Factors Associated with ICU Admission in Patients with COVID-19: The GOL2DS Score.

Background and Objectives: The COVID-19 pandemic has been shaking lives around the world for nearly two years. The discovery of highly effective vaccines has not been able to stop the transmission of the virus. SARS-CoV-2 shows completely different clinical manifestations. A large percentage (about 40%) of admitted patients require treatment in an intensive care unit (ICU). This study investigates the factors associated with admission of COVID-19 patients to the ICU and whether it is possible to obtain a score that can help the emergency physician to select the hospital ward. Materials and Methods: We retrospectively recorded 313 consecutive patients who were presented to the emergency department (ED) of our hospital and had a diagnosis of COVID-19 confirmed by polymerase chain reaction (PCR) on an oropharyngeal swab. We used multiple logistic regression to evaluate demographic, clinical, and laboratory data statistically associated with ICU admission. These variables were used to create a prognostic score for ICU admission. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and receiver-operating characteristic curve (ROC) of the score for predicting ICU admission during hospitalization were calculated. Results: Of the variables evaluated, only blood type A (p = 0.003), PaO2/FiO2 (p = 0.002), LDH (p = 0.004), lactate (p = 0.03), dyspnea (p = 0.03) and SpO2 (p = 0.0228) were significantly associated with ICU admission after adjusting for sex, age and comorbidity using multiple logistic regression analysis. We used these variables to create a prognostic score called GOL2DS (group A, PaO2/FiO2, LDH, lactate and dyspnea, and SpO2), which had high accuracy in predicting ICU admission (AUROC 0.830 [95% CI, 0.791-0.892). Conclusions: In our single-center experience, the GOL2DS score could be useful in identifying patients at high risk for ICU admission.

Effect of influenza vaccine on COVID-19 mortality: a retrospective study.

It has been proposed that vaccines may exert an unspecific protective effect against infectious agents, different than expected. Coronavirus disease 2019 (COVID-19) is a pandemic infection with high mortality in older patients due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The high number of vaccinations may be one of the reasons why children show a lower susceptibility to SARS-CoV-2 infection and milder severity when compared to adults. We have designed a study aimed at investigating whether the influenza vaccine may reduce the susceptibility and severity of SARS-CoV-2 infection. We retrospectively enrolled 635 patients who accessed our Emergency Department from March 1st to June 30th, 2020, and were diagnosed with COVID-19 infection confirmed by an RT-PCR on an oropharyngeal swab. Clinical data, outcomes, and influenza vaccination status were collected from the electronic medical records of our Hospital. We also used data from the Italian Health Ministry to compare the prevalence of flu vaccination among the general population of the Lazio Region and our enrolled patients. We then compared clinical outcomes between vaccinated and non-vaccinated patients, by univariate and multivariate analysis. COVID-19-positive patients older than 65 years reported a lower prevalence of flu vaccination when compared to the general population residing in the Lazio (p = 0.004). After correction for gender, age, and comorbidities, we found a lower risk of death at 60 days in patients with flu vaccination than in not vaccinated patients (p = 0.001). Our study shows that flu vaccination could reduce the mortality of COVID-19. Prospective studies are needed to confirm this result.

Predictors of in-hospital mortality AND death RISK STRATIFICATION among COVID-19 PATIENTS aged ≥ 80 YEARs OLD.

INTRODUCTION: To date, mainly due to age-related vulnerability and to coexisting comorbidities, older patients often face a more severe COVID-19. This study aimed to identify at Emergency Department (ED) admission the predictors of in-hospital mortality and suitable scores for death risk stratification among COVID-19 patients ≥ 80 years old. METHODS: Single-centre prospective study conducted in the ED of an university hospital, referral center for COVID-19 in central Italy. We included 239 consecutive patients ≥ 80 years old with laboratory-confirmed COVID-19. The primary study endpoint was all-cause in-hospital mortality. Multivariable Cox regression analysis was performed on significant variables at univariate analysis to identify independent risk factor for death. Overall performance in predicting mortality of WHO severity scale, APACHE II score, NEWS score, and CURB-65 was calculated. RESULTS: Median age was 85 [82-89] and 112 were males (46.9%). Globally, 77 patients (32.2%) deceased. The presence of consolidations at chest x-ray and the hypoxemic respiratory failure were significant predictors of poor prognosis. Moreover, age ≥ 85 years, dependency in activities of daily living (ADL), and dementia were risk factors for death, even after adjusting for clinical covariates and disease severity. All the evaluated scores showed a fairly good predictive value in identifying patients who could experience a worse outcome. CONCLUSIONS: Among patients ≥ 80 years old hospitalized with COVID-19, not only a worse clinical and radiological presentation of the disease, but also the increasing age, dementia, and impairment in ADL were strong risk factors for in-hospital death, regardless of disease severity.

Lung Ultrasound Findings Are Associated with Mortality and Need for Intensive Care Admission in COVID-19 Patients Evaluated in the Emergency Department.

Lung ultrasound (LUS) has recently been advocated as an accurate tool to diagnose coronavirus disease 2019 (COVID-19) pneumonia. However, reports on its use are based mainly on hypothesis studies, case reports or small retrospective case series, while the prognostic role of LUS in COVID-19 patients has not yet been established. We conducted a prospective study aimed at assessing the ability of LUS to predict mortality and intensive care unit admission of COVID-19 patients evaluated in a tertiary level emergency department. Patients in our sample had a median of 6 lung areas with pathologic findings (inter-quartile range [IQR]: 6, range: 0-14), defined as a score different from 0. The median rate of lung areas involved was 71% (IQR: 64%, range: 0-100), while the median average score was 1.14 (IQR: 0.93, range: 0-3). A higher rate of pathologic lung areas and a higher average score were significantly associated with death, with an estimated difference of 40.5% (95% confidence interval [CI]: 4%-68%, p = 0.01) and of 0.47 (95% CI: 0.06-0.93, p = 0.02), respectively. Similarly, the same parameters were associated with a significantly higher risk of intensive care unit admission with estimated differences of 29% (95% CI: 8%-50%, p = 0.008) and 0.47 (95% CI: 0.05-0.93, p = 0.02), respectively. Our study indicates that LUS is able to detect COVID-19 pneumonia and to predict, during the first evaluation in the emergency department, patients at risk for intensive care unit admission and death.