Antiretrovirals and Risk of COVID-19 Diagnosis and Hospitalization in HIV-Positive Persons.
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ABSTRACT:
SUBMITTER: Del Amo J
PROVIDER: S-EPMC7541717 | biostudies-literature | 2020 Nov
REPOSITORIES: biostudies-literature
Publications
Antiretrovirals and Risk of COVID-19 Diagnosis and Hospitalization in HIV-Positive Persons.
Del Amo Julia J Polo Rosa R Moreno Santiago S Díaz Asunción A Martínez Esteban E Arribas José Ramón JR Jarrín Inma I Hernán Miguel A MA
Epidemiology (Cambridge, Mass.) 20201101 6
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Project description:ImportanceHigher prepandemic physical activity (PA) levels have been associated with lower risk and severity of COVID-19.ObjectiveTo investigate the association between self-reported prepandemic PA levels and the risk and severity of COVID-19 in older US adults.Design, setting, and participantsThis cohort study combined cohorts from 3 ongoing prospective randomized clinical trials of US adults aged 45 years or older who provided prepandemic self-reports of baseline leisure-time PA and risk factors for COVID-19 outcomes using the most recent questionnaire completed as of December 31, 2019, as the baseline PA assessment. In multiple surveys from May 2020 through May 2022, participants indicated whether they had at least 1 positive COVID-19 test result or were diagnosed with or hospitalized for COVID-19.ExposurePrepandemic PA, categorized into 3 groups by metabolic equivalent hours per week: inactive (0-3.5), insufficiently active (>3.5 to <7.5), and sufficiently active (≥7.5).Main outcome and measuresPrimary outcomes were risk of COVID-19 and hospitalization for COVID-19. Multivariable logistic regression was used to estimate odd ratios (ORs) and 95% CIs for the association of COVID-19 diagnosis and/or hospitalization with each of the 2 upper PA categories vs the lowest PA category.ResultsThe pooled cohort included 61 557 participants (mean [SD] age, 75.7 [6.4] years; 70.7% female), 20.2% of whom were inactive; 11.4%, insufficiently active; and 68.5%, sufficiently active. A total of 5890 confirmed incident cases of COVID-19 were reported through May 2022, including 626 hospitalizations. After controlling for demographics, body mass index, lifestyle factors, comorbidities, and medications used, compared with inactive individuals, those insufficiently active had no significant reduction in infection (OR, 0.96; 95% CI, 0.86-1.06) or hospitalization (OR, 0.98; 95% CI, 0.76-1.28), whereas those sufficiently active had a significant reduction in infection (OR, 0.90; 95% CI, 0.84-0.97) and hospitalization (OR, 0.73; 95% CI, 0.60-0.90). In subgroup analyses, the association between PA and SARS-CoV-2 infection differed by sex, with only sufficiently active women having decreased odds (OR, 0.87; 95% CI, 0.79-0.95; P = .04 for interaction).Conclusions and relevanceIn this cohort study of adults aged 45 years or older, those who adhered to PA guidelines before the pandemic had lower odds of developing or being hospitalized for COVID-19. Thus, higher prepandemic PA levels may be associated with reduced odds of SARS-CoV-2 infection and hospitalization for COVID-19.
| S-EPMC10865155 | biostudies-literature
Project description:RationaleThe association between smoking status and severe Coronavirus Disease 2019 (COVID-19) remains controversial.ObjectiveTo assess the risk of hospitalization (as a marker of severe COVID-19) in patients by smoking status: former, current and never smokers, who tested positive for the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV2) at an academic medical center in the United States.MethodsWe conducted a retrospective cohort study in patients with SARS-COV2 between March-1-2020 and January-31-2021 to identify the risk of hospitalization due to COVID-19 by smoking status.ResultsWe identified 10216 SARS-COV2-positive patients with complete documentation of smoking habits. Within 14 days of a SARS-COV2 positive test, 1150 (11.2%) patients were admitted and 188 (1.8%) died. Significantly more former smokers were hospitalized from COVID-19 than current or never smokers (21.2% former smokers; 7.3% current smokers; 10.4% never smokers, p<0.0001). In univariable analysis, former smokers had higher odds of hospitalization from COVID-19 than never smokers (OR 2.31; 95% CI 1.94-2.74). This association remained significant when analysis was adjusted for age, race and gender (OR 1.28; 95% CI 1.06-1.55), but became non-significant when analysis included Body Mass Index, previous hospitalization and number of comorbidities (OR 1.05; 95% CI 0.86-1.29). In contrast, current smokers were less likely than never smokers to be hospitalized due to COVID-19.ConclusionsSignificantly more former smokers were hospitalized and died from COVID-19 than current or never smokers. This effect is mediated via age and comorbidities in former smokers.
| S-EPMC8052507 | biostudies-literature
Project description:We conducted a nationwide, registry-based study to investigate the importance of 34 potential risk factors for coronavirus disease 2019 (COVID-19) diagnosis, hospitalization (with or without intensive care unit [ICU] admission), and subsequent all-cause mortality. The study population comprised all COVID-19 cases confirmed in Sweden by mid-September 2020 (68,575 non-hospitalized, 2494 ICU hospitalized, and 13,589 non-ICU hospitalized) and 434,081 randomly sampled general-population controls. Older age was the strongest risk factor for hospitalization, although the odds of ICU hospitalization decreased after 60-69 years and, after controlling for other risk factors, the odds of non-ICU hospitalization showed no trend after 40-49 years. Residence in a long-term care facility was associated with non-ICU hospitalization. Male sex and the presence of at least one investigated comorbidity or prescription medication were associated with both ICU and non-ICU hospitalization. Three comorbidities associated with both ICU and non-ICU hospitalization were asthma, hypertension, and Down syndrome. History of cancer was not associated with COVID-19 hospitalization, but cancer in the past year was associated with non-ICU hospitalization, after controlling for other risk factors. Cardiovascular disease was weakly associated with non-ICU hospitalization for COVID-19, but not with ICU hospitalization, after adjustment for other risk factors. Excess mortality was observed in both hospitalized and non-hospitalized COVID-19 cases. These results confirm that severe COVID-19 is related to age, sex, and comorbidity in general. The study provides new evidence that hypertension, asthma, Down syndrome, and residence in a long-term care facility are associated with severe COVID-19.
| S-EPMC7946619 | biostudies-literature
Project description:Background: Tuberculosis (TB) among persons living with HIV (PLWH) poses diagnostic challenges. Although several transcriptional signatures have recently been identified as promising tool for TB diagnosis, data are limited in persons with advanced HIV. Methodology: Reads were aligned to the human transcriptome (GRCh38 version 100), comprising both mRNA and ncRNA, with Salmon v1.2.0. A Random Forest algorithm with “leave-one-out” cross-validation was applied in the variance stabilizing transformation gene expression. The identified biomarkers were compared to previous TB transcriptional signatures using the Area Under the Curve (AUC). Results: Functional analysis indicated that common upregulated pathways in TB/HIV patients were associated with Toll-like receptor cascades and neutrophil degranulation. A machine learning decision tree algorithm identified the expression values from RAB20 and INSL3 as most informative for classifying TB status in PLWH. Only these two genes were able to correctly classify all samples.
2021-02-02 | GSE162164 | GEO
Project description:BackgroundEcologic analyses suggest that living in areas with higher levels of ambient fine particulate matter air pollution (PM2.5) is associated with higher risk of adverse COVID-19 outcomes. Studies accounting for individual-level health characteristics are lacking.MethodsWe leveraged the breadth and depth of the US Department of Veterans Affairs national healthcare databases and built a national cohort of 169,102 COVID-19 positive United States Veterans, enrolled between March 2, 2020 and January 31, 2021, and followed them through February 15, 2021. Annual average 2018 PM2.5 exposure, at an approximately 1 km2 resolution, was linked with residential street address at the year prior to COVID-19 positive test. COVID-19 hospitalization was defined as first hospital admission between 7 days prior to, and 15 days after, the first COVID-19 positive date. Adjusted Poisson regression assessed the association of PM2.5 with risk of hospitalization.ResultsThere were 25,422 (15.0%) hospitalizations; 5,448 (11.9%), 5,056 (13.0%), 7,159 (16.1%), and 7,759 (19.4%) were in the lowest to highest PM2.5 quartile, respectively. In models adjusted for State, demographic and behavioral factors, contextual characteristics, and characteristics of the pandemic a one interquartile range increase in PM2.5 (1.9 µg/m3) was associated with a 10% (95% CI: 8%-12%) increase in risk of hospitalization. The association of PM2.5 and risk of hospitalization among COVID-19 individuals was present in each wave of the pandemic. Models of non-linear exposure-response suggested increased risk at PM2.5 concentrations below the national standard 12 µg/m3. Formal effect modification analyses suggested higher risk of hospitalization associated with PM2.5 in Black people compared to White people (p = 0.045), and in those living in socioeconomically disadvantaged neighborhoods (p < 0.001).ConclusionsExposure to higher levels of PM2.5 was associated with increased risk of hospitalization among COVID-19 infected individuals. The risk was evident at PM2.5 levels below the regulatory standards. The analysis identified those of Black race and those living in disadvantaged neighborhoods as population groups that may be more susceptible to the untoward effect of PM2.5 on risk of hospitalization in the setting of COVID-19.
| S-EPMC8040542 | biostudies-literature
Project description:BackgroundCOVID-19 has caused a global pandemic unprecedented in a century. Though primarily a respiratory illness, cardiovascular risk factors predict adverse outcomes. We aimed to investigate the role of baseline echocardiographic abnormalities in further refining risk in addition to clinical risk factors.MethodsAdults with COVID-19 positive RT-PCR test across St Luke's University Health Network between March 1st 2020-October 31st 2020 were identified. Those with trans-thoracic echocardiography (TTE) within 15-180 days preceding COVID-19 positivity were selected, excluding severe valvular disease, acute cardiac event between TTE and COVID-19, or asymptomatic patients positive on screening. Demographic, clinical, and echocardiographic variables were manually extracted from patients' EHR and compared between groups stratified by disease severity. Logistic regression was used to identify independent predictors of hospitalization.Results192 patients met inclusion criteria. 87 (45.3%) required hospitalization, 34 (17.7%) suffered severe disease (need for ICU care/mechanical ventilation/in-hospital death). Age, co-morbidities, and several echocardiographic abnormalities were more prevalent in those with moderate-severe disease than in mild disease, with notable exceptions of systolic/diastolic dysfunction. On multivariate analysis, age (OR 1.039, 95% CI 1.011-1.067), coronary artery disease (OR 4.184, 95% CI 1.451-12.063), COPD (OR 6.886, 95% CI 1.396-33.959) and left atrial diameter ≥ 4.0 cm (OR 2.379, 95% CI 1.031-5.493) predicted need for hospitalization. Model showed excellent discrimination (ROC AUC 0.809, 95% CI 0.746-0.873).ConclusionsBaseline left atrial enlargement is an independent risk factor for risk of hospitalization among patients with COVID-19. When available, baseline LA enlargement may identify patients for (1) closer outpatient follow up, and (2) counseling vaccine-hesitancy.
| S-EPMC8982906 | biostudies-literature
Project description:ObjectiveTo determine factors associated with baseline neurocognitive performance in HIV-infected participants enrolled in the Strategies for Management of Antiretroviral Therapy (SMART) neurology substudy.MethodsParticipants from Australia, North America, Brazil, and Thailand were administered a 5-test neurocognitive battery. Z scores and the neurocognitive performance outcome measure, the quantitative neurocognitive performance z score (QNPZ-5), were calculated using US norms. Neurocognitive impairment was defined as z scores <-2 in two or more cognitive domains. Associations of test scores, the QNPZ-5, and impairment with baseline factors including demographics and risk factors for HIV-associated dementia (HAD) and cardiovascular disease (CVD) were determined in multiple regression.ResultsThe 292 participants had a median CD4 cell count of 536 cells/mm(3), 88% had an HIV viral load < or =400 copies/mL, and 92% were taking antiretrovirals. Demographics, HIV, and clinical factors differed between locations. The mean QNPZ-5 score was -0.72; 14% of participants had neurocognitive impairment. For most tests, scores and z scores differed significantly between locations, with and without adjustment for age, sex, education, and race. Prior CVD was associated with neurocognitive impairment. Prior CVD, hypercholesterolemia, and hypertension were associated with poorer neurocognitive performance but conventional HAD risk factors and the CNS penetration effectiveness rank of antiretroviral regimens were not.ConclusionsIn this HIV-positive population with high CD4 cell counts, neurocognitive impairment was associated with prior CVD. Lower neurocognitive performance was associated with prior CVD, hypertension, and hypercholesterolemia, but not conventional HAD risk factors. The contribution of CVD and cardiovascular risk factors to the neurocognition of HIV-positive populations warrants further investigation.
| S-EPMC2938971 | biostudies-literature
Project description:ObjectiveData on COVID-19 outcomes in persons with epilepsy (PWE) are scarce and inconclusive. We aimed to study the risk of hospitalization and death for COVID-19 in a large cohort of PWE from March 1, 2020 to October 31, 2021.MethodsThe historical cohort design (EpiLink Bologna) compared adult PWE grouped into people with focal epilepsy (PFE), idiopathic generalized epilepsy (PIGE), and developmental and/or epileptic encephalopathy (PDEE), and a population cohort matched (ratio 1:10) for age, sex, residence, and comorbidity (assessed with the multisource comorbidity score), living in the local health trust of Bologna (approximately 800 000 residents). Clinical data were linked to health administrative data.ResultsIn both cohorts (EpiLink: n = 1575 subjects, 1128 PFE, 267 PIGE, 148 PDEE, 32 other; controls: n = 15 326 subjects), 52% were females, and the mean age was 50 years (SD = 18). Hospital admissions for COVID-19 in the whole period were 49 (3.1%) in PWE and 225 (1.5%) in controls. The adjusted hazard ratio (aHR) in PWE was 1.9 (95% confidence interval [CI] = 1.4-2.7). The subgroups at higher risk were PFE (aHR = 1.9, 95% CI = 1.3-2.8) and PDEE (aHR = 3.9, 95% CI = 1.7-8.7), whereas PIGE had a risk comparable to the controls (aHR = 1.1, 95% CI = .3-3.5). Stratified analyses of the two main epidemic waves (March-May 2020, October 2020-May 2021) disclosed a higher risk of COVID-19-related hospitalization during the first epidemic wave (March-May 2020; aHR = 3.8, 95% CI = 2.2-6.7). Polytherapy with antiseizure medications contributed to a higher risk of hospital admission. Thirty-day risk of death after hospitalization was 14% in both PWE and controls.SignificanceDuring the first 20 months since the outbreak of COVID-19 in Bologna, PWE had a doubled risk of COVID-19 hospital admission compared to a matched control population. Conversely, epilepsy did not represent a risk factor for COVID-19-related death.
| S-EPMC9349826 | biostudies-literature
Project description:ObjectivesThe coronavirus disease 2019 (COVID-19) is a resource-intensive global pandemic. It is important for healthcare systems to identify high-risk COVID-19-positive patients who need timely health care. This study was conducted to predict the hospitalization of older adults who have tested positive for COVID-19.MethodsWe screened all patients with COVID test records from 11 Mass General Brigham hospitals to identify the study population. A total of 1495 patients with age 65 and above from the outpatient setting were included in the final cohort, among which 459 patients were hospitalized. We conducted a clinician-guided, 3-stage feature selection, and phenotyping process using iterative combinations of literature review, clinician expert opinion, and electronic healthcare record data exploration. A list of 44 features, including temporal features, was generated from this process and used for model training. Four machine learning prediction models were developed, including regularized logistic regression, support vector machine, random forest, and neural network.ResultsAll 4 models achieved area under the receiver operating characteristic curve (AUC) greater than 0.80. Random forest achieved the best predictive performance (AUC = 0.83). Albumin, an index for nutritional status, was found to have the strongest association with hospitalization among COVID positive older adults.ConclusionsIn this study, we developed 4 machine learning models for predicting general hospitalization among COVID positive older adults. We identified important clinical factors associated with hospitalization and observed temporal patterns in our study cohort. Our modeling pipeline and algorithm could potentially be used to facilitate more accurate and efficient decision support for triaging COVID positive patients.
| S-EPMC9129151 | biostudies-literature
Project description:We report a case of a 50-year-old male with a history of HIV and kidney transplant who presented with SARS-CoV-2. We also present a review of COVID-19 cases in kidney transplant recipients.
| S-EPMC7267082 | biostudies-literature