Infection Rates and Impact of Glucose Lowering Medications on the Clinical Course of COVID-19 in People with Type 2 Diabetes: A Retrospective Observational Study.

Purpose: Diabetes is a risk factor for COVID-19 severity, but the role played by glucose lowering medications (GLM) is still unclear. The aim of this study was to assess infection rates and outcomes of COVID-19 (hospitalization and mortality) in adults with diabetes assisted by the Local Health Unit of Padua (North-East Italy) according to the ongoing GLM. Patients and Methods: People with diabetes were identified using administrative claims, while those with SARS-CoV-2 infection were detected by cross referencing with the local COVID-19 surveillance registry. A multivariate logistic regression model was used to verify the association between GLM classes and the outcome. Results: SARS-CoV-2 infection rates were marginally but significantly higher in individuals with diabetes as compared to those without diabetes (RR 1.04, p = 0.043), though such relative 4% increase may be irrelevant from a clinical and epidemiological perspective. 1923 individuals with GLM-treated diabetes were diagnosed with COVID-19; 456 patients were hospitalized and 167 died. Those treated with insulin had a significantly higher risk of hospitalizations for COVID-19 (OR 1.48 p < 0.01) as were those treated with sulphonylureas/glinides (OR 1.34, p = 0.02). Insulin use was also significantly associated with higher mortality (OR 1.90, p < 0.01). Use of metformin was significantly associated with lower death rates (OR 0.62, p = 0.02). The association of other GLM classes with the outcome was not significant. Conclusion: Diabetes does not appear to modify the risk of SARS-CoV-2 infection in a clinically meaningful way, but strongly increases the rates of hospitalization and death. Insulin use was associated with worse outcomes, whereas metformin use was associated with lower mortality.

Infection Rates and Impact of Glucose Lowering Medications on the Clinical Course of COVID-19 in People with Type 2 Diabetes: A Retrospective Observational Study

Purpose Diabetes is a risk factor for COVID-19 severity, but the role played by glucose lowering medications (GLM) is still unclear. The aim of this study was to assess infection rates and outcomes of COVID-19 (hospitalization and mortality) in adults with diabetes assisted by the Local Health Unit of Padua (North-East Italy) according to the ongoing GLM. Patients and Methods People with diabetes were identified using administrative claims, while those with SARS-CoV-2 infection were detected by cross referencing with the local COVID-19 surveillance registry. A multivariate logistic regression model was used to verify the association between GLM classes and the outcome. Results SARS-CoV-2 infection rates were marginally but significantly higher in individuals with diabetes as compared to those without diabetes (RR 1.04, p = 0.043), though such relative 4% increase may be irrelevant from a clinical and epidemiological perspective. 1923 individuals with GLM-treated diabetes were diagnosed with COVID-19;456 patients were hospitalized and 167 died. Those treated with insulin had a significantly higher risk of hospitalizations for COVID-19 (OR 1.48 p < 0.01) as were those treated with sulphonylureas/glinides (OR 1.34, p = 0.02). Insulin use was also significantly associated with higher mortality (OR 1.90, p < 0.01). Use of metformin was significantly associated with lower death rates (OR 0.62, p = 0.02). The association of other GLM classes with the outcome was not significant. Conclusion Diabetes does not appear to modify the risk of SARS-CoV-2 infection in a clinically meaningful way, but strongly increases the rates of hospitalization and death. Insulin use was associated with worse outcomes, whereas metformin use was associated with lower mortality.

Time-series analysis of multidimensional clinical-laboratory data by dynamic Bayesian networks reveals trajectories of COVID-19 outcomes.

BACKGROUND AND OBJECTIVE: COVID-19 severity spans an entire clinical spectrum from asymptomatic to fatal. Most patients who require in-hospital care are admitted to non-intensive wards, but their clinical conditions can deteriorate suddenly and some eventually die. Clinical data from patients' case series have identified pre-hospital and in-hospital risk factors for adverse COVID-19 outcomes. However, most prior studies used static variables or dynamic changes of a few selected variables of interest. In this study, we aimed at integrating the analysis of time-varying multidimensional clinical-laboratory data to describe the pathways leading to COVID-19 outcomes among patients initially hospitalised in a non-intensive care setting. METHODS: We collected the longitudinal retrospective data of 394 patients admitted to non-intensive care units at the University Hospital of Padova (Padova, Italy) due to COVID-19. We trained a dynamic Bayesian network (DBN) to encode the conditional probability relationships over time between death and all available demographics, pre-existing conditions, and clinical laboratory variables. We applied resampling, dynamic time warping, and prototyping to describe the typical trajectories of patients who died vs. those who survived. RESULTS: The DBN revealed that the trajectory linking demographics and pre-existing clinical conditions to death passed directly through kidney dysfunction or, more indirectly, through cardiac damage. As expected, admittance to the intensive care unit was linked to markers of respiratory function. Notably, death was linked to elevation in procalcitonin and D-dimer levels. Death was associated with persistently high levels of procalcitonin from admission and throughout the hospital stay, likely reflecting bacterial superinfection. A sudden raise in D-dimer levels 3-6 days after admission was also associated with subsequent death, possibly reflecting a worsening thrombotic microangiopathy. CONCLUSIONS: This innovative application of DBNs and prototyping to integrated data analysis enables visualising the patient's trajectories to COVID-19 outcomes and may instruct timely and appropriate clinical decisions.

Hematopoietic progenitor cell liabilities and alarmins S100A8/A9-related inflammaging associate with frailty and predict poor cardiovascular outcomes in older adults.

Frailty affects the physical, cognitive, and social domains exposing older adults to an increased risk of cardiovascular disease and death. The mechanisms linking frailty and cardiovascular outcomes are mostly unknown. Here, we studied the association of abundance (flow cytometry) and gene expression profile (RNAseq) of stem/progenitor cells (HSPCs) and molecular markers of inflammaging (ELISA) with the cardiorespiratory phenotype and prospective adverse events of individuals classified according to levels of frailty. Two cohorts of older adults were enrolled in the study. In a cohort of pre-frail 35 individuals (average age: 75 years), a physical frailty score above the median identified subjects with initial alterations in cardiorespiratory function. RNA sequencing revealed S100A8/A9 upregulation in HSPCs from the bone marrow (>10-fold) and peripheral blood (>200-fold) of individuals with greater physical frailty. Moreover higher frailty was associated with increased alarmins S100A8/A9 and inflammatory cytokines in peripheral blood. We then studied a cohort of 104 more frail individuals (average age: 81 years) with multidomain health deficits. Reduced levels of circulating HSPCs and increased S100A8/A9 concentrations were independently associated with the frailty index. Remarkably, low HSPCs and high S100A8/A9 simultaneously predicted major adverse cardiovascular events at 1-year follow-up after adjustment for age and frailty index. In conclusion, inflammaging characterized by alarmin and pro-inflammatory cytokines in pre-frail individuals is mirrored by the pauperization of HSPCs in frail older people with comorbidities. S100A8/A9 is upregulated within HSPCs, identifying a phenotype that associates with poor cardiovascular outcomes.

In hospital risk factors for acute kidney injury and its burden in patients with Sars-Cov-2 infection: a longitudinal multinational study.

Acute kidney injury (AKI) is associated with increased mortality in most critical settings. However, it is unclear whether its mild form (i.e. AKI stage 1) is associated with increased mortality also in non-critical settings. Here we conducted an international study in patients hospitalized with SARS-CoV-2 infection aiming 1. to estimate the incidence of AKI at each stage and its impact on mortality 2. to identify AKI risk factors at admission (susceptibility) and during hospitalization (exposures) and factors contributing to AKI-associated mortality. We included 939 patients from medical departments in Moscow (Russia) and Padua (Italy). In-hospital AKI onset was identified in 140 (14.9%) patients, mainly with stage 1 (65%). Mortality was remarkably higher in patients with AKI compared to those without AKI (55 [39.3%] vs. 34 [4.3%], respectively). Such association remained significant after adjustment for other clinical conditions at admission (relative risk [RR] 5.6; CI 3.5- 8.8) or restricting to AKI stage 1 (RR 3.2; CI 1.8-5.5) or to subjects with AKI onset preceding deterioration of clinical conditions. After hospital admission, worsening of hypoxic damage, inflammation, hyperglycemia, and coagulopathy were identified as hospital-acquired risk factors predicting AKI onset. Following AKI onset, the AKI-associated worsening of respiratory function was identified as the main contributor to AKI-induced increase in mortality risk. In conclusion, AKI is a common complication of Sars-CoV2 infection in non-intensive care settings where it markedly increases mortality risk also at stage 1. The identification of hospital-acquired risk factors and exposures might help prevention of AKI onset and of its complications.

Hyperglycemia, Reduced Hematopoietic Stem Cells, and Outcome of COVID-19.

Admission hyperglycemia has emerged worldwide as a predictor of poor coronavirus disease 2019 (COVID-19) outcome. Hyperglycemia leads to a defect in circulating hematopoietic stem/progenitor cells (HSPCs), which, in turn, predicts diabetic complications. Here, we explored whether reduced HSPCs mediated at least part of the prognostic effect of hyperglycemia on COVID-19 outcome. We found that patients with COVID-19 (n = 100) hospitalized in a nonintensive setting displayed dramatically (50-60%) reduced levels of HSPCs measured by flow cytometry as CD34+, CD34+CD45dim, or CD34+CD133+ cells, compared with control subjects (n = 595). This finding was highly significant (all P < 10-10) after multivariable adjustment, or manual 1:1 patient match, or propensity score matching. Admission hyperglycemia (≥7.0 mmol/L) was present in 45% of patients, was associated with a significant further ∼30% HSPCs reduction, and predicted a 2.6-fold increased risk of the primary outcome of adverse COVID-19 course (admittance to the intensive care unit or death). Low HSPCs were also associated with advanced age, higher peak C-reactive protein, and neutrophil-to-lymphocyte ratio. Independently from confounders, 1 SD lower CD34+ HSPCs was associated with a more than threefold higher risk of adverse outcome. Upon formal analysis, reduction of HSPCs was a significant mediator of the admission hyperglycemia on COVID-19 outcome, being responsible for 28% of its prognostic effect.

Managing diabetes in diabetic patients with COVID: where do we start from?

AIMS: COVID-19 has and still is sweeping away the national health systems worldwide. In this review, we sought to determine the evidence base proofs on the antidiabetic treatment capable to reduce the risk of COVID-19-related mortality. METHODS: We have performed a systematic search of published articles using PubMed, and EMBASE from March 2020 to March 31st, 2021. We excluded editorials, commentary, letters to the editor, reviews, and studies that did not have mortality as an outcome. For metformin and insulin only, we performed a meta-analysis using Cochrane RevMan 5.2. RESULTS: Among antidiabetic drugs, metformin was the only drug associated with a reduced risk of mortality. Conversely, insulin appears associated with an increased risk. The other classes of drugs were neutral. CONCLUSIONS: The totality of articles reports retrospective data strongly affected by "channeling bias" so that most of the existing results on each class of drugs are driven by the phenotype of patients likely to receive that specific drug by prescription.

Lung Ultrasound Patterns and Clinical-Laboratory Correlates during COVID-19 Pneumonia: A Retrospective Study from North East Italy.

BACKGROUND AND AIM: Lung ultrasound (LUS) is a convenient imaging modality in the setting of coronavirus disease-19 (COVID-19) because it is easily available, can be performed bedside and repeated over time. We herein examined LUS patterns in relation to disease severity and disease stage among patients with COVID-19 pneumonia. METHODS: We performed a retrospective case series analysis of patients with confirmed SARS-CoV-2 infection who were admitted to the hospital because of pneumonia. We recorded history, clinical parameters and medications. LUS was performed and scored in a standardized fashion by experienced operators, with evaluation of up to 12 lung fields, reporting especially on B-lines and consolidations. RESULTS: We included 96 patients, 58.3% men, with a mean age of 65.9 years. Patients with a high-risk quick COVID-19 severity index (qCSI) were older and had worse outcomes, especially for the need for high-flow oxygen. B-lines and consolidations were located mainly in the lower posterior lung fields. LUS patterns for B-lines and consolidations were significantly worse in all lung fields among patients with high versus low qCSI. B-lines and consolidations were worse in the intermediate disease stage, from day 7 to 13 after onset of symptoms. While consolidations correlated more with inflammatory biomarkers, B-lines correlated more with end-organ damage, including extrapulmonary involvement. CONCLUSIONS: LUS patterns provide a comprehensive evaluation of patients with COVID-19 pneumonia that correlated with severity and dynamically reflect disease stage. LUS patterns may reflect different pathophysiological processes related to inflammation or tissue damage; consolidations may represent a more specific sign of localized disease, whereas B-lines seem to be also dependent upon generalized illness due to SARS-CoV-2 infection.

Response to a massive SARS-CoV-2 infection in a nursing home transformed into a caring center.

BACKGROUND: The best policy to follow when nursing homes are massively hit by SARS-CoV2 is unclear. AIM: To describe COVID-19 containment in a nursing home transformed into a caring center. METHODS: Physicians and nurses were recruited. The facility was reorganized and connected with the laboratory of the reference hospital. Ultrasound was used to diagnose pneumonia. Patients needing intensive care were transferred to the reference hospital. Hydroxychloroquine/azithromycin/enoxaparin were used initially, while amiodarone/enoxaparin were used at a later phase. Under both regimens, methylprednisolone was added for severe cases. Prophylaxis was done with hydroxychloroquine initially and then with amiodarone. PERIOD COVERED: March 22-July 31, 2020. RESULTS: The facility was reorganized in two days. Ninety-two guests of the 121 (76%) and 25 personnel of 118 (21.1%) became swab test positive. Seven swab test negative patients who developed symptoms were considered to have COVID-19. Twenty-seven patients died, 23 swab test positive, 5 of whom after full recovery. Four patients needing intensive care were transferred (3 died). Mortality, peaking in April 2020, was correlated with symptoms, comorbidities, dyspnea, fatigue, stupor/coma, high neutrophil to lymphocyte ratio, C-reactive protein, interleukin-6, pro-calcitonin, and high oxygen need (p ≤ 0.001 for all). Among swab-positive staff, 3 had pneumonia and recovered. Although no comparison could be made between different treatment and prophylaxis strategies, potentially useful suggestions emerged. Mortality compared well with that of nursing homes of the same area not transformed into care centers. CONCLUSION: Nursing homes massively hit by SARS-CoV-2 can become caring centers for patients not needing intensive care.

Newly-diagnosed diabetes and admission hyperglycemia predict COVID-19 severity by aggravating respiratory deterioration.

AIMS: We investigated whether pre-existing diabetes, newly-diagnosed diabetes, and admission hyperglycemia were associated with COVID-19 severity independently from confounders. METHODS: We retrospectively analyzed data on patients with COVID-19 hospitalized between February and April 2020 in an outbreak hospital in North-East Italy. Pre-existing diabetes was defined by self-reported history, electronic medical records, or ongoing medications. Newly-diagnosed diabetes was defined by HbA1c and fasting glucose. The primary outcome was a composite of ICU admission or death. RESULTS: 413 subjects were included, 107 of whom (25.6%) had diabetes, including 21 newly-diagnosed. Patients with diabetes were older and had greater comorbidity burden. The primary outcome occurred in 37.4% of patients with diabetes compared to 20.3% in those without (RR 1.85; 95%C.I. 1.33-2.57; p < 0.001). The association was stronger for newly-diagnosed compared to pre-existing diabetes (RR 3.06 vs 1.55; p = 0.004). Higher glucose level at admission was associated with COVID-19 severity, with a stronger association among patients without as compared to those with pre-existing diabetes (interaction p < 0.001). Admission glucose was correlated with most clinical severity indexes and its association with adverse outcome was mostly mediated by a worse respiratory function. CONCLUSION: Newly-diagnosed diabetes and admission hyperglycemia are powerful predictors of COVID-19 severity due to rapid respiratory deterioration.

Exposure to dipeptidyl-peptidase-4 inhibitors and COVID-19 among people with type 2 diabetes: A case-control study.

Because other coronaviruses enter the cells by binding to dipeptidyl-peptidase-4 (DPP-4), it has been speculated that DPP-4 inhibitors (DPP-4is) may exert an activity against severe acute respiratory syndrome coronavirus 2. In the absence of clinical trial results, we analysed epidemiological data to support or discard such a hypothesis. We retrieved information on exposure to DPP-4is among patients with type 2 diabetes (T2D) hospitalized for COVID-19 at an outbreak hospital in Italy. As a reference, we retrieved information on exposure to DPP-4is among matched patients with T2D in the same region. Of 403 hospitalized COVID-19 patients, 85 had T2D. The rate of exposure to DPP-4is was similar between T2D patients with COVID-19 (10.6%) and 14 857 matched patients in the region (8.8%), or 793 matched patients in the local outpatient clinic (15.4%), 8284 matched patients hospitalized for other reasons (8.5%), and when comparing 71 patients hospitalized for COVID-19 pneumonia (11.3%) with 351 matched patients with pneumonia of another aetiology (10.3%). T2D patients with COVID-19 who were on DPP-4is had a similar disease outcome as those who were not. In summary, we found no evidence that DPP-4is might affect hospitalization for COVID-19.

Glycaemic Control Among People with Type 1 Diabetes During Lockdown for the SARS-CoV-2 Outbreak in Italy.

INTRODUCTION: In late February 2020, due to the spread of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the Italian Government closed down all educational and sport activities. In March, it introduced further measures to stop the spread of coronavirus disease (COVID-19), placing the country in a state of almost complete lockdown. We report the impact of these restrictions on glucose control among people with type 1 diabetes (T1D). METHODS: Data were collected on 33 individuals with T1D who were monitoring their glucose levels using a flash glucose monitoring device and remotely connected to the diabetes clinic on a cloud platform. We retrieved information on average glucose, standard deviation and percentage time in hypoglycaemia (< 70 mg/dl), glucose range (70-180 mg/dl) and hyperglycaemia (> 180 mg/dl). We compared glycaemic measures collected during lockdown to those collected before the SARS-CoV-2 epidemic and to the periods immediately before lockdown. RESULTS: In 20 patients who had stopped working and were at home as a result of the lockdown, overall glycaemic control improved during the first 7 days of the lockdown as compared to the weeks before the spread of SARS-CoV-2. Average glucose declined from 177 ± 45 mg/dl (week before lockdown) to 160 ± 40 mg/dl (lockdown; p = 0.005) and the standard deviation improved significantly. Time in range increased from 54.4 to 65.2% (p = 0.010), and time in hyperglycaemia decreased from 42.3 to 31.6% (p = 0.016). The number of scans per day remained unchanged. In 13 patients who continued working, none of the measures of glycaemic control changed during lockdown. CONCLUSION: Despite the limited possibility to exercise and the incumbent psychologic stress, glycaemic control improved in patients with T1D who stopped working during the lockdown, suggesting that slowing down routine daily activities can have beneficial effects on T1D management, at least in the short term.