Pre-existing conditions in Hispanics/Latinxs that are COVID-19 risk factors.
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ABSTRACT:
SUBMITTER: Chang TS
PROVIDER: S-EPMC7879099 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Myocardial injury is a life-threatening complication of coronavirus disease 2019 (COVID-19). Pre-existing health conditions and early morphological alterations may precipitate cardiac injury and dysfunction after contracting the virus. The current study aimed at assessing potential risk factors for COVID-19 cardiac complications in patients with pre-existing conditions and imaging predictors. Methods and Results: The multi-center, retrospective cohort study consecutively enrolled 400 patients with lab-confirmed COVID-19 in six Chinese hospitals remote to the Wuhan epicenter. Patients were diagnosed with or without the complication of myocardial injury by history and cardiac biomarker Troponin I/T (TnI/T) elevation above the 99th percentile upper reference limit. The majority of COVID-19 patients with myocardial injury exhibited pre-existing health conditions, such as hypertension, diabetes, hypercholesterolemia, and coronary disease. They had increased levels of the inflammatory cytokine interleukin-6 and more in-hospital adverse events (admission to an intensive care unit, invasive mechanical ventilation, or death). Chest CT scan on admission demonstrated that COVID-19 patients with myocardial injury had higher epicardial adipose tissue volume ([EATV] 139.1 (83.8-195.9) vs. 92.6 (76.2-134.4) cm2; P = 0.036). The optimal EATV cut-off value (137.1 cm2) served as a useful factor for assessing myocardial injury, which yielded sensitivity and specificity of 55.0% (95%CI, 32.0-76.2%) and 77.4% (95%CI, 71.6-82.3%) in adverse cardiac events, respectively. Multivariate logistic regression analysis showed that EATV over 137.1 cm2 was a strong independent predictor for myocardial injury in patients with COVID-19 [OR 3.058, (95%CI, 1.032-9.063); P = 0.044]. Conclusions: Augmented EATV on admission chest CT scan, together with the pre-existing health conditions (hypertension, diabetes, and hyperlipidemia) and inflammatory cytokine production, is associated with increased myocardial injury and mortality in COVID-19 patients. Assessment of pre-existing conditions and chest CT scan EATV on admission may provide a threshold point potentially useful for predicting cardiovascular complications of COVID-19.
| S-EPMC7829196 | biostudies-literature
Project description:BackgroundThe relative association between cardiovascular (CV) risk factors, such as diabetes and hypertension, established CV disease (CVD), and susceptibility to CV complications or mortality in COVID-19 remains unclear.MethodsWe conducted a cohort study of consecutive adults hospitalised for severe COVID-19 between 1st March and 30th June 2020. Pre-existing CVD, CV risk factors and associations with mortality and CV complications were ascertained.ResultsAmong 1721 patients (median age 71 years, 57% male), 349 (20.3%) had pre-existing CVD (CVD), 888 (51.6%) had CV risk factors without CVD (RF-CVD), 484 (28.1%) had neither. Patients with CVD were older with a higher burden of non-CV comorbidities. During follow-up, 438 (25.5%) patients died: 37% with CVD, 25.7% with RF-CVD and 16.5% with neither. CVD was independently associated with in-hospital mortality among patients < 70 years of age (adjusted HR 2.43 [95% CI 1.16-5.07]), but not in those ≥ 70 years (aHR 1.14 [95% CI 0.77-1.69]). RF-CVD were not independently associated with mortality in either age group (< 70 y aHR 1.21 [95% CI 0.72-2.01], ≥ 70 y aHR 1.07 [95% CI 0.76-1.52]). Most CV complications occurred in patients with CVD (66%) versus RF-CVD (17%) or neither (11%; p < 0.001). 213 [12.4%] patients developed venous thromboembolism (VTE). CVD was not an independent predictor of VTE.ConclusionsIn patients hospitalised with COVID-19, pre-existing established CVD appears to be a more important contributor to mortality than CV risk factors in the absence of CVD. CVD-related hazard may be mediated, in part, by new CV complications. Optimal care and vigilance for destabilised CVD are essential in this patient group. Trial registration n/a.
| S-EPMC8254437 | biostudies-literature
Project description:Post-acute sequelae of COVID-19 (PASC) are conditions that occur or remain at least 28 days after SARS-CoV-2 infection. While some risk factors for PASC have been identified, little is known about pre-existing conditions that render one susceptible to developing PASC. Data from participants (n = 1224) in a longitudinal COVID-19 cohort study in Arizona were used to investigate comorbid conditions associated with PASC. After adjustment of the models for age, BMI, gender, race, and smoking, the following pre-existing conditions were statistically significantly associated with the development of PASC: asthma (OR = 1.54; 95% CI = 1.10-2.15); chronic constipation (OR = 4.29; 95% CI = 1.15-16.00); reflux (OR = 1.54; 95% CI = 1.01-2.34); rheumatoid arthritis (OR = 3.69; 95%CI = 1.15-11.82); seasonal allergies (OR = 1.56; 95% CI = 1.22-1.98); and depression/anxiety (OR = 1.72; 95% CI = 1.17-2.52). When grouping conditions together, statistically significant associations with PASC were observed for respiratory (OR = 1.47; 95% CI = 1.06-2.14); gastrointestinal (OR = 1.62; 95% CI = 1.16-2.26), and autoimmune conditions (OR = 4.38; 95% CI = 1.59-12.06). After adjustment for severity of acute SARS-CoV-2 infection and depression/anxiety, seasonal allergies (OR = 1.48; 95% CI 1.15-1.91) and autoimmune disease (OR = 3.78; 95% CI - 1.31-10.91) remained significantly associated with risk for PASC. These findings indicate that numerous pre-existing conditions may be associated with an increased risk for the development of PASC. Patients with these conditions should consider taking extra steps to avoid infection.
| S-EPMC9816074 | biostudies-literature
Project description:BackgroundCoronavirus disease 2019 (COVID-19) pandemic continues to escalate intensively worldwide. Massive studies on general populations with SARS-CoV-2 infection have revealed that pre-existing comorbidities were a major risk factor for the poor prognosis of COVID-19. Notably, 49-75% of COVID-19 patients had no comorbidities, but this cohort would also progress to severe COVID-19 or even death. However, risk factors contributing to disease progression and death in patients without chronic comorbidities are largely unknown; thus, specific clinical interventions for those patients are challenging.MethodsA multicenter, retrospective study based on 4806 COVID-19 patients without chronic comorbidities was performed to identify potential risk factors contributing to COVID-19 progression and death using LASSO and a stepwise logistic regression model.ResultsAmong 4806 patients without pre-existing comorbidities, the proportions with severe progression and mortality were 34.29% and 2.10%, respectively. The median age was 47.00 years [interquartile range, 36.00-56.00], and 2162 (44.99%) were men. Among 51 clinical parameters on admission, age ≥ 47, oxygen saturation < 95%, increased lactate dehydrogenase, neutrophil count, direct bilirubin, creatine phosphokinase, blood urea nitrogen levels, dyspnea, increased blood glucose and prothrombin time levels were associated with COVID-19 mortality in the entire cohort. Of the 3647 patients diagnosed with non-severe COVID-19 on admission, 489(13.41%) progressed to severe disease. The risk factors associated with COVID-19 progression from non-severe to severe illness were increased procalcitonin levels, SpO2 < 95%, age ≥ 47, increased LDH, activated partial thromboplastin time levels, decreased high-density lipoprotein cholesterol levels, dyspnea and increased D-dimer levels.ConclusionsCOVID-19 patients without pre-existing chronic comorbidities have specific traits and disease patterns. COVID-19 accompanied by severe bacterial infections, as indicated by increased procalcitonin levels, was highly associated with disease progression from non-severe to severe. Aging, impaired respiratory function, coagulation dysfunction, tissue injury, and lipid metabolism dysregulation were also associated with disease progression. Once factors for multi-organ damage were elevated and glucose increased at admission, these findings indicated a higher risk for mortality. This study provides information that helps to predict COVID-19 prognosis specifically in patients without chronic comorbidities.
| S-EPMC8598256 | biostudies-literature
Project description:COVID-19 can be life-threatening to individuals with chronic diseases. To prevent severe outcomes, it is critical that we comprehend pre-existing molecular abnormalities found in common health conditions that predispose patients to poor prognoses. In this study, we focused on 14 pre-existing health conditions for which increased hazard ratios of COVID-19 mortality have been documented. We hypothesized that dysregulated gene expression in these pre-existing health conditions were risk factors of COVID-19 related death, and the magnitude of dysregulation (measured by fold change) were correlated with the severity of COVID-19 outcome (measured by hazard ratio). To test this hypothesis, we analyzed transcriptomics data sets archived before the pandemic in which no sample had COVID-19. For a given pre-existing health condition, we identified differentially expressed genes by comparing individuals affected by this health condition with those unaffected. Among genes differentially expressed in multiple health conditions, the fold changes of 70 upregulated genes and 181 downregulated genes were correlated with hazard ratios of COVID-19 mortality. These pre-existing dysregulations were molecular risk factors of severe COVID-19 outcomes. These genes were enriched with endoplasmic reticulum and mitochondria function, proinflammatory reaction, interferon production, and programmed cell death that participate in viral replication and innate immune responses to viral infections. Our results suggest that impaired innate immunity in pre-existing health conditions is associated with increased hazard of COVID-19 mortality. The discovered molecular risk factors are potential prognostic biomarkers and targets for therapeutic intervention.
| S-EPMC9083528 | biostudies-literature
Project description:Recent exposure to seasonal coronaviruses (sCoVs) may stimulate cross-reactive antibody responses against SARS-CoV-2. Previous studies have shown divergent results regarding protective or damaging immunity induced by prior exposure to sCoVs. It is still unknown whether pre-existing humoral immunity may play a role in the vaccine-induced neutralization and antibody responses. In this study, we collected 36 paired sera in healthy volunteers before and after immunization with inactivated SARS-CoV-2 vaccines, and analyzed the distribution and intensity of pre-existing antibody responses at the epitope level before vaccine immunization, as well as the relationship between pre-existing sCoVs immunity and vaccine-induced neutralization.
2021-10-13 | E-MTAB-11084 | biostudies-arrayexpress
Project description:Recent exposure to seasonal coronaviruses (sCoVs) may stimulate cross-reactive antibody responses against SARS-CoV-2. Previous studies have shown divergent results regarding protective or damaging immunity induced by prior exposure to sCoVs. It is still unknown whether pre-existing humoral immunity may play a role in the vaccine-induced neutralization and antibody responses. In this study, we collected 36 paired sera in healthy volunteers before and after immunization with inactivated SARS-CoV-2 vaccines, and analyzed the distribution and intensity of pre-existing antibody responses at the epitope level before vaccine immunization, as well as the relationship between pre-existing sCoVs immunity and vaccine-induced neutralization.
2021-10-29 | E-MTAB-11117 | biostudies-arrayexpress
Project description: Not available
| S-EPMC7815629 | biostudies-literature
Project description:ObjectivesPredictive algorithms to inform risk management decisions are needed for patients with COVID-19, although the traditional risk scores have not been adequately assessed in Asian patients. We aimed to evaluate the performance of a COVID-19-specific prediction model, the 4C (Coronavirus Clinical Characterisation Consortium) Mortality Score, along with other conventional critical care risk models in Japanese nationwide registry data.DesignRetrospective cohort study.Setting and participantsHospitalised patients with COVID-19 and cardiovascular disease or coronary risk factors from January to May 2020 in 49 hospitals in Japan.Main outcome measuresTwo different types of outcomes, in-hospital mortality and a composite outcome, defined as the need for invasive mechanical ventilation and mortality.ResultsThe risk scores for 693 patients were tested by predicting in-hospital mortality for all patients and composite endpoint among those not intubated at baseline (n=659). The number of events was 108 (15.6%) for mortality and 178 (27.0%) for composite endpoints. After missing values were multiply imputed, the performance of the 4C Mortality Score was assessed and compared with three prediction models that have shown good discriminatory ability (RISE UP score, A-DROP score and the Rapid Emergency Medicine Score (REMS)). The area under the receiver operating characteristic curve (AUC) for the 4C Mortality Score was 0.84 (95% CI 0.80 to 0.88) for in-hospital mortality and 0.78 (95% CI 0.74 to 0.81) for the composite endpoint. It showed greater discriminatory ability compared with other scores, except for the RISE UP score, for predicting in-hospital mortality (AUC: 0.82, 95% CI 0.78 to 0.86). Similarly, the 4C Mortality Score showed a positive net reclassification improvement index over the A-DROP and REMS for mortality and over all three scores for the composite endpoint. The 4C Mortality Score model showed good calibration, regardless of outcome.ConclusionsThe 4C Mortality Score performed well in an independent external COVID-19 cohort and may enable appropriate disposition of patients and allocation of medical resources.Trial registration number UMIN000040598.
| S-EPMC8438580 | biostudies-literature
Project description:BackgroundWe aimed to determine if pre-existing immunocompromising conditions (ICCs) were associated with the presentation or outcome of patients with acute coronavirus disease 2019 (COVID-19) admitted for pediatric intensive care.MethodsFifty-five hospitals in 30 US states reported cases through the Overcoming COVID-19 public health surveillance registry. Patients <21 years admitted 12 March 2020-30 December 2021 to the pediatric intensive care unit (PICU) or high-acuity unit for acute COVID-19 were included.ResultsOf 1274 patients, 105 (8.2%) had an ICC, including 33 (31.4%) hematologic malignancies, 24 (22.9%) primary immunodeficiencies and disorders of hematopoietic cells, 19 (18.1%) nonmalignant organ failure with solid-organ transplantation, 16 (15.2%) solid tumors, and 13 (12.4%) autoimmune disorders. Patients with ICCs were older, had more underlying renal conditions, and had lower white blood cell and platelet counts than those without ICCs, but had similar clinical disease severity upon admission. In-hospital mortality from COVID-19 was higher (11.4% vs 4.6%, P = .005) and hospitalization was longer (P = .01) in patients with ICCs. New major morbidities upon discharge were not different between those with and without ICC (10.5% vs 13.9%, P = .40). In patients with ICCs, bacterial coinfection was more common in those with life-threatening COVID-19.ConclusionsIn this national case series of patients <21 years of age with acute COVID-19 admitted for intensive care, existence of a prior ICCs were associated with worse clinical outcomes. Reassuringly, most patients with ICCs hospitalized in the PICU for severe acute COVID-19 survived and were discharged home without new severe morbidities.
| S-EPMC11327788 | biostudies-literature