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Predictors of Acute Encephalopathy in Patients with COVID-19.

ABSTRACT: The majority of patients with severe COVID-19 suffer from delirium as the main sign of encephalopathy associated with this viral infection. The aim of this study was to identify early markers of the development of this condition. The prospective cohort-based study included patients with community-acquired pneumonia and confirmed pulmonary tissue infiltration based on CT data, with a lesion consisting of at least 25% of one lung. The main group included patients who have developed acute encephalopathy (10 patients, 3 (30%) women; average age, 47.9 ± 7.3 years). The control group included patients who at discharge did not have acute encephalopathy (20 patients, 11 (55%) women; average age, 51.0 ± 10.5 years). The study collected clinical examination data, comprehensive laboratory data, neurophysiological data, pulse oximetry and CT data to identify the predictors of acute encephalopathy (study ClinicalTrials.gov identifier NCT04405544). Data analysis showed a significant relationship between encephalopathy with the degree of lung tissue damage, arterial hypertension, and type 2 diabetes mellitus, as well as with D-dimer, LDH, and lymphopenia. The development of encephalopathy is secondary to the severity of the patient's condition since a more severe course of the coronavirus infection leads to hypoxic brain damage.

SUBMITTER: Vinogradov OI

PROVIDER: S-EPMC8584437 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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Predictors of Acute Encephalopathy in Patients with COVID-19.

Vinogradov Oleg I OI Ogarkova Tatyana K TK Shamtieva Kamila V KV Alexandrov Pavel V PV Mushba Astanda V AV Kanshina Daria S DS Yakovleva Daria V DV Surma Maria A MA Nikolaev Ilia S IS Gorst Nadezhda Kh NK

Journal of clinical medicine 20211020 21

<h4>Introduction</h4>The majority of patients with severe COVID-19 suffer from delirium as the main sign of encephalopathy associated with this viral infection. The aim of this study was to identify early markers of the development of this condition.<h4>Materials</h4>The prospective cohort-based study included patients with community-acquired pneumonia and confirmed pulmonary tissue infiltration based on CT data, with a lesion consisting of at least 25% of one lung. The main group included patie ...[more]

PMID: 34768339

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Project description:AbstractDeep venous thrombosis (DVT) is associated with high mortality in coronavirus disease 2019 (COVID-19) but there remains uncertainty about the benefit of anti-coagulation prophylaxis and how to decide when ultrasound screening is indicated. We aimed to determine parameters predicting which COVID-19 patients are at risk of DVT and to assess the benefit of prophylactic anti-coagulation.Adult hospitalized patients with positive severe acute respiratory syndrome coronavirus-2 reverse transcription-polymerase chain reaction (RT-PCR) undergoing venous duplex ultrasound for DVT assessment (n = 451) were retrospectively reviewed. Clinical and laboratory data within 72 hours of ultrasound were collected. Using split sampling and a 10-fold cross-validation, a random forest model was developed to find the most important variables for predicting DVT. Different d-dimer cutoffs were examined for classification of DVT. We also compared the rate of DVT between the patients going and not going under thromboprophylaxis.DVT was found in 65 (14%) of 451 reverse transcription-polymerase chain reaction positive patients. The random forest model, trained and cross-validated on 2/3 of the original sample (n = 301), had area under the receiver operating characteristic curve = 0.91 (95% confidence interval [CI]: 0.85-0.97) for prediction of DVT in the test set (n = 150), with sensitivity = 93% (95%CI: 68%-99%) and specificity = 82% (95%CI: 75%-88%). The following variables had the highest importance: d-dimer, thromboprophylaxis, systolic blood pressure, admission to ultrasound interval, and platelets. Thromboprophylaxis reduced DVT risk 4-fold from 26% to 6% (P < .001), while anti-coagulation therapy led to hemorrhagic complications in 14 (22%) of 65 patients with DVT including 2 fatal intra-cranial hemorrhages. D-dimer was the most important predictor with area under curve = 0.79 (95%CI: 0.73-0.86) by itself, and a 5000 ng/mL threshold at 7 days postCOVID-19 symptom onset had 75% (95%CI: 53%-90%) sensitivity and 81% (95%CI: 72%-88%) specificity. In comparison with d-dimer alone, the random forest model showed 68% versus 32% specificity at 95% sensitivity, and 44% versus 23% sensitivity at 95% specificity.D-dimer >5000 ng/mL predicts DVT with high accuracy suggesting regular monitoring with d-dimer in the early stages of COVID-19 may be useful. A random forest model improved the prediction of DVT. Thromboprophylaxis reduced DVT in COVID-19 patients and should be considered in all patients. Full anti-coagulation therapy has a risk of life-threatening hemorrhage.

Project description:BackgroundToxic metabolic encephalopathy (TME) has been reported in 7-31% of hospitalized patients with coronavirus disease 2019 (COVID-19); however, some reports include sedation-related delirium and few data exist on the etiology of TME. We aimed to identify the prevalence, etiologies, and mortality rates associated with TME in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-positive patients.MethodsWe conducted a retrospective, multicenter, observational cohort study among patients with reverse transcriptase-polymerase chain reaction-confirmed SARS-CoV-2 infection hospitalized at four New York City hospitals in the same health network between March 1, 2020, and May 20, 2020. TME was diagnosed in patients with altered mental status off sedation or after an adequate sedation washout. Patients with structural brain disease, seizures, or primary neurological diagnoses were excluded. The coprimary outcomes were the prevalence of TME stratified by etiology and in-hospital mortality (excluding comfort care only patients) assessed by using a multivariable time-dependent Cox proportional hazards models with adjustment for age, race, sex, intubation, intensive care unit requirement, Sequential Organ Failure Assessment scores, hospital location, and date of admission.ResultsAmong 4491 patients with COVID-19, 559 (12%) were diagnosed with TME, of whom 435 of 559 (78%) developed encephalopathy immediately prior to hospital admission. The most common etiologies were septic encephalopathy (n = 247 of 559 [62%]), hypoxic-ischemic encephalopathy (HIE) (n = 331 of 559 [59%]), and uremia (n = 156 of 559 [28%]). Multiple etiologies were present in 435 (78%) patients. Compared with those without TME (n = 3932), patients with TME were older (76 vs. 62 years), had dementia (27% vs. 3%) or psychiatric history (20% vs. 10%), were more often intubated (37% vs. 20%), had a longer hospital length of stay (7.9 vs. 6.0 days), and were less often discharged home (25% vs. 66% [all P < 0.001]). Excluding comfort care patients (n = 267 of 4491 [6%]) and after adjustment for confounders, TME remained associated with increased risk of in-hospital death (n = 128 of 425 [30%] patients with TME died, compared with n = 600 of 3799 [16%] patients without TME; adjusted hazard ratio [aHR] 1.24, 95% confidence interval [CI] 1.02-1.52, P = 0.031), and TME due to hypoxemia conferred the highest risk (n = 97 of 233 [42%] patients with HIE died, compared with n = 631 of 3991 [16%] patients without HIE; aHR 1.56, 95% CI 1.21-2.00, P = 0.001).ConclusionsTME occurred in one in eight hospitalized patients with COVID-19, was typically multifactorial, and was most often due to hypoxemia, sepsis, and uremia. After we adjustment for confounding factors, TME was associated with a 24% increased risk of in-hospital mortality.

Dataset Information

Predictors of Acute Encephalopathy in Patients with COVID-19.

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Predictors of Acute Encephalopathy in Patients with COVID-19.

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