black race or ethnic group. Proportionate increases in screening these underserved populations may improve representation in trials. Trial registration number: PROSPERO CRD42018048202.

Trends in cause-specific mortality among people with type 2 and type 1 diabetes from 2002 to 2019: a Danish population-based study.

Background: Despite advances in primary and secondary prevention of cardiovascular disease, excess mortality persists within the diabetes population. This study explores the components of this excess mortality and their interaction with sex. Methods: Using Danish registries (2002-2019), we identified residents aged 18-99 years, their diabetes status, and recorded causes of death. Applying Lexis-based methods, we computed age-standardized mortality rates (asMRs), mortality relative risks (asMRRs), and log-linear trends for cause-specific mortality. Findings: From 2002 to 2019, 958,278 individuals died in Denmark (T2D: 148,620; T1D: 7830) during 84.4 M person-years. During the study period, overall asMRs declined, driven by reducing cardiovascular mortality, notably in men with T2D. Conversely, cancer mortality remained high, making cancer the leading cause of death in individuals with T2D. Individuals with T2D faced an elevated mortality risk from nearly all cancer types, ranging from 9% to 257% compared to their non-diabetic counterparts. Notably, obesity-related cancers exhibited the highest relative risks: liver cancer (Men: asMRR 3.58 (3.28; 3.91); Women: asMRR 2.49 (2.14; 2.89)), pancreatic cancer (Men: asMRR 3.50 (3.25; 3.77); Women: asMRR 3.57 (3.31; 3.85)), and kidney cancer (Men: asMRR 2.10 (1.84; 2.40); Women: asMRR 2.31 (1.92; 2.79)). In men with type 2 diabetes, excess mortality remained stable, except for dementia. In women, diabetes-related excess mortality increased by 6-17% per decade across all causes of death, except cardiovascular disease. Interpretation: In the last decade, cancer has emerged as the leading cause of death among individuals with T2D in Denmark, emphasizing the need for diabetes management strategies incorporating cancer prevention. A sex-specific approach is crucial to address persistently higher relative mortality in women with diabetes. Funding: Supported by Steno Diabetes Center Aarhus, which is partially funded by an unrestricted donation from the Novo Nordisk Foundation, and by The Danish Diabetes Academy.

Trends in Incidence of Hospitalization for Hypoglycemia and Diabetic Ketoacidosis in Individuals With Type 1 or Type 2 Diabetes With and Without Severe Mental Illness in Denmark From 1996 to 2020: A Nationwide Study.

OBJECTIVE: To examine trends in incidence of acute diabetes complications in individuals with type 1 or type 2 diabetes with and without severe mental illness (SMI) in Denmark by age and calendar year. RESEARCH DESIGN AND METHODS: We conducted a cohort study using nationwide registers from 1996 to 2020 to identify individuals with diabetes, ascertain SMI status (namely, schizophrenia, bipolar disorder, or major depression) and identify the outcomes: hospitalization for hypoglycemia and diabetic ketoacidosis (DKA). We used Poisson regression to estimate incidence rates (IRs) and incidence rate ratios (IRRs) of recurrent hypoglycemia and DKA events by SMI, age, and calendar year, accounting for sex, diabetes duration, education, and country of origin. RESULTS: Among 433,609 individuals with diabetes, 8% had SMI. Risk of (first and subsequent) hypoglycemia events was higher for individuals with SMI than for those without SMI (for first hypoglycemia event, IRR: type 1 diabetes, 1.77 [95% CI 1.56-2.00]; type 2 diabetes, 1.64 [95% CI 1.55-1.74]). Individuals with schizophrenia were particularly at risk for recurrent hypoglycemia events. The risk of first DKA event was higher in individuals with SMI (for first DKA event, IRR: type 1 diabetes, 1.78 [95% CI 1.50-2.11]; type 2 diabetes, 1.85 [95% CI 1.64-2.09]). Except for DKA in the type 2 diabetes group, IR differences between individuals with and without SMI were highest in younger individuals (<50 years old) but stable across the calendar year. CONCLUSIONS: SMI is an important risk factor for acute diabetes complication and effective prevention is needed in this population, especially among the younger population and those with schizophrenia.