Risk Factors of COVID-19 Patients.
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ABSTRACT:
SUBMITTER: Ouchetto O
PROVIDER: S-EPMC8007946 | biostudies-literature | 2021 Jan
REPOSITORIES: biostudies-literature
Publications
Risk Factors of COVID-19 Patients.
Ouchetto Ouail O Drissi Bourhanbour Asmaa A
Disaster medicine and public health preparedness 20210108 4
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Project description:AIMS:COVID-19 is a current global pandemic. However, comprehensive global data analyses for its mortality risk factors are lacking. The current investigation aimed to assess the predictors of death among COVID-19 patients from worldwide open access data. METHODS:A total of 828 confirmed cases of COVID-19 with definite outcomes were retrospectively identified from open access individual-level worldwide data. Univariate followed by multivariable regression analysis were used to evaluate the association between potential risk factors and mortality. RESULTS:Majority of the patients were males 59.1% located in Asia 69.3%. Based on the data, older age (adjusted odds ratio (aOR), 1.079; 95% confidence intervals (95% CI), 1.064-1.095 per year increase), males (aOR, 1.607; 95% CI, 1.002-2.576), patients with hypertension (aOR, 3.576; 95% CI, 1.694-7.548), diabetes mellitus (aOR, 12.234; 95% CI, 4.126-36.272), and patients located in America (aOR, 7.441; 95% CI, 3.546-15.617) were identified as the risk factors of mortality among COVID-19 patients. CONCLUSIONS:Males, advanced age, hypertension patients, diabetes mellitus patients, and patients located in America were the independent risk factors of death among COVID-19 patients. Extra attention is required to be given to these factors and additional studies on the underlying mechanisms of these effects.
| S-EPMC7332436 | biostudies-literature
Project description:Post-acute sequelae of COVID-19 (PASC) represent an emerging global crisis. However, quantifiable risk-factors for PASC and their biological associations are poorly resolved. We executed a deep multi-omic, longitudinal investigation of 309 COVID-19 patients from initial diagnosis to convalescence (2-3 months later), integrated with clinical data, and patient-reported symptoms. We resolved four PASC-anticipating risk factors at the time of initial COVID-19 diagnosis: type 2 diabetes, SARS-CoV-2 RNAemia, Epstein-Barr virus viremia, and specific autoantibodies. In patients with gastrointestinal PASC, SARS-CoV-2-specific and CMV-specific CD8+ T cells exhibited unique dynamics during recovery from COVID-19. Analysis of symptom-associated immunological signatures revealed coordinated immunity polarization into four endotypes exhibiting divergent acute severity and PASC. We find that immunological associations between PASC factors diminish over time leading to distinct convalescent immune states. Detectability of most PASC factors at COVID-19 diagnosis emphasizes the importance of early disease measurements for understanding emergent chronic conditions and suggests PASC treatment strategies.
2022-02-01 | E-MTAB-10129 | biostudies-arrayexpress
Project description:BackgroundHypertension, as the most common comorbidity for patients with coronavirus disease 19 (COVID-19), has resulted in cases with more severe symptoms and higher mortality. The risk factors associated with COVID-19 in patients with hypertension are unknown.MethodsAll the available and confirmed patients with COVID-19 from February 3 to March 10, 2020, were enrolled from Huoshenshan Hospital, Wuhan, China. The demographic characteristics, clinical manifestations, laboratory data, radiological assessments, and treatments on admission were extracted and compared. Univariate and multivariate logistic regression methods were used to explore risk factors associated with COVID-19 in patients with hypertension and the severity of the cohort.ResultsA total of 430 available patients with COVID-19 were enrolled in the study, including 151 eligible patients with COVID-19 and hypertension. After PSM analysis, 141 patients without hypertension and 141 cases with hypertension were well matched. Compared with cases without hypertension, patients with hypertension were more severe (28.4% vs. 12.1%, p=0.001). In multivariate analysis, we found that neutrophil count (OR: 1.471; p=0.001), coronary heart disease (OR: 5.281; p=0.011), and the level of K+ (OR: 0.273; p < 0.001) were associated with patients with hypertension. In addition, the percentage of pulmonary infection volume was larger in cases with hypertension (4.55 vs. 5.8, p=0.017) and was a high risk factor for severe COVID-19 in patients with hypertension (OR: 1.084; p < 0.001).ConclusionOn admission, coronary heart disease, neutrophil count, and the level of K+ were associated with COVID-19 patients with hypertension. The percentage of the pulmonary infection volume was significantly larger in COVID-19 patients with hypertension and was a risk factor for COVID-19 severity of the cohort.
| S-EPMC8112195 | biostudies-literature
Project description:BACKGROUND:Coronavirus disease (COVID-19) is rapidly spreading worldwide. Although 10-20% of patients with COVID-19 have severe symptoms, little is known about the risk factors related to the aggravation of COVID-19 symptoms from asymptomatic or mild to severe disease states. METHODS:This retrospective study included 211 patients who were asymptomatic or with mild presentations of COVID-19. We evaluated the differences in demographic and clinical data between the cured (discharged to home) and transferred (aggravated to severe-stage COVID-19) groups. RESULTS:A multivariate logistic analysis showed that body temperature, chills, initial chest X-ray findings, and the presence of diabetes were significantly associated with predicting the progression to severe stage of COVID-19 (p?<?0.05). The odds ratio of transfer in patients with COVID-19 increased by 12.7-fold for abnormal findings such as haziness or consolidation in initial chest X-ray, 6.32-fold for initial symptom of chills, and 64.1-fold for diabetes. CONCLUSIONS:Even if patients are asymptomatic or have mild symptoms, clinicians should closely observe patients with COVID-19 presenting with chills, body temperature?>?37.5?°C, findings of pneumonia in chest X-ray, or diabetes.
| S-EPMC7309210 | biostudies-literature
Project description: Not available
| S-BSST416 | biostudies-other
Project description:Intracerebral hemorrhage (ICH) can be a devastating complication of coronavirus disease (COVID-19). We aimed to assess risk factors associated with ICH in this population. We performed a retrospective cohort study of adult patients admitted to NYU Langone Health system between March 1 and April 27 2020 with a positive nasopharyngeal swab polymerase chain reaction test result and presence of primary nontraumatic intracranial hemorrhage or hemorrhagic conversion of ischemic stroke on neuroimaging. Patients with intracranial procedures, malignancy, or vascular malformation were excluded. We used regression models to estimate odds ratios and 95% confidence intervals (OR, 95% CI) of the association between ICH and covariates. We also used regression models to determine association between ICH and mortality. Among 3824 patients admitted with COVID-19, 755 patients had neuroimaging and 416 patients were identified after exclusion criteria were applied. The mean (standard deviation) age was 69.3 (16.2), 35.8% were women, and 34.9% were on therapeutic anticoagulation. ICH occurred in 33 (7.9%) patients. Older age, non-Caucasian race, respiratory failure requiring mechanical ventilation, and therapeutic anticoagulation were associated with ICH on univariate analysis (p < 0.01 for each variable). In adjusted regression models, anticoagulation use was associated with a five-fold increased risk of ICH (OR 5.26, 95% CI 2.33-12.24, p < 0.001). ICH was associated with increased mortality (adjusted OR 2.6, 95 % CI 1.2-5.9). Anticoagulation use is associated with increased risk of ICH in patients with COVID-19. Further investigation is required to elucidate underlying mechanisms and prevention strategies in this population.
| S-EPMC7511245 | biostudies-literature
Project description: Not available
| S-EPMC7236829 | biostudies-literature
Project description:Objectives: To compare the outcomes of tracheostomised COVID-19 patients with non-COVID-19 tracheostomised patients to identify factors influencing severity and mortality. Methods: A retrospective, single-centre cohort study was conducted on COVID-19 tracheostomised patients admitted from May 2020 to February 2022, compared with a cohort of non-COVID-19 tracheostomised patients. Results: COVID-19 tracheostomised patients had a higher mortality rate (50% vs. 27.3% in non-COVID-19 patients). Mortality risk factors in COVID-19 tracheostomised patients included female sex (HR 1.99, CI 1.09-3.61, p = 0.025), ischemic heart disease (HR 5.71, CI 1.59-20.53, p = 0.008), elevated pre-tracheostomy values of PEEP (HR 1.06, CI 1.01-1.11, p = 0.017) and INR (HR 1.04, CI 1.01-1.07, p = 0.004), and ventilatory complications (HR 8.63, CI 1.09-68.26, p = 0.041). No significant differences in complication rates were found based on Sars-CoV-2 infection or tracheostomy type. Conclusions: Tracheostomy technique did not impact complications, discharge circumstances, or mortality, supporting the safety of bedside percutaneous tracheostomies for COVID-19 patients. COVID-19 tracheostomised patients exhibited a higher mortality rate.
| S-EPMC11765842 | biostudies-literature
Project description:The primary objective of this study was to investigate the factors contributing to hyperglycemic adverse events (AEs) associated with the administration of remdesivir in hospitalized patients diagnosed with coronavirus disease 2019 (COVID-19). Furthermore, the study aimed to develop a risk score model employing various machine learning approaches. A total of 1262 patients were enrolled in this investigation. The relationship between covariates and hyperglycemic AEs was assessed through logistic regression analysis. Diverse machine learning algorithms were employed for the purpose of forecasting hyperglycemia-related complications. After adjusting for covariates, individuals with a body mass index ≥23 kg/m2 , those using proton pump inhibitors, cholinergic medications, or individuals with cardiovascular diseases exhibited approximately 2.41-, 2.73-, 2.65-, and 1.97-fold higher risks of experiencing hyperglycemic AEs (95% CI 1.271-4.577, 1.223-6.081, 1.168-5.989, and 1.119-3.472, respectively). Multivariate logistic regression, elastic net, and random forest models displayed area under the receiver operating characteristic curve values of 0.65, 0.66, and 0.60, respectively (95% CI 0.572-0.719, 0.640-0.671, and 0.583-0.611, respectively). This study comprehensively explored factors associated with hyperglycemic complications arising from remdesivir administration and, concurrently, leveraged a range of machine learning methodologies to construct a risk scoring model, thereby facilitating the tailoring of individualized remdesivir treatment regimens for patients with COVID-19.
| S-EPMC10766056 | biostudies-literature
Project description:ObjectiveA critical role in coronavirus disease 2019 (COVID-19) pathogenesis is played by immune dysregulation that leads to a generalized uncontrolled multisystem inflammatory response, caused by overproduction of proinflammatory cytokines, known as "a cytokine storm" (CS), strongly associated with a severe course of disease. The aim of this study is to identify prognostic biomarkers for CS development in COVID-19 patients and integrate them into a prognostic score for CS-associated risk applicable to routine clinical practice.Materials and methodsThe authors performed a review of 458 medical records from COVID-19 patients (241 men and 217 women aged 60.0 ± 10.0) who received treatment in the St. Petersburg State Budgetary Institution of Healthcare City Hospital 40 (City Hospital 40, St. Petersburg), from Apr. 18, 2020 to Nov. 21, 2020. The patients were split in two groups: one group included 100 patients with moderate disease symptoms; the other group included 358 patients with progressive moderately severe, severe, and extremely severe disease. The National Early Warning Score (NEWS) score was used alongside with clinical assessment, chest computed tomographic (CT) scans, electrocardiography (ECG), and lab tests, like ferritin, C-reactive protein (CRP), interleukin (IL)-6, lactate dehydrogenase (LDH), and D-dimer.ResultsThe basic risk factors for cytokine storms in COVID-19 patients are male gender, age over 40 years, positive test result for replicative severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA, absolute lymphocyte count, dynamics in the NEWS score, as well as LDH, D-dimer, ferritin, and IL-6 levels. These clinical and instrumental findings can be also used as laboratory biomarkers for diagnosis and dynamic monitoring of cytokine storms. The suggested prognostic scale (including the NEWS score dynamics; serum IL-6 greater than 23 pg/ml; serum CRP 50 mg/L or greater; absolute lymphocyte count less than 0.72 × 109/L; positive test result for replicative coronavirus (SARS-CoV-2) RNA; age 40 years and over) is a useful tool to identify patients at a high risk for cytokine storm, requiring an early onset of anti-inflammatory therapy.
| S-EPMC8631447 | biostudies-literature