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1.
Ann Neurol ; 2022 Mar 07.
Article in English | MEDLINE | ID: covidwho-1729093

ABSTRACT

OBJECTIVE: Estimate time to recovery of command-following and associations between hypoxemia with time to recovery of command-following METHODS: In this multi-center, retrospective, cohort study during the initial surge of the United States' pandemic (March-July 2020) we estimate the time from intubation to recovery of command-following, using Kaplan Meier cumulative-incidence curves and Cox proportional hazard models. Patients were included if admitted to one of three hospitals with severe COVID-19, endotracheal intubation for at least seven days, and impairment of consciousness (Glasgow Coma Scale motor score <6). RESULTS: 571 patients of the 795 patients recovered command-following. The median time to recovery of command-following was 30 days (95%-confidence interval [CI]:27-32). Median time to recovery of command-following increased by 16 days for patients with at least one episode of an arterial partial pressure of oxygen (PaO2 ) value ≤55mmHg (p<0.001), and 25% recovered ≥10 days after cessation of mechanical ventilation. The time to recovery of consciousness was associated with hypoxemia (PaO2 ≤55mmHg hazard ratio (HR):0.56; 95%-CI:0.46-0.68; PaO2 ≤70 HR:0.88; 95%-CI:0.85-0.91), and each additional day of hypoxemia decreased the likelihood of recovery, accounting for confounders including sedation. These findings were confirmed among patients without any imagining evidence of structural brain injury (n=199), and in a non-overlapping second surge cohort (N=427, October-April 2021). INTERPRETATION: Survivors of severe COVID-19 commonly recover consciousness weeks after cessation of mechanical ventilation. Long recovery periods are associated with more severe hypoxemia. This relationship is not explained by sedation or brain injury identified on clinical imaging and should inform decisions about life-sustaining therapies. This article is protected by copyright. All rights reserved.

2.
J Neuroophthalmol ; 2022 Feb 15.
Article in English | MEDLINE | ID: covidwho-1700156

ABSTRACT

BACKGROUND: The literature on neurological manifestations, cerebrospinal fluid analyses, and autopsies in patients with COVID-19 continues to grow. The proposed mechanisms for neurological disease in patients with COVID-19 include indirect processes such as inflammation, microvascular injury, and hypoxic-ischemic damage. An alternate hypothesis suggests direct viral entry of SARS-CoV-2 into the brain and cerebrospinal fluid, given varying reports regarding isolation of viral components from these anatomical sites. EVIDENCE ACQUISITION: PubMed, Google Scholar databases, and neuroanatomical textbooks were manually searched and reviewed. RESULTS: We provide clinical concepts regarding the mechanisms of viral pathogen invasion in the central nervous system (CNS); advances in our mechanistic understanding of CNS invasion in well-known neurotropic pathogens can aid in understanding how viruses evolve strategies to enter brain parenchyma. We also present the structural components of CNS compartments that influence viral entry, focusing on hematogenous and transneuronal spread, and discuss this evidence as it relates to our understanding of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). CONCLUSIONS: Although there is a paucity of data supporting direct viral entry of SARS-CoV-2 in humans, increasing our knowledge of the structural components of CNS compartments that block viral entry and pathways exploited by pathogens is fundamental to preparing clinicians and researchers for what to expect when a novel emerging virus with neurological symptoms establishes infection in the CNS, and how to design therapeutics to mitigate such an infection.

3.
Ann Neurol ; 91(3): 367-379, 2022 03.
Article in English | MEDLINE | ID: covidwho-1636023

ABSTRACT

OBJECTIVE: The purpose of this study was to describe cerebrovascular, neuropathic, and autonomic features of post-acute sequelae of coronavirus disease 2019 ((COVID-19) PASC). METHODS: This retrospective study evaluated consecutive patients with chronic fatigue, brain fog, and orthostatic intolerance consistent with PASC. Controls included patients with postural tachycardia syndrome (POTS) and healthy participants. Analyzed data included surveys and autonomic (Valsalva maneuver, deep breathing, sudomotor, and tilt tests), cerebrovascular (cerebral blood flow velocity [CBFv] monitoring in middle cerebral artery), respiratory (capnography monitoring), and neuropathic (skin biopsies for assessment of small fiber neuropathy) testing and inflammatory/autoimmune markers. RESULTS: Nine patients with PASC were evaluated 0.8 ± 0.3 years after a mild COVID-19 infection, and were treated as home observations. Autonomic, pain, brain fog, fatigue, and dyspnea surveys were abnormal in PASC and POTS (n = 10), compared with controls (n = 15). Tilt table test reproduced the majority of PASC symptoms. Orthostatic CBFv declined in PASC (-20.0 ± 13.4%) and POTS (-20.3 ± 15.1%), compared with controls (-3.0 ± 7.5%, p = 0.001) and was independent of end-tidal carbon dioxide in PASC, but caused by hyperventilation in POTS. Reduced orthostatic CBFv in PASC included both subjects without (n = 6) and with (n = 3) orthostatic tachycardia. Dysautonomia was frequent (100% in both PASC and POTS) but was milder in PASC (p = 0.002). PASC and POTS cohorts diverged in frequency of small fiber neuropathy (89% vs 60%) but not in inflammatory markers (67% vs 70%). Supine and orthostatic hypocapnia was observed in PASC. INTERPRETATION: PASC following mild COVID-19 infection is associated with multisystem involvement including: (1) cerebrovascular dysregulation with persistent cerebral arteriolar vasoconstriction; (2) small fiber neuropathy and related dysautonomia; (3) respiratory dysregulation; and (4) chronic inflammation. ANN NEUROL 2022;91:367-379.


Subject(s)
Blood Pressure/physiology , COVID-19/complications , Cerebrovascular Circulation/physiology , Heart Rate/physiology , Inflammation Mediators/blood , Adult , COVID-19/blood , COVID-19/diagnosis , COVID-19/physiopathology , Fatigue/blood , Fatigue/diagnosis , Fatigue/physiopathology , Female , Humans , Male , Middle Aged , Orthostatic Intolerance/blood , Orthostatic Intolerance/diagnosis , Orthostatic Intolerance/physiopathology , Retrospective Studies
4.
Nat Med ; 28(1): 20-23, 2022 01.
Article in English | MEDLINE | ID: covidwho-1636011
5.
J Neurol Sci ; 430: 120023, 2021 Nov 15.
Article in English | MEDLINE | ID: covidwho-1446884

ABSTRACT

OBJECTIVE: Little is known about CSF profiles in patients with acute COVID-19 infection and neurological symptoms. Here, CSF was tested for SARS-CoV-2 RNA and inflammatory cytokines and chemokines and compared to controls and patients with known neurotropic pathogens. METHODS: CSF from twenty-seven consecutive patients with COVID-19 and neurological symptoms was assayed for SARS-CoV-2 RNA using quantitative reverse transcription PCR (RT-qPCR) and unbiased metagenomic sequencing. Assays for blood brain barrier (BBB) breakdown (CSF:serum albumin ratio (Q-Alb)), and proinflammatory cytokines and chemokines (IL-6, IL-8, IL-15, IL-16, monocyte chemoattractant protein -1 (MCP-1) and monocyte inhibitory protein - 1ß (MIP-1ß)) were performed in 23 patients and compared to CSF from patients with HIV-1 (16 virally suppressed, 5 unsuppressed), West Nile virus (WNV) (n = 4) and 16 healthy controls (HC). RESULTS: Median CSF cell count for COVID-19 patients was 1 white blood cell/µL; two patients were infected with a second pathogen (Neisseria, Cryptococcus neoformans). No CSF samples had detectable SARS-CoV-2 RNA by either detection method. In patients with COVID-19 only, CSF IL-6, IL-8, IL-15, and MIP-1ß levels were higher than HC and suppressed HIV (corrected-p < 0.05). MCP-1 and MIP-1ß levels were higher, while IL-6, IL-8, IL-15 were similar in COVID-19 compared to WNV patients. Q-Alb correlated with all proinflammatory markers, with IL-6, IL-8, and MIP-1ß (r ≥ 0.6, p < 0.01) demonstrating the strongest associations. CONCLUSIONS: Lack of SARS-CoV-2 RNA in CSF is consistent with pre-existing literature. Evidence of intrathecal proinflammatory markers in a subset of COVID-19 patients with BBB breakdown despite minimal CSF pleocytosis is atypical for neurotropic pathogens.


Subject(s)
COVID-19 , Inflammation/virology , RNA, Viral/cerebrospinal fluid , Blood-Brain Barrier , COVID-19/physiopathology , Case-Control Studies , Chemokines , Cytokines , Humans , SARS-CoV-2
6.
Neurology ; 97(8): e849-e858, 2021 08 24.
Article in English | MEDLINE | ID: covidwho-1261289

ABSTRACT

OBJECTIVE: To explore the spectrum of skeletal muscle and nerve pathology of patients who died after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and to assess for direct viral invasion of these tissues. METHODS: Psoas muscle and femoral nerve sampled from 35 consecutive autopsies of patients who died after SARS-CoV-2 infection and 10 SARS-CoV-2-negative controls were examined under light microscopy. Clinical and laboratory data were obtained by chart review. RESULTS: In SARS-CoV-2-positive patients, mean age at death was 67.8 years (range 43-96 years), and the duration of symptom onset to death ranged from 1 to 49 days. Four patients had neuromuscular symptoms. Peak creatine kinase was elevated in 74% (mean 959 U/L, range 29-8,413 U/L). Muscle showed type 2 atrophy in 32 patients, necrotizing myopathy in 9, and myositis in 7. Neuritis was seen in 9. Major histocompatibility complex-1 (MHC-1) expression was observed in all cases of necrotizing myopathy and myositis and in 8 additional patients. Abnormal expression of myxovirus resistance protein A (MxA) was present on capillaries in muscle in 9 patients and in nerve in 7 patients. SARS-CoV-2 immunohistochemistry was negative in muscle and nerve in all patients. In the 10 controls, muscle showed type 2 atrophy in all patients, necrotic muscle fibers in 1, MHC-1 expression in nonnecrotic/nonregenerating fibers in 3, MxA expression on capillaries in 2, and inflammatory cells in none, and nerves showed no inflammatory cells or MxA expression. CONCLUSIONS: Muscle and nerve tissue demonstrated inflammatory/immune-mediated damage likely related to release of cytokines. There was no evidence of direct SARS-CoV-2 invasion of these tissues. CLASSIFICATION OF EVIDENCE: This study provides Class IV evidence that muscle and nerve biopsies document a variety of pathologic changes in patients dying of coronavirus disease 2019 (COVID-19).


Subject(s)
COVID-19/pathology , Muscle, Skeletal/pathology , Peripheral Nerves/pathology , Adult , Aged , Aged, 80 and over , Autopsy , COVID-19/immunology , COVID-19/virology , Female , Humans , Male , Middle Aged , Muscle, Skeletal/immunology , Muscle, Skeletal/virology , Peripheral Nerves/immunology , Peripheral Nerves/virology
7.
Front Neurol ; 12: 642912, 2021.
Article in English | MEDLINE | ID: covidwho-1202073

ABSTRACT

Objectives: Patients with comorbidities are at increased risk for poor outcomes in COVID-19, yet data on patients with prior neurological disease remains limited. Our objective was to determine the odds of critical illness and duration of mechanical ventilation in patients with prior cerebrovascular disease and COVID-19. Methods: A observational study of 1,128 consecutive adult patients admitted to an academic center in Boston, Massachusetts, and diagnosed with laboratory-confirmed COVID-19. We tested the association between prior cerebrovascular disease and critical illness, defined as mechanical ventilation (MV) or death by day 28, using logistic regression with inverse probability weighting of the propensity score. Among intubated patients, we estimated the cumulative incidence of successful extubation without death over 45 days using competing risk analysis. Results: Of the 1,128 adults with COVID-19, 350 (36%) were critically ill by day 28. The median age of patients was 59 years (SD: 18 years) and 640 (57%) were men. As of June 2nd, 2020, 127 (11%) patients had died. A total of 177 patients (16%) had a prior cerebrovascular disease. Prior cerebrovascular disease was significantly associated with critical illness (OR = 1.54, 95% CI = 1.14-2.07), lower rate of successful extubation (cause-specific HR = 0.57, 95% CI = 0.33-0.98), and increased duration of intubation (restricted mean time difference = 4.02 days, 95% CI = 0.34-10.92) compared to patients without cerebrovascular disease. Interpretation: Prior cerebrovascular disease adversely affects COVID-19 outcomes in hospitalized patients. Further study is required to determine if this subpopulation requires closer monitoring for disease progression during COVID-19.

8.
Ann Neurol ; 89(5): 872-883, 2021 05.
Article in English | MEDLINE | ID: covidwho-1148790

ABSTRACT

OBJECTIVE: The aim was to determine the prevalence and risk factors for electrographic seizures and other electroencephalographic (EEG) patterns in patients with Coronavirus disease 2019 (COVID-19) undergoing clinically indicated continuous electroencephalogram (cEEG) monitoring and to assess whether EEG findings are associated with outcomes. METHODS: We identified 197 patients with COVID-19 referred for cEEG at 9 participating centers. Medical records and EEG reports were reviewed retrospectively to determine the incidence of and clinical risk factors for seizures and other epileptiform patterns. Multivariate Cox proportional hazards analysis assessed the relationship between EEG patterns and clinical outcomes. RESULTS: Electrographic seizures were detected in 19 (9.6%) patients, including nonconvulsive status epilepticus (NCSE) in 11 (5.6%). Epileptiform abnormalities (either ictal or interictal) were present in 96 (48.7%). Preceding clinical seizures during hospitalization were associated with both electrographic seizures (36.4% in those with vs 8.1% in those without prior clinical seizures, odds ratio [OR] 6.51, p = 0.01) and NCSE (27.3% vs 4.3%, OR 8.34, p = 0.01). A pre-existing intracranial lesion on neuroimaging was associated with NCSE (14.3% vs 3.7%; OR 4.33, p = 0.02). In multivariate analysis of outcomes, electrographic seizures were an independent predictor of in-hospital mortality (hazard ratio [HR] 4.07 [1.44-11.51], p < 0.01). In competing risks analysis, hospital length of stay increased in the presence of NCSE (30 day proportion discharged with vs without NCSE: HR 0.21 [0.03-0.33] vs 0.43 [0.36-0.49]). INTERPRETATION: This multicenter retrospective cohort study demonstrates that seizures and other epileptiform abnormalities are common in patients with COVID-19 undergoing clinically indicated cEEG and are associated with adverse clinical outcomes. ANN NEUROL 2021;89:872-883.


Subject(s)
COVID-19/epidemiology , COVID-19/physiopathology , Electroencephalography/trends , Seizures/epidemiology , Seizures/physiopathology , Aged , COVID-19/diagnosis , Female , Humans , Male , Middle Aged , Retrospective Studies , Risk Factors , Seizures/diagnosis , Treatment Outcome
9.
Front Neurol ; 12: 634827, 2021.
Article in English | MEDLINE | ID: covidwho-1127991

ABSTRACT

The World Health Organization (WHO) monitors the spread of diseases globally and maintains a list of diseases with epidemic or pandemic potential. Currently listed diseases include Chikungunya, cholera, Crimean-Congo hemorrhagic fever, Ebola virus disease, Hendra virus infection, influenza, Lassa fever, Marburg virus disease, Neisseria meningitis, MERS-CoV, monkeypox, Nipah virus infection, novel coronavirus (COVID-19), plague, Rift Valley fever, SARS, smallpox, tularemia, yellow fever, and Zika virus disease. The associated pathogens are increasingly important on the global stage. The majority of these diseases have neurological manifestations. Those with less frequent neurological manifestations may also have important consequences. This is highlighted now in particular through the ongoing COVID-19 pandemic and reinforces that pathogens with the potential to spread rapidly and widely, in spite of concerted global efforts, may affect the nervous system. We searched the scientific literature, dating from 1934 to August 2020, to compile data on the cause, epidemiology, clinical presentation, neuroimaging features, and treatment of each of the diseases of epidemic or pandemic potential as viewed through a neurologist's lens. We included articles with an abstract or full text in English in this topical and scoping review. Diseases with epidemic and pandemic potential can be spread directly from human to human, animal to human, via mosquitoes or other insects, or via environmental contamination. Manifestations include central neurologic conditions (meningitis, encephalitis, intraparenchymal hemorrhage, seizures), peripheral and cranial nerve syndromes (sensory neuropathy, sensorineural hearing loss, ophthalmoplegia), post-infectious syndromes (acute inflammatory polyneuropathy), and congenital syndromes (fetal microcephaly), among others. Some diseases have not been well-characterized from a neurological standpoint, but all have at least scattered case reports of neurological features. Some of the diseases have curative treatments available while in other cases, supportive care remains the only management option. Regardless of the pathogen, prompt, and aggressive measures to control the spread of these agents are the most important factors in lowering the overall morbidity and mortality they can cause.

10.
J Infect Dis ; 223(1): 38-46, 2021 01 04.
Article in English | MEDLINE | ID: covidwho-1066343

ABSTRACT

BACKGROUND: We sought to develop an automatable score to predict hospitalization, critical illness, or death for patients at risk for coronavirus disease 2019 (COVID-19) presenting for urgent care. METHODS: We developed the COVID-19 Acuity Score (CoVA) based on a single-center study of adult outpatients seen in respiratory illness clinics or the emergency department. Data were extracted from the Partners Enterprise Data Warehouse, and split into development (n = 9381, 7 March-2 May) and prospective (n = 2205, 3-14 May) cohorts. Outcomes were hospitalization, critical illness (intensive care unit or ventilation), or death within 7 days. Calibration was assessed using the expected-to-observed event ratio (E/O). Discrimination was assessed by area under the receiver operating curve (AUC). RESULTS: In the prospective cohort, 26.1%, 6.3%, and 0.5% of patients experienced hospitalization, critical illness, or death, respectively. CoVA showed excellent performance in prospective validation for hospitalization (expected-to-observed ratio [E/O]: 1.01; AUC: 0.76), for critical illness (E/O: 1.03; AUC: 0.79), and for death (E/O: 1.63; AUC: 0.93). Among 30 predictors, the top 5 were age, diastolic blood pressure, blood oxygen saturation, COVID-19 testing status, and respiratory rate. CONCLUSIONS: CoVA is a prospectively validated automatable score for the outpatient setting to predict adverse events related to COVID-19 infection.


Subject(s)
COVID-19/diagnosis , Severity of Illness Index , Adult , Aged , Critical Illness , Female , Hospitalization , Humans , Intensive Care Units , Male , Middle Aged , Models, Theoretical , Outpatients , Predictive Value of Tests , Prognosis , Prospective Studies , ROC Curve , Sensitivity and Specificity
11.
J Neurol Sci ; 421: 117308, 2021 02 15.
Article in English | MEDLINE | ID: covidwho-1033825

ABSTRACT

We evaluated the incidence, distribution, and histopathologic correlates of microvascular brain lesions in patients with severe COVID-19. Sixteen consecutive patients admitted to the intensive care unit with severe COVID-19 undergoing brain MRI for evaluation of coma or neurologic deficits were retrospectively identified. Eleven patients had punctate susceptibility-weighted imaging (SWI) lesions in the subcortical and deep white matter, eight patients had >10 SWI lesions, and four patients had lesions involving the corpus callosum. The distribution of SWI lesions was similar to that seen in patients with hypoxic respiratory failure, sepsis, and disseminated intravascular coagulation. Brain autopsy in one patient revealed that SWI lesions corresponded to widespread microvascular injury, characterized by perivascular and parenchymal petechial hemorrhages and microscopic ischemic lesions. Collectively, these radiologic and histopathologic findings add to growing evidence that patients with severe COVID-19 are at risk for multifocal microvascular hemorrhagic and ischemic lesions in the subcortical and deep white matter.


Subject(s)
Brain Injuries/diagnostic imaging , COVID-19/diagnostic imaging , Magnetic Resonance Imaging/methods , Microvessels/diagnostic imaging , Severity of Illness Index , Brain/blood supply , Brain/diagnostic imaging , Brain Injuries/etiology , COVID-19/complications , Humans , Intensive Care Units/trends , Male , Microvessels/injuries , Middle Aged , Retrospective Studies
12.
JMIR Med Inform ; 9(2): e25457, 2021 Feb 10.
Article in English | MEDLINE | ID: covidwho-1032549

ABSTRACT

BACKGROUND: Medical notes are a rich source of patient data; however, the nature of unstructured text has largely precluded the use of these data for large retrospective analyses. Transforming clinical text into structured data can enable large-scale research studies with electronic health records (EHR) data. Natural language processing (NLP) can be used for text information retrieval, reducing the need for labor-intensive chart review. Here we present an application of NLP to large-scale analysis of medical records at 2 large hospitals for patients hospitalized with COVID-19. OBJECTIVE: Our study goal was to develop an NLP pipeline to classify the discharge disposition (home, inpatient rehabilitation, skilled nursing inpatient facility [SNIF], and death) of patients hospitalized with COVID-19 based on hospital discharge summary notes. METHODS: Text mining and feature engineering were applied to unstructured text from hospital discharge summaries. The study included patients with COVID-19 discharged from 2 hospitals in the Boston, Massachusetts area (Massachusetts General Hospital and Brigham and Women's Hospital) between March 10, 2020, and June 30, 2020. The data were divided into a training set (70%) and hold-out test set (30%). Discharge summaries were represented as bags-of-words consisting of single words (unigrams), bigrams, and trigrams. The number of features was reduced during training by excluding n-grams that occurred in fewer than 10% of discharge summaries, and further reduced using least absolute shrinkage and selection operator (LASSO) regularization while training a multiclass logistic regression model. Model performance was evaluated using the hold-out test set. RESULTS: The study cohort included 1737 adult patients (median age 61 [SD 18] years; 55% men; 45% White and 16% Black; 14% nonsurvivors and 61% discharged home). The model selected 179 from a vocabulary of 1056 engineered features, consisting of combinations of unigrams, bigrams, and trigrams. The top features contributing most to the classification by the model (for each outcome) were the following: "appointments specialty," "home health," and "home care" (home); "intubate" and "ARDS" (inpatient rehabilitation); "service" (SNIF); "brief assessment" and "covid" (death). The model achieved a micro-average area under the receiver operating characteristic curve value of 0.98 (95% CI 0.97-0.98) and average precision of 0.81 (95% CI 0.75-0.84) in the testing set for prediction of discharge disposition. CONCLUSIONS: A supervised learning-based NLP approach is able to classify the discharge disposition of patients hospitalized with COVID-19. This approach has the potential to accelerate and increase the scale of research on patients' discharge disposition that is possible with EHR data.

13.
Neurosci Lett ; 742: 135528, 2021 01 18.
Article in English | MEDLINE | ID: covidwho-1006393

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19) for which there have been over 50 million confirmed cases and 1.2 million deaths globally. While many SARS-CoV-2 infected individuals are asymptomatic or experience respiratory symptoms, extrapulmonary manifestations, including neurological symptoms and conditions, are increasingly recognized. There remains no clear understanding of the mechanisms that underlie neurological symptoms in COVID-19 and whether SARS-CoV-2 has the potential for neuroinvasion in humans. In this minireview, we discuss what is known from human autopsies in fatal COVID-19, including highlighting studies that investigate for the presence of SARS-CoV-2 in brain and olfactory tissue, and summarize the neuropathological consequences of infection. Incorporating microscopic and molecular findings from brain tissue into what we know about clinical disease will inform best practice management guidance and direct research priorities as it relates to neurological morbidity from COVID-19.


Subject(s)
Brain/pathology , Brain/virology , COVID-19/pathology , SARS-CoV-2/isolation & purification , Autopsy , Humans , Reverse Transcriptase Polymerase Chain Reaction/methods
14.
Chest ; 159(6): 2264-2273, 2021 06.
Article in English | MEDLINE | ID: covidwho-987252

ABSTRACT

BACKGROUND: Objective and early identification of hospitalized patients, and particularly those with novel coronavirus disease 2019 (COVID-19), who may require mechanical ventilation (MV) may aid in delivering timely treatment. RESEARCH QUESTION: Can a transparent deep learning (DL) model predict the need for MV in hospitalized patients and those with COVID-19 up to 24 h in advance? STUDY DESIGN AND METHODS: We trained and externally validated a transparent DL algorithm to predict the future need for MV in hospitalized patients, including those with COVID-19, using commonly available data in electronic health records. Additionally, commonly used clinical criteria (heart rate, oxygen saturation, respiratory rate, Fio2, and pH) were used to assess future need for MV. Performance of the algorithm was evaluated using the area under receiver operating characteristic curve (AUC), sensitivity, specificity, and positive predictive value. RESULTS: We obtained data from more than 30,000 ICU patients (including more than 700 patients with COVID-19) from two academic medical centers. The performance of the model with a 24-h prediction horizon at the development and validation sites was comparable (AUC, 0.895 vs 0.882, respectively), providing significant improvement over traditional clinical criteria (P < .001). Prospective validation of the algorithm among patients with COVID-19 yielded AUCs in the range of 0.918 to 0.943. INTERPRETATION: A transparent deep learning algorithm improves on traditional clinical criteria to predict the need for MV in hospitalized patients, including in those with COVID-19. Such an algorithm may help clinicians to optimize timing of tracheal intubation, to allocate resources and staff better, and to improve patient care.


Subject(s)
COVID-19/complications , COVID-19/therapy , Deep Learning , Health Services Needs and Demand , Respiration, Artificial , Aged , Critical Care , Female , Hospitalization , Humans , Intubation, Intratracheal , Male , Middle Aged , Predictive Value of Tests , Prospective Studies , ROC Curve
15.
Neurohospitalist ; 11(3): 204-213, 2021 Jul.
Article in English | MEDLINE | ID: covidwho-965426

ABSTRACT

BACKGROUND AND PURPOSE: Reports have suggested that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes neurologic manifestations including encephalopathy and seizures. However, there has been relatively limited electrophysiology data to contextualize these specific concerns and to understand their associated clinical factors. Our objective was to identify EEG abnormalities present in patients with SARS-CoV-2, and to determine whether they reflect new or preexisting brain pathology. METHODS: We studied a consecutive series of hospitalized patients with SARS-CoV-2 who received an EEG, obtained using tailored safety protocols. Data from EEG reports and clinical records were analyzed to identify EEG abnormalities and possible clinical associations, including neurologic symptoms, new or preexisting brain pathology, and sedation practices. RESULTS: We identified 37 patients with SARS-CoV-2 who underwent EEG, of whom 14 had epileptiform findings (38%). Patients with epileptiform findings were more likely to have preexisting brain pathology (6/14, 43%) than patients without epileptiform findings (2/23, 9%; p = 0.042). There were no clear differences in rates of acute brain pathology. One case of nonconvulsive status epilepticus was captured, but was not clearly a direct consequence of SARS-CoV-2. Abnormalities of background rhythms were common, as may be seen in systemic illness, and in part associated with recent sedation (p = 0.022). CONCLUSIONS: Epileptiform abnormalities were common in patients with SARS-CoV-2 referred for EEG, but particularly in the context of preexisting brain pathology and sedation. These findings suggest that neurologic manifestations during SARS-CoV-2 infection may not solely relate to the infection itself, but rather may also reflect patients' broader, preexisting neurologic vulnerabilities.

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