Comparison of systemic immune-inflammation index (SII), early warning score (ANDC) and prognostic nutritional index (PNI) in hospitalized patients with malignancy, and their influence on mortality from COVID-19

Can the Early Warning Score (ANDC) Predict Tocilizumab Efficacy in Patients with COVID-19 Cytokine Storm?

Background

The aim of this study is to assess the effectiveness of the Early Warning Score [ANDC (age (A), neutrophil-to-lymphocyte ratio (NLR (N)), D-dimer (D), and CRP (C)] in predicting the treatment response in patients receiving tocilizumab for Coronavirus Disease 2019 (COVID-19)-related cytokine storm.

Methods

A retrospective review of medical records was conducted for patients treated with tocili- zumab for a cytokine storm related to COVID-19 between April 1, 2020, and April 1, 2021. Patient demographics, clinical characteristics, and laboratory parameters within 24 hours before tocilizumab were recorded. 1.14 × (age - 20) (years) + 1.63 × NLR + 5.00 × D-dimer (mg/L) + 0.14 × C-reactive protein (CRP) (mg/L) was used as the formula for the ANDC score. The study population was divided into 2 groups: those who died within 28 days of receiving tocilizumab and those who recovered. A comparative analysis was conducted.

Results

Within 28 days of tocilizumab treatment, 59 (35.32%) patients died. In comparison with living patients, deceased patients exhibited considerably higher levels of interleukin (IL)-6, lactate dehydro- genase (LDH), ANDC score, and CRP (P < .05). Lactate dehydrogenase was an independent predictor of response to tocilizumab treatment (P < .001) in a multivariate logistic regression analysis. In patients who did not receive steroid therapy before tocilizumab treatment, the ANDC score had the highest area under the curve (AUC). The optimal cut-off value was determined to be 92.56, with a sensitivity of 91.67% and a specificity of 60.61% (P < .001). In patients receiving steroids before tocilizumab, LDH had the highest AUC. The optimal cut-off value was 484.5 U/L (P < .001).

Conclusion

Lactate dehydrogenase was identified as an independent predictor of response to tocili- zumab treatment. The ANDC score showed the highest AUC value in steroid-naïve patients before tocilizumab, whereas LDH showed the highest AUC value in patients receiving steroids before tocili- zumab. Both the ANDC score and LDH levels show potential as valuable tools to guide treatment decisions.

Predicting Severe COVID-19 Outcomes in the Elderly: The Role of Systemic Immune Inflammation, Liver Function Tests, and Neutrophil-to-Lymphocyte Ratio

Background: Patients aged 80 years and above are at increased risk for severe COVID-19 outcomes. This study aimed to evaluate the prognostic utility of the derived neutrophil-to-lymphocyte ratio (dNLR), aspartate-aminotransferase-to-lymphocyte ratio index (ALRI), aspartate-aminotransferase-to-platelet ratio index (APRI), and systemic immune inflammation index (SII) in predicting severe disease, intensive care unit (ICU) admission, and mortality among COVID-19 patients aged 80 years and older. Methods: In this retrospective cohort study, 138 elderly patients (≥80 years) and 215 younger controls (<65 years) with confirmed COVID-19 were included. Laboratory data at admission were collected, and the dNLR, ALRI, APRI, and SII scores were calculated. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive performance of these indices. Results: The SII had the highest area under the ROC curve (AUC) for predicting severe disease in elderly patients (AUC = 0.857, 95% CI: 0.795-0.919, p < 0.001), with an optimal cutoff value of 920 × 10⁹/L (sensitivity 86%, specificity 78%). Elevated SII was significantly associated with increased risk of ICU admission (hazard ratio (HR): 2.9, 95% CI: 1.8-4.6, p < 0.001) and mortality (HR: 3.2, 95% CI: 1.9-5.2, p < 0.001). Similarly, dNLR showed good predictive value (AUC = 0.792, 95% CI: 0.722-0.862, p < 0.001). Conclusions: SII and dNLR are valuable prognostic biomarkers for predicting severe outcomes in COVID-19 patients aged 80 years and above. Early identification using these indices can assist clinicians in risk stratification and management decisions to improve patient outcomes.

Clinical presentations, systemic inflammation response and ANDC scores in hospitalized patients with COVID-19

The association of anosmia/ageusia with a positive severe respiratory syndrome coronavirus 2 (SARS-CoV-2) test is well-established, suggesting these symptoms are reliable indicators of coronavirus disease 2019 (COVID-19) infection. This study investigates the clinical characteristics and systemic inflammatory markers in hospitalized COVID-19 patients in Taiwan, focusing on those with anosmia/ageusia. We conducted a retrospective observational study on 231 hospitalized COVID-19 patients (alpha variant) from April to July 2021. Clinical symptoms, dyspnea grading, and laboratory investigations, including neutrophil-lymphocyte ratios (NLRs), platelet-lymphocyte ratios (PLRs), and ANDC scores (an early warning score), were analyzed. Cough (64.1%), fever (58.9%), and dyspnea (56.3%) were the most common symptoms, while anosmia/ageusia affected 9% of patients. Those with anosmia/ageusia were younger, had lower BMI, lower systemic inflammatory markers, and better ANDC scores than those without these symptoms. Female patients exhibited lower NLR values and ANDC scores compared to male patients (all p < 0.05). Multivariable regression analysis demonstrated significant associations between NLR and CRP and ferritin levels (all p < 0.01), and between PLR and ESR and ferritin levels (p < 0.01). Categorized ANDC scores significantly correlated with the total hospital length of stay (all p < 0.05). Despite ethnic differences in the prevalence of anosmia/ageusia, our study highlights similar clinical presentations and inflammatory profiles to those observed in Western countries. The ANDC score effectively predicted hospital stay duration. These findings suggest that anosmia/ageusia may be associated with less severe disease and a lower inflammatory response, particularly in younger and female patients. The ANDC score can serve as a valuable prognostic tool in assessing the severity and expected hospital stay of COVID-19 patients.

Evaluation of malnutrition by objective nutritional indexes and predictors in hospitalized patients with COVID-19

Nutritional information on hospitalized patients with COVID-19 is limited. We aimed to (1) investigate the prevalence of nutrition risk defined by the Scored Nutritional Risk Screening (NRS 2002) and malnutrition assessed by prognostic nutritional index (PNI) and controlling nutritional status score (CONUT), (2) observe the nutritional intervention, and (3) explore the predictors of critical condition and mortality. Nutritional risk was 53.00% and the prevalence of malnutrition was 79.09% and 88.79% among 464 patients based on PNI and CONUT, respectively. The area under the receiver operating characteristic curve for hypersensitivity C-reactive protein (hs-CRP), platelet-to-lymphocyte ratio (PLR), PNI, neutrophil/lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and CONUT were 0.714, 0.677, 0.243, 0.778, 0.742, and 0.743, respectively, in discerning critical patients. The mortality-related area under the curve of hs-CRP, PLR, PNI, NLR, SII, and CONUT were 0.740, 0.647, 0.247, 0.814, 0.758, and 0.767, respectively. The results showed that CONUT and NLR were significantly correlated with the critical conditions. Our study revealed a high prevalence of nutritional risk and malnutrition among hospitalized patients with COVID-19. NLR, PLR, hs-CRP, SII, and CONUT are independent predictors of critical conditions and mortality. CONUT and NLR could assist clinicians in discerning critical cases.

Prognostic Nutritional Index (PNI) and Systemic Immune-Inflammatory Index (SII) as markers of severity among patients having COVID-19 infection

Background

Prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) are two novel markers that have emerged as potential candidates as an early indication of the severity of the disease in coronavirus disease 2019 (COVID-19) patients.

Objective

The objective of the study is to assess the utility of the prognostic nutritional index (PNI) and systemic immune-inflammatory index (SII) as markers of severity among patients with COVID-19 infection.

Methods

This is a retrospective study conducted in a tertiary care centre in South India. A total of 80 patients diagnosed with COVID-19 were included in the study. The patients were divided into mild, moderate, and severe groups based on the clinical parameters as per Indian Council of Medical Research guidelines. Lab values taken at admission were obtained from patient records, using which the PNI and SII were calculated using standard formulae. These markers were correlated with the severity of the COVID-19 illness.

Results

PNI and SII were significantly elevated in the patients with severe COVID-19 illness as compared with mild COVID-19 illness. The mean PNI among subjects with mild COVID-19 and severe COVID-19 being 46.62 ± 6.51 and 34.09 ± 5.81, respectively. The mean SII among subjects with mild COVID-19 was 9,52,287.2 ± 1,42,113, and among subjects with severe COVID-19 was 15,39,461 ± 8,04,285. The cut-off value for PNI and SII for predicting severity of COVID-19 illness was 35.93 and 5,82,400, respectively. The sensitivity for PNI was 87.5, and the SII was 95.

Conclusion

The present study showed a significant correlation between the SII and PNI as markers used to determine the severity of COVID-19. Based on these findings, it can be effectively used independently of other markers to predict critical illness among COVID-19 patients.

Predictivity of the Prognostic Nutritional Index and Systemic Inflammation Index for All-Cause In-Hospital Mortality in Geriatric and Adult COVID-19 Inpatients

Background: The prognostic nutritional index (PNI) and the systemic immune inflammation index (SII) have been used as simple risk-stratification predictors for COVID-19 severity and mortality in the general population. However, the associations between these indices and mortality might differ due to age-related changes such as inflammaging and several comorbid conditions in older patients. Therefore, we aimed to compare the predictivity of the PNI and SII for mortality among hospitalized older patients and patients under 65 years old. Methods: Patients hospitalized with COVID-19 from March 2020 to December 2020 were retrospectively included. The PNI and SII were calculated from hospital records within the first 48 h after admission. Data were evaluated in the whole group and according to age groups (≥65 < years). Receiver operating characteristic curves were drawn to evaluate the predictivity of the PNI and SII. Results: Out of 407 patients included in this study, 48.4% (n = 197) were older patients, and 51.6% (n = 210) were under 65 years old. For mortality, the area under the curve (AUC) of the PNI and SII in the adult group (<65 years) was 0.706 (95% CI 0.583-0.828) (p = 0.003) and 0.697 (95% CI 0.567-0.827) (p < 0.005), respectively. The AUC of the PNI and SII in the older group was 0.515 (95% CI 0.427-0.604) (p = 0.739) and 0.500 (95% CI 0.411-0.590) (p = 0.993). Conclusions: The accuracy of the PNI and SII in predicting mortality in adult COVID-19 patients seemed to be fair, but no association was found in geriatric patients in this study. The predictivity of the PNI and SII for mortality varies according to age groups.

Life's essential 8 metrics and mortality outcomes in insulin resistance: The role of inflammation, vascular aging, and gender

BACKGROUND

Insulin resistance (IR) elevates cardiovascular disease (CVD) and mortality risks. Insulin resistance (IR) increases the risk of CVDs and mortality. Recently, the American Heart Association introduced the Life's Essential 8 (LE8) framework to assess cardiovascular health (CVH). However, its impact on mortality in IR populations is unknown.

METHODS

Analyzing 2005-2018 National Health and Nutrition Examination Survey data, we studied 5301 IR adults (≥20 years). LE8 scores were calculated and participants were categorized into low, moderate, and high CVH groups. Systemic immune-inflammation index (SII) and heart age/vascular age (HVA) were measured as potential mediators. Cox models estimated all-cause and CVD mortality hazard ratios (HRs), stratified by LE8 score and sex, and adjusted for covariates. Mediation analyses assessed SII and HVA's indirect effects. This study is an observational cohort study.

RESULTS

Over a 7.5-year median follow-up, 625 deaths occurred, including 159 CVD-related. Compared to low CVH, moderate and high CVH groups showed reduced all-cause (HR = 0.72, 95% CI 0.58-0.89; HR = 0.38, 95% CI 0.22-0.67) and CVD mortality (HR = 0.42, 95% CI 0.26-0.69; HR = 0.15, 95% CI 0.04-0.57). A 10-point LE8 increase correlated with 15% and 31% reductions in all-cause and CVD mortality, respectively. SII and HVA mediated up to 38% and 12% of these effects. The LE8's protective effect was more pronounced in men.

CONCLUSION

LE8 effectively evaluates CVH and lowers mortality risk in IR adults, partially mediated by SII and HVA. The findings inform clinical practice and public health strategies for CVD prevention in IR populations.

Association between the systemic immune-inflammation index and GnRH antagonist protocol IVF outcomes: a cohort study

RESEARCH QUESTION

What is the relationship between the systemic immune-inflammation index (SII) and IVF outcomes in women undergoing a gonadotrophin-releasing hormone (GnRH) antagonist protocol?

DESIGN

This retrospective cohort study analysed clinical data and blood samples collected before oocyte retrieval from participants undergoing IVF with the GnRH antagonist protocol. Logistic regression and generalized additive models were used to examine the association between SII quartiles and continuous SII values and IVF outcomes.

RESULTS

Higher SII values correlated negatively with biochemical pregnancy, clinical pregnancy, live birth and implantation rates, and positively with early pregnancy loss, independent of age, body mass index, anti-Müllerian hormone and stimulation parameters. The most significant adverse outcomes were observed in the highest SII quartile. A non-linear relationship was identified between log-transformed SII and IVF outcomes, with an inflection point at an SII of approximately 6.72, indicating a threshold effect.

CONCLUSIONS

Elevated SII is associated with poorer IVF outcomes in women after the GnRH antagonist protocol, suggesting its potential as a predictive marker in IVF treatments. Further research is needed to confirm these findings and explore the underlying mechanisms.

Association Between Hemoglobin-Albumin-Lymphocyte-Platelet Index and Mortality in Hospitalized COVID-19 Omicron BA.2 Infected Patients

Background

The hemoglobin-albumin-lymphocyte-platelet (HALP) index is a novel biomarker reflecting systemic inflammation and nutritional status which are important for coronavirus disease 2019 (COVID-19) mortality. However, the association between HALP and mortality in patients with COVID-19 has yet to be investigated.

Methods

A cohort of COVID-19 Omicron BA.2 infected patients admitted to the Shanghai Fourth People's Hospital, School of Medicine, Tongji University from April 12, 2022 to June 17, 2022 was retrospectively analyzed. Laboratory examinations on hospital admission, including hemoglobin, albumin, and lymphocyte and platelet, were collected. The association between baseline HALP and in-hospital poor overall survival (OS) was assessed using Kaplan-Meier curves, Cox regression models, interaction, and stratified analyses.

Results

A total of 2147 patients with COVID-19 Omicron BA.2 infection were included in the final analyses, and mortality in the hospital was 2.65%. Multivariate analysis indicated that low HALP index was independently associated with in-hospital mortality of COVID-19 patients [hazard ratio (HR) = 2.08; 95% confidence interval (CI) = 1.17-3.73]. Subgroup analysis demonstrated that low HALP index was an independent risk factor for in-hospital mortality in COVID-19 patients with age ≥70 (HR = 2.22, CI = 1.18-4.15) and severe cases (HR = 2.09, CI = 1.13-3.86).

Conclusion

HALP index is independently related to in-hospital poor OS for COVID-19 Omicron BA.2 infected patients, especially for age ≥70 and severe cases. HALP index on hospital admission is a useful candidate biomarker for identifying high risk of mortality in COVID-19 Omicron BA.2 infected patients.

Prognostic Nutritional Index as a Predictive Biomarker of Post-Operative Infectious Morbidity in Gynecological Cancer Patients: A Prospective Cohort Study

Malnutrition significantly impacts the post-operative process of gynecological cancer patients. A prominent variable for determining perioperative morbidity is the Prognostic Nutritional Index (PNI). To investigate PNI's predictive value on the risk of post-operative infections, we conducted a prospective cohort study involving women who underwent surgery for gynecological malignancies. Out of the 208 patients enrolled, 28 (13.5%) were malnourished and post-operative infections occurred in 43 patients. Notably, there was a significant difference in PNI between patients who developed infections and those who did not (p = 0.027), as well as between malnourished patients and those with normal nutritional status (p = 0.043). Univariate analysis showed that preoperative PNI predicts the risk of post-operative infections better than post-operative white blood cell count (AUC of 0.562 vs 0.375). However, the most accurate diagnostic results in the multivariate analysis were obtained from random forest and classification tree models (AUC of 0.987 and 0.977, respectively). Essentially, PNI and post-operative white blood cell count provided the best information gain according to rank probabilities. In conclusion, PNI appears to be a critical parameter that merits further investigation during the preoperative evaluation of gynecological malignancies.

It's in the blood: a review of the hematological system in SARS-CoV-2-associated COVID-19

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an unprecedented global healthcare crisis. While SARS-CoV-2-associated COVID-19 affects primarily the respiratory system, patients with COVID-19 frequently develop extrapulmonary manifestations. Notably, changes in the hematological system, including lymphocytopenia, neutrophilia and significant abnormalities of hemostatic markers, were observed early in the pandemic. Hematological manifestations have since been recognized as important parameters in the pathophysiology of SARS-CoV-2 and in the management of patients with COVID-19. In this narrative review, we summarize the state-of-the-art regarding the hematological and hemostatic abnormalities observed in patients with SARS-CoV-2-associated COVID-19, as well as the current understanding of the hematological system in the pathophysiology of acute and chronic SARS-CoV-2-associated COVID-19.

Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) to predict postoperative pneumonia in elderly hip fracture patients

PURPOSE

Investigate the association between the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) about the presence of postoperative pneumonia (POP) in geriatric patients with hip fractures. Compare the predictive value of these biomarkers for POP and assess their potential for early detection of POP.

METHODS

We retrospectively included elderly patients with hip fractures who underwent surgical treatment at our institution. POP was diagnosed according to the guidelines provided by the American Thoracic Society. We collected neutrophil, lymphocyte, and platelet counts upon admission to calculate the NLR, PLR, and SII. Receiver operating characteristic curves were utilized to establish the optimal cutoff values for each index. Multivariate logistic regression analysis and propensity score matching analysis were utilized to assess the independent association between each index and POP after adjusting for demographic, comorbidity, and surgery-related variables.

RESULTS

The study included a total of 1199 patients, among whom 111 cases (9.26%) developed POP. NLR exhibited the highest predictive value for POP in elderly patients with hip fractures compared to PLR and SII (AUC = 0.648, 95% CI 0.594-0.701). A high NLR, using the optimal cutoff value of 5.84, was significantly associated with an increased incidence of POP (OR = 2.24, 95% CI 1.43-3.51). This finding remained statistically significant even after propensity score matching (OR = 2.04, 95% CI 1.31-3.20).

CONCLUSIONS

Among the three inflammatory/immune markers considered, the NLR demonstrates the highest reliability as a predictor for POP in elderly patients with hip fractures. Therefore, it serves as a valuable tool for early identification.

Anti-Viral Surfaces in the Fight against the Spread of Coronaviruses

This review is conducted against the background of nanotechnology, which provides us with a chance to effectively combat the spread of coronaviruses, and which primarily concerns polyelectrolytes and their usability for obtaining protective function against viruses and as carriers for anti-viral agents, vaccine adjuvants, and, in particular, direct anti-viral activity. This review covers nanomembranes in the form of nano-coatings or nanoparticles built of natural or synthetic polyelectrolytes--either alone or else as nanocomposites for creating an interface with viruses. There are not a wide variety of polyelectrolytes with direct activity against SARS-CoV-2, but materials that are effective in virucidal evaluations against HIV, SARS-CoV, and MERS-CoV are taken into account as potentially active against SARS-CoV-2. Developing new approaches to materials as interfaces with viruses will continue to be relevant in the future.

Clinical Significance and Diagnostic Utility of NLR, LMR, PLR and SII in the Course of COVID-19: A Literature Review

Nowadays, society is increasingly struggling with infectious diseases that are characterized by severe course and even death. Recently, the whole world has faced the greatest epidemiological threat, which is COVID-19 caused by SARS CoV-2 virus. SARS CoV-2 infection is often accompanied by severe inflammation, which can lead to the development of different complications. Consequently, clinicians need easily interpreted and effective markers of inflammation that can predict the efficacy of the treatment and patient prognosis. Inflammation is associated with changes in many biochemical and hematological parameters, including leukocyte counts and their populations. In COVID-19, changes in leukocytes count populations such as neutrophils, lymphocytes or monocytes are observed. The numerous research confirm that indicators like neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelets-to-lymphocyte ratio (PLR) and systemic inflammatory index (SII) may prove effective in assessment patient prognosis and choosing optimal therapy. Therefore, in this review, we would like to summarize the latest knowledge about the diagnostic utility of systemic inflammatory ratios - NLR, LMR, PLR and SII in patients with COVID-19. We focused on the papers evaluating the diagnostic utility of inflammatory ratios using ROC curve published in the recent 3 years. Identification of biomarkers associated with inflammation would help the selection of patients with severe course of COVID-19 and high risk of death.

The use of prognostic nutritional index (PNI) and selected inflammatory indicators for predicting malnutrition in COVID-19 patients: A retrospective study

BACKGROUND

Malnutrition causes diverse alterations in the immune system, and COVID-19 is an infection affecting the immune system, consequently leading to malnutrition.

AIMS

This study aimed to investigate the use of prognostic nutritional index (PNI) and selected inflammatory indices for malnutrition screening among COVID-19 hospitalized patients.

MATERIAL AND METHODOLOGY

This is a single-center retrospective study that enrolled 289 hospitalized COVID-19 patients between 1st January to 30th April 2021, their median age was 59 years. Demographic and biochemical data were collected from patients' records. The PNI, platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and an early warning score to predict mortality risk (ANDC) were calculated. Univariate and multivariate logistic regression analyses were performed. A P-value of < 0.05 was considered statistically significant.

RESULTS

about 30 % of patients were admitted to the intensive care unit (ICU), and ICU patients had significantly higher levels of white blood cell (WBCs) count, neutrophils, C-reactive protein (C-RP), and D-dimer (P < 0.05). On the other hand, they had significantly lower levels of lymphocytes and serum albumin (P < 0.001; for both). Those with high ANDC scores were more likely to develop severe conditions affecting nutritional status compared to non-ICU (OR = 1.04, 95 % CI:1.014-1.057; P < 0.001). ANDC showed good discrimination ability with an AUC of 0.784 (cut-off value > 68.19 score).

CONCLUSION

It is suggested that ANDC could be used as a predictor for nutritional status and severity in COVID-19 hospitalized patients.

The derived neutrophil to lymphocyte ratio can be the predictor of prognosis for COVID-19 Omicron BA.2 infected patients

BACKGROUND

Several systemic inflammatory biomarkers have been associated with poor overall survival (OS) and disease severity in patients with coronavirus disease 2019 (COVID-19). However, it remains unclear which markers are better for predicting prognosis, especially for COVID-19 Omicron BA.2 infected patients. The present study aimed to identify reliable predictors of prognosis of COVID-19 Omicron BA.2 from inflammatory indicators.

METHODS

A cohort of 2645 COVID-19 Omicron BA.2 infected patients were retrospectively analyzed during the Omicron BA.2 surge in Shanghai between April 12, 2022, and June 17, 2022. The patients were admitted to the Shanghai Fourth People's Hospital, School of Medicine, Tongji University. Six systemic inflammatory indicators were included, and their cut-off points were calculated using maximally selected rank statistics. The analysis involved Kaplan-Meier curves, univariate and multivariate Cox proportional hazard models, and time-dependent receiver operating characteristic curves (time-ROC) for OS-associated inflammatory indicators.

RESULTS

A total of 2347 COVID-19 Omicron BA.2 infected patients were included. All selected indicators proved to be independent predictors of OS in the multivariate analysis (all P < 0.01). A high derived neutrophil to lymphocyte ratio (dNLR) was associated with a higher mortality risk of COVID-19 [hazard ratio, 4.272; 95% confidence interval (CI), 2.417-7.552]. The analyses of time-AUC and C-index showed that the dNLR (C-index: 0.844, 0.824, and 0.718 for the 5^th, 10^th, and 15^th day, respectively) had the best predictive power for OS in COVID-19 Omicron BA.2 infected patients. Among different sub-groups, the dNLR was the best predictor for OS regardless of age (0.811 for patients aged ≥70 years), gender (C-index, 0.880 for men and 0.793 for women) and disease severity (C-index, 0.932 for non-severe patients and 0.658 for severe patients). However, the platelet to lymphocyte ratio was superior to the other indicators in patients aged <70 years.

CONCLUSIONS

The prognostic ability of the dNLR was higher than the other evaluated inflammatory indicators for all COVID-19 Omicron BA.2 infected patients.