High glycaemic variability is associated with progression of COVID-19.
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ABSTRACT:
SUBMITTER: Hoong CWS
PROVIDER: S-EPMC8335709 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:There is high mortality among intensive care unit (ICU) patients with acute respiratory distress syndrome (ARDS) caused by coronavirus disease (COVID-19). Important factors for COVID-19 mortality are diabetes status and elevated fasting plasma glucose (FPG). However, the effect of glycaemic variability on survival has not been explored in patients with COVID-19 and ARDS. This single-centre cohort study compared several metrics of glycaemic variability for goodness-of-fit in patients requiring mechanical ventilation due to COVID-19 ARDS in the ICU at University Hospital Aachen, Germany. 106 patients had moderate to severe ARDS (P/F ratio median [IQR]: 112 [87-148] mmHg). Continuous HRs showed a proportional increase in mortality risk with daily glycaemic variability (DGV). Multivariable unadjusted and adjusted Cox-models showed a statistically significant difference in mortality for DGV (HR: 1.02, (P) < 0.001, LR(P) < 0.001; HR: 1.016, (P) = 0.001, LR(P) < 0.001, respectively). Kaplan-Meier estimators yielded a shorter median survival (25 vs. 87 days) and a higher likelihood of death (75% vs. 31%) in patients with DGV ≥ 25.5 mg/dl (P < 0.0001). High glycaemic variability during ICU admission is associated with significant increase in all-cause mortality for patients admitted with COVID-19 ARDS to the ICU. This effect persisted even after adjustment for clinically predetermined confounders, including diabetes, median procalcitonin and FPG.
| S-EPMC9194894 | biostudies-literature
Project description: Not available
| S-BSST563 | biostudies-other
Project description:The coronavirus pandemic (COVID-19) is associated with secondary bacterial and fungal infections globally. In India, inappropriate use of glucocorticoids, high prevalence of diabetes mellitus and a conducive environment for fungal growth are considered as the main factors for increased incidence of COVID-19 associated mucormycosis (CAM). Few cases of CAM without steroid abuse and normal blood glucose levels were also reported during the pandemic. This study was designed to explore whether altered immune responses due to severe COVID-19 infection predisposes towards development of mucormycosis. The global transcriptome profiling of monocytes and granulocytic cells derived from CAM, Mucormycosis, COVID-19 and healthy control groups were performed to identify the differentially expressed genes (DEGs) involved in dysregulated host immune response towards respective diseased and healthy conditions.
2024-02-09 | GSE226677 | GEO
Project description:AimsIncreased visit-to-visit glycaemic variability is independently associated with adverse outcomes in Type 2 diabetes. Our aim was to identify the patient characteristics associated with raised visit-to-visit glycaemic variability in people with Type 2 diabetes.MethodsA case-control study was conducted to establish associations between HbA1c variability and clinical covariates in 10 130 people with Type 2 diabetes. Variability was calculated by two metrics [sd and coefficient of variation (CV)] from a minimum of four HbA1c readings obtained over a 4-year period. High and low variability groups were defined as the top and bottom tertile of the sd or CV, and used in logistic regression analyses including a number of clinical and biochemical covariates. The analyses were stratified into low mean (< 53 mmol/mol; 7%) and high mean (≥ 53 mmol/mol; 7%) HbA1c groups.ResultsFindings were consistent across both HbA1c groups and variability metrics. Treatment, independent of other factors, was the most strongly associated covariate for the risk of high HbA1c variability. A six-fold increased risk was observed in the low HbA1c group, between the most and least intense treatment regimens (P < 0.001). Similar findings were present in the high HbA1c group with a three-fold increase in risk (P < 0.001). In addition, male gender, younger age, reduced HDL-cholesterol and increased BMI were all found to be independently associated with raised visit-to-visit glycaemic variability.ConclusionsIntensive treatment resulting in low mean HbA1c was associated with marked increase in HbA1c variability. Irrespective of diabetes control, the greatest visit-to-visit variability was observed in young, insulin resistant men.
| S-EPMC5811920 | biostudies-literature
Project description:IntroductionSmoking depresses pulmonary immune function and is a risk factor contracting other infectious diseases and more serious outcomes among people who become infected. This paper presents a meta-analysis of the association between smoking and progression of the infectious disease COVID-19.MethodsPubMed was searched on April 28, 2020, with search terms "smoking", "smoker*", "characteristics", "risk factors", "outcomes", and "COVID-19", "COVID", "coronavirus", "sar cov-2", "sar cov 2". Studies reporting smoking behavior of COVID-19 patients and progression of disease were selected for the final analysis. The study outcome was progression of COVID-19 among people who already had the disease. A random effects meta-analysis was applied.ResultsWe identified 19 peer-reviewed papers with a total of 11,590 COVID-19 patients, 2,133 (18.4%) with severe disease and 731 (6.3%) with a history of smoking. A total of 218 patients with a history of smoking (29.8%) experienced disease progression, compared with 17.6% of non-smoking patients. The meta-analysis showed a significant association between smoking and progression of COVID-19 (OR 1.91, 95% confidence interval [CI] 1.42-2.59, p = 0.001). Limitations in the 19 papers suggest that the actual risk of smoking may be higher.ConclusionsSmoking is a risk factor for progression of COVID-19, with smokers having higher odds of COVID-19 progression than never smokers.ImplicationsPhysicians and public health professionals should collect data on smoking as part of clinical management and add smoking cessation to the list of practices to blunt the COVID-19 pandemic.
| S-EPMC7239135 | biostudies-literature
Project description:Manuscript describes the daily dynamics of transcriptional responses in whole blood, from acute to convalescent phase, in severe and non-severe COVID-19 patients.
2020-12-31 | E-MTAB-9721 | biostudies-arrayexpress
Project description: Not available
| S-BSST416 | biostudies-other
Project description: Not available
| S-EPMC7869034 | biostudies-literature
Project description:ObjectivesWe aimed to identify high-risk factors for disease progression and fatality for coronavirus disease 2019 (COVID-19) patients.MethodsWe enrolled 2433 COVID-19 patients and used LASSO regression and multivariable cause-specific Cox proportional hazard models to identify the risk factors for disease progression and fatality.ResultsThe median time for progression from mild-to-moderate, moderate-to-severe, severe-to-critical, and critical-to-death were 3.0 (interquartile range: 1.8-5.5), 3.0 (1.0-7.0), 3.0 (1.0-8.0), and 6.5 (4.0-16.3) days, respectively. Among 1,758 mild or moderate patients at admission, 474 (27.0%) progressed to a severe or critical stage. Age above 60 years, elevated levels of blood glucose, respiratory rate, fever, chest tightness, c-reaction protein, lactate dehydrogenase, direct bilirubin, and low albumin and lymphocyte count were significant risk factors for progression. Of 675 severe or critical patients at admission, 41 (6.1%) died. Age above 74 years, elevated levels of blood glucose, fibrinogen and creatine kinase-MB, and low plateleta count were significant risk factors for fatality. Patients with elevated blood glucose level were 58% more likely to progress and 3.22 times more likely to die of COVID-19.ConclusionsOlder age, elevated glucose level, and clinical indicators related to systemic inflammatory responses and multiple organ failures, predict both the disease progression and the fatality of COVID-19 patients.
| S-EPMC7903375 | biostudies-literature
