Neutrophil to Lymphocyte Ratio on Admission to Predict Mortality of COVID-19 Elderly Patients

Severe Acute Respiratory Syndrome Corona Virus Disease-2 (SARS-COV-2) is the cause of COVID-19, which led to a global pandemic and high mortality rate, especially in elderly patients. The declining immune system in elderly patients and comorbid diseases lead to more severe symptoms and an increased mortality rate. Many studies have shown that a high Neutrophil-Lymphocyte Ratio (NLR) value can predict the severity and mortality of COVID-19. However, studies on NLR in elderly patients in Indonesia have rarely been conducted. This study aimed to determine the role of NLR on admission as a mortality predictor in COVID-19 elderly patients who underwent in-hospital treatment. This research is an analytical observational study with a retrospective cohort method conducted in Bethesda Hospital, Yogyakarta, Indonesia. The research subjects were selected from July 2020 to October 2021 according to inclusion and exclusion criteria. Inclusion criteria were all elderly COVID-19 patients with an age limit of ≥ 60 years old who had complete hemogram data on admission, demographic data, diagnostic criteria, types of comorbid diseases, and patient outcomes (survivor or non-survivor). The exclusion criteria were elderly COVID-19 patients with incomplete Electronic Medical Records (EMR). This study found 122 elderly patients with COVID-19 with a mortality rate of 30.33%. The result showed that NLR on admission significantly increased significantly in the non-survivor group compared to the survivor group. Multivariate Cox regression analysis presented severity (RR: 5.181; CI 1.662-16.154; p=0.005), comorbid diabetes mellitus (RR: 2.829; CI: 1.115-7.178), NLR > 6.04 (RR: 6.356; CI: 2.428-16.639) and other comorbid, namely thyroid, autoimmune, cancer, and anemia (RR: 15.836; CI: 1.841-136.234; p=0.012) as factors of mortality in hospitalized elderly patients.


INTRODUCTION
Severe Acute Respiratory Syndrome Corona Virus Disease-2 (SARS-COV-2) is the cause of COVID-19 that was first discovered in Wuhan, Hubei Province, 1 China, in December 2019.This disease soon spread across the countries and was declared a global pandemic.The data from WHO, dated January 25, 2023, showed that there were 664,873,023 confirmed cases of SARS-COV-2 and 6,724,248 2 deaths globally.In Indonesia, on January 27, 2023, 6,729,209 confirmed cases were reported, with 160,801 (2.4%) deaths and 6,563,882 (97.5%) 3 recoveries.
COVID-19 patients can experience different severities, such as asymptomatic, mild, moderate, severe, and critical, which is determined by the clinical manifestations and can worsen and increase disease as the predictor of COVID-19 mortality.The NLR cut-off values that were discovered in prior studies were taken from the COVID-19 adult patient group and not specifically the elderly patient group.
In regards to the prior studies, it can be inferred that the research on NLR as the predictor of COVID-19 mortality, especially in elderly patients in Yogyakarta, is very substantial as DIY has the largest elderly population with the percentage of 14.5% while the nationwide percentage of older adults is only 9.6% according to National Socioeconomic 27 Census in 2019.Furthermore, the COVID-19 mortality rate is comparatively high in elderly patients, especially ones with comorbid degenerative disease.The investigation of NLR on admission is critical to predict the severity of the disease to increase awareness of COVID-19 treatment for elderly patients, and it is also hoped to lower the mortality rate.This study aimed to determine the role of NLR on admission as a mortality predictor in COVID-19 elderly patients who underwent in-hospital treatment.

METHODS
This study was a retrospective observational cohort study of elderly patients with COVID-19 who were hospitalized in Bethesda Hospital, Yogyakarta, from July 2020 to October 2021.The Health Research Ethics Committee of Bethesda Hospital, Yogyakarta, approved the study with No. 14/KEPK-RSB/II/23.
The data collection method used in this study was carried out by recording all confirmed COVID-19 adult patients based on RT-PCR examination from July 2020 to October 2021; then, research subjects who fulfilled the inclusion and exclusion criteria through Electronic Medical Records (EMR) were selected.Inclusion criteria were all elderly COVID-19 patients with an age limit of ≥ 60 years old and who had complete hemogram data on admission (neutrophil count, lymphocyte count, NLR, and platelet count), complete demographic data, diagnostic criteria, types of comorbid diseases, and 28,29 patient outcomes (survivor or non-survivor).
The exclusion criterion was elderly COVID-19 patients with incomplete EMR.
The Kolmogorov-Smirnov test was used to assess the normality distribution of continuous data.The results of this test showed that the data was not normally distributed, so it was presented as the median (min-max), and the Mann-Whitney U test was used for non-normally distributed continuous data.Categorical variables were expressed as numbers (%), and a Chi-Square test was used.
Receiver Operating Characteristic (ROC) curve analysis was used to determine the predictive value of laboratory hemogram parameters on admission for predicting mortality.The sensitivity and specificity with 95% confidence intervals and the optimal cut-off value for each predictor based on the maximum value of Youden's index were measured.Univariate and multivariate logistic regression models were performed to determine predictors of mortality in hospitalized elderly COVID-19 patients.The results from the models were expressed as odds ratio (95% confidence interval) and p-value.All statistical analyses were performed using IBM SPSS Statistics version 22.0 software, and a p-value of less than 0.05 was considered statistically significant.

RESULTS AND DISCUSSIONS
During the study period (from July 2020 to October 2021), there were 122 elderly patients in Bethesda Hospital with confirmed diagnoses of COVID- elderly patients.
In Table 1, no significant difference could be seen between the gender and the age of the elderly patients who recovered or died.The result of this 30,33 research resembles prior research.
However, according to the severity of the disease, the non-survivor had higher severity than those with non-severe symptoms (26.2% vs. 4.1%).The laboratory parameters on admission, neutrophil count, and NLR were proven to increase significantly in the non-survivor group compared to the survivor group.On the other hand, lymphocyte and platelet counts did not show significant differences in either group.This study result supports the prior study, which reported the increase in neutrophil count and NLR on admission in elderly patients from This study showed the median lymphocyte count on admission in the non-survivor group was lower than in the survivor group, although it was not statistically 9 9 significant (1.1 × 10 /L vs. 1.2 × 10 /L).In this study, the platelet count in both groups showed insignificant differences.Prior related studies showed similar results, but others stated that the non-survivor group tends to have a lower [30][31][32][33]17,31 platelet count.
Another study claimed thrombocytopenia occurred among 23.9% of COVID-19 patients.In COVID-19, it is assumed that there is an increased rate of P-selectin expression and activated platelets, elevated circulating platelet-leucocyte aggregates, an increase in platelet aggregation, and thromboxane production, which causes platelet consumption that leads to 34 thrombocytopenia.
A ROC curve for hemogram parameters was used  to determine the cut-off value (Figure 1).Table 2 showed that neutrophil counts with a cut-off >7.55 and NLR with a cut-off > 6.04 could predict elderly COVID-19 mortality.Still, lymphocyte and platelet counts showed insignificance as predictors.This study proved that a high NLR value over the 6.04 limit significantly predicted the mortality of COVID-19 elderly patients who underwent in-hospital treatment.In contrast to the result of univariate analysis where lymphocyte and neutrophil counts were shown to be significant as mortality predictors in elderly patients, a further analysis involving other factors found them insignificant as mortality predictors in elderly patients of COVID-19.This study result is consistent with other studies, which claimed NLR as an independent risk factor in the mortality of COVID-19 adult patients, especially in elderly patients 13,[35][36][37][38][39] who were admitted to in-hospital treatment.
The severity of COVID-19 is mainly affected by the innate inflammatory response of the body; the severe case is caused by cytokine storm, a condition where the immune system shows hyperresponse.The NLR is one of the systemic inflammation indicators in our body.In COVID-19, an unbalanced inflammatory response causes neutrophil count to increase while the lymphocyte count decreases.Aside from the NLR factor, this study also showed the severity of disease as an independent predictor in COVID-19 (Tables 1,3 and 4).Many other studies stated that a high NLR count was associated with 38,39 severity and mortality rate.This study also found that comorbid diseases such as diabetes mellitus and others (thyroid, autoimmune, cancer, and anemia) are mortality predictors in elderly patients of COVID-19 (Tables 3 and 4).This finding supports the prior study, which stated that comorbidity could increase the severity and mortality rate in adult 9 patients of COVID-19.
The findings in this study support the statement that NLR can predict mortality in COVID-19 patients, especially among the elderly with comorbid diseases.The results of this study show that NLR >6.04 is associated with a higher risk of death.Still, further extensive research should involve many healthcare centers in Yogyakarta to achieve a clinically relevant cut-off value, especially among the elderly population.The NLR parameter is a cost-effective marker, a simple test that can easily be calculated from peripheral blood routine tests and provided in many primary healthcare centers.Therefore, medical workers must monitor NLR value on admission to perform early risk stratification among elderly patients.Consequently, patients with a high NLR value can be prioritized to get proper treatment to lower the mortality rate in elderly patients with COVID-19.

CONCLUSIONS AND SUGGESTIONS
The NLR on admission has the potential to be an independent predictor of COVID-19 mortality in 32 non-survivor groups.Many studies claimed that lymphocytopenia is a mortality predictor in elderly patients of COVID-19 17,28,30 who were admitted to hospitals.Only the studies by Chinnaduri et al. and Mostaza et al. used lymphocyte count on admission as parameters, while the study by Wang et al. did not explain whether or not the lymphocyte count used was on admission; the study by Tam et al. showed that the baseline lymphocyte count in non-survivor group compared to survivor group was not statistically significant (p:0.541),but trough lymphocyte count showed 17,30-32 significant difference (p<0.001).

Figure 1 .
Figure 1.ROC curve analysis using laboratory parameters for the assessment of mortality risk in elderly COVID-19 patients Indonesian Journal of Clinical Pathology and Medical Laboratory, 2024 March, 30 (2) : 107 -112 demographic, clinical, and laboratory admission of patient characteristics are shown in Table 1.Among 122 elderly patients undergoing in-hospital treatment, 37 were reported as non-survivors.Several results from different studies on elderly patients of COVID-19 stated different mortality rates, as follows; a survey conducted by Wang et al. reported 65 deaths (19.2%) from the total 339 elderly patients, the research by Tam et al. mentioned 17 deaths (16.8%) from 101 elderly patients; a study by Moztaza et al. disclosed 145 deaths from 404 elderly patients; Chinnadurai et al. reported 86 deaths (40%) from a total of 215 Neutrophil to Lymphocyte Ratio -Fenty, et al.PAGE 193

Table 1 .
The demographic, clinical, and laboratory parameters of COVID-19 patients at hospital admission

Table 2 .
Prognostic test of the laboratory on admission for mortality risk of elderly COVID-19 patients Neutrophil to Lymphocyte Ratio -Fenty, et al.

Table 3 .
Association of demographic and clinical characteristics with mortality outcome through univariate analysis

Table 4 .
Multivariate logistic regression analysis of severity, comorbid, and laboratory results on admission according to mortality