One-year mortality after ICU admission due to COVID-19 infection.
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ABSTRACT:
SUBMITTER: Ceccato A
PROVIDER: S-EPMC8764887 | biostudies-literature | 2022 Mar
REPOSITORIES: biostudies-literature
Publications
One-year mortality after ICU admission due to COVID-19 infection.
Ceccato Adrian A Pérez-Arnal Raquel R Motos Anna A Barbé Ferran F Torres Antoni A
Intensive care medicine 20220118 3
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Project description:Individuals infected with SARS-CoV-2 vary greatly in their symptomatology and disease progression, likely as a result of numerous genetic, biological and environmental factors and their complex interactions. Meanwhile, the potential roles of microRNAs (miRNAs) in SARS-CoV-2 infection have not been fully described. MiRNAs have emerged as key post-transcriptional regulators of gene expression, and their dysregulation can be indicative of aberrant immune function. In this study, we characterize the potential roles of mIRNAs in early COVID-19 disease progression. We studied a diverse cohort of 259 patients admitted to hospitals in Abu Dhabi, United Arab Emirates to understand the clinical and biological factors associated with ICU admission during COVID-19 treatment, integrating electronic health records (EHR), global miRNA and RNA expression, and genotyping data. Using EHR, we identified 26 factors correlated with ICU admission, including 8 blood phenotypes such as neutrophil-to-lymphocyte ratio, Interleukin-6, and C-reactive protein levels. Using genome-wide miRNA expression data for a subset of 96 individuals from Southeast Asia and the Middle East and North Africa, we identified 27 miRNAs significantly associated with ICU admission (p < 0.01), and 97 miRNAs associated with at least one of the 8 blood phenotypes. [cross-cor] Integrating expression data for 632 miRNAs and genotyping data for ~260,000 SNPs, we identified 168 significant cis-expression quantitative trait loci (cis-eQTLs), of which 59 were associated with either ICU admission or one of the 8 blood phentoypes. Overall, our findings characterize the miRNA architecture of blood phenotypes during the early stages of COVID-19 infection, identify miRNAs associated with ICU admission and therefore COVID-19 disease severity, and suggest a potential genetic control of miRNA expression during early COVID-19 disease progression.
2023-06-14 | GSE220077 | GEO
Project description:Individuals infected with SARS-CoV-2 vary greatly in their symptomatology and disease progression, likely as a result of numerous genetic, biological and environmental factors and their complex interactions. Meanwhile, the potential roles of microRNAs (miRNAs) in SARS-CoV-2 infection have not been fully described. MiRNAs have emerged as key post-transcriptional regulators of gene expression, and their dysregulation can be indicative of aberrant immune function. In this study, we characterize the potential roles of mIRNAs in early COVID-19 disease progression. We studied a diverse cohort of 259 patients admitted to hospitals in Abu Dhabi, United Arab Emirates to understand the clinical and biological factors associated with ICU admission during COVID-19 treatment, integrating electronic health records (EHR), global miRNA and RNA expression, and genotyping data. Using EHR, we identified 26 factors correlated with ICU admission, including 8 blood phenotypes such as neutrophil-to-lymphocyte ratio, Interleukin-6, and C-reactive protein levels. Using genome-wide miRNA expression data for a subset of 96 individuals from Southeast Asia and the Middle East and North Africa, we identified 27 miRNAs significantly associated with ICU admission (p < 0.01), and 97 miRNAs associated with at least one of the 8 blood phenotypes. [cross-cor] Integrating expression data for 632 miRNAs and genotyping data for ~260,000 SNPs, we identified 168 significant cis-expression quantitative trait loci (cis-eQTLs), of which 59 were associated with either ICU admission or one of the 8 blood phentoypes. Overall, our findings characterize the miRNA architecture of blood phenotypes during the early stages of COVID-19 infection, identify miRNAs associated with ICU admission and therefore COVID-19 disease severity, and suggest a potential genetic control of miRNA expression during early COVID-19 disease progression.
2023-06-14 | GSE220076 | GEO
Project description:BackgroundSeveral studies have recently addressed factors associated with severe Coronavirus disease 2019 (COVID-19); however, some medications and comorbidities have yet to be evaluated in a large matched cohort. We therefore explored the role of relevant comorbidities and medications in relation to the risk of intensive care unit (ICU) admission and mortality.MethodsAll ICU COVID-19 patients in Sweden until 27 May 2020 were matched to population controls on age and gender to assess the risk of ICU admission. Cases were identified, comorbidities and medications were retrieved from high-quality registries. Three conditional logistic regression models were used for risk of ICU admission and three Cox proportional hazards models for risk of ICU mortality, one with comorbidities, one with medications and finally with both models combined, respectively.ResultsWe included 1981 patients and 7924 controls. Hypertension, type 2 diabetes mellitus, chronic renal failure, asthma, obesity, being a solid organ transplant recipient and immunosuppressant medications were independent risk factors of ICU admission and oral anticoagulants were protective. Stroke, asthma, chronic obstructive pulmonary disease and treatment with renin-angiotensin-aldosterone inhibitors (RAASi) were independent risk factors of ICU mortality in the pre-specified primary analyses; treatment with statins was protective. However, after adjusting for the use of continuous renal replacement therapy, RAASi were no longer an independent risk factor.ConclusionIn our cohort oral anticoagulants were protective of ICU admission and statins was protective of ICU death. Several comorbidities and ongoing RAASi treatment were independent risk factors of ICU admission and ICU mortality.
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Project description:ObjectivesThis study aimed to investigate the association of baseline coagulation proteins with hospitalization variables in COVID-19 patients admitted to ICU, as well as coagulation system changes after one-year post-discharge, taking into account gender-specific bias in the coagulation profile.MethodsWe conducted a prospective longitudinal study on 49 ICU-admitted COVID-19 patients. Proteins were measured using a Luminex 200™. The association between coagulation protein levels and hospitalization variables was carried out by generalized linear models adjusted by the most relevant covariates.ResultsAt ICU admission, lower factor XII, antithrombin, and protein C levels were linked to the need for invasive mechanical ventilation (IMV) or its duration (p=0.028; p=0.047 and p=0.015, respectively). Likewise, lower factor XII, antithrombin, and prothrombin levels were associated with longer ICU length of stay (ICU LOS) (p=0.045; p=0.022; p=0.036, respectively). From baseline to the end of the follow-up, factor XII, antithrombin, prothrombin, and protein C levels notably increased in patients with longer ICU LOS. One-year post-discharge, differences were found for factor IX, aPTT, and INR. Gender-stratified analysis showed sustained alterations in males.ConclusionsDepleted specific coagulation factors on ICU admission are associated with increased severity in critically ill COVID-19 patients. Most coagulation alterations recover one-year post-discharge, except for factor IX, aPTT and INR, which remain reduced.
| S-EPMC11751041 | biostudies-literature
Project description:BackgroundRecent single-center reports have suggested that community-acquired bacteremic co-infection in the context of Coronavirus disease 2019 (COVID-19) may be an important driver of mortality; however, these reports have not been validated with a multicenter, demographically diverse, cohort study with data spanning the pandemic.MethodsIn this multicenter, retrospective cohort study, inpatient encounters were assessed for COVID-19 with community-acquired bacteremic co-infection using 48-h post-admission blood cultures and grouped by: (1) confirmed co-infection [recovery of bacterial pathogen], (2) suspected co-infection [negative culture with ≥ 2 antimicrobials administered], and (3) no evidence of co-infection [no culture]. The primary outcomes were in-hospital mortality, ICU admission, and mechanical ventilation. COVID-19 bacterial co-infection risk factors and impact on primary outcomes were determined using multivariate logistic regressions and expressed as adjusted odds ratios with 95% confidence intervals (Cohort, OR 95% CI, Wald test p value).ResultsThe studied cohorts included 13,781 COVID-19 inpatient encounters from 2020 to 2022 in the University of Alabama at Birmingham (UAB, n = 4075) and Ochsner Louisiana State University Health-Shreveport (OLHS, n = 9706) cohorts with confirmed (2.5%), suspected (46%), or no community-acquired bacterial co-infection (51.5%) and a comparison cohort consisting of 99,170 inpatient encounters from 2010 to 2019 (UAB pre-COVID-19 pandemic cohort). Significantly increased likelihood of COVID-19 bacterial co-infection was observed in patients with elevated ≥ 15 neutrophil-to-lymphocyte ratio (UAB: 1.95 [1.21-3.07]; OLHS: 3.65 [2.66-5.05], p < 0.001 for both) within 48-h of hospital admission. Bacterial co-infection was found to confer the greatest increased risk for in-hospital mortality (UAB: 3.07 [2.42-5.46]; OLHS: 4.05 [2.29-6.97], p < 0.001 for both), ICU admission (UAB: 4.47 [2.87-7.09], OLHS: 2.65 [2.00-3.48], p < 0.001 for both), and mechanical ventilation (UAB: 3.84 [2.21-6.12]; OLHS: 2.75 [1.87-3.92], p < 0.001 for both) across both cohorts, as compared to other risk factors for severe disease. Observed mortality in COVID-19 bacterial co-infection (24%) dramatically exceeds the mortality rate associated with community-acquired bacteremia in pre-COVID-19 pandemic inpatients (5.9%) and was consistent across alpha, delta, and omicron SARS-CoV-2 variants.ConclusionsElevated neutrophil-to-lymphocyte ratio is a prognostic indicator of COVID-19 bacterial co-infection within 48-h of admission. Community-acquired bacterial co-infection, as defined by blood culture-positive results, confers greater increased risk of in-hospital mortality, ICU admission, and mechanical ventilation than previously described risk factors (advanced age, select comorbidities, male sex) for COVID-19 mortality, and is independent of SARS-CoV-2 variant.
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Project description:As predicting the trajectory of COVID-19 is challenging, machine learning models could assist physicians in identifying high-risk individuals. This study compares the performance of 18 machine learning algorithms for predicting ICU admission and mortality among COVID-19 patients. Using COVID-19 patient data from the Mass General Brigham (MGB) Healthcare database, we developed and internally validated models using patients presenting to the Emergency Department (ED) between March-April 2020 (n = 3597) and further validated them using temporally distinct individuals who presented to the ED between May-August 2020 (n = 1711). We show that ensemble-based models perform better than other model types at predicting both 5-day ICU admission and 28-day mortality from COVID-19. CRP, LDH, and O2 saturation were important for ICU admission models whereas eGFR <60 ml/min/1.73 m2, and neutrophil and lymphocyte percentages were the most important variables for predicting mortality. Implementing such models could help in clinical decision-making for future infectious disease outbreaks including COVID-19.
| S-EPMC8140139 | biostudies-literature
Project description:This study aimed to develop risk scores based on clinical characteristics at presentation to predict intensive care unit (ICU) admission and mortality in COVID-19 patients. 641 hospitalized patients with laboratory-confirmed COVID-19 were selected from 4997 persons under investigation. We performed a retrospective review of medical records of demographics, comorbidities and laboratory tests at the initial presentation. Primary outcomes were ICU admission and death. Logistic regression was used to identify independent clinical variables predicting the two outcomes. The model was validated by splitting the data into 70% for training and 30% for testing. Performance accuracy was evaluated using area under the curve (AUC) of the receiver operating characteristic analysis (ROC). Five significant variables predicting ICU admission were lactate dehydrogenase, procalcitonin, pulse oxygen saturation, smoking history, and lymphocyte count. Seven significant variables predicting mortality were heart failure, procalcitonin, lactate dehydrogenase, chronic obstructive pulmonary disease, pulse oxygen saturation, heart rate, and age. The mortality group uniquely contained cardiopulmonary variables. The risk score model yielded good accuracy with an AUC of 0.74 ([95% CI, 0.63-0.85], p = 0.001) for predicting ICU admission and 0.83 ([95% CI, 0.73-0.92], p<0.001) for predicting mortality for the testing dataset. This study identified key independent clinical variables that predicted ICU admission and mortality associated with COVID-19. This risk score system may prove useful for frontline physicians in clinical decision-making under time-sensitive and resource-constrained environment.
| S-EPMC7392248 | biostudies-literature
Project description:BackgroundAs lung ultrasound (LUS) has emerged as a diagnostic tool in patients with COVID-19, we sought to investigate the association between LUS findings and the composite in-hospital outcome of ARDS incidence, ICU admission, and all-cause mortality.MethodsIn this prospective, multi-center, observational study, adults with laboratory-confirmed SARS-CoV-2 infection were enrolled from non-ICU in-patient units. Subjects underwent an LUS evaluating a total of 8 zones. Images were analyzed off-line, blinded to clinical variables and outcomes. A LUS score was developed to integrate LUS findings: ≥ 3 B-lines corresponded to a score of 1, confluent B-lines to a score of 2, and subpleural or lobar consolidation to a score of 3. The total LUS score ranged from 0-24 per subject.ResultsAmong 215 enrolled subjects, 168 with LUS data and no current signs of ARDS or ICU admission (mean age 59 y, 56% male) were included. One hundred thirty-six (81%) subjects had pathologic LUS findings in ≥ 1 zone (≥ 3 B-lines, confluent B-lines, or consolidations). Markers of disease severity at baseline were higher in subjects with the composite outcome (n = 31, 18%), including higher median C-reactive protein (90 mg/L vs 55, P < .001) and procalcitonin levels (0.35 μg/L vs 0.13, P = .033) and higher supplemental oxygen requirements (median 4 L/min vs 2, P = .001). However, LUS findings and score did not differ significantly between subjects with the composite outcome and those without, and were not associated with outcomes in unadjusted and adjusted logistic regression analyses.ConclusionsPathologic findings on LUS were common a median of 3 d after admission in this cohort of non-ICU hospitalized subjects with COVID-19 and did not differ among subjects who experienced the composite outcome of incident ARDS, ICU admission, and all-cause mortality compared to subjects who did not. These findings should be confirmed in future investigations. The study is registered at Clinicaltrials.gov (NCT04377035).
| S-EPMC10408365 | biostudies-literature