Quantitative assessment of fibrosis-4 score and adverse clinical outcomes in patients with COVID-19.
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ABSTRACT:
SUBMITTER: Tang K
PROVIDER: S-EPMC9244247 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:We perform shotgun transcriptome sequencing of human RNA obtained from nasopharyngeal swabs of patients with COVID-19, and identify a molecular signature associated with disease severity
2020-12-19 | GSE162835 | GEO
Project description:Background and aimsWe investigated the association between liver fibrosis scores and clinical outcomes in patients with COVID-19.MethodsWe performed a post-hoc analysis among patients with COVID-19 from the trial study Outcomes Related to COVID-19 treated with Hydroxychloroquine among Inpatients with symptomatic Disease (ORCHID) trial. The relationship between aspartate aminotransferase (AST) to platelet ratio index (APRI), non-alcoholic fatty liver disease fibrosis score (NFS), Fibrosis-4 index (FIB-4), and discharge and death during the 28-days of hospitalization was investigated.ResultsDuring the 28 days after randomization, 237 (80.6%) patients were discharged while 31 (10.5%) died among the 294 patients with COVID-19. The prevalence for advanced fibrosis was estimated to be 34, 21.8, and 37.8% for FIB-4 (>2.67), APRI (>1), and NFS (>0.676), respectively. In multivariate analysis, FIB-4 >2.67 [28-days discharge: hazard ratio (HR): 0.62; 95% CI: 0.46-0.84; 28-days mortality: HR: 5.13; 95% CI: 2.18-12.07], APRI >1 (28-days discharge: HR: 0.62; 95% CI: 0.44-0.87; 28-days mortality: HR: 2.85, 95% CI: 1.35-6.03), and NFS >0.676 (28-days discharge: HR: 0.5; 95% CI: 0.35-0.69; 28-days mortality: HR: 4.17; 95% CI: 1.62-10.72) was found to significantly reduce the discharge rate and increase the risk of death. Additionally, FIB-4, APRI, and NFS were found to have good predictive ability and calibration performance for 28-day death (C-index: 0.74 for FIB-4, 0.657 for APRI, and 0.745 for NFS) and discharge (C-index: 0.649 for FIB-4, 0.605 for APRI, and 0.685 for NFS).ConclusionIn hospitalized patients with COVID-19, FIB-4, APRI, and NFS may be good predictors for death and discharge within 28 days. The link between liver fibrosis and the natural history of COVID-19 should be further investigated.
| S-EPMC9024307 | biostudies-literature
Project description:AimsMidwall myocardial fibrosis on cardiovascular magnetic resonance (CMR) is a marker of early ventricular decompensation and adverse outcomes in aortic stenosis (AS). We aimed to develop and validate a novel clinical score using variables associated with midwall fibrosis.Methods and resultsOne hundred forty-seven patients (peak aortic velocity (Vmax) 3.9 [3.2,4.4] m/s) underwent CMR to determine midwall fibrosis (CMR cohort). Routine clinical variables that demonstrated significant association with midwall fibrosis were included in a multivariate logistic score. We validated the prognostic value of the score in two separate outcome cohorts of asymptomatic patients (internal: n = 127, follow-up 10.3 [5.7,11.2] years; external: n = 289, follow-up 2.6 [1.6,4.5] years). Primary outcome was a composite of AS-related events (cardiovascular death, heart failure, and new angina, dyspnoea, or syncope). The final score consisted of age, sex, Vmax, high-sensitivity troponin I concentration, and electrocardiographic strain pattern [c-statistic 0.85 (95% confidence interval 0.78-0.91), P < 0.001; Hosmer-Lemeshow χ(2) = 7.33, P = 0.50]. Patients in the outcome cohorts were classified according to the sensitivity and specificity of this score (both at 98%): low risk (probability score <7%), intermediate risk (7-57%), and high risk (>57%). In the internal outcome cohort, AS-related event rates were >10-fold higher in high-risk patients compared with those at low risk (23.9 vs. 2.1 events/100 patient-years, respectively; log rank P < 0.001). Similar findings were observed in the external outcome cohort (31.6 vs. 4.6 events/100 patient-years, respectively; log rank P < 0.001).ConclusionWe propose a clinical score that predicts adverse outcomes in asymptomatic AS patients and potentially identifies high-risk patients who may benefit from early valve replacement.
| S-EPMC4761400 | biostudies-literature
Project description:Severe coronavirus disease 2019 (COVID-19) is characterized by hyperinflammation, vascular damage, and hypercoagulability. Insufficient responses of Annexin A1 (AnxA1), a pro-resolving inhibitor of neutrophil infiltration and activation, might contribute to a severe course of the disease. We longitudinally evaluated AnxA1's role in terms of inflammation, vascular damage, and clinical outcomes in a large prospective cohort of patients with COVID-19. AnxA1 was measured at presentation and during follow-up in the sera of 220 consecutive patients who presented at our hospital during the first wave. AnxA1 was significantly higher in the moderate and severe cases of COVID-19 compared to the healthy controls. Elevated AnxA1 was associated with markers of inflammation and endothelial damage. AnxA1 was significantly higher in patients with thrombotic events and ICU admission. Multivariable logistic regression indicated baseline AnxA1 (per ten units) as a predictor of thrombotic events. Linear mixed models predicted that AnxA1 tended to increase more steeply over time in patients without adverse events, with a statistically significant rise in patients without thrombotic events. These findings might reflect an insufficient increase in AnxA1 as a response to the excessive hyperinflammation in COVID-19. Future studies should evaluate whether hyperinflammation could be reduced through the administration of human recombinant AnxA1 or Ac2-26 peptide.
| S-EPMC9781714 | biostudies-literature
Project description:ObjectivesTo develop and validate a machine learning model for the prediction of adverse outcomes in hospitalized patients with COVID-19.MethodsWe included 424 patients with non-severe COVID-19 on admission from January 17, 2020, to February 17, 2020, in the primary cohort of this retrospective multicenter study. The extent of lung involvement was quantified on chest CT images by a deep learning-based framework. The composite endpoint was the occurrence of severe or critical COVID-19 or death during hospitalization. The optimal machine learning classifier and feature subset were selected for model construction. The performance was further tested in an external validation cohort consisting of 98 patients.ResultsThere was no significant difference in the prevalence of adverse outcomes (8.7% vs. 8.2%, p = 0.858) between the primary and validation cohorts. The machine learning method extreme gradient boosting (XGBoost) and optimal feature subset including lactic dehydrogenase (LDH), presence of comorbidity, CT lesion ratio (lesion%), and hypersensitive cardiac troponin I (hs-cTnI) were selected for model construction. The XGBoost classifier based on the optimal feature subset performed well for the prediction of developing adverse outcomes in the primary and validation cohorts, with AUCs of 0.959 (95% confidence interval [CI]: 0.936-0.976) and 0.953 (95% CI: 0.891-0.986), respectively. Furthermore, the XGBoost classifier also showed clinical usefulness.ConclusionsWe presented a machine learning model that could be effectively used as a predictor of adverse outcomes in hospitalized patients with COVID-19, opening up the possibility for patient stratification and treatment allocation.Key points• Developing an individually prognostic model for COVID-19 has the potential to allow efficient allocation of medical resources. • We proposed a deep learning-based framework for accurate lung involvement quantification on chest CT images. • Machine learning based on clinical and CT variables can facilitate the prediction of adverse outcomes of COVID-19.
| S-EPMC8046645 | biostudies-literature
Project description:BackgroundRecent studies have demonstrated a complex interplay between comorbid cardiovascular disease, COVID-19 pathophysiology, and poor clinical outcomes. Coronary artery calcification (CAC) may therefore aid in risk stratification of COVID-19 patients.MethodsNon-contrast chest CT studies on 180 COVID-19 patients ≥ age 21 admitted from March 1, 2020 to April 27, 2020 were retrospectively reviewed by two radiologists to determine CAC scores. Following feature selection, multivariable logistic regression was utilized to evaluate the relationship between CAC scores and patient outcomes.ResultsThe presence of any identified CAC was associated with intubation (AOR: 3.6, CI: 1.4-9.6) and mortality (AOR: 3.2, CI: 1.4-7.9). Severe CAC was independently associated with intubation (AOR: 4.0, CI: 1.3-13) and mortality (AOR: 5.1, CI: 1.9-15). A greater CAC score (UOR: 1.2, CI: 1.02-1.3) and number of vessels with calcium (UOR: 1.3, CI: 1.02-1.6) was associated with mortality. Visualized coronary stent or coronary artery bypass graft surgery (CABG) had no statistically significant association with intubation (AOR: 1.9, CI: 0.4-7.7) or death (AOR: 3.4, CI: 1.0-12).ConclusionCOVID-19 patients with any CAC were more likely to require intubation and die than those without CAC. Increasing CAC and number of affected arteries was associated with mortality. Severe CAC was associated with higher intubation risk. Prior CABG or stenting had no association with elevated intubation or death.
| S-EPMC7875715 | biostudies-literature
Project description:To identify the association between the kinetics of viral load and clinical outcome in severe coronavirus disease 2019 (COVID-19) patients, a retrospective study was performed by involved 188 hospitalized severe COVID-19 patients in the LOTUS China trial. Among the collected 578 paired throat swab (TS) and anal swab (AS) samples, viral RNA was detected in 193 (33.4%) TS and 121 (20.9%) AS. A higher viral RNA load was found in TS than that of AS, with means of 1.0 × 106 and 2.3 × 105 copies/ml, respectively. In non-survivors, the viral RNA in AS was detected earlier than that in survivors (median of 14 days vs 19 days, P = 0.007). The positivity and viral load in AS were higher in non-survivors than that of survivors at week 2 post symptom onset (P = 0.006). A high initial viral load in AS was associated with death (OR 1.368, 95% CI 1.076-1.741, P = 0.011), admission to the intensive care unit (OR 1.237, 95% CI 1.001-1.528, P = 0.049) and need for invasive mechanical ventilation (OR 1.340, 95% CI 1.076-1.669, P = 0.009). Our findings indicated viral replication in extrapulmonary sites should be monitored intensively during antiviral therapy.
| S-EPMC7782020 | biostudies-literature
Project description:The vast majority of SARS-CoV-2 infections are uncomplicated and do not require hospitalization, but these infections contribute to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of virologic and clinical outcomes in planning future treatment studies of COVID-19. We recently completed a randomized clinical trial of Pegylated PegIinterferon Lambda for treatment of SARS-CoV-2 infected patients conducted in the Stanford COVID-19 CTRU. Leveraging longitudinal samples and data from this trial, we define early immunebaseline and infection-induced signatures that predict the duration of viral shedding, resolution of symptoms, and immunologic memory.
2021-10-01 | GSE178967 | GEO
Project description:BackgroundLittle is known about the association between acute mental changes and adverse outcomes in hospitalized adults with COVID-19.ObjectivesTo investigate the occurrence of delirium in hospitalized patients with COVID-19 and explore its association with adverse outcomes.DesignLongitudinal observational study.SettingTertiary university hospital dedicated to the care of severe cases of COVID-19 in São Paulo, Brazil.ParticipantsA total of 707 patients, aged 50 years or older, consecutively admitted to the hospital between March and May 2020.MeasurementsWe completed detailed reviews of electronic medical records to collect our data. We identified delirium occurrence using the Chart-Based Delirium Identification Instrument (CHART-DEL). Trained physicians with a background in geriatric medicine completed all CHART-DEL assessments. We complemented our baseline clinical information using telephone interviews with participants or their proxy. Our outcomes of interest were in-hospital death, length of stay, admission to intensive care, and ventilator utilization. We adjusted all multivariable analyses for age, sex, clinical history, vital signs, and relevant laboratory biomarkers (lymphocyte count, C-reactive protein, glomerular filtration rate, D-dimer, and albumin).ResultsOverall, we identified delirium in 234 participants (33%). On admission, 86 (12%) were delirious. We observed 273 deaths (39%) in our sample, and in-hospital mortality reached 55% in patients who experienced delirium. Delirium was associated with in-hospital death, with an adjusted odds ratio of 1.75 (95% confidence interval = 1.15-2.66); the association held both in middle-aged and older adults. Delirium was also associated with increased length of stay, admission to intensive care, and ventilator utilization.ConclusionDelirium was independently associated with in-hospital death in adults aged 50 years and older with COVID-19. Despite the difficulties for patient care during the pandemic, clinicians should routinely monitor delirium when assessing severity and prognosis of COVID-19 patients.
| S-EPMC7460960 | biostudies-literature
Project description:PurposeWe aimed to evaluate the relation between admission COVID-19 associated hyperinflammatory syndrome (cHIS) score and intensive care unit (ICU) outcomes.Materials and methodsPatients with laboratory confirmed COVID-19 admitted to our ICU between 20th March 2020-15th June 2021 were included. Patients who received immunomodulatory treatment except corticosteroids were excluded. Main outcomes were ICU mortality and invasive mechanical ventilation (IMV) requirement after ICU admission.ResultsThree hundred and seventy patients with a median (IQR) age of 66 (56-77) were analyzed. Median admission cHIS score was 3 (2-4). A cHIS score ≥3 was found to be associated with ICU mortality (sensitivity = 0.63, specificity = 0.50; p < 0.01) and IMV requirement after ICU admission (sensitivity = 0.61, specificity = 0.51; p < 0.01). Patients with an admission cHIS score ≥3 (n = 199) had worse median admission APACHEII, SOFA scores and PaO2/FiO2 ratio than others (n = 171) (p < 0.01). IMV requirement after ICU admission (38.5% vs 26.1%;p = 0.03), ICU (36.2% vs 25.1%;p = 0.02), hospital (39.1% vs 26.9%;p = 0.01) and 28th day (28.1% vs 19.1%;p = 0.04) mortality were higher in patients with admission cHIS score ≥3 than others (p < 0.01). Age <65 years, malignancy and higher admission SOFA score were independent variables associated with admission cHIS score ≥3.ConclusionCritically-ill COVID-19 patients with admission cHIS score ≥3 have worse disease severity and outcomes than other patients.
| S-EPMC9549159 | biostudies-literature