Lymphopenia in critically ill COVID‐19 patients: A predictor factor of severity and mortality

Ziadi, Amra; Hachimi, Abdelhamid; Admou, Brahim; Hazime, Raja; Brahim, Imane; Douirek, Fouzia; Zarrouki, Youssef; Adib, Ahmed Rhassane El; Younous, S.; Samkaoui, A.

doi:10.1111/ijlh.13351

Cited by 30 publications

(29 citation statements)

References 9 publications

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“…In accordance with what has previously been described in the literature [ 39 , 45 , 46 ], the lymphopenia might be due to the massive activation of lymphocytes in response to the virus. However, as it has emerged from the literature [ 47 , 48 ], in the Good Prognosis Group, we observed an increase in the absolute lymphocyte count, while in the Exitus Group, the lymphopenia remained constant, without showing any improvement during the course of the disease. These findings suggest that lymphopenia might not only be a consequence of the infection but that it is probably a critical factor in driving the development and deterioration of the disease.…”

Section: Discussionsupporting

confidence: 52%

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes’ iTNF-α Expression

Madonna

Sale

Capone

et al. 2021

Biology

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In December 2019, a novel coronavirus, “SARS-CoV-2”, was recognized as the cause of coronavirus disease 2019 (COVID-19). Several studies have explored the changes and the role of inflammatory cells and cytokines in the immunopathogenesis of the disease, but until today, the results have been controversial. Based on these premises, we conducted a retrospective assessment of monocyte intracellular TNF-α expression (iTNF-α) and on the frequencies of lymphocyte sub-populations in twenty-five patients with moderate/severe COVID-19. We found lymphopenia in all COVID-19 infected subjects compared to healthy subjects. On initial observation, in patients with favorable outcomes, we detected a high absolute eosinophil count and a high CD4+/CD8+ T lymphocytes ratio, while in the Exitus Group, we observed high neutrophil and CD8+ T lymphocyte counts. During infection, in patients with favorable outcomes, we observed a rise in the lymphocyte count, in the monocyte and in Treg lymphocyte counts, and in the CD4+ and in CD8+ T lymphocytes count but a reduction in the CD4+/CD8+ T lymphocyte ratio. Instead, in the Exitus Group, we observed a reduction in the Treg lymphocyte counts and a decrease in iTNF-α expression. Our preliminary findings point to a modulation of the different cellular mediators of the immune system, which probably play a key role in the outcomes of COVID-19.

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Section: Discussionsupporting

confidence: 52%

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes’ iTNF-α Expression

Madonna

Sale

Capone

et al. 2021

Biology

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“…Although we did not collect data on all presenting features that have been associated with death in COVID‐19, abnormal chest imaging, lymphopenia, and ICU admission are established predictors of mortality in COVID‐19 and likely correlated with other predictors of baseline disease severity, including baseline oxygen saturation. 15 , 16 , 17 A higher proportion of patients in the late period required some form of supplemental oxygen despite lower mortality in the late period, further suggesting that the variations in disease severity do not explain the observed decline in mortality.…”

Section: Discussionmentioning

confidence: 99%

Changing trends in mortality among solid organ transplant recipients hospitalized for COVID-19 during the course of the pandemic

Heldman

Kates

Safa

et al. 2022

American Journal of Transplantation

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Mortality among patients hospitalized for COVID‐19 has declined over the course of the pandemic. Mortality trends specifically in solid organ transplant recipients (SOTR) are unknown. Using data from a multicenter registry of SOTR hospitalized for COVID‐19, we compared 28‐day mortality between early 2020 (March 1, 2020–June 19, 2020) and late 2020 (June 20, 2020–December 31, 2020). Multivariable logistic regression was used to assess comorbidity‐adjusted mortality. Time period of diagnosis was available for 1435/1616 (88.8%) SOTR and 971/1435 (67.7%) were hospitalized: 571/753 (75.8%) in early 2020 and 402/682 (58.9%) in late 2020 ( p < .001). Crude 28‐day mortality decreased between the early and late periods (112/571 [19.6%] vs. 55/402 [13.7%]) and remained lower in the late period even after adjusting for baseline comorbidities (aOR 0.67, 95% CI 0.46–0.98, p = .016). Between the early and late periods, the use of corticosteroids (≥6 mg dexamethasone/day) and remdesivir increased (62/571 [10.9%] vs. 243/402 [61.5%], p < .001 and 50/571 [8.8%] vs. 213/402 [52.2%], p < .001, respectively), and the use of hydroxychloroquine and IL‐6/IL‐6 receptor inhibitor decreased (329/571 [60.0%] vs. 4/492 [1.0%], p < .001 and 73/571 [12.8%] vs. 5/402 [1.2%], p < .001, respectively). Mortality among SOTR hospitalized for COVID‐19 declined between early and late 2020, consistent with trends reported in the general population. The mechanism(s) underlying improved survival require further study.

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“…Several of these have previously been noted as predictors of various adverse outcomes in COVID-19. 21,26,37,38 For example, elevated fibrinogen has been linked to high plasma viscosity in COVID-19, which may contribute to morbidity and mortality. 28 This serves as a “sanity check” that the model is learning reasonable associations between predictors and outcomes, despite its novel real-time nature.…”

Section: Supplementary Resultsmentioning

confidence: 99%

COVID-HEART: Development and Validation of a Multi-Variable Model for Real-Time Prediction of Cardiovascular Complications in Hospitalized Patients with COVID-19

Shade

Doshi

Sung

et al. 2021

Preprint

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Cardiovascular (CV) manifestations of COVID-19 infection carry significant morbidity and mortality. Current risk prediction for CV complications in COVID-19 is limited and existing approaches fail to account for the dynamic course of the disease. Here, we develop and validate the COVID-HEART predictor, a novel continuously-updating risk prediction technology to forecast CV complications in hospitalized patients with COVID-19. The risk predictor is trained and tested with retrospective registry data from 2178 patients to predict two outcomes: cardiac arrest and imaging-confirmed thromboembolic events. In repeating model validation many times, we show that it predicts cardiac arrest with an average median early warning time of 18 hours (IQR: 13-20 hours) and an AUROC of 0.92 (95% CI: 0.91-0.92), and thromboembolic events with a median early warning time of 72 hours (IQR: 12-204 hours) and an AUROC of 0.70 (95% CI: 0.67-0.73). The COVID-HEART predictor is anticipated to provide tangible clinical decision support in triaging patients and optimizing resource utilization, with its clinical utility potentially extending well beyond COVID-19.

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Lymphopenia in critically ill COVID‐19 patients: A predictor factor of severity and mortality

Cited by 30 publications

References 9 publications

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes’ iTNF-α Expression

Clinical Outcome Prediction in COVID-19 Patients by Lymphocyte Subsets Analysis and Monocytes’ iTNF-α Expression

Changing trends in mortality among solid organ transplant recipients hospitalized for COVID-19 during the course of the pandemic

COVID-HEART: Development and Validation of a Multi-Variable Model for Real-Time Prediction of Cardiovascular Complications in Hospitalized Patients with COVID-19

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