Differential evolution of diabetic ketoacidosis in adults with pre-existent versus newly diagnosed type 1 and type 2 diabetes mellitus.

BACKGROUND: Diabetic ketoacidosis (DKA) was once known to be specific to type-1 diabetes-mellitus (T1D); however, many cases are now seen in patients with type-2 diabetes-mellitus (T2D). Little is known about how this etiology shift affects DKA's outcomes. METHODS: We studied consecutive index DKA admissions from January 2015 to March 2021. Descriptive analyses were performed based on pre-existing T1D and T2D (PT1D and PT2D, respectively) and newly diagnosed T1D and T2D (NT1D and NT2D, respectively). RESULTS: Of the 922 patients, 480 (52%) had T1D, of which 69% had PT1D and 31% NT1D, whereas 442 (48%) had T2D, of which 60% had PT2D and 40% NT2D. The mean age was highest in PT2D (47.6 ± 13.1 years) and lowest in PT1D (27.3 ± 0.5 years) (P < 0.001). Patients in all groups were predominantly male except in the PT1D group (55% females) (P < 0.001). Most patients were Arabic (76% in PT1D, 51.4% in NT1D, 46.6% in PT2D) except for NT2D, which mainly comprised Asians (53%) (P < 0.001). Patients with NT2D had the longest hospital length of stay (LOS) (6.8 ± 11.3 days) (P < 0.001), longest DKA duration (26.6 ± 21.1 h) (P < 0.001), and more intensive-care unit (ICU) admissions (31.2%) (P < 0.001). Patients with PT1D had the shortest LOS (2.5 ± 3.5 days) (P < 0.001), DKA duration (18.9 ± 4.2 h) (P < 0.001), and lowest ICU admissions (16.6%) (P < 0.001). CONCLUSIONS/INTERPRETATION: We presented the largest regional data on differences in DKA based on the type and duration of diabetes- mellitus (DM), showing that T2D is becoming an increasing cause of DKA, with worse clinical outcomes (especially newly diagnosed T2D) compared to T1D.

Integrated genomic surveillance enables tracing of person-to-person SARS-CoV-2 transmission chains during community transmission and reveals extensive onward transmission of travel-imported infections, Germany, June to July 2021.

BackgroundTracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective.AimWe demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters.MethodsGenomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021.ResultsCluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, sampled mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June; 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf.ConclusionIGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.