An immune-protein score combining TRAIL, IP-10 and CRP for predicting severe COVID-19 disease.

COVID-19 patients are oftentimes over- or under-treated due to a deficit in predictive management tools. This study reports derivation of an algorithm that integrates the host levels of TRAIL, IP-10, and CRP into a single numeric score that is an early indicator of severe outcome for COVID-19 patients and can identify patients at-risk to deteriorate. 394 COVID-19 patients were eligible; 29% meeting a severe outcome (intensive care unit admission/non-invasive or invasive ventilation/death). The score's area under the receiver operating characteristic curve (AUC) was 0.86, superior to IL-6 (AUC 0.77; p = 0.033) and CRP (AUC 0.78; p < 0.001). Likelihood of severe outcome increased significantly (p < 0.001) with higher scores. The score differentiated severe patients who further deteriorated from those who improved (p = 0.004) and projected 14-day survival probabilities (p < 0.001). The score accurately predicted COVID-19 patients at-risk for severe outcome, and therefore has potential to facilitate timely care escalation and de-escalation and appropriate resource allocation.

Risk-factors for re-admission and outcome of patients hospitalized with confirmed COVID-19.

Burden of COVID-19 on Hospitals across the globe is enormous and has clinical and economic implications. In this retrospective study including consecutive adult patients with confirmed SARS-CoV-2 who were admitted between 3/2020 and 30/9/20, we aimed to identify post-discharge outcomes and risk factors for re-admission among COVID-19 hospitalized patients. Mortality and re-admissions were documented for a median post discharge follow up of 59 days (interquartile range 28,161). Univariate and multivariate analyses of risk factors for re-admission were performed. Overall, 618 hospitalized COVID-19 patients were included. Of the 544 patient who were discharged, 10 patients (1.83%) died following discharge and 50 patients (9.2%) were re-admitted. Median time to re-admission was 7 days (interquartile range 3, 24). Oxygen saturation or treatment prior to discharge were not associated with re-admissions. Risk factors for re-admission in multivariate analysis included solid organ transplantation (hazard ratio [HR] 3.37, 95% confidence interval [CI] 2.73-7.5, p = 0.0028) and higher Charlson comorbidity index (HR 1.34, 95% CI 1.23-1.46, p < 0.0001). Mean age of post discharge mortality cases was 85.0 (SD 9.98), 80% of them had cognitive decline or needed help in ADL at baseline. In conclusion, re-admission rates of hospitalized COVID-19 are fairly moderate. Predictors of re-admission are non-modifiable, including baseline comorbidities, rather than COVID-19 severity or treatment.

Evaluation of Seropositivity Following BNT162b2 Messenger RNA Vaccination for SARS-CoV-2 in Patients Undergoing Treatment for Cancer.

Importance: Patients with cancer undergoing treatment are at high risk of COVID-19 following SARS-CoV-2 infection; however, their ability to produce an adequate antibody response to messenger RNA SARS-CoV-2 vaccines is unclear. Objective: To evaluate rates of antispike (anti-S) antibody response to a BNT162b2 vaccine in patients with cancer who are undergoing systemic treatment vs healthy controls. Design, Setting, and Participants: This prospective cohort study included 102 adult patients with solid tumors undergoing active intravenous anticancer treatment and 78 controls who received the second dose of the BNT162b2 vaccine at least 12 days before enrollment. The controls were taken from a convenience sample of the patients' family/caregivers who accompanied them to treatment. The study was conducted between February 22, 2021, and March 15, 2021 at Davidoff Cancer Center at Beilinson Hospital (Petah Tikva, Israel). Interventions: Blood samples were drawn from the study participants. Serum samples were analyzed and the titers of the IgG antibodies against SARS-CoV-2 spike receptor-binding domain were determined using a commercially available immunoassay. Seropositivity was defined as 50 or greater AU/mL. Main Outcomes and Measures: The primary outcome was the rate of seropositivity. Secondary outcomes included comparisons of IgG titers and identifying factors that were associated with seropositivity using univariate/multivariable analyses. Results: The analysis included 180 participants, which comprised 102 patients with cancer (median [interquartile range (IQR)] age, 66 [56-72] years; 58 men [57%]) and 78 healthy controls (median [IQR] age, 62 [49-70] years; 25 men [32%]). The most common tumor type was gastrointestinal (29 [28%]). In the patient group, 92 (90%) were seropositive for SARS-CoV 2 antispike IgG antibodies after the second vaccine dose, whereas in the control group, all were seropositive. The median IgG titer in the patients with cancer was significantly lower than that in the controls (1931 [IQR, 509-4386] AU/mL vs 7160 [IQR, 3129-11 241] AU/mL; P < .001). In a multivariable analysis, the only variable that was significantly associated with lower IgG titers was treatment with chemotherapy plus immunotherapy (ß, -3.5; 95% CI, -5.6 to -1.5). Conclusions and Relevance: In this cohort study of patients with cancer who were receiving active systemic therapy, 90% of patients exhibited adequate antibody response to the BNT162b2 vaccine, although their antibody titers were significantly lower than those of healthy controls. Further research into the clinical relevance of lower titers and their durability is required. Nonetheless, the data support vaccinating patients with cancer as a high priority, even during therapy.

Observational cohort study of IP-10's potential as a biomarker to aid in inflammation regulation within a clinical decision support protocol for patients with severe COVID-19.

BACKGROUND: Treatment of severely ill COVID-19 patients requires simultaneous management of oxygenation and inflammation without compromising viral clearance. While multiple tools are available to aid oxygenation, data supporting immune biomarkers for monitoring the host-pathogen interaction across disease stages and for titrating immunomodulatory therapy is lacking. METHODS: In this single-center cohort study, we used an immunoassay platform that enables rapid and quantitative measurement of interferon γ-induced protein 10 (IP-10), a host protein involved in lung injury from virus-induced hyperinflammation. A dynamic clinical decision support protocol was followed to manage patients infected with severe acute respiratory syndrome coronavirus 2 and examine the potential utility of timely and serial measurements of IP-10 as tool in regulating inflammation. RESULTS: Overall, 502 IP-10 measurements were performed on 52 patients between 7 April and 10 May 2020, with 12 patients admitted to the intensive care unit. IP-10 levels correlated with COVID-19 severity scores and admission to the intensive care unit. Among patients in the intensive care unit, the number of days with IP-10 levels exceeding 1,000 pg/mL was associated with mortality. Administration of corticosteroid immunomodulatory therapy decreased IP-10 levels significantly. Only two patients presented with subsequent IP-10 flare-ups exceeding 1,000 pg/mL and died of COVID-19-related complications. CONCLUSIONS: Serial and readily available IP-10 measurements potentially represent an actionable aid in managing inflammation in COVID-19 patients and therapeutic decision-making. TRIAL REGISTRATION: Clinicaltrials.gov, NCT04389645, retrospectively registered on May 15, 2020.

Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients.

Facing the novel coronavirus disease (COVID-19) pandemic, evidence to inform decision-making at all care levels is essential. Based on the results of a study by Petrilli et al., we have developed a calculator using patient data at admission to predict critical illness (intensive care, mechanical ventilation, hospice care, or death). We report a retrospective validation of the calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Despite considerable differences between the original and validation study populations, of 18 patients with critical illness, 17 were correctly identified (sensitivity: 94.4%, 95% CI, 72.7%-99.9%; specificity: 81.9%, 95% CI, 74.1%-88.2%). Of 127 patients with non-critical illness, 104 were correctly identified. Our results indicate that published knowledge can be reliably applied to assess patient risk, potentially reducing the cognitive burden on physicians, and helping policymakers better prepare for future needs.