Ethnic disparities in mortality among overweight or obese adults with newly diagnosed type 2 diabetes: a population-based cohort study.

PURPOSE: Ethnic variation in risk of type 2 diabetes is well established, but its impact on mortality is less well understood. This study investigated the risk of all-cause and cardiovascular mortality associated with newly diagnosed type 2 diabetes in White, Asian and Black adults who were overweight or obese. METHODS: This population-based cohort study used primary care records from the UK Clinical Practice Research Datalink, linked with secondary care and death registry records. A total of 193,528 obese or overweight adults (BMI of 25 or greater), with ethnicity records and no pre-existing type 2 diabetes were identified between 01 January 1995 and 20 April 2018. Multivariable Cox proportional hazards regression estimated hazards ratios (HR) for incident type 2 diabetes in different ethnic groups. Adjusted hazards ratios for all-cause and cardiovascular mortality were determined in individuals with newly diagnosed type 2 diabetes. RESULTS: During follow-up (median 9.8 years), the overall incidence rate of type 2 diabetes (per 1,000 person-years) was 20.10 (95% CI 19.90-20.30). Compared to Whites, type 2 diabetes risk was 2.2-fold higher in Asians (HR 2.19 (2.07-2.32)) and 30% higher in Blacks (HR 1.34 (1.23-1.46)). In individuals with newly diagnosed type 2 diabetes, the rates (per 1,000 person-years) of all-cause mortality and cardiovascular mortality were 24.34 (23.73-24.92) and 4.78 (4.51-5.06), respectively. Adjusted hazards ratios for mortality were significantly lower in Asians (HR 0.70 (0.55-0.90)) and Blacks (HR 0.71 (0.51-0.98)) compared to Whites, and these differences in mortality risk were not explained by differences in severity of hyperglycaemia. CONCLUSIONS/INTERPRETATION: Type 2 diabetes risk in overweight and obese adults is greater in Asian and Black compared to White ethnic populations, but mortality is significantly higher in the latter. Greater attention to optimising screening, disease and risk management appropriate to all communities with type 2 diabetes is needed.

Data-driven machine-learning analysis of potential embolic sources in embolic stroke of undetermined source.

BACKGROUND AND PURPOSE: Hierarchical clustering, a common 'unsupervised' machine-learning algorithm, is advantageous for exploring potential underlying aetiology in particularly heterogeneous diseases. We investigated potential embolic sources in embolic stroke of undetermined source (ESUS) using a data-driven machine-learning method, and explored variation in stroke recurrence between clusters. METHODS: We used a hierarchical k-means clustering algorithm on patients' baseline data, which assigned each individual into a unique clustering group, using a minimum-variance method to calculate the similarity between ESUS patients based on all baseline features. Potential embolic sources were categorised into atrial cardiopathy, atrial fibrillation, arterial disease, left ventricular disease, cardiac valvulopathy, patent foramen ovale (PFO) and cancer. RESULTS: Among 800 consecutive ESUS patients (43.3% women, median age 67 years), the optimal number of clusters was four. Left ventricular disease was most prevalent in cluster 1 (present in all patients) and perfectly associated with cluster 1. PFO was most prevalent in cluster 2 (38.9% of patients) and associated significantly with increased likelihood of cluster 2 [adjusted odds ratio: 2.69, 95% confidence interval (CI): 1.64-4.41]. Arterial disease was most prevalent in cluster 3 (57.7%) and associated with increased likelihood of cluster 3 (adjusted odds ratio: 2.21, 95% CI: 1.43-3.13). Atrial cardiopathy was most prevalent in cluster 4 (100%) and perfectly associated with cluster 4. Cluster 3 was the largest cluster involving 53.7% of patients. Atrial fibrillation was not significantly associated with any cluster. CONCLUSIONS: This data-driven machine-learning analysis identified four clusters of ESUS that were strongly associated with arterial disease, atrial cardiopathy, PFO and left ventricular disease, respectively. More than half of the patients were assigned to the cluster associated with arterial disease.

A systematic review showing the lack of diagnostic criteria and tools developed for lower-limb cellulitis.

BACKGROUND: Cellulitis can be a difficult diagnosis to make. Furthermore, 31% of patients admitted from the emergency department with suspected lower-limb cellulitis have been misdiagnosed, with incorrect treatment potentially resulting in avoidable hospital admission and the prescription of unnecessary antibiotics. OBJECTIVES: We sought to identify diagnostic criteria or tools that have been developed for lower-limb cellulitis. METHODS: We conducted a systematic review using Ovid MEDLINE and Embase databases in May 2018, with the aim of describing diagnostic criteria and tools developed for lower-limb cellulitis, and we assessed the quality of the studies identified using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. We included all types of study that described diagnostic criteria or tools. RESULTS: Eight observational studies were included. Five studies examined biochemical markers, two studies assessed imaging and one study developed a diagnostic decision model. All eight studies were considered to have a high risk for bias in at least one domain. The quantity and quality of available data was low and results could not be pooled owing to the heterogeneity of the findings. CONCLUSIONS: There is a lack of high-quality publications describing criteria or tools for diagnosing lower-limb cellulitis. Future studies using prospective designs, validated in both primary and secondary care settings, are needed. What's already known about this topic? Diagnosing lower-limb cellulitis on first presentation is challenging. Approximately one in three patients admitted from the emergency department with suspected lower-limb cellulitis do not have cellulitis and are given another diagnosis on discharge. Consequently, this results in potentially avoidable hospital admissions and the prescription of unnecessary antibiotics. There are no diagnostic criteria available for lower-limb cellulitis in the U.K. What does this study add? This systematic review has identified a key research gap in the diagnosis of lower-limb cellulitis. There is a current lack of robustly developed and validated diagnostic criteria or tools for use in clinical practice.