Simple Parameters from Complete Blood Count Predict In-Hospital Mortality in COVID-19.

INTRODUCTION: The clinical course of Coronavirus Disease 2019 (COVID-19) is highly heterogenous, ranging from asymptomatic to fatal forms. The identification of clinical and laboratory predictors of poor prognosis may assist clinicians in monitoring strategies and therapeutic decisions. MATERIALS AND METHODS: In this study, we retrospectively assessed the prognostic value of a simple tool, the complete blood count, on a cohort of 664 patients (F 260; 39%, median age 70 (56-81) years) hospitalized for COVID-19 in Northern Italy. We collected demographic data along with complete blood cell count; moreover, the outcome of the hospital in-stay was recorded. RESULTS: At data cut-off, 221/664 patients (33.3%) had died and 453/664 (66.7%) had been discharged. Red cell distribution width (RDW) (χ 2 10.4; p < 0.001), neutrophil-to-lymphocyte (NL) ratio (χ 2 7.6; p = 0.006), and platelet count (χ 2 5.39; p = 0.02), along with age (χ 2 87.6; p < 0.001) and gender (χ 2 17.3; p < 0.001), accurately predicted in-hospital mortality. Hemoglobin levels were not associated with mortality. We also identified the best cut-off for mortality prediction: a NL ratio > 4.68 was characterized by an odds ratio for in-hospital mortality (OR) = 3.40 (2.40-4.82), while the OR for a RDW > 13.7% was 4.09 (2.87-5.83); a platelet count > 166,000/µL was, conversely, protective (OR: 0.45 (0.32-0.63)). CONCLUSION: Our findings arise the opportunity of stratifying COVID-19 severity according to simple lab parameters, which may drive clinical decisions about monitoring and treatment.

Pattern of Emergency Department referral during the COVID-19 outbreak in Italy.

BACKGROUND: The Coronavirus disease (COVID-19) outbreak is putting the European National Health Systems under pressure. Interestingly, Emergency Department (ED) referrals for other reasons than COVID-19 seem to have declined steeply. In the present paper, we aimed to verify how the COVID-19 outbreak changed ED referral pattern. METHODS: We retrospectively reviewed the clinical records of patients referred to the ED of a University Hospital in Northern Italy from 1 March to 13 April 2020. We compared the following data with those belonging to the same period in 2019: number of EDs accesses, rate of hospital admission, frequencies of the most common causes of ED referral, priority codes of access. RESULTS: The number of ED referrals during the COVID-19 outbreak was markedly reduced when compared to the same period in 2019 (3059 vs. 5691; -46.3%). Conversely, the rate of hospital admission raised from 16.9% to 35.4% (P<0.0001), with a shift toward higher priority codes of ED admission. In 2020, we observed both a reduction of the number of patients referred for both traumatic (513, 16.8% vs. 1544, 27.1%; χ2=118.7, P<0.0001) and non-traumatic (4147 vs. 2546) conditions. Among the latter, suspected COVID-19 accounted for 1101 (43.2%) accesses. CONCLUSIONS: The COVID-19 pandemic completely changed the pattern of ED referral in Italy, with a marked reduction of the accesses to the hospitals. This could be related to a limited exposure to traumas and to a common fear of being infected during EDs in-stay. This may limit the misuse of EDs for non-urgent conditions but may also delay proper referrals for urgent conditions.

Clinical stability and in-hospital mortality prediction in COVID-19 patients presenting to the Emergency Department.

BACKGROUND: The Novara-COVID score was developed to help the emergency physician to decide which Coronavirus disease (COVID) patient required hospitalization at Emergency Department (ED) presentation and to which intensity of care. We aimed at evaluating its prognostic role. METHODS: We retrospectively collected data of COVID patients admitted to our ED between March 16 and April 22, 2020. The Novara-COVID score was systematically applied to all COVID patients since its introduction in clinical practice and adopted to decide patients' destination. The ability of the Novara-COVID score to predict in-hospital clinical stability and in-hospital mortality were evaluated through multivariable logistic regression and cox regression hazard models, respectively. RESULTS: Among the 480 COVID patients admitted to the ED, 338 were hospitalized: the Novara-COVID score was 0-1 in 49.7%, 2 in 24.6%, 3 in 15.4% and 4-5 in 10.3% of patients. Novara-COVID score values of 3 and 4-5 were associated with lower clinical stability with adjusted odds ratios of 0.28 (0.13-0.59) and 0.03 (0.01-0.12), respectively. When in-hospital mortality was evaluated, a significant difference emerged between scores of 0-1 and 2 vs. 3 and 4-5. In particular, the death adjusted hazard ratio for Novara-COVID scores of 3 and 4-5 were 2.6 (1.4-4.8) and 8.4 (4.7-15.2), respectively. CONCLUSIONS: The Novara-COVID score reliably predicts in-hospital clinical instability and mortality of COVID patients at ED presentation. This tool allows the emergency physician to detect patients at higher risk of clinical deterioration, suggesting a more aggressive therapeutic management from the beginning.

Fatality rate and predictors of mortality in an Italian cohort of hospitalized COVID-19 patients.

Clinical features and natural history of coronavirus disease 2019 (COVID-19) differ widely among different countries and during different phases of the pandemia. Here, we aimed to evaluate the case fatality rate (CFR) and to identify predictors of mortality in a cohort of COVID-19 patients admitted to three hospitals of Northern Italy between March 1 and April 28, 2020. All these patients had a confirmed diagnosis of SARS-CoV-2 infection by molecular methods. During the study period 504/1697 patients died; thus, overall CFR was 29.7%. We looked for predictors of mortality in a subgroup of 486 patients (239 males, 59%; median age 71 years) for whom sufficient clinical data were available at data cut-off. Among the demographic and clinical variables considered, age, a diagnosis of cancer, obesity and current smoking independently predicted mortality. When laboratory data were added to the model in a further subgroup of patients, age, the diagnosis of cancer, and the baseline PaO2/FiO2 ratio were identified as independent predictors of mortality. In conclusion, the CFR of hospitalized patients in Northern Italy during the ascending phase of the COVID-19 pandemic approached 30%. The identification of mortality predictors might contribute to better stratification of individual patient risk.