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: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: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: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:BACKGROUND:The population in Mexico has high prevalence rates of noncommunicable diseases (NCDs). Hospitalization and death of COVID-19 patients in the countries most affected by the pandemic has been associated to chronic comorbidities. OBJECTIVE:To describe the prevalence of NCDs in patients with COVID-19 in Mexico and analyze the increased risk due to comorbidities and risk factors on hospitalization, utilization of intensive care units and death. METHODS:A cross-sectional study was performed from 212,802 confirmed COVID-19 cases reported by the Ministry of Health up to June 27, 2020. Odds ratios were performed using logistic regression model. RESULTS:Up to 47.40% of patients with COVID-19 diagnosis were also reported with a comorbidity, with hypertension being the most frequent (20.12%). The report of at least one NCD significantly increased the risk of death with respect to patients without such diagnoses. Chronic kidney disease increased the risk of death the most (OR 2.31), followed by diabetes (OR 1.69), immunosuppression (OR 1.62), obesity (OR 1.42), hypertension (OR 1.24), chronic obstructive pulmonary disease (OR 1.20). The comorbidities that most increased the risk of ICU and of intubation were diabetes, immunosuppression and obesity. CONCLUSION:NCD comorbidities increase the severity of COVID-19 infection. Given high NCD prevalence rates among the Mexican population, the pandemic poses a special threat to the health system and to society. Special prevention measures need to be strengthened for persons with NCD diagnoses in the short-term. In the mid-term, disease control strategies need to be improved to protect these patients against COVID-19 severity.
| S-EPMC7375298 | biostudies-literature
Project description:IMPORTANCE:Certain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear. OBJECTIVE:To determine the demographic and clinical characteristics associated with increased severity of Covid-19 infection. DESIGN:Retrospective observational study. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation. SETTING:A large, multihospital healthcare system in Southern California. PARTICIPANTS:All patients with confirmed Covid-19 infection (N = 442). RESULTS:Of all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P<0.001), male (OR 2.0, P = 0.001), African American (OR 2.1, P = 0.011), obese (OR 2.0, P = 0.021), with diabetes mellitus (OR 1.8, P = 0.037), and with a higher comorbidity index (OR 1.8 per SD, P<0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction<0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P = 0.003) irrespective of age, race, or morbidity profile. CONCLUSIONS AND RELEVANCE:In our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings.
| S-EPMC7377468 | biostudies-literature
Project description: Not available
| S-EPMC8743833 | biostudies-literature
Project description:Globally, the Coronavirus disease (COVID-19) outbreak is linked with air pollution of both indoor and outdoor environments and co-morbidities conditions of human beings. To find out the risk factor zones associated with Coronavirus disease among under-five children using pre-existing morbidity conditions and indoor air pollution (IAP) environmental factors and also with current fatality and recovery rate of COVID-19 disease in India. Data was utilized from the 4th round of the National Family Health Survey (NFHS), 2015-16, and from the Ministry of Health and Family Welfare (MoHFW) on 18th May 2020. Mean, standard deviation, and Z-score statistical methods have been employed to find out the risk factor zones i.e. to execute the objective. Findings of this study are, the states and UTs which have more likely to very higher to higher risk factors or zones of Coronavirus disease (COVID-19) are Mizoram (1.4), Meghalaya (1.27), Uttarakhand (0.92), West Bengal (0.73), Uttar Pradesh (0.66), Jammu and Kashmir (0.44), Odisha (0.33), Madhya Pradesh (0.21), Jharkhand (0.20), Bihar (0.19), Maharashtra (0.16 risk score), compared to UTs like Assam (-0.12), Rajasthan (-0.13), Goa (-0.14), Manipur (-0.17), Chandigarh (-0.19), Haryana (-0.22), Delhi (-0.27) have moderate risk factors of COVID-19, and the states and UTs like Daman and Diu (-1.18), Sikkim (-0.98), Andaman and Nicobar Islands (-0.84), Kerala (-0.69), Dadra and Nagar Haveli (-0.68), Arunachal Pradesh ( 0.-53), Karnataka (-0.42), and Nagaland (-0.36) have very low-risk zones of COVID-19 deaths. From a research viewpoint, there is a prerequisite need for epidemiological studies to investigate the connection between indoor air pollution and pre-existing morbidity which are associated with COVID-19. Well-built public health measures, including rapidly searching in high focus areas and testing of COVID-19, should be performed in vulnerable areas of COVID-19.
| S-EPMC7362832 | biostudies-literature