Data on residual clinical damage after Coronavirus disease-2019 (COVID-19) are lacking. The aims of this study were to investigate whether COVID-19 leaves behind residual dysfunction, and identify ...patients who might benefit from post-discharge monitoring. All patients aged ≥18 years admitted to the Emergency Department (ED) for COVID-19, and evaluated at post-discharge follow-up between 7 April and 7 May, 2020, were enrolled. Primary outcome was need of follow-up, defined as the presence at follow-up of at least one among: respiratory rate (RR) >20 breaths/min, uncontrolled blood pressure (BP) requiring therapeutic change, moderate to very severe dyspnoea, malnutrition, or new-onset cognitive impairment, according to validated scores. Post-traumatic stress disorder (PTSD) served as secondary outcome. 185 patients were included. Median interquartile range time from hospital discharge to follow-up was 23 20-29 days. 109 (58.9%) patients needed follow-up. At follow-up evaluation, 58 (31.3%) patients were dyspnoeic, 41 (22.2%) tachypnoeic, 10 (5.4%) malnourished, 106 (57.3%) at risk for malnutrition. Forty (21.6%) patients had uncontrolled BP requiring therapeutic change, and 47 (25.4%) new-onset cognitive impairment. PTSD was observed in 41 (22.2%) patients. At regression tree analysis, the ratio of arterial oxygen partial pressure to fractional inspired oxygen (PaO2/FiO2) and body mass index (BMI) at ED presentation, and age emerged as independent predictors of the need of follow-up. Patients with PaO2/FiO2 <324 and BMI ≥33 Kg/m2 had the highest odds to require follow-up. Among hospitalised patients, age ≥63 years, or age <63 plus non-invasive ventilation or diabetes identified those with the highest probability to need follow-up. PTSD was independently predicted by female gender and hospitalisation, the latter being protective (odds ratio, OR, 4.03, 95% confidence interval, CI, 1.76 to 9.47, p 0.0011; OR 0.37, 95% CI 0.14 to 0.92, p 0.033, respectively). COVID-19 leaves behind physical and psychological dysfunctions. Follow-up programmes should be implemented for selected patients.
Aims/hypothesis
The aim of the study was to characterise the humoral response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in patients with diabetes. Demonstrating the ability ...to mount an appropriate antibody response in the presence of hyperglycaemia is relevant for the comprehension of mechanisms related to the observed worse clinical outcome of coronavirus disease 2019 (COVID-19) pneumonia in patients with diabetes and for the development of any future vaccination campaign to prevent SARS-CoV-2 infection.
Methods
Using a highly specific and sensitive measurement of antibodies by fluid-phase luciferase immunoprecipitation assays, we characterised the IgG, IgM and IgA response against multiple antigens of SARS-CoV-2 in a cohort of 509 patients with documented diagnosis of COVID-19, prospectively followed at our institution. We analysed clinical outcomes and antibody titres according to the presence of hyperglycaemia, i.e., either diagnosed or undiagnosed diabetes, at the time of, or during, hospitalisation.
Results
Among patients with confirmed COVID-19, 139 (27.3%) had diabetes: 90 (17.7%) had diabetes diagnosed prior to the hospital admission (comorbid diabetes) while 49 (9.6%) had diabetes diagnosed at the time of admission (newly diagnosed). Diabetes was associated with increased levels of inflammatory biomarkers and hypercoagulopathy, as well as leucocytosis and neutrophilia. Diabetes was independently associated with risk of death (HR 2.32 95% CI 1.44, 3.75,
p
= 0.001), even after adjustment for age, sex and other relevant comorbidities. Moreover, a strong association between higher glucose levels and risk of death was documented irrespective of diabetes diagnosis (HR 1.14 × 1.1 mmol/l 95% CI 1.08, 1.21,
p
< 0.001). The humoral response against SARS-CoV-2 in patients with diabetes was present and superimposable, as for timing and antibody titres, to that of non-diabetic patients, with marginal differences, and was not influenced by glucose levels. Of the measured antibody responses, positivity for IgG against the SARS-CoV-2 spike receptor-binding domain (RBD) was predictive of survival rate, both in the presence or absence of diabetes.
Conclusions/interpretation
The observed increased severity and mortality risk of COVID-19 pneumonia in patients with hyperglycaemia was not the result of an impaired humoral response against SARS-CoV-2. RBD IgG positivity was associated with a remarkable protective effect, allowing for a cautious optimism about the efficacy of future vaccines against SARs-COV-2 in people with diabetes.
Graphical abstract
OBJECTIVE:--We sought to evaluate the efficacy and safety of vildagliptin, a new dipeptidyl peptidase-4 inhibitor, added to metformin during 24 weeks of treatment in patients with type 2 diabetes. ...RESEARCH DESIGN AND METHODS--This was a double-blind, randomized, multicenter, parallel group study of a 24-week treatment with 50 mg vildagliptin daily (n = 177), 100 mg vildagliptin daily (n = 185), or placebo (n = 182) in patients continuing a stable metformin dose regimen (>=1,500 mg/day) but achieving inadequate glycemic control (A1C 7.5-11%). RESULTS:--The between-treatment difference (vildagliptin - placebo) in adjusted mean change (AMΔ) ± SE in A1C from baseline to end point was -0.7 ± 0.1% (P < 0.001) and -1.1 ± 0.1% (P < 0.001) in patients receiving 50 or 100 mg vildagliptin daily, respectively. The between-treatment difference in the AMΔ fasting plasma glucose (FPG) was -0.8 ± 0.3 mmol/l (P = 0.003) and -1.7 ± 0.3 mmol/l (P < 0.001) in patients receiving 50 or 100 mg vildagliptin daily, respectively. Adverse events (AEs) were reported by 63.3, 65.0, and 63.5% of patients receiving 50 mg vildagliptin daily, 100 mg vildagliptin daily, or placebo, respectively. Gastrointestinal AEs were reported by 9.6 (P = 0.022 vs. placebo), 14.8, and 18.2% of patients receiving 50 mg vildagliptin daily, 100 mg vildagliptin daily, or placebo, respectively. One patient in each treatment group experienced one mild hypoglycemic event. CONCLUSIONS:--Vildagliptin is well tolerated and produces clinically meaningful, dose-related decreases in A1C and FPG as add-on therapy in patients with type 2 diabetes inadequately controlled by metformin.
COVID-19 is associated with unintentional weight loss. Little is known on whether and how patients regain the lost weight. We assessed changes in weight and abdominal adiposity over a three-month ...follow-up after discharge in COVID-19 survivors.
In this sub-study of a large prospective observational investigation, we collected data from individuals who had been hospitalized for COVID-19 and re-evaluated at one (V1) and three (V2) months after discharge. Patient characteristics upon admission and anthropometrics, waist circumference and hunger levels assessed during follow-up were analyzed across BMI categories.
One-hundred-eighty-five COVID-19 survivors (71% male, median age 62.1 54.3; 72.1 years, 80% with overweight/obesity) were included. Median BMI did not change from admission to V1 in normal weight subjects (-0.5 -1.2; 0.6 kg/m
, p = 0.08), but significantly decreased in subjects with overweight (-0.8 -1.8; 0.3 kg/m
, p < 0.001) or obesity (-1.38 -3.4; -0.3 kg/m
, p < 0.001; p < 0.05 vs. normal weight or obesity). Median BMI did not change from V1 to V2 in normal weight individuals (+0.26 -0.34; 1.15 kg/m
, p = 0.12), but significantly increased in subjects with overweight (+0.4 0.0; 1.0 kg/m
, p < 0.001) or obesity (+0.89 0.0; 1.6 kg/m
, p < 0.001; p = 0.01 vs. normal weight). Waist circumference significantly increased from V1 to V2 in the whole group (p < 0.001), driven by the groups with overweight or obesity. At multivariable regression analyses, male sex, hunger at V1 and initial weight loss predicted weight gain at V2.
Patients with overweight or obesity hospitalized for COVID-19 exhibit rapid, wide weight fluctuations that may worsen body composition (abdominal adiposity). CLINICALTRIALS.
NCT04318366.
A fatty liver, which is a common feature in insulin‐resistant states, can lead to chronic liver disease. It has been hypothesized that a fatty liver can also increase the rates of non–hepatic‐related ...morbidity and mortality. Therefore, we wanted to determine whether the fatty liver index (FLI), a surrogate marker and a validated algorithm derived from the serum triglyceride level, body mass index, waist circumference, and γ‐glutamyltransferase level, was associated with the prognosis in a population study. The 15‐year all‐cause, hepatic‐related, cardiovascular disease (CVD), and cancer mortality rates were obtained through the Regional Health Registry in 2011 for 2074 Caucasian middle‐aged individuals in the Cremona study, a population study examining the prevalence of diabetes mellitus in Italy. During the 15‐year observation period, 495 deaths were registered: 34 were hepatic‐related, 221 were CVD‐related, 180 were cancer‐related, and 60 were attributed to other causes. FLI was independently associated with the hepatic‐related deaths (hazard ratio = 1.04, 95% confidence interval = 1.02‐1.05, P < 0.0001). Age, sex, FLI, cigarette smoking, and diabetes were independently associated with all‐cause mortality. Age, sex, FLI, systolic blood pressure, and fibrinogen were independently associated with CVD mortality; meanwhile, age, sex, FLI, and smoking were independently associated with cancer mortality. FLI correlated with the homeostasis model assessment of insulin resistance (HOMA‐IR), a surrogate marker of insulin resistance (Spearman's ρ = 0.57, P < 0.0001), and when HOMA‐IR was included in the multivariate analyses, FLI retained its association with hepatic‐related mortality but not with all‐cause, CVD, and cancer‐related mortality. Conclusion: FLI is independently associated with hepatic‐related mortality. It is also associated with all‐cause, CVD, and cancer mortality rates, but these associations appear to be tightly interconnected with the risk conferred by the correlated insulin‐resistant state. (HEPATOLOGY 2011;)
Bacteria have evolved to efficiently interact each other, forming complex entities known as microbial communities. These "super-organisms" play a central role in maintaining the health of their ...eukaryotic hosts and in the cycling of elements like carbon and nitrogen. However, despite their crucial importance, the mechanisms that influence the functioning of microbial communities and their relationship with environmental perturbations are obscure. The study of microbial communities was boosted by tremendous advances in sequencing technologies, and in particular by the possibility to determine genomic sequences of bacteria directly from environmental samples. Indeed, with the advent of metagenomics, it has become possible to investigate, on a previously unparalleled scale, the taxonomical composition and the functional genetic elements present in a specific community. Notwithstanding, the metagenomic approach
suffers some limitations, among which the impossibility of modeling molecular-level (e.g., metabolic) interactions occurring between community members, as well as their effects on the overall stability of the entire system. The family of constraint-based methods, such as flux balance analysis, has been fruitfully used to translate genome sequences in predictive, genome-scale modeling platforms. Although these techniques have been initially developed for analyzing single, well-known model organisms, their recent improvements allowed engaging in multi-organism
analyses characterized by a considerable predictive capability. In the face of these advances, here we focus on providing an overview of the possibilities and challenges related to the modeling of metabolic interactions within a bacterial community, discussing the feasibility and the perspectives of this kind of analysis in the (near) future.
Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the ...microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i.e. following antibiotic exposure). This allowed us to describe the metabolic reprogramming that occurs in this bacterium when treated with colistin (the currently adopted last-line treatment) and identify a set of genes that are primary targets for developing new drugs against A. baumannii, including colistin-resistant strains. It can be anticipated that the metabolic model presented herein will represent a solid and reliable resource for the future treatment of A. baumannii infections.
Cold environments dominate Earth's biosphere, hosting complex microbial communities with the ability to thrive at low temperatures. However, the underlying molecular mechanisms and the metabolic ...pathways involved in bacterial cold-adaptation mechanisms are still not fully understood. Herein, we assessed the metabolic features of the Antarctic bacterium Pseudoalteromonas haloplanktis TAC125 (PhTAC125), a model organism for cold-adaptation, at both 4 °C and 15 °C, by integrating genomic and phenomic (high-throughput phenotyping) data and comparing the obtained results to the taxonomically related Antarctic bacterium Pseudoalteromonas sp. TB41 (PspTB41). Although the genome size of PspTB41 is considerably larger than PhTAC125, the higher number of genes did not reflect any higher metabolic versatility at 4 °C as compared to PhTAC125. Remarkably, protein S-thiolation regulated by glutathione and glutathionylspermidine appeared to be a new possible mechanism for cold adaptation in PhTAC125. More in general, this study represents an example of how 'multi-omic' information might potentially contribute in filling the gap between genotypic and phenotypic features related to cold-adaptation mechanisms in bacteria.
Antarctica, one of the most extreme environments on Earth, hosts diverse microbial communities. These microbes have evolved and adapted to survive in these hostile conditions, but knowledge on the ...molecular mechanisms underlying this process remains limited. The Italian Collection of Antarctic Bacteria (Collezione Italiana Batteri Antartici (CIBAN)), managed by the University of Messina, represents a valuable repository of cold-adapted bacterial strains isolated from various Antarctic environments. In this study, we sequenced and analyzed the genomes of 58 marine Gammaproteobacteria strains from the CIBAN collection, which were isolated during Italian expeditions from 1990 to 2005. By employing genome-scale metrics, we taxonomically characterized these strains and assigned them to four distinct genera: Pseudomonas, Pseudoalteromonas, Shewanella, and Psychrobacter. Genome annotation revealed a previously untapped functional potential, including secondary metabolite biosynthetic gene clusters and antibiotic resistance genes. Phylogenomic analyses provided evolutionary insights, while assessment of cold-shock protein presence shed light on adaptation mechanisms. Our study emphasizes the significance of CIBAN as a resource for understanding Antarctic microbial life and its biotechnological potential. The genomic data unveil new horizons for insight into bacterial existence in Antarctica.
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