Serial Changes in Blood-Cell-Count-Derived and CRP-Derived Inflammatory Indices of COVID-19 Patients.

The aim of the study was to investigate the serial changes in inflammatory indices derived from blood cell counts and C-reactive protein (CRP) levels in COVID-19 patients with good and poor outcomes. We retrospectively analyzed the serial changes in the inflammatory indices in 169 COVID-19 patients. Comparative analyses were performed on the first and last days of a hospital stay or death and serially from day 1 to day 30 from the symptom onset. On admission, non-survivors had higher CRP to lymphocytes ratio (CLR) and multi-inflammatory index (MII) values than survivors, while at the time of discharge/death, the largest differences were found for the neutrophil to lymphocyte ratio (NLR), systemic inflammation response index (SIRI), and MII. A significant decrease in NLR, CLR, and MII by the time of discharge was documented in the survivors, and a significant increase in NLR was documented in the non-survivors. The NLR was the only one that remained significant from days 7-30 of disease in intergroup comparisons. The correlation between the indices and the outcome was observed starting from days 13-15. The changes in the index values over time proved to be more helpful in predicting COVID-19 outcomes than those measured on admission. The values of the inflammatory indices could reliably predict the outcome no earlier than days 13-15 of the disease.

The Dynamics of the Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios Predict Progression to Septic Shock and Death in Patients with Prolonged Intensive Care Unit Stay.

Background and objectives: The prognoses of patients experiencing a prolonged stay in the intensive care unit (ICU) are often significantly altered by hospital-acquired infections (HAIs), the early detection of which might be cumbersome. The aim of this study was to investigate the roles of the neutrophil-to-lymphocyte (NLR), derived-NRL (d-NLR), platelet-to-lymphocyte (PLR), and lymphocyte-to-C-reactive protein (LCR) ratios in predicting the progression to septic shock and death. Materials and Methods: A retrospective analysis of a consecutive series of ninety COVID-19 patients with prolonged hospitalization (exceeding 15 days) admitted to the ICU was conducted. The prevalence of culture-proven HAIs throughout their hospital stays was documented. NLR, dNLR, PLR, and LCR were recorded on admission, day 7, and day 14 to assess their discriminative prowess for detecting further progression to septic shock or death. Results: The prevalence of HAIs was 76.6%, 50% of patients met the criteria for septic shock, and 50% died. The median time to the first positive culture was 13.5 days and 20.5 days for developing septic shock. Mechanical ventilation was a key contributing factor to HAI, septic shock, and mortality. On admission and day 7 NLR, dNLR, PLR, and LCR values had no prognostic relevance for events occurring late during hospitalization. However, day-14 NLR, dNLR, and PLR were independent predictors for progression to septic shock and mortality and have shown good discriminative capabilities. The AUCs for septic shock were 0.762, 0.764, and 0.716, while the values for predicting in-hospital death were 0.782, 0.778, and 0.758, respectively. Conclusions: NLR, dNLR, and PLR are quick, easy-to-use, cheap, effective biomarkers for the detection of a more severe disease course, of the late development of HAIs, and of the risk of death in critically ill patients requiring a prolonged ICU stay.

Predictive value of neutrophil-to-lymphocyte ratio in terms of need for intensive care unit and mortality in maintenance hemodialysis patients with COVID-19.

INTRODUCTION: The transmission risk of Severe Acute Respiratory Syndrome Coronavirus-2 virus infection is increased in maintenance hemodialysis (MHD) patients, and also the disease causes much higher mortality than the normal population. The aim of this study is to define the predictive value of neutrophil-to-lymphocyte ratio (NLR) in terms of worse outcomes in MHD patients. METHODS: A total of 123 MHD patients who had received inpatient care due to COVID-19 infection were included in this multicentered retrospective study. Receiver operating curve analysis were plotted to illustrate C reactive protein (C-rp), systemic inflammatory index (SII) and NLR best cut-off values for estimation of need for intensive care unit (ICU) and mortality. Multivariate regression analysis and Cox proportional hazard models were constructed to determine the association between C-rp, SII and NLR and mortality. RESULTS: Twenty-eight (23%) patients with MHD were dead due to COVID-19. Nonsurvivor patients was significantly older than the survivors (p < 0.001) and also had higher rates of diabetes mellitus (p = 0.01) and coronary artery disease (p = 0.02). Cox regression analysis revealed that NLR >5.17 significantly associated with mortality [HR: 6.508, p < 0.001]. Similarly, SII > 726 [HR: 3.124, p = 0.006] and C-rp > 88 [HR: 4.590, p = 0.002] were significantly associated with mortality due to COVID-19 in hospitalized MHD patients. Multivarite logistic regression analysis showed that age older than 60 years, higher ferritin, and NLR > 5.17 were independent factors associated with mortality. CONCLUSION: NLR had favorable predictive value than the C-rp and SII in terms of need for ICU and mortality in MHD patients. Determining the poor prognosis with simple and easily applicable markers may reduce mortality in these patients with early supportive treatments.

Cardiovascular and Renal Comorbidities Included into Neural Networks Predict the Outcome in COVID-19 Patients Admitted to an Intensive Care Unit: Three-Center, Cross-Validation, Age- and Sex-Matched Study.

Here, we performed a multicenter, age- and sex-matched study to compare the efficiency of various machine learning algorithms in the prediction of COVID-19 fatal outcomes and to develop sensitive, specific, and robust artificial intelligence tools for the prompt triage of patients with severe COVID-19 in the intensive care unit setting. In a challenge against other established machine learning algorithms (decision trees, random forests, extra trees, neural networks, k-nearest neighbors, and gradient boosting: XGBoost, LightGBM, and CatBoost) and multivariate logistic regression as a reference, neural networks demonstrated the highest sensitivity, sufficient specificity, and excellent robustness. Further, neural networks based on coronary artery disease/chronic heart failure, stage 3-5 chronic kidney disease, blood urea nitrogen, and C-reactive protein as the predictors exceeded 90% sensitivity and 80% specificity, reaching AUROC of 0.866 at primary cross-validation and 0.849 at secondary cross-validation on virtual samples generated by the bootstrapping procedure. These results underscore the impact of cardiovascular and renal comorbidities in the context of thrombotic complications characteristic of severe COVID-19. As aforementioned predictors can be obtained from the case histories or are inexpensive to be measured at admission to the intensive care unit, we suggest this predictor composition is useful for the triage of critically ill COVID-19 patients.

Neutrophil to lymphocyte ratio and in-hospital mortality among patients with SARS-CoV-2: A retrospective study.

The goal of this study was to investigate in-hospital mortality in patients suffering from acute respiratory syndrome coronavirus 2 (SARS-CoV-2) relative to the neutrophil to lymphocyte ratio (NLR) and to determine if there are gender disparities in outcome. Between February 26 and September 8, 2020, patients having SARS-CoV-2 infection were enrolled in this retrospective cohort research, which was categorized by NLR levels ≥9 and < 9. In total, 6893 patients were involved included of whom6591 had NLR <9, and 302 had NLR ≥9. The age of most of the patients in the NLR<9 group was 50 years, on the other hand, the age of most of the NLR ≥9 group patients was between 50 and 70 years. The majority of patients in both groups were male 2211 (66.1%). The ICU admission time and mortality rate for the patients with NLR ≥9 was significantly higher compared to patients with NLR <9. Logistic regression's outcome indicated that NLR ≥9 (odds ratio (OR), 24.9; 95% confidence interval (CI): 15.5-40.0; p < 0.001), male sex (OR, 3.5; 95% CI: 2.0-5.9; p < 0.001) and haemoglobin (HB) (OR, 0.95; 95% CI; 0.94-0.96; p < 0.001) predicted in-hospital mortality significantly. Additionally, Cox proportional hazards analysis (B = 4.04, SE = 0.18, HR = 56.89, p < 0.001) and Kaplan-Meier survival probability plots also indicated that NLR>9 had a significant effect on mortality. NLR ≥9 is an independent predictor of mortality(in-hospital) among SARS-CoV-2 patients.

The Value of Early and Follow-Up Elevated Scores Based on Peripheral Complete Blood Cell Count for Predicting Adverse Outcomes in COVID-19 Patients.

Background: The ongoing COVID-19 pandemic has put a constant strain on hospital resources, so there is a dire need for investigation methods that are widely available and that can predict mortality and the need for critical care. Hematological indices, which can be easily calculated from a complete blood count (CBC), are useful in determining a patient's inflammatory response to infectious diseases. Aim: This was a prospective cohort study that aimed to assess the prognostic value of scores based on CBCs in hospitalized patients with mild or moderate COVID-19 and medical comorbidities regarding the need for intensive care unit (ICU) therapy and short-term mortality. Methods: We included 607 patients with confirmed COVID-19, followed up for the need for ICU admission (15.5%) and 30 day mortality post-discharge (21.7%). CBC-derived scores were tested upon emergency department (ED) admission and after a median of 8 days. Results: In a multivariate model, elevated followed-up neutrophil-to-lymphocyte ratio (NLR) predicted increased odds for ICU admission (OR: 1.14 [95%CI: 1.06−1.22], p < 0.001) and short-term mortality (OR: 1.30 [95%CI: 1.09−1.57], p = 0.005). Monocyte-to-lymphocyte ratio (MLR) predicted 2.5-fold increased odds for ICU admission and 2.2-fold increased odds for mortality. Conclusion: NLR and MLR followed up 8 days post-admission are predictive for adverse outcomes in mild or moderate COVID-19 patients.

Dapsone Lowers Neutrophil to Lymphocyte Ratio and Mortality in COVID-19 Patients Admitted to the ICU.

Some physicians use dapsone as part of the standard treatment of severe COVID-19 patients entering the ICU, though some do not. To obtain an indication of whether dapsone is helping or not, we undertook a retrospective chart review of 29 consecutive ICU COVID-19 patients receiving dapsone and 30 not receiving dapsone. As we previously reported, of those given dapsone, 9/29 (30%) died, while of those not given dapsone, 18/30 (60%) died. We looked back on that data set to determine if there might be basic laboratory findings in these patients that might give an indication of a mechanism by which dapsone was acting. We found that the neutrophil-to-lymphocyte ratio decreased in 48% of those given dapsone and in 30% of those not given dapsone. We concluded that dapsone might be lowering that ratio. We then reviewed collected data on neutrophil related inflammation pathways on which dapsone might act as presented here. As this was not a controlled study, many variables prevent drawing any conclusions from this work; a formal, randomized controlled study of dapsone in severe COVID-19 is warranted.

Humulus lupus extract rich in xanthohumol improves the clinical course in critically ill COVID-19 patients.

BACKGROUND: The systemic inflammatory response following severe COVID-19 is associated with poor outcomes. Several anti-inflammatory medications have been studied in COVID-19 patients. Xanthohumol (Xn), a natural extract from hop cones, possesses strong anti-inflammatory and antioxidative properties. The aim of this study was to analyze the effect of Xn on the inflammatory response and the clinical outcome of COVID-19 patients. METHODS: Adult patients treated for acute respiratory failure (PaO2/FiO2 less than 150) were studied. Patients were randomized into two groups: Xn - patients receiving adjuvant treatment with Xn at a daily dose of 4.5 mg/kg body weight for 7 days, and C - controls. Observations were performed at four time points: immediately after admission to the ICU and on the 3rd, 5th, and 7th days of treatment. The inflammatory response was assessed based on the plasma IL-6 concentration, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), C-reactive protein (CRP) and D-dimer levels. The mortality rate was determined 28 days after admission to the ICU. RESULTS: Seventy-two patients were eligible for the study, and 50 were included in the final analysis. The mortality rate was significantly lower and the clinical course was shorter in the Xn group than in the control group (20% vs. 48%, p < 0.05, and 9 ± 3 days vs. 22 ± 8 days, p < 0.001). Treatment with Xn decreased the plasma IL-6 concentration (p < 0.01), D-dimer levels (p < 0.05) and NLR (p < 0.01) more significantly than standard treatment alone. CONCLUSION: Adjuvant therapy with Xn appears to be a promising anti-inflammatory treatment in COVID-19 patients.

A case series report on successful management of patients with COVID-19-associated lymphopenia and potential application of PG2.

Background: Lymphopenia and the resultant high neutrophil-to-lymphocyte ratio (NLR) are hallmark signs of severe COVID-19, and effective treatment remains unavailable. We retrospectively reviewed the outcomes of COVID-19 in a cohort of 26 patients admitted to Chung Shan Medical University Hospital (Taichung City, Taiwan). Twenty-five of the 26 patients recovered, including 9 patients with mild/moderate illness and 16 patients with severe/critical illness recovered. One patient died after refusing treatment. Case presentation: We report the cases of four patients with high NLRs and marked lymphopenia, despite receiving standard care. A novel injectable botanical drug, PG2, containing Astragalus polysaccharides, was administered to them as an immune modulator. The decrease in the NLR in these four patients was faster than that of other patients in the cohort (0.80 vs. 0.34 per day). Conclusion: All patients recovered from severe COVID-19 showed decreased NLR and normalized lymphocyte counts before discharge. Administration of PG2 may be of benefit to patients with moderate to severe COVID-19 and lymphopenia.

Prognostic Nutritional Index, Controlling Nutritional Status (CONUT) Score, and Inflammatory Biomarkers as Predictors of Deep Vein Thrombosis, Acute Pulmonary Embolism, and Mortality in COVID-19 Patients.

BACKGROUND: Numerous tools, including nutritional and inflammatory markers, have been evaluated as the predictors of poor outcomes in COVID-19 patients. This study aims to verify the predictive role of the prognostic nutritional index (PNI), CONUT Score, and inflammatory markers (monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in cases of deep vein thrombosis (DVT) and acute pulmonary embolism (APE) risk, as well as mortality, in COVID-19 patients. METHODS: The present study was designed as an observational, analytical, retrospective cohort study, and included 899 patients over the age of 18 who had a COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and were admitted to the County Emergency Clinical Hospital and Modular Intensive Care Unit of UMFST "George Emil Palade" of Targu Mures, Romania between January 2020 and March 20212. RESULTS: Non-Surviving patients were associated with a higher incidence of chronic kidney disease (p = 0.01), cardiovascular disease (atrial fibrillation (AF) p = 0.01; myocardial infarction (MI) p = 0.02; peripheral arterial disease (PAD) p = 0.0003), malignancy (p = 0.0001), tobacco (p = 0.0001), obesity (p = 0.01), dyslipidemia (p = 0.004), and malnutrition (p < 0.0001). Multivariate analysis showed that both nutritional and inflammatory markers had a high baseline value and were all independent predictors of adverse outcomes for all enrolled patients (for all p < 0.0001). The presence of PAD, malignancy, and tobacco, were also independent predictors of all outcomes. CONCLUSIONS: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, CONUT Score, and lower PNI values at admission strongly predict DVT risk, APE risk, and mortality in COVID-19 patients. Moreover, PAD, malignancy, and tobacco, all predicted all outcomes, while CKD predicts APE risk and mortality, but not the DVT risk.

Neutrophil-to-lymphocyte ratio as a potential biomarker in predicting influenza susceptibility.

Background: Human population exposed to influenza viruses exhibited wide variation in susceptibility. The ratio of neutrophils to lymphocytes (NLR) has been examined to be a marker of systemic inflammation. We sought to investigate the relationship between influenza susceptibility and the NLR taken before influenza virus infection. Methods: We investigated blood samples from five independent influenza challenge cohorts prior to influenza inoculation at the cellular level by using digital cytometry. We used multi-cohort gene expression analysis to compare the NLR between the symptomatic infected (SI) and asymptomatic uninfected (AU) subjects. We then used a network analysis approach to identify host factors associated with NLR and influenza susceptibility. Results: The baseline NLR was significantly higher in the SI group in both discovery and validation cohorts. The NLR achieved an AUC of 0.724 on the H3N2 data, and 0.736 on the H1N1 data in predicting influenza susceptibility. We identified four key modules that were not only significantly correlated with the baseline NLR, but also differentially expressed between the SI and AU groups. Genes within these four modules were enriched in pathways involved in B cell-mediated immune responses, cellular metabolism, cell cycle, and signal transduction, respectively. Conclusions: This study identified the NLR as a potential biomarker for predicting disease susceptibility to symptomatic influenza. An elevated NLR was detected in susceptible hosts, who may have defects in B cell-mediated immunity or impaired function in cellular metabolism, cell cycle or signal transduction. Our work can serve as a comparative model to provide insights into the COVID-19 susceptibility.

Interaction Effect Between Hemoglobin and Hypoxemia on COVID-19 Mortality: an observational study from Bogotá, Colombia.

Purpose: We aimed to assess the effect of hemoglobin (Hb) concentration and oxygenation index on COVID-19 patients' mortality risk. Patients and Methods: We retrospectively reviewed sociodemographic and clinical characteristics, laboratory findings, and clinical outcomes from patients admitted to a tertiary care hospital in Bogotá, Colombia, from March to July 2020. We assessed exploratory associations between oxygenation index and Hb concentration at admission and clinical outcomes. We used a generalized additive model (GAM) to evaluate the observed nonlinear relations and the classification and regression trees (CART) algorithm to assess the interaction effects. Results: We included 550 patients, of which 52% were male. The median age was 57 years old, and the most frequent comorbidity was hypertension (29%). The median value of SpO2/FiO2 was 424, and the median Hb concentration was 15 g/dL. The mortality was 15.1% (83 patients). Age, sex, and SpO2/FiO2, were independently associated with mortality. We described a nonlinear relationship between Hb concentration and neutrophil-to-lymphocyte ratio with mortality and an interaction effect between SpO2/FiO2 and Hb concentration. Patients with a similar oxygenation index had different mortality likelihoods based upon their Hb at admission. CART showed that patients with SpO2/FiO2 < 324, who were less than 81 years with an NLR >9.9, and Hb > 15 g/dl had the highest mortality risk (91%). Additionally, patients with SpO2/FiO2 > 324 but Hb of < 12 g/dl and a history of hypertension had a higher mortality likelihood (59%). In contrast, patients with SpO2/FiO2 > 324 and Hb of > 12 g/dl had the lowest mortality risk (9%). Conclusion: We found that a decreased SpO2/FiO2 increased mortality risk. Extreme values of Hb, either low or high, showed an increase in the likelihood of mortality. However, Hb concentration modified the SpO2/FiO2 effect on mortality; the probability of death in patients with low SpO2/FiO2 increased as Hb increased.

A study to evaluate the role of eosinophil count as a prognostic marker for assessing the outcome in patients with COVID-19 infection.

Background and Objectives: The triaging of COVID-19 patients is of paramount importance to plan further management. There are several clinical and laboratory parameters that help in categorizing the disease severity, triaging, and prognostication. Little is known about the prognostic significance of eosinopenia in predicting the severity of COVID-19 from large hospital data, especially from low- and middle-income countries. The objective of this study is to evaluate the level of eosinopenia as an early prognostic marker for assessing the outcomes in COVID-19 patients and to assess the superiority of eosinopenia as a prognostic marker for assessing the outcomes in COVID-19 patients compared to lymphopenia and neutrophil-to-lymphocyte ratio (NLR). Methods: The study was carried out in a tertiary care hospital. A retrospective longitudinal approach was adopted wherein the hospital records of COVID-19 patients were analyzed. In our study, two separate groups of patients were included for analysis to describe the association between initial eosinophil counts of the patients and the clinical outcomes. In the first group, the disease severity in terms of clinical and radiological parameters was compared in patients of COVID-19 presenting with and without the presence of initial eosinopenia. Commonly used markers for triage, namely lymphopenia and NLR, were compared with the presence of initial eosinopenia among the patients who progressed to moderate and severe disease. In the second group, an analysis of eosinopenia was made among the patients who succumbed to the illness. Results: It was seen that 29.6% of patients with eosinopenia had moderate and severe disease compared to those without eosinopenia where only 10.8% had moderate disease, none had severe disease. It was seen that 19.7% of patients with eosinopenia but no lymphopenia had more severe disease compared to patients with lymphopenia but no eosinopenia where 10.8% of the patients had moderate disease, none had severe disease. In patients younger than 60 years who died of COVID-19, it was found that initial eosinopenia was found in 86%, whereas a high NLR >17 was seen in only 25.6% of patients who died, thus implying that is eosinopenia is an important marker of disease severity in COVID-19. Conclusions: Eosinopenia is an important parameter in the evaluation of COVID-19 and the presence of it should alert the clinicians regarding the further progression of the disease. It is not only an important marker but also an early marker for severe disease.

Neutrophil-to-lymphocyte ratio as a predictor of clinical outcomes in critically ill COVID-19 patients: A retrospective observational study.

Background: Timely identification of patients at risk of worse clinical outcomes is vital in managing coronavirus disease 2019 (COVID-19). The neutrophil-to-lymphocyte ratio (NLR) calculated from complete blood count can predict the degree of systemic inflammation and guide therapy accordingly. Hence, we did a study to investigate the role of NLR value on intensive care unit (ICU) admission in predicting clinical outcomes of critically ill COVID-19 patients. Methods: We conducted a retrospective analysis of electronic health records of COVID-19 patients admitted to ICUs at Hazm Mebaireek General Hospital, Qatar, from March 7, 2020 to July 18, 2020. Patients with an NLR equal to or higher than the cut-off value derived from the receiver operating characteristic curve were compared to those with an NLR value below the cut-off. The primary outcome studied was all-cause ICU mortality. The secondary outcomes evaluated were the requirement of mechanical ventilation and ICU length of stay (LOS). Results: Five hundred and nineteen patients were admitted to ICUs with severe COVID-19 infection during the study period. Overall, ICU mortality in the study population was 14.6% (76/519). NLR on ICU admission of ≥6.55 was obtained using Youden's index to predict ICU mortality, with a sensitivity of 81% and specificity of 41%. Mortality was significantly higher in patients with age ≥60 years (p < 0.001), chronic kidney disease (p = 0.03), malignancy (p < 0.002), and NLR ≥ 6.55 (p < 0.003). There was also a significant association between the requirement of mechanical ventilation (34.7% vs. 51.8%, p < 0.001) and increased ICU LOS (8 vs. 10 days, p < 0.01) in patients with ICU admission NLR ≥ 6.55. Conclusion: Higher NLR values on ICU admission are associated with worse clinical outcomes in critically ill COVID-19 patients.

Plasma-induced nanoparticle aggregation for stratifying COVID-19 patients according to disease severity.

Stratifying patients according to disease severity has been a major hurdle during the COVID-19 pandemic. This usually requires evaluating the levels of several biomarkers, which may be cumbersome when rapid decisions are required. In this manuscript we show that a single nanoparticle aggregation test can be used to distinguish patients that require intensive care from those that have already been discharged from the intensive care unit (ICU). It consists of diluting a platelet-free plasma sample and then adding gold nanoparticles. The nanoparticles aggregate to a larger extent when the samples are obtained from a patient in the ICU. This changes the color of the colloidal suspension, which can be evaluated by measuring the pixel intensity of a photograph. Although the exact factor or combination of factors behind the different aggregation behavior is unknown, control experiments demonstrate that the presence of proteins in the samples is crucial for the test to work. Principal component analysis demonstrates that the test result is highly correlated to biomarkers of prognosis and inflammation that are commonly used to evaluate the severity of COVID-19 patients. The results shown here pave the way to develop nanoparticle aggregation assays that classify COVID-19 patients according to disease severity, which could be useful to de-escalate care safely and make a better use of hospital resources.

Charlson comorbidity index, neutrophil-to-lymphocyte ratio and undertreatment with renin-angiotensin-aldosterone system inhibitors predict in-hospital mortality of hospitalized COVID-19 patients during the omicron dominant period.

Purpose: To investigate the clinical predictors of in-hospital mortality in hospitalized patients with Coronavirus disease 2019 (COVID-19) infection during the Omicron period. Methods: All consecutive hospitalized laboratory-confirmed COVID-19 patients between January and May 2022 were retrospectively analyzed. All patients underwent accurate physical, laboratory, radiographic and echocardiographic examination. Primary endpoint was in-hospital mortality. Results: 74 consecutive COVID-19 patients (80.0 ± 12.6 yrs, 45.9% males) were included. Patients who died during hospitalization (27%) and those who were discharged alive (73%) were separately analyzed. Compared to patients discharged alive, those who died were significantly older, with higher comorbidity burden and greater prevalence of laboratory, radiographic and echographic signs of pulmonary and systemic congestion. Charlson comorbidity index (CCI) (OR 1.76, 95%CI 1.07-2.92), neutrophil-to-lymphocyte ratio (NLR) (OR 1.24, 95%CI 1.10-1.39) and absence of angiotensin-converting enzyme inhibitors (ACEI)/angiotensin II receptor blockers (ARBs) therapy (OR 0.01, 95%CI 0.00-0.22) independently predicted the primary endpoint. CCI ≥7 and NLR ≥9 were the best cut-off values for predicting mortality. The mortality risk for patients with CCI ≥7, NLR ≥9 and not in ACEI/ARBs therapy was high (86%); for patients with CCI <7, NLR ≥9, with (16.6%) or without (25%) ACEI/ARBs therapy was intermediate; for patients with CCI <7, NLR <9 and in ACEI/ARBs therapy was of 0%. Conclusions: High comorbidity burden, high levels of NLR and the undertreatment with ACEI/ARBs were the main prognostic indicators of in-hospital mortality. The risk stratification of COVID-19 patients at hospital admission would help the clinicians to take care of the high-risk patients and reduce the mortality.