Predicting Severe/Critical Outcomes in Patients With SARS-CoV2 Pneumonia: Development of the prediCtion seveRe/crItical ouTcome in COVID-19 (CRITIC) Model

Salaffi, Fausto; Carotti, Marina; Carlo, Marco Di; Ceccarelli, Luca; Galli, Massimo; Sarzi‐Puttini, Piercarlo; Giovagnoni, Andrea

doi:10.3389/fmed.2021.695195

Cited by 10 publications

(10 citation statements)

References 56 publications

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“…To better compare patients with multiple comorbidities, we employed the use of an age-excluding CCI to quantify comorbidity burden. Although previous studies have demonstrated that CCI commonly predicts survival (37)(38)(39), we demonstrate that an age-excluding CCI can also be predictive of mortality. Based on the how CCI is calculated, certain comorbidities such as diabetes and CKD are weighted more than other factors such as coronary heart disease and are predicted to have a greater influence on mortality.…”

Section: Discussioncontrasting

confidence: 88%

Age and Comorbidities Predict COVID-19 Outcome, Regardless of Innate Immune Response Severity: A Single Institutional Cohort Study

Mohan

Olson

Naqvi

et al. 2022

Critical Care Explorations

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OBJECTIVES: The COVID-19 pandemic has claimed over eight hundred thousand lives in the United States alone, with older individuals and those with comorbidities being at higher risk of severe disease and death. Although severe acute respiratory syndrome coronavirus 2–induced hyperinflammation is one of the mechanisms underlying the high mortality, the association between age and innate immune responses in COVID-19 mortality remains unclear. DESIGN: Flow cytometry of fresh blood and multiplexed inflammatory chemokine measurements of sera were performed on samples collected longitudinally from our cohort. Aggregate impact of comorbid conditions was calculated with the Charlson Comorbidity Index, and association between patient factors and outcomes was calculated via Cox proportional hazard analysis and repeated measures analysis of variance. SETTING: A cohort of severely ill COVID-19 patients requiring ICU admission was followed prospectively. PATIENTS: In total, 67 patients (46 male, age 59 ± 14 yr) were included in the study. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Mortality in our cohort was 41.8%. We identified older age (hazard ratio [HR] 1.09 [95% CI 1.07–1.11]; p = 0.001), higher comorbidity index (HR 1.24 [95% CI 1.14–1.35]; p = 0.039), and hyponatremia (HR 0.90 [95% CI 0.82–0.99]; p = 0.026) to each independently increase risk for death in COVID-19. We also found that neutrophilia (R = 0.2; p = 0.017), chemokine C-C motif ligand (CCL) 2 (R = 0.3; p = 0.043), and C-X-C motif chemokine ligand 9 (CXCL9) (R = 0.3; p = 0.050) were weakly but significantly correlated with mortality. Older age was associated with lower monocyte (R = –0.2; p = 0.006) and cluster of differentiation (CD) 16+ cell counts (R = –0.2; p = 0.002) and increased CCL11 concentration (R = 0.3; p = 0.050). Similarly, younger patients (< 65 yr) demonstrated a rise in CD4 (b-coefficient = 0.02; p = 0.036) and CD8 (0.01; p = 0.001) counts, as well as CCL20 (b-coefficient = 6.8; p = 0.036) during their ICU stay. This CD8 count rise was also associated with survival (b-coefficient = 0.01; p = 0.023). CONCLUSIONS: Age, comorbidities, and hyponatremia independently predict mortality in severe COVID-19. Neutrophilia and higher CCL2 and CXCL9 levels are also associated with higher mortality, while independent of age.

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Section: Discussioncontrasting

confidence: 88%

Age and Comorbidities Predict COVID-19 Outcome, Regardless of Innate Immune Response Severity: A Single Institutional Cohort Study

Mohan

Olson

Naqvi

et al. 2022

Critical Care Explorations

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“… 48 The CCI demonstrated excellent discriminative ability, with an AUC of 0.854 (p < .001) and an optimal cut-off point of 3 (sensitivity 83.8%, specificity 69.6%, + LR 2.76). 49 Additionally, multiple studies have demonstrated SAPS-3 and NEWS-2 scoring systems as severity and mortality predictor tools of COVID-19 infection. 50 – 52 Despite serum KL-6 having a similar AUC to this severity assessment tool, the low sensitivity of KL-6 makes it a weaker test.…”

Section: Discussionmentioning

confidence: 99%

“…The CT severity score has an AUC of 0.824 (p < .001) and an optimal cut-off point of 53 (sensitivity 64.9%, specificity 84.4%, and PLR 4.17. 49 A study by Saeed et al suggested that the CT chest, despite having a pivotal role in severity assessment, is prone to interpreter bias. 53 However, compared with the detection of COVID-19 through chest CT and nucleic acid detection, the measurement of KL-6 levels is fast, inexpensive, noninvasive, no radiation hazard, and sensitive.…”

Section: Discussionmentioning

confidence: 99%

Serum Krebs von den Lungen-6 for Predicting the Severity of COVID-19: A Systematic Review, Meta-Analysis, and Trial Sequence Analysis

Shrestha

Pokharel

Singh

et al. 2023

Clin Med Insights Circ Respir Pulm Med

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OBJECTIVE This systematic review and meta-analysis aimed to find the association between serum Krebs von den Lungen-6 (KL-6) and the severity of Coronavirus disease 2019 (COVID-19) infection. DATA SOURCES Databases of Embase, PubMed, Web of Science, Science Direct, and Google Scholar were searched for studies reporting KL-6 levels in COVID-19 patients, published between January 2020 and September 30 2022. DATA SYNTHESIS For comparison between the groups, standard mean difference (SMD) and 95% confidence intervals (CI) were computed as the effect sizes. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were measured to assess the diagnostic power of KL-6. In addition, the summary receiver operating characteristics curve (sROC) was constructed to summarize the true positive (TP), and false positive (FP) rates. To validate the findings of meta-analysis, Trial Sequential Analysis (TSA) was conducted. RESULTS Altogether 497 severe COVID-19 patients and 934 non-severe (mild to moderate) COVID-19 patients were included. Pooling of 12 studies indicated that the serum KL-6 level had significant association with severity of COVID-19 infection: standard mean difference = 1.18 (95% CI: 0.93-1.43), p = 0.01; I2: 58.56%]. Pooled diagnostic parameters calculated from eight studies were: sensitivity 0.53 (95% CI: 0.47-0.59); specificity 0.90 (95% CI: 0.88-0.93); positive likelihood ratio 4.80 (95% CI: 3.53-6.53); negative likelihood ratio 0.46 (95% CI: 0.32-0.68); and area under curve: 0.8841. Additionally, TSA verified the adequacy of sample size and robustness of the meta-analysis. CONCLUSION Serum KL-6 level has a moderate degree of correlation with the severity of COVID-19 infection but has low sensitivity. So, it is not recommended as a screening test for severe COVID-19 infection.

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“…However, because the COVID-19 pandemic has impacted profoundly on those with concomitant cardiovascular comorbidities [16], we considered whether digoxin-treated patients might be more susceptible to COVID-19 than those treated with standard of care. The reason for this consideration was that increased comorbidities, as defined by the Charlson Comorbidity Index (CCI), have been widely seen to be associated with worse outcomes for COVID-19 [17][18][19][20]. By contrast, it has been reported that digitoxin and ouabain, and with lesser potency digoxin, interfere with penetration of the SARS-CoV-2 virus into human lung cells [21] and green monkey kidney cells [22].…”

Section: Introductionmentioning

confidence: 99%

Digoxin and Standard-of-Care Therapy for Heart Failure Patients with COVID-19: Analysis of Data from the US Military Health System (MHS) Data Repository

Banaag¹,

Pollard²,

Koehlmoos³

2023

Drugs - Real World Outcomes

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Background Cardiac glycosides such as digoxin, digitoxin and ouabain are still used around the world to treat patients with chronic heart failure with reduced ejection fraction (HFrEF) and/or atrial fibrillation (AF). However, in the US, only digoxin is licensed for treating these illnesses, and the use of digoxin for this group of patients is increasingly being replaced in the US by a new standard of care with groups of more expensive drugs. However, ouabain and digitoxin, and less potently digoxin, have also recently been reported to inhibit SARS-CoV-2 virus penetration into human lung cells, thus blocking COVID-19 infection. COVID-19 is known to be a more aggressive disease in patients with cardiac comorbidities, including heart failure. Objective We therefore considered the possibility that digoxin might provide at least a measure of relief from COVID-19 in digoxin-treated heart failure patients. To this end, we hypothesized that treatment with digoxin rather than standard of care might equivalently protect heart failure patients with regard to diagnosis of COVID-19, hospitalization and death. Methods To test this hypothesis, we conducted a cross-sectional study by using the US Military Health System (MHS) Data Repository to identify all MHS TRICARE Prime and Plus beneficiaries aged 18–64 years with a heart failure (HF) diagnosis during the period April 2020 to August 2021. In the MHS, all patients receive equal, optimal care without regard to rank or ethnicity. Analyses included descriptive statistics on patient demographics and clinical characteristics, and logistic regressions to determine likelihood of digoxin use. Results We identified 14,044 beneficiaries with heart failure in the MHS during the study period. Of these, 496 were treated with digoxin. However, we found that both digoxin-treated and standard-of-care groups were equivalently protected from COVID-19. We also noted that younger active duty service members and their dependents with HF were less likely to receive digoxin compared with older, retired beneficiaries with more comorbidities. Conclusion The hypothesis of equivalent protection by digoxin treatment of HF patients in terms of susceptibility to COVID-19 infection appears to be supported by the data. Supplementary Information The online version contains supplementary material available at 10.1007/s40801-023-00360-8.

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Predicting Severe/Critical Outcomes in Patients With SARS-CoV2 Pneumonia: Development of the prediCtion seveRe/crItical ouTcome in COVID-19 (CRITIC) Model

Cited by 10 publications

References 56 publications

Age and Comorbidities Predict COVID-19 Outcome, Regardless of Innate Immune Response Severity: A Single Institutional Cohort Study

Age and Comorbidities Predict COVID-19 Outcome, Regardless of Innate Immune Response Severity: A Single Institutional Cohort Study

Serum Krebs von den Lungen-6 for Predicting the Severity of COVID-19: A Systematic Review, Meta-Analysis, and Trial Sequence Analysis

Digoxin and Standard-of-Care Therapy for Heart Failure Patients with COVID-19: Analysis of Data from the US Military Health System (MHS) Data Repository

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