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

Low-Carbon Monoxide Diffusing Capacity, Patient-Reported Measures and Reduced Nailfold Capillary Density Are Associated with Interstitial Lung Disease in Systemic Sclerosis

The aim of this paper is to identify factors associated with interstitial lung disease (ILD) in patients with systemic sclerosis (SSc) and build an algorithm to better define this association for a personalised application in clinical practice.

METHODS

A total of 78 SSc patients underwent HRCT to assess ILD. Demographic, clinical and laboratory variables were collected, focusing on those associated either directly or indirectly with lung involvement. The discriminant value of each variable was determined using the operating characteristic curves (ROC) and included in a model to estimate the strength of ILD association in SSc.

RESULTS

Thirty-three (42.31%) patients showed ILD on HRCT. DLco, M-Borg, GERD-Q and capillary density were significantly associated with the presence of ILD-SSc. A model including these variables had a coefficient of determination (R2) of 0.697. DLco had an AUC of 0.861 (p < 0.001) with a cut-off of ≤72.3% (sensitivity 78.8%, specificity 91.1%, +LR 8.86). The m-Borg Scale showed an AUC of 0.883 (p < 0.001) with a cut-off >2 (sensitivity 84.8%, specificity 82.2%, +LR 4.77), GERD-Q had an AUC of 0.815 (p < 0.001) with a cut-off >7 (sensitivity 72.7%, specificity 86.7%, +LR 5.45). The capillary density showed an AUC of 0.815 (p < 0.001) with a cut-off of ≤4.78 (sensitivity 87.9%, specificity 68.9%, +LR 2.82). Based on the pre-test probability values, these four variables were applied to Fagan's nomogram to calculate the post-test probability of this association.

CONCLUSIONS

Our study identified four associated clinical factors of ILD in SSc patients. Moreover, their inclusion in an algorithm for the post-test probability, tailored to the specific patients' characteristics, significantly increases the ability to find out the presence of SSc-ILD.

Development and validation of a predictive model for 30-day mortality in patients with severe community-acquired pneumonia in intensive care units

Background

Based on the high prevalence and fatality rates associated with severe community-acquired pneumonia (SCAP), this study endeavored to construct an innovative nomogram for early identification of individuals at high risk of all-cause death within a 30-day period among SCAP patients receiving intensive care units (ICU) treatment.

Methods

In this single-center, retrospective study, 718 SCAP patients were screened from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database for the development of a predictive model. A total of 97 patients eligible for inclusion were included from Chongqing General Hospital, China between January 2020 and July 2023 for external validation. Clinical data and short-term prognosis were collected. Risk factors were determined using the least absolute shrinkage and selection operator (LASSO) and multiple logistic regression analysis. The model's performance was evaluated through area under the curve (AUC), calibration curve, and decision curve analysis (DCA).

Results

Eight risk predictors, including age, presence of malignant cancer, heart rate, mean arterial pressure, albumin, blood urea nitrogen, prothrombin time, and lactate levels were adopted in a nomogram. The nomogram exhibited high predictive accuracy, with an AUC of 0.803 (95% CI: 0.756-0.845) in the training set, 0.756 (95% CI: 0.693-0.816) in the internal validation set, 0.778 (95% CI: 0.594-0.893) in the external validation set concerning 30-day mortality. Meanwhile, the nomogram demonstrated effective calibration through well-fitted calibration curves. DCA confirmed the clinical application value of the nomogram.

Conclusion

This simple and reliable nomogram can help physicians assess the short-term prognosis of patients with SCAP quickly and effectively, and could potentially be adopted widely in clinical settings after more external validations.

Do-Not-ResuscitateDecision-Making during the COVID-19 Pandemic in a Teaching Hospital: Lessons Learned for the Future

Method

A cross-sectional survey study was conducted between February 2021 and April 2021 for all doctors and doctors in training, working in the Antwerp University Hospital during the COVID-19 pandemic.

Results

127 doctors participated in this study. The familiarity with the different scores used in the triage during the COVID-10 pandemic was 51% for the Clinical Frailty Scale (CFS) and 20% for the Charlson Comorbidity Index (CCI). Participants indicated that their DNR decision is based on various aspects such as clinical assessment, comorbidities, patient's wishes, age, prognosis, and functional state.

Conclusion

The familiarity with the different scores used during triage assessments is low. The total clinical picture of the patient is needed to make a considered decision, and this total picture of the patient seems to be well encompassed by frailty measurement (CFS). Although many participants indicated that the different scores do not offer much added value compared to their clinical assessment, it can help guide DNR decisions, especially for doctors in training.

Evaluation of safety and effectiveness of remdesivir in treating COVID-19 patients after emergency use authorization study

Background: This study aimed to determine the real-world safety and effectiveness of remdesivir in hospitalized adult COVID-19 patients with moderate-to-critical disease in Indonesia. Methods: A multicenter, retrospective cohort study was conducted at four COVID-19 referral hospitals in Jakarta. A total of 587 patients were included, of whom 243 received remdesivir within 72 h of admission. The safety endpoints were the proportions of patients with any adverse event (AE), any grade 3 AE, and AE of each system organ class. The effectiveness endpoints were ICU admission >24 h from baseline, live discharge and mortality at day 14, live discharge and mortality at day 28, and virologic conversion. Patients who received remdesivir within 72 h of admission were considered the treatment group, and those who did not were the control group. Multivariate adjustments were performed using a modified Poisson regression. Results: The study found no significant differences in safety endpoints between the two groups. However, the effectiveness endpoints showed that remdesivir was associated with a decreased risk of ICU admission >24 h from baseline (RR 0.71, 95% CI 0.52-0.96), an increased probability of live discharge at day 14 (RR 1.37, 95% CI 1.08-1.74), and an increased probability of live discharge at day 28 (RR 1.28, 95% CI 1.05-1.57). The rate of virologic conversion was not significantly different between the two groups. Conclusion: The study concludes that remdesivir is safe and effective in the treatment of moderate-to-critical COVID-19 in a real-world setting in Indonesia.

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

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.

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

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.

Usefulness of KL-6 for Predicting Clinical Outcomes in Hospitalized COVID-19 Patients

Background: Krebs von den Lungen 6 (KL-6) is a novel biomarker for interstitial lung disease, and it reflects acute lung injury. We explored the usefulness of KL-6 to predict clinical outcomes in hospitalized coronavirus disease 2019 (COVID-19) patients. Methods: In a total of 48 hospitalized COVID-19 patients, KL-6 levels were measured using the HISCL KL-6 assay (Sysmex, Kobe, Japan) with the HISCL 5000 automated analyzer (Sysmex). Clinical outcomes (intensive care unit [ICU] admission, ventilator use, extracorporeal membrane oxygenation [ECMO] use, and 30-day mortality) were analyzed according to KL-6 percentiles. Age, initial KL-6 level, Charlson comorbidity index (CCI), and critical disease were compared using the receiver operating characteristic (ROC) curve and Kaplan-Meier methods for clinical outcomes. Results: KL-6 quartiles were associated with ICU admission, ventilator use, and ECMO use (all p < 0.05), except 30-day mortality (p = 0.187). On ROC curve analysis, initial KL-6 level predicted ICU admission, ventilator use, and ECMO use significantly better than age, CCI, and critical disease (all p < 0.05); age, initial KL-6 level, CCI, and critical disease predicted 30-day mortality comparably. On Kaplan−Meier survival analysis, hazard ratios (95% confidence interval) were 4.8 (1.2−19.3) for age, 4.7 (1.1−21.6) for initial KL-6 level, 3.9 (0.9−16.2) for CCI, and 2.1 (0.5−10.3) for critical disease. Conclusions: This study demonstrated that KL-6 could be a useful biomarker to predict clinical outcomes in hospitalized COVID-19 patients. KL-6 may contribute to identifying COVID-19 patients requiring critical care, including ICU admission and ventilator and/or ECMO use.