Early prediction of the risk of severe coronavirus disease 2019: A key step in therapeutic decision making

Côté, Andréanne; Ternacle, Julien

doi:10.1016/j.ebiom.2020.102948

Cited by 15 publications

(12 citation statements)

References 10 publications

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“…Assessment of 3-class severity (mild, moderate, severe) is crucial to determine the treatment route [14] and is well summarized in the WHO interim guidance on clinical management of COVID-19 2 . Some recent literature have shown chest CT to determine COVID-19 severity qualitatively and quantitatively with good correlation with clinical parameters [15][16][17].…”

Section: Review Of Literaturementioning

confidence: 99%

A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19

Ghosh

Kumar

Sadhu

et al. 2020

Preprint

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The COVID-19 pandemic has affected millions and congested healthcare systems globally. Hence an objective severity assessment is crucial in making therapeutic decisions judiciously. Computed Tomography (CT)-scans can provide demarcating features to identify the severity of pneumonia, commonly associated with COVID-19, in the affected lungs. Here, a semi-quantitative severity assessing lung CT image feature is demonstrated for COVID-19 patients. An open-source multi-center Italian database was used, among which 61 cases were incorporated in the study (age 27-86, 71% males) from 27 CT imaging centers. Lesions in the form of opacifications, crazy-paving patterns, and consolidations were heuristically marked and the severity determining feature L_norm was quantified and established to be statistically distinct for the three classes i.e., mild, moderate, and severe (p-value < 0.0001). The thresholds of L_norm for a 3-class classification were determined based on the optimum sensitivity/specificity combination from ROC analyses. The feature L_norm classified the cases in the three severity categories with 89.34% accuracy when L_norm was calculated based on experts' heuristic annotations. Substantial to almost-perfect intra-rater and inter-rater agreements were achieved involving expert and non-expert based evaluations (κ-score 0.79-0.97). We trained machine learning based classification models and showed L_norm alone has a superior diagnostic accuracy over standard image intensity and texture features. Classification accuracy was further increased when L_norm was used to delineate the severe cases from non-severe ones (98.9%) with high sensitivity (97.7%), and specificity (97.49%). Therefore, key highlights of this severity assessment feature are accuracy, lower dependency on expert availability, and wide utility across multiple imaging centers.

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Section: Review Of Literaturementioning

confidence: 99%

A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19

Ghosh

Kumar

Sadhu

et al. 2020

Preprint

View full text Add to dashboard Cite

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“…We demonstrated proof-of-principle that an ATAC-PCR-based assay can potentially be used as an epigenetic test to stratify disease severity (33) . Development of a host-response assay that leverages the highly sensitive epigenetic biomarkers established early during infection and capable of predicting disease severity has the potential to fill an unmet clinical need in the care of COVID-19 patients (34, 35) . It will be important to apply this analysis to a longitudinal cohort of subjects who go on to develop worsening symptoms and require critical care in order to generate data for a prognostic epigenetic assay.…”

Section: Discussionmentioning

confidence: 99%

Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity

Giroux

Ding

McClain

et al. 2020

Preprint

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SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects.One sentence summaryChromatin accessibility in immune cells from COVID-19 subjects is remodeled prior to seroconversion to reflect disease severity.

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“…47 Small observational studies and experiential reports have demonstrated high sensitivity of lung ultrasound to detect COVID-19 disease and utility in reducing use of other imaging modalities, 47,48 and multiple groups have investigated integrating ultrasound in the screening and triage process. 5,6,[49][50][51][52] However, none of these studies were set in LMICs, and we did not identify studies showing additional benefit from ultrasound in the triage process beyond standard clinical and laboratory-based approaches. Therefore, we do not currently recommend such a practice be used in LMICs.…”

Section: Stratification Through Diagnostic Imagingmentioning

confidence: 99%

Pragmatic Recommendations for Identification and Triage of Patients with COVID-19 Disease in Low- and Middle-Income Countries

Barros

Pigoga

Chea

et al. 2021

The American Journal of Tropical Medicine and Hygiene

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Effective identification and prognostication of severe COVID-19 patients presenting to healthcare facilities are essential to reducing morbidity and mortality. Low- and middle-income country (LMIC) facilities often suffer from restrictions in availability of human resources, laboratory testing, medications, and imaging during routine functioning, and such shortages may worsen during times of surge. Low- and middle-income country healthcare providers will need contextually appropriate tools to identify and triage potential COVID-19 patients. We report on a series of LMIC-appropriate recommendations and suggestions for screening and triage of COVID-19 patients in LMICs, based on a pragmatic, experience-based appraisal of existing literature. We recommend that all patients be screened upon first contact with the healthcare system using a locally approved questionnaire to identify individuals who have suspected or confirmed COVID-19. We suggest that primary screening tools used to identify individuals who have suspected or confirmed COVID-19 include a broad range of signs and symptoms based on standard case definitions of COVID-19 disease. We recommend that screening include endemic febrile illness per routine protocols upon presentation to a healthcare facility. We recommend that, following screening and implementation of appropriate universal source control measures, suspected COVID-19 patients be triaged with a triage tool appropriate for the setting. We recommend a standardized severity score based on the WHO COVID-19 disease definitions be assigned to all suspected and confirmed COVID-19 patients before their disposition from the emergency unit. We suggest against using diagnostic imaging to improve triage of reverse transcriptase (RT)-PCR–confirmed COVID-19 patients, unless a patient has worsening respiratory status. We suggest against the use of point-of-care lung ultrasound to improve triage of RT-PCR–confirmed COVID-19 patients. We suggest the use of diagnostic imaging to improve sensitivity of appropriate triage in suspected COVID-19 patients who are RT-PCR negative but have moderate to severe symptoms and are suspected of a false-negative RT-PCR with high risk of disease progression. We suggest the use of diagnostic imaging to improve sensitivity of appropriate triage in suspected COVID-19 patients with moderate or severe clinical features who are without access to RT-PCR testing for SARS-CoV-2.

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Early prediction of the risk of severe coronavirus disease 2019: A key step in therapeutic decision making

Cited by 15 publications

References 10 publications

A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19

A Quantitative Lung Computed Tomography Image Feature for Multi-Center Severity Assessment of COVID-19

Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity

Pragmatic Recommendations for Identification and Triage of Patients with COVID-19 Disease in Low- and Middle-Income Countries

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