Correlation between the NRS-2002 score and PD-1/CTLA-4 levels in patients with CAP

Correlation between the NRS-2002 score and PD-1/CTLA-4 levels in patients with CAP | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Correlation between the NRS-2002 score and PD-1/CTLA-4 levels in patients with CAP CHENGUANG ZHANG, MINGQIANG ZHANG, XUYAN CHEN, XIANGDONG MU, HE YIN, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8228282/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Objective This study aimed to investigate the association between nutritional status, immunosuppression mediated by PD-1/CTLA-4 which expressed on T cells and prognosis in patients with community-acquired pneumonia (CAP). Methods According to the enrollment strategy, we enrolled 60 participants and collected their medical records. Collecting their blood samples, and exploring the distributions of PD-1 and CTLA-4 in different T-cell subgroups. Results Elevated levels of PD-1 and CTLA-4 on CD4 + T cells (CD4 + ), CD8 + T cells (CD8 + ) and regulatory T cells (Tregs) cells were associated with the occurrance of SCAP, higher mortality, and increased Pneumonia Severity Index (PSI) scores. The malnutrition risk group (nutritional risk scring(NRS)-2002 score ≥ 3) exhibited a higher proportion of SCAP cases, prolonged hospital stays, and higher mortality when compared with the no-risk group. Higher PD-1/CTLA-4 levels were observed in the malnutrition risk group. Conclusion Malnutrition status prolonged hospitalization and increased the risk of severe CAP (SCAP). Higher PD-1 and CTLA-4 levels were associated with a higher PSI score. Nutritional status influences the occurrence of immunosuppression, and malnutrition status may increase the risk of immunosuppression, which is regulated by PD-1 and CTLA-4. Health sciences/Biomarkers Health sciences/Diseases Biological sciences/Immunology Health sciences/Medical research Health sciences/Risk factors NRS-2002 PD-1 CTLA-4 CAP Malnutrition Figures Figure 1 Figure 2 Figure 3 1. Introduction Nutritional status has an important influence on all populations, particularly in individuals with comorbidities, critical illnesses, or advanced age, and it is correlated with the prognosis and mortality of many diseases 1 – 3 . In Asia, the prevalence of malnutrition risk among the elder is as high as 73% 4 . In recognition of the increasing trends of hospitalization and mortality associated with community-acquired pneumonia (CAP) in modern times, especially after the coronavirus disease 2019 (COVID-19) pandemic, in-hospital mortality of CAP has reached 40%, and the costs have increased sharply 5 . Malnutrition compromises immune function by impairing antibody production, exacerbating oxidative stress, and disrupting inflammatory response. Hypoproteinemia leads to low production of antibodies, including functionally active immunoglobulins and those associated with gut-associated lymphoid tissue, and increases the risk of infection. When patients are infected with a virus or bacteria, lymphocytes secrete cytokines and chemokines, triggering inflammation 6 , 7 . The Nutritional Risk Screening-2002 (NRS-2002) is a classic, validated and rapid method for assessing nutritional status, categorizing patients into malnutrition risk (score ≥ 3) and no-risk (score < 3) groups.Studies by Iddir M and Sümer A demonstrated that an NRS-2002 score ≥ 3 increases the risk of severe COVID-19 by 5.6-fold (P = 0.0001, 95% CI = 66.636–1321.163). 8 However, the relationship between CAP and nutritional status hasn’t clarified. T-cell subsets, including CD4 + T cells (CD4 + ), CD8 + T cells (CD8 + ), and regulatory T cells (Tregs), play pivotal roles in immune responses to infections. PD-1 and CTLA-4, inhibitory molecules expressed on activated T cells, are upregulated in pneumonia and sepsis, indicating their role in immunosuppression 9 – 12 . Given that PD-1 and cytotoxic T lymphocyte antigen 4 (CTLA-4) expression is higher in patients with pneumonia or sepsis than in controls, we propose that the duration of immunosuppression, which is regulated by CD4 + , CD8 + , and Tregs on the T-cell surface, plays an important role in the early stage of infection 10 , 12 . Nutrients interact with anti-inflammatory cytokines via interactions with T cells. Malnutrition may induce immune deficiencies and result in a compromised immune response. While nutrients modulate immune function via T-cell interactions, the molecular mechanisms linking malnutrition to immunosuppression haven’t illustrated clearly. This study investigated the association between nutritional status and PD-1/CTLA-4 expression in CAP patients to elucidate whether malnutrition contributes to T-cell-mediated immunosuppression. 2. Materials and methods 2.1 Definitions The American Thoracic Society (ATS)/Infectious Diseases Society of America (IDSA) CAP guidelines defined CAP as pneumonia acquired outside of hospital. Severe CAP (SCAP) was diagnosed according to the CAP severity criteria of IDSA/ATS. The guidelines also strongly recommend that the pneumonia severity index (PSI) could serve as an effective clinical predictor for the prognosis of CAP. 13–16 In accordance with the European Society of Parenteral Enteral Nutrition guidelines, the NRS-2002 is a valuable assessment for screening nutritional status and dividing participants into a malnutrition risk group (score ≥ 3 points) and a no-risk group (score < 3 points). 17 , 18 PD-1 and CTLA-4, which are expressed on the surface of CD4 + , CD8 + and Treg cells, are considered indicators of immunosuppression that regulate T-cell function. 2.2 Study Design 2.2.1 Enrollment strategy At the beginning of the study, all the participants’ main diagnosis was community-acquired pneumonia and the age above 18-year-old. The general demographic data, medical history, laboratory tests and clinical data of the patients were complete. After understanding the study purpose and the research procedure, the participants agreed to participate in the study and could cooperate to the research. Patients who were younger than 18-year-old or who were pregnant should not enrolled in the study. The patients’ clinical records were incomplete, and patients who had a history of immune diseases (such as HIV/AIDS, primary immunodeficiency,et al) or used immunosuppressive drugs in the past 3 months were excluded. Patients with COVID-19 and hospital-acquired pneumonia were also excluded. In addition, patients with a main diagnosis other than community-acquired pneumonia, such as heart failure with pneumonia and postprocedural pneumonia, were not considered for enrollment. Furthermore, patients suffered severe kidney diease (chronic kidney diease(CKD) ≥ 2 grade) and chrnoic heart failure (New York Heart Association(NYHA) classfication ≥ 2 grade) should not take part in the research. 2.2.2 Data collection This study was approved by the Ethics Committee of Beijing Tsinghua Changguang Hospital (BTCH) and was performed by the Emergency Department and Infectious Disease Center of BTCH (Ethics number:18190-0-02, Date:Sep 7,2021). All patients agreed to participate in the research, blood samples were drawn for examination, and the patients signed a consent form. We screened 103 patients and enrolled 64 patients in the study according to the enrollment exclusion criteria from September 2021 to September 2022. The participants were divided into a malnutrition risk group (NRS-2002 score ≥ 3) and a no-risk group (NRS-2002 score < 3) according to their NRS-2002 scores. However, 4 participants withdrew from the study and were transferred to other hospitals or they abandoned the treatment during the process. Finally, 60 participants completed the study. The participants in the malnutrition risk group accounted for 63.33%, whereas the participants in the no-risk group accounted for 36.67% (38 vs. 22). The demographic information, comorbidities, laboratory parameters, PSI scores and NRS-2002 scores were collected through the hospital information system (HIS) of BTCH. (Fig. 1 ) 2.2.3 Laboratory methods After providing informed consent, 4 ml of venous blood was collected from participants within 24 hours(h) and placed in an anticoagulant tube containing ethylenediamine tetraacetic acid dipotassium. The samples were transported and processed at 4°C within 2h of collection. First, mononuclear cells were isolated from the blood, and 3 ml of lymphocyte separation solution was added to the centrifuge tube. Heparin anticoagulated blood with an equivalent volume of PBS was mixed (4 ml) and then centrifuged at 400 g at 20°C for 30 min. After centrifugation, the liquid in the tube was separated into three layers, and the mononuclear cell layer (middle layer) was transferred to another short medium tube, then more than 3 times the volume of PBS was added. The mixture was centrifuged at 1500 rpm for 6 min at 4°C, and the supernatant was discarded. After 10 ml of PBS was added and the sample mixed, the mixture was centrifuged at 1500 rpm for 6 min at 4°C and discarded the supernatant. The cells were cultured in an incubator at 37°C with 5% CO2. To stimulate and block the secretion of cytokines, two-thirds of the upper lymphocyte medium was aspirated, and fresh medium was added. PMA (Sigma) and ionomycin (Sigma) were added at final concentrations of 50 ng/ml and 1 µM respectively. GolgiStop™ (BD) (1 µl/ml) was added and returned to the incubator and incubated for 5 hours after mixed. Direct immunofluorescence staining of the cell surface: The lymphocyte suspension was added to the flow tube and centrifuged at 1500 rpm for 5 min and discared the supernatant. After three milliliters of PBS was added at 4°C, the mixture was centrifuged and washed at 1500 rpm for 5 min, then discared the supernatant. The sample was mixed for lymphocyte precipitation after 100 µl of PBS was added, and the labeled antibodies (anti-CD4, anti-CD8, anti-PD-1, anti-CTLA-4) were added to the cell surface molecules; the sample was incubated at 4°C for 30 min after being mixed. Three milliliters of PBS was added at 4°C, and the mixture was centrifuged and washed at 1500 rpm for 5 min, after which the supernatant was discarded to remove the unbound excess antibody components.Flow cytometry was performed using a FACS Canto II (BD Biosciences), and the results were analyzed using FCS Express 4 (De Novo Software) .(Fig. 2 ) 2.3 Outcomes SCAP occurrence and mortality were compared across the different groups. SCAP was diagnosed according to the standards of the IDSA/ATS CAP severity criteria: 1) Major criteria (requiring Intensive Care Unit (ICU) admission if ≥ 1 is present): invasive mechanical ventilation (IMV) is needed. Septic shock with vasopressors is needed (systolic Blood Pressure(SBP) < 90 mmHg after fluid resuscitation). 2) Minor criteria (≥ 3 minor criteria suggest severe CAP and ICU consideration): respiratory rate ≥ 30 breaths/min, PaO 2 /FiO 2 ratio ≤ 250 (hypoxemia requiring high oxygen support), multilobar infiltrates on chest imaging (≥ 2 lobes involved), confusion/disorientation (altered mental status), blood urea nitrogen (BUN) ≥ 20 mg/dL (or elevated creatinine, indicating renal dysfunction), leukopenia (white blood cell(WBC) < 4,000 cells/mm³) due to infection, thrombocytopenia (platelets < 100,000 cells/mm³), hypothermia (core temperature < 36°C), and hypotension requiring aggressive fluid resuscitation. Mortality was considered to have occurred within 28 days after the enrollment of patients. To determine the correlation between PD-1/CTLA-4 expression and SCAP and death, nutritional risk was assessed according to the NRS-2002 and dividing participants into a malnutrition risk group (score ≥ 3 points) and a no-risk group (score < 3 points). We aim to identify the relationship between the nutritional risk screening results and outcomes of CAP. Furthermore, we also measured BMI and the ALB level to explore the influence on PD-1/CTLA-4 expression. 2.4 Statistical analysis The data were analyzed by SPSS 30.0 and PRISM 10. The data with a normal distribution are expressed as x ± s values, and a t-test was used for comparisons of the means among different groups. Nonnormally distributed data are presented as M(P 25 ,P 75 ), the rank sum test was used for component comparisons, and cross-tabulation was used for multigroup data analysis. Count data are expressed as a percentage of the number of cases. The correlation between the data and patient survival was analyzed by survival analysis. A correlation analysis was used to determine the correlation among studies; a positive number of correlation coefficients was considered a positive correlation, and a negative number was considered a negative correlation. The difference was statistically significant at P < 0.05. 3. Results 3.1 Correlations between PD-1/CTLA-4 status and the severity of pneumonia With concern to CD4 + PD-1, CD4 + CTLA-4, CD8 + PD-1, CD8 + CTLA-4, Tregs PD-1 and Tregs CTLA-4, the results of the logistic regression models concerning the associations with SCAP occurrence (P 1 = 0.46, P 2 = 0.30, P 3 = 0.25, P 4 = 0.10, P 5 = 0.89, P 6 = 0.57 ) and mortality(P 1 = 0.44, P 2 = 0.75, P 3 = 0.36, P 4 = 0.31, P 5 = 0.10, P 6 = 0.60 ) showed no significance. (Table 1 ) Table 1 Correlations between PD-1/CTLA-4 and SCAP and death SCAP Death Wals P OR 95% CI Wals P OR 95% CI NRS-2002 score 3.98 0.04 4.18 1.02–17.04 2.54 1.11 0.12 0.01–1.63 BMI(kg/m 2 ) 1 0.72 0.40 1.91 0.79–1.78 0.07 0.80 1.07 0.65–1.77 ALB(g/L) 1.21 0.27 0.78 0.50–1.21 3.09 0.08 0.57 0.31–1.07 CD4 + PD1 0.54 0.46 1.15 0.80–1.65 0.60 0.44 1.19 0.79–1.83 CD4 + CTLA4 1.07 0.30 1.37 0.75–2.49 0.11 0.75 1.09 0.66–1.78 CD8 + PD1 1.32 0.25 1.15 0.91–1.45 0.83 0.36 0.89 0.70–1.13 CD8 + CTLA4 2.72 0.10 0.74 0.52–1.06 1.02 0.31 1.20 0.84–1.70 Treg-PD1 0.02 0.89 1.02 0.75–1.39 2.66 0.10 1.28 0.95–1.71 Treg-CTLA4 0.32 0.57 0.89 0.59–1.34 0.27 0.60 0.91 0.64–1.63 1. BMI = body mass index PD-1 and CTLA-4 of CD4 + , CD8 + and Tregs showed no difference in different gender group (CD4 + :t 1 =-0.376, t 2 =-0.37; P 1 = 0.71, P 2 = 0.71; CD8 + :t 1 = 1.37, t 2 = 0.48; P 1 = 0.17, P 2 = 0.63; Tregs: t 1 =-0.95, t 2 =-1.31; P 1 = 0.35, P 2 = 0.19). Except for PD-1 and CTLA-4 on CD4 T cells (P 1 = 0.01, P 2 < 0.01), the correlations of CD4 + PD-1, CD4 + CTLA-4, CD8 + PD-1, CD8 + CTLA-4, Tregs PD-1 and Tregs CTLA-4 with the PSI score were not statistically significant. (Table 2 ) Table 2 Correlations of PD-1/CTLA-4 with the PSI, ALB concentration, BMI and NRS-2002 score PSI score ALB BMI NRS-2002 score Corralation coefficient P Corralation coefficient P Corralation coefficient P Corralation coefficient P CD4 + PD1 0.32 0.01 -0.67 < 0.01 0.05 0.72 0.86 < 0.01 CD4 + CTLA4 0.38 < 0.01 -0.67 < 0.01 -0.01 0.98 0.80 < 0.01 CD8 + PD1 0.11 0.42 -0.34 0.01 0.18 0.17 0.36 < 0.01 CD8 + CTLA4 0.19 0.14 -0.28 0.03 0.18 0.17 0.29 0.02 Treg-PD1 0.19 0.14 -0.36 0.01 0.02 0.89 0.47 < 0.01 Treg-CTLA4 0.21 0.12 -0.37 < 0.01 -0.05 0.72 0.48 < 0.01 3.2 Influence of nutritional status on pneumonia According to the inclusion criteria, 60 participants were enrolled and divided into a malnutrition risk group and no-risk group (38 vs. 22). The NRS-2002 score in the malnutrition risk group was 4.02 ± 1.21, whereas that in the no-risk group was 1.54 ± 0.50. No differences between the two groups were confirmed for sex, age or comorbidities at baseline. Hospital mortality in the malnutrition risk group was greater than that in the no-risk group (23.68% vs. 4.54%). For the outcomes of hospital-free days and the occurrence of SAP, the no-risk group was prioritized over the malnutrition risk group. (Table 3 ) Table 3 Comparison of the different nutritional groups No-risk group Malnutrition risk group Value P Number 22 38 - - Age(years) 63.40 ± 19.19 69.57 ± 19.18 1.20 0.23 Male 10(45.5) 20(52.6) 0.29 0.59 Heart disease 6(27.3) 11(28.9) 0.02 0.89 Diabetes 7(31.8) 15(39.5) 0.35 0.55 CKD 1 2(0.9) 8(21.1) 1.43 0.23 Mental disorder 4(18.1) 10(26.3) 0.51 0.47 NRS-2002 score 1.54 ± 0.50 4.02 ± 1.21 9.07 < 0.01 CRP(mg/L) 2 47.60(13.92,104.50) 33.00(11.00,88.00) 367.50 0.44 PCT(ng/L) 3 2.80(1.22,4.32) 8.80(3.20,18.92) 662 < 0.01 PSI score 3.50(2.00,4.00) 3.00(2.22,4.00) 408.50 0.88 Length of hospitalization(days) 11(8.00,16.50) 15.00(13.50,20.50) 450 < 0.01 SCAP 1(0.5) 13(34.2) 10.6 < 0.01 Death 1(0.5) 9(23.7) 3.67 0.06 1. CKD = chronic kidney disease; 2. CRP = C-reactive protein; 3. PCT = Procalcitonin After taking NRS-2002 score, BMI and serum ALB concentration into the logistic regression models for SCAP and death, NRS-2002 score were associated with the occurrence of SCAP. None of these factors was related to the risk of death. (Table 1 ) 3.3 Distribution of PD-1/CTLA-4 in patients with different nutritional statuses After CD4 + PD-1, CD4 + CTLA-4, CD8 + PD-1, CD8 + CTLA-4, Tregs PD-1 and Tregs CTLA-4 were analyzed in the two groups, the malnutrition risk group presented higher levels when compared with the no-risk group. PD-1/CTLA-4 expression in the CD4 + , CD8 + and Treg subgroups was positively correlated with the NRS-2002 score. The higher NRS-2002 score, the higher PD-1/CTLA-4 levels. Similar results were obtained for the relationship between PD-1/CTLA-4 levels with ALB concentration and BMI, which are essential for the evaluation of nutritional status. (Fig. 3 ) CD4 + PD-1, CD4 + CTLA-4, CD8 + PD-1, CD8 + CTLA-4, Tregs PD-1 and Tregs CTLA-4 were subjected to a correlation analysis with the NRS-2002 score, BMI and ALB level, and the P values were statistically significant. (Table 2 ) 4. Discussion Considering the interaction between nutritional status with prognosis and mortality of cardiovascular disease, cancer, et al, an increasing number of studies concerned the importance of nutritional status screening 1 – 3 , 19 , 20 . Yanagita Y 21 used the Geriatric Nutritional Risk Index (GNRI) as a tool to distinguish the relationship between nutritional status and aspiration pneumonia risk then concluded that the GNRI scores were greater in the survivor group than in the nonsurvivor group (78.1 vs. 68.6, P < 0.01), the same result also put forward in the fields of the total protein (6.7 g/dL vs. 6.2 g/dL, P < 0.01) and serum albumin (3.1 g/dL vs. 2.5 g/dL, P < 0.01) levels among different groups. He also reported that the GNRI was an independent early predictor of mortality (OR = 0.383; 95% CI, 0.178–0.824; P < 0.05). We obtained similar results when we used the NRS-2002 score as a tool to assess nutritional status in our study. The number of hospital-free days (t = 450, P < 0.01), mortality and occurrence of SCAP (X 2 = 10.6, P < 0.01) were lower in the no-risk group than in the malnutrition risk group. Furthermore, we also found that the nutritional status, as indicated by the NRS-2002 score, was a risk factor for SCAP development. Even though Both Iddir M and Yanagita Y emphasized the influence of ALB level on the prognosis of pneumonia patients, there were no distinctions between the two groups when focused on the serum ALB concentration and BMI in our research. Many studies have shown that ALB concentration was related to infectious disease risk. In combination with our previous study 22 , it indicated that nutritional risk screening score and the level of ALB were correlated with the prognosis of elder with severe pneumonia. The study also revealed that shock, invasive mechanical ventilation (IMV) or renal replacement therapy and the costs associated with the malnutrition risk group increased more severely than those of the no-risk group. Therefore, we conclude that the NRS-2002 score influences the prognosis of CAP patients. Most studies focus on the effect of nutritional status on the prognosis of infection (such as pneumonia), but limited studies have addressed the effect of infection on nutrition satues.We only discussed the impact of nutritional status on the prognosis of patients with pneumonia. Even whether severe CAP could itself worsen nutritional status haven’t clarified in our research, many studies have suggested that the increased consumption of carbohydrate, fat, and protein caused by severe infections may lead to malnutrition 22 – 24 . T cells, including CD4 + T cells, CD8 + T cells and Tregs, are foundational to the immune system. PD-1 is often expressed on activated T lymphocytes and regulates T-cell activation. It can lead to immune tolerance by binding to antigen-presenting cell (APC) ligands, which results in T lymphocyte dysfunction, apoptosis and cytokine damage. CTLA-4 is an immunosuppressive factor that is expressed on the surface of activated T lymphocytes where it generates signals that prevent T lymphocyte activation through competitively inhibiting ligand binding to CD28 and APCs. CD4 + and CD8 + T cells and Tregs, which affected by PD-1 and CTLA-4, are decreased in sepsis, whereas PD-1 and CTLA-4 are upregulated. 9 – 11 Gong investigated the expression of PD-1 and CTLA-4 in CAP patients and reported that the percentages of Tregs with PD-1 and CTLA-4 expression were significantly greater than those in healthy controls. However, for both the CD4 + and CD8 + T-cell cell groups, no differences were observed between healthy individuals and CAP patients 12 . Unlike in Gong’s study, PD-1 and CTLA-4 expressed on CD4 + and CD8 + T cells and on Tregs were related to the occurrence of SCAP and mortality in our study. However, when we performed a correlation analysis between PD-1/CTLA-4 and the PSI score, we found that the results were positive, as higher PD-1 and CTLA-4 percentages indicated higher PSI scores. PSI is an important tool to evaluate and predict the severity and prognosis of CAP. Therefore, we concluded that the percentage of cells with PD-1/CTLA-4 was associated with the severity of CAP. Malnutrition interferes with the suppression of immune reactions, but few studies have demonstrated this process at the molecular level. We investigated this process in patients with CAP and reported that PD-1 and CTLA-4 expression was greater in the malnutrition risk group than in the no-risk group. Furthermore, we also demonstrated that the percentages of PD-1 and CTLA-4 cells were positively correlated to the NRS-2002 score. The ALB concentration and BMI are important indicators for the evaluation of nutritional status and are used to evaluate malnutrition 1 . In our research, the level of ALB was also related to PD-1 and CTLA-4 levels, whereas BMI was not correlated with these parameters. Patients who had higher NRS-2002 scores or lower ALB levels presented higher PD-1 and CTLA-4 levels. Therefore, we proposed that CAP patients who present with malnutrition or hypoalbuminemia may also have a high risk of immunosuppression. However, this was a single-center study and the number of enrollment was not very large, which may lead to confounding and sampling bias. Tang W 25 reported that the NRS-2002 score can predict the efficacy and prognosis of immunotherapy in patients with solid tumors treated with immune checkpoint inhibitor therapy. It is difficult to evaluate the immunosuppression status in an effective and precise methods during clinical practice. According to our research, the NRS-2002 score could also be an indicator of immunosuppression in patients with CAP and may be a prognostic factor in the treatment of CAP or other diseases.It can help us acknowledge the immune status in time and may provide new ideas for the immunosuppression therapies for severe pneumonia in future. 5. Conclusion Malnutrition, as assessed by NRS-2002, is associated with prolonged hospitalization, higher SCAP incidence, and elevated PD-1/CTLA-4 levels. Higher PD-1 and CTLA-4 levels which regulate the immunosupression process were associated with a higher PSI score. Nutritional status influences the occurrence of immunosuppression, which is associated with the prognosis of CAP. Malnutrition statues may increase the risk of immunosuppression, which is regulated by PD-1 and CTLA-4. Declarations Authors’ contributions Chenguang Zhang was responsible for data collection, literature review and writing the manuscript. Mingqiang Zhang and Xiangdong Mu conducted the experiments and tested the levels of PD-1 and CTLA-4 in different T-cell subgroups. Sheng Wu and Xuyan Chen was responsible for writing and reviewing the manuscript. Hao Yang were engaged in data collection and figure drawing. Jingjing Li contributed to the collection, preservation and transportation of blood samples. Funding This research was supported by the Special Program of Major Epidemic Prevention and Control in Beijing (XKB2022B101). Ethics approval and consent to participate In accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) and the Declaration of Helsinki (2013), the Ethics Committee of the Beijing Tsinghua Changgung Hospital approved this research(18190-0-02, Sep 7,2021), and all patients provided informed consent and agreed to participate in the study. Competing interests The authors declare that they have no competing interests. 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Nutrients 2021, 13, 3716. Yanagita Y, Arizono S, Tawara Y, Oomagari M, Machiguchi H, Yokomura K, Katagiri N, Iida Y. The severity of nutrition and pneumonia predicts survival in patients with aspiration pneumonia: A retrospective observational study. Clin Respir J. 2022 Jul;16(7):522-532. doi: 10.1111/crj.13521. Epub 2022 Jul 5. PMID: 35789107; PMCID: PMC9329015. Zhang CG, Chen XY, Zhang XY,et al. Correlation between nutritional risk screening and the prognosis of elderly severe pneumonia. Chin J Crit Care Med, 2023, 43 (03): 175-179. Collins K, Huen SC. Metabolism and Nutrition in Sepsis: In Need of a Paradigm Shift. Nephron. 2023;147(12):733-736. doi: 10.1159/000534074. Epub 2023 Sep 13. PMID: 37703850; PMCID: PMC11098033. De Waele E, Malbrain MLNG, Spapen H. Nutrition in Sepsis: A Bench-to-Bedside Review. Nutrients. 2020 Feb 2;12(2):395. doi: 10.3390/nu12020395. PMID: 32024268; PMCID: PMC7071318. Tang W, Li C, Huang D, Zhou S, Zheng H, Wang Q, Zhang X, Fu J. NRS2002 score as a prognostic factor in solid tumors treated with immune checkpoint inhibitor therapy: a real-world evidence analysis. Cancer Biol Ther. 2024 Dec 31;25(1):2358551. doi: 10.1080/15384047.2024.2358551. Epub 2024 May 30. PMID: 38813753; PMCID: PMC11141475. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 24 Feb, 2026 Reviews received at journal 20 Feb, 2026 Reviews received at journal 17 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviewers invited by journal 08 Dec, 2025 Editor invited by journal 05 Dec, 2025 Editor assigned by journal 03 Dec, 2025 Submission checks completed at journal 03 Dec, 2025 First submitted to journal 28 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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1","display":"","copyAsset":false,"role":"figure","size":153639,"visible":true,"origin":"","legend":"\u003cp\u003eResearch enrollment strategy\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8228282/v1/469da0eb0c1f608840f90c17.png"},{"id":97990244,"identity":"6119e72b-4ced-4678-a8ff-bd9c97d23b6c","added_by":"auto","created_at":"2025-12-11 14:25:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":101019,"visible":true,"origin":"","legend":"\u003cp\u003eLaboratory methods\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8228282/v1/d56d456c13649a771d942e7c.png"},{"id":98424575,"identity":"bb205954-f469-45c0-8015-83ac7a9a0532","added_by":"auto","created_at":"2025-12-17 16:33:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":122033,"visible":true,"origin":"","legend":"\u003cp\u003ePD-1/CTLA-4 levels in patients with different nutritional statuses\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8228282/v1/0af15e2bc67629fb4bd0c946.png"},{"id":98443956,"identity":"cf2a4162-60ff-4bf0-8043-db7d1eae0c6a","added_by":"auto","created_at":"2025-12-17 17:14:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1098638,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8228282/v1/809b04a3-649c-4b2f-9f81-4b8af8fc73ab.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Correlation between the NRS-2002 score and PD-1/CTLA-4 levels in patients with CAP","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNutritional status has an important influence on all populations, particularly in individuals with comorbidities, critical illnesses, or advanced age, and it is correlated with the prognosis and mortality of many diseases\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In Asia, the prevalence of malnutrition risk among the elder is as high as 73%\u003csup\u003e4\u003c/sup\u003e. In recognition of the increasing trends of hospitalization and mortality associated with community-acquired pneumonia (CAP) in modern times, especially after the coronavirus disease 2019 (COVID-19) pandemic, in-hospital mortality of CAP has reached 40%, and the costs have increased sharply\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eMalnutrition compromises immune function by impairing antibody production, exacerbating oxidative stress, and disrupting inflammatory response. Hypoproteinemia leads to low production of antibodies, including functionally active immunoglobulins and those associated with gut-associated lymphoid tissue, and increases the risk of infection. When patients are infected with a virus or bacteria, lymphocytes secrete cytokines and chemokines, triggering inflammation\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. The Nutritional Risk Screening-2002 (NRS-2002) is a classic, validated and rapid method for assessing nutritional status, categorizing patients into malnutrition risk (score\u0026thinsp;\u0026ge;\u0026thinsp;3) and no-risk (score\u0026thinsp;\u0026lt;\u0026thinsp;3) groups.Studies by Iddir M and S\u0026uuml;mer A demonstrated that an NRS-2002 score\u0026thinsp;\u0026ge;\u0026thinsp;3 increases the risk of severe COVID-19 by 5.6-fold (P\u0026thinsp;=\u0026thinsp;0.0001, 95% CI\u0026thinsp;=\u0026thinsp;66.636\u0026ndash;1321.163).\u003csup\u003e8\u003c/sup\u003e However, the relationship between CAP and nutritional status hasn\u0026rsquo;t clarified.\u003c/p\u003e\u003cp\u003eT-cell subsets, including CD4\u003csup\u003e+\u003c/sup\u003e T cells (CD4\u003csup\u003e+\u003c/sup\u003e), CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8\u003csup\u003e+\u003c/sup\u003e), and regulatory T cells (Tregs), play pivotal roles in immune responses to infections. PD-1 and CTLA-4, inhibitory molecules expressed on activated T cells, are upregulated in pneumonia and sepsis, indicating their role in immunosuppression\u003csup\u003e\u003cspan additionalcitationids=\"CR10 CR11\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Given that PD-1 and cytotoxic T lymphocyte antigen 4 (CTLA-4) expression is higher in patients with pneumonia or sepsis than in controls, we propose that the duration of immunosuppression, which is regulated by CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e, and Tregs on the T-cell surface, plays an important role in the early stage of infection\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNutrients interact with anti-inflammatory cytokines via interactions with T cells. Malnutrition may induce immune deficiencies and result in a compromised immune response. While nutrients modulate immune function via T-cell interactions, the molecular mechanisms linking malnutrition to immunosuppression haven\u0026rsquo;t illustrated clearly. This study investigated the association between nutritional status and PD-1/CTLA-4 expression in CAP patients to elucidate whether malnutrition contributes to T-cell-mediated immunosuppression.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Definitions\u003c/h2\u003e\u003cp\u003e The American Thoracic Society (ATS)/Infectious Diseases Society of America (IDSA) CAP guidelines defined CAP as pneumonia acquired outside of hospital. Severe CAP (SCAP) was diagnosed according to the CAP severity criteria of IDSA/ATS. The guidelines also strongly recommend that the pneumonia severity index (PSI) could serve as an effective clinical predictor for the prognosis of CAP. \u003csup\u003e13\u0026ndash;16\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn accordance with the European Society of Parenteral Enteral Nutrition guidelines, the NRS-2002 is a valuable assessment for screening nutritional status and dividing participants into a malnutrition risk group (score\u0026thinsp;\u0026ge;\u0026thinsp;3 points) and a no-risk group (score\u0026thinsp;\u0026lt;\u0026thinsp;3 points).\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003ePD-1 and CTLA-4, which are expressed on the surface of CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e and Treg cells, are considered indicators of immunosuppression that regulate T-cell function.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study Design\u003c/h2\u003e\u003cdiv id=\"Sec5\" class=\"Section3\"\u003e\u003ch2\u003e2.2.1 Enrollment strategy\u003c/h2\u003e\u003cp\u003eAt the beginning of the study, all the participants\u0026rsquo; main diagnosis was community-acquired pneumonia and the age above 18-year-old. The general demographic data, medical history, laboratory tests and clinical data of the patients were complete. After understanding the study purpose and the research procedure, the participants agreed to participate in the study and could cooperate to the research.\u003c/p\u003e\u003cp\u003ePatients who were younger than 18-year-old or who were pregnant should not enrolled in the study. The patients\u0026rsquo; clinical records were incomplete, and patients who had a history of immune diseases (such as HIV/AIDS, primary immunodeficiency,et al) or used immunosuppressive drugs in the past 3 months were excluded. Patients with COVID-19 and hospital-acquired pneumonia were also excluded. In addition, patients with a main diagnosis other than community-acquired pneumonia, such as heart failure with pneumonia and postprocedural pneumonia, were not considered for enrollment. Furthermore, patients suffered severe kidney diease (chronic kidney diease(CKD)\u0026thinsp;\u0026ge;\u0026thinsp;2 grade) and chrnoic heart failure (New York Heart Association(NYHA) classfication\u0026thinsp;\u0026ge;\u0026thinsp;2 grade) should not take part in the research.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section3\"\u003e\u003ch2\u003e2.2.2 Data collection\u003c/h2\u003e\u003cp\u003e This study was approved by the Ethics Committee of Beijing Tsinghua Changguang Hospital (BTCH) and was performed by the Emergency Department and Infectious Disease Center of BTCH (Ethics number:18190-0-02, Date:Sep 7,2021). All patients agreed to participate in the research, blood samples were drawn for examination, and the patients signed a consent form.\u003c/p\u003e\u003cp\u003e We screened 103 patients and enrolled 64 patients in the study according to the enrollment exclusion criteria from September 2021 to September 2022. The participants were divided into a malnutrition risk group (NRS-2002 score\u0026thinsp;\u0026ge;\u0026thinsp;3) and a no-risk group (NRS-2002 score\u0026thinsp;\u0026lt;\u0026thinsp;3) according to their NRS-2002 scores. However, 4 participants withdrew from the study and were transferred to other hospitals or they abandoned the treatment during the process. Finally, 60 participants completed the study. The participants in the malnutrition risk group accounted for 63.33%, whereas the participants in the no-risk group accounted for 36.67% (38 vs. 22). The demographic information, comorbidities, laboratory parameters, PSI scores and NRS-2002 scores were collected through the hospital information system (HIS) of BTCH. (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section3\"\u003e\u003ch2\u003e2.2.3 Laboratory methods\u003c/h2\u003e\u003cp\u003e After providing informed consent, 4 ml of venous blood was collected from participants within 24 hours(h) and placed in an anticoagulant tube containing ethylenediamine tetraacetic acid dipotassium. The samples were transported and processed at 4\u0026deg;C within 2h of collection.\u003c/p\u003e\u003cp\u003eFirst, mononuclear cells were isolated from the blood, and 3 ml of lymphocyte separation solution was added to the centrifuge tube. Heparin anticoagulated blood with an equivalent volume of PBS was mixed (4 ml) and then centrifuged at 400 g at 20\u0026deg;C for 30 min. After centrifugation, the liquid in the tube was separated into three layers, and the mononuclear cell layer (middle layer) was transferred to another short medium tube, then more than 3 times the volume of PBS was added. The mixture was centrifuged at 1500 rpm for 6 min at 4\u0026deg;C, and the supernatant was discarded. After 10 ml of PBS was added and the sample mixed, the mixture was centrifuged at 1500 rpm for 6 min at 4\u0026deg;C and discarded the supernatant. The cells were cultured in an incubator at 37\u0026deg;C with 5% CO2.\u003c/p\u003e\u003cp\u003eTo stimulate and block the secretion of cytokines, two-thirds of the upper lymphocyte medium was aspirated, and fresh medium was added. PMA (Sigma) and ionomycin (Sigma) were added at final concentrations of 50 ng/ml and 1 \u0026micro;M respectively. GolgiStop\u0026trade; (BD) (1 \u0026micro;l/ml) was added and returned to the incubator and incubated for 5 hours after mixed.\u003c/p\u003e\u003cp\u003eDirect immunofluorescence staining of the cell surface: The lymphocyte suspension was added to the flow tube and centrifuged at 1500 rpm for 5 min and discared the supernatant. After three milliliters of PBS was added at 4\u0026deg;C, the mixture was centrifuged and washed at 1500 rpm for 5 min, then discared the supernatant. The sample was mixed for lymphocyte precipitation after 100 \u0026micro;l of PBS was added, and the labeled antibodies (anti-CD4, anti-CD8, anti-PD-1, anti-CTLA-4) were added to the cell surface molecules; the sample was incubated at 4\u0026deg;C for 30 min after being mixed. Three milliliters of PBS was added at 4\u0026deg;C, and the mixture was centrifuged and washed at 1500 rpm for 5 min, after which the supernatant was discarded to remove the unbound excess antibody components.Flow cytometry was performed using a FACS Canto II (BD Biosciences), and the results were analyzed using FCS Express 4 (De Novo Software) .(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Outcomes\u003c/h2\u003e\u003cp\u003eSCAP occurrence and mortality were compared across the different groups. SCAP was diagnosed according to the standards of the IDSA/ATS CAP severity criteria: 1) Major criteria (requiring Intensive Care Unit (ICU) admission if\u0026thinsp;\u0026ge;\u0026thinsp;1 is present): invasive mechanical ventilation (IMV) is needed. Septic shock with vasopressors is needed (systolic Blood Pressure(SBP)\u0026thinsp;\u0026lt;\u0026thinsp;90 mmHg after fluid resuscitation). 2) Minor criteria (\u0026ge;\u0026thinsp;3 minor criteria suggest severe CAP and ICU consideration): respiratory rate\u0026thinsp;\u0026ge;\u0026thinsp;30 breaths/min, PaO\u003csub\u003e2\u003c/sub\u003e/FiO\u003csub\u003e2\u003c/sub\u003e ratio\u0026thinsp;\u0026le;\u0026thinsp;250 (hypoxemia requiring high oxygen support), multilobar infiltrates on chest imaging (\u0026ge;\u0026thinsp;2 lobes involved), confusion/disorientation (altered mental status), blood urea nitrogen (BUN)\u0026thinsp;\u0026ge;\u0026thinsp;20 mg/dL (or elevated creatinine, indicating renal dysfunction), leukopenia (white blood cell(WBC)\u0026thinsp;\u0026lt;\u0026thinsp;4,000 cells/mm\u0026sup3;) due to infection, thrombocytopenia (platelets\u0026thinsp;\u0026lt;\u0026thinsp;100,000 cells/mm\u0026sup3;), hypothermia (core temperature\u0026thinsp;\u0026lt;\u0026thinsp;36\u0026deg;C), and hypotension requiring aggressive fluid resuscitation.\u003c/p\u003e\u003cp\u003eMortality was considered to have occurred within 28 days after the enrollment of patients. To determine the correlation between PD-1/CTLA-4 expression and SCAP and death, nutritional risk was assessed according to the NRS-2002 and dividing participants into a malnutrition risk group (score\u0026thinsp;\u0026ge;\u0026thinsp;3 points) and a no-risk group (score\u0026thinsp;\u0026lt;\u0026thinsp;3 points). We aim to identify the relationship between the nutritional risk screening results and outcomes of CAP. Furthermore, we also measured BMI and the ALB level to explore the influence on PD-1/CTLA-4 expression.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e\u003cp\u003eThe data were analyzed by SPSS 30.0 and PRISM 10. The data with a normal distribution are expressed as x\u0026thinsp;\u0026plusmn;\u0026thinsp;s values, and a t-test was used for comparisons of the means among different groups. Nonnormally distributed data are presented as M(P\u003csub\u003e25\u003c/sub\u003e,P\u003csub\u003e75\u003c/sub\u003e), the rank sum test was used for component comparisons, and cross-tabulation was used for multigroup data analysis. Count data are expressed as a percentage of the number of cases. The correlation between the data and patient survival was analyzed by survival analysis. A correlation analysis was used to determine the correlation among studies; a positive number of correlation coefficients was considered a positive correlation, and a negative number was considered a negative correlation. The difference was statistically significant at P\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003e3.1 Correlations between PD-1/CTLA-4 status and the severity of pneumonia\u003c/h2\u003e\u003cp\u003eWith concern to CD4\u003csup\u003e+\u003c/sup\u003e PD-1, CD4\u003csup\u003e+\u003c/sup\u003e CTLA-4, CD8\u003csup\u003e+\u003c/sup\u003e PD-1, CD8\u003csup\u003e+\u003c/sup\u003e CTLA-4, Tregs PD-1 and Tregs CTLA-4, the results of the logistic regression models concerning the associations with SCAP occurrence (P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.46, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.30, P\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.25, P\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.10, P\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.89, P\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.57 ) and mortality(P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.44, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.75, P\u003csub\u003e3\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.36, P\u003csub\u003e4\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.31, P\u003csub\u003e5\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.10, P\u003csub\u003e6\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.60 ) showed no significance. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations between PD-1/CTLA-4 and SCAP and death\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u003cp\u003eSCAP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e\u003cp\u003eDeath\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWals\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eWals\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNRS-2002 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e4.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.02\u0026ndash;17.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.01\u0026ndash;1.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI(kg/m\u003csup\u003e2\u003c/sup\u003e)\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.79\u0026ndash;1.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.65\u0026ndash;1.77\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.50\u0026ndash;1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e3.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.31\u0026ndash;1.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003ePD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.80\u0026ndash;1.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.79\u0026ndash;1.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003eCTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u0026ndash;2.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.66\u0026ndash;1.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003ePD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.91\u0026ndash;1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.70\u0026ndash;1.13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003eCTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.52\u0026ndash;1.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.84\u0026ndash;1.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreg-PD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e1.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.75\u0026ndash;1.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e2.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e1.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.95\u0026ndash;1.71\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreg-CTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.59\u0026ndash;1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.64\u0026ndash;1.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e1. BMI\u0026thinsp;=\u0026thinsp;body mass index\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003ePD-1 and CTLA-4 of CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e and Tregs showed no difference in different gender group (CD4\u003csup\u003e+\u003c/sup\u003e:t\u003csub\u003e1\u003c/sub\u003e=-0.376, t\u003csub\u003e2\u003c/sub\u003e=-0.37; P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.71, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.71; CD8\u003csup\u003e+\u003c/sup\u003e:t\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;1.37, t\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.48; P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.17, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.63; Tregs: t\u003csub\u003e1\u003c/sub\u003e=-0.95, t\u003csub\u003e2\u003c/sub\u003e=-1.31; P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.35, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.19). Except for PD-1 and CTLA-4 on CD4 T cells (P\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.01, P\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01), the correlations of CD4\u003csup\u003e+\u003c/sup\u003e PD-1, CD4\u003csup\u003e+\u003c/sup\u003e CTLA-4, CD8\u003csup\u003e+\u003c/sup\u003e PD-1, CD8\u003csup\u003e+\u003c/sup\u003e CTLA-4, Tregs PD-1 and Tregs CTLA-4 with the PSI score were not statistically significant. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eCorrelations of PD-1/CTLA-4 with the PSI, ALB concentration, BMI and NRS-2002 score\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003ePSI score\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eALB\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e\u003cp\u003eBMI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003eNRS-2002 score\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCorralation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCorralation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eCorralation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eCorralation coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003e PD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003eCTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003e PD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCD8\u003csup\u003e+\u003c/sup\u003eCTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreg-PD1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreg-CTLA4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e-0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003e3.2 Influence of nutritional status on pneumonia\u003c/h2\u003e\u003cp\u003eAccording to the inclusion criteria, 60 participants were enrolled and divided into a malnutrition risk group and no-risk group (38 vs. 22). The NRS-2002 score in the malnutrition risk group was 4.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21, whereas that in the no-risk group was 1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50. No differences between the two groups were confirmed for sex, age or comorbidities at baseline. Hospital mortality in the malnutrition risk group was greater than that in the no-risk group (23.68% vs. 4.54%). For the outcomes of hospital-free days and the occurrence of SAP, the no-risk group was prioritized over the malnutrition risk group. (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eComparison of the different nutritional groups\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo-risk group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMalnutrition risk group\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eValue\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNumber\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63.40\u0026thinsp;\u0026plusmn;\u0026thinsp;19.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e69.57\u0026thinsp;\u0026plusmn;\u0026thinsp;19.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10(45.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20(52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.59\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHeart disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6(27.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11(28.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7(31.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15(39.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.55\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCKD\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2(0.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8(21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMental disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4(18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10(26.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.47\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNRS-2002 score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.54\u0026thinsp;\u0026plusmn;\u0026thinsp;0.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.02\u0026thinsp;\u0026plusmn;\u0026thinsp;1.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCRP(mg/L)\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.60(13.92,104.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33.00(11.00,88.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e367.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCT(ng/L)\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.80(1.22,4.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.80(3.20,18.92)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e662\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePSI score\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.50(2.00,4.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.00(2.22,4.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e408.50\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLength of hospitalization(days)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11(8.00,16.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15.00(13.50,20.50)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e450\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSCAP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(34.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDeath\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1(0.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9(23.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e1. CKD\u0026thinsp;=\u0026thinsp;chronic kidney disease; 2. CRP\u0026thinsp;=\u0026thinsp;C-reactive protein; 3. PCT\u0026thinsp;=\u0026thinsp;Procalcitonin\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAfter taking NRS-2002 score, BMI and serum ALB concentration into the logistic regression models for SCAP and death, NRS-2002 score were associated with the occurrence of SCAP. None of these factors was related to the risk of death. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003e3.3 Distribution of PD-1/CTLA-4 in patients with different nutritional statuses\u003c/h2\u003e\u003cp\u003eAfter CD4\u003csup\u003e+\u003c/sup\u003e PD-1, CD4\u003csup\u003e+\u003c/sup\u003e CTLA-4, CD8\u003csup\u003e+\u003c/sup\u003e PD-1, CD8\u003csup\u003e+\u003c/sup\u003e CTLA-4, Tregs PD-1 and Tregs CTLA-4 were analyzed in the two groups, the malnutrition risk group presented higher levels when compared with the no-risk group. PD-1/CTLA-4 expression in the CD4\u003csup\u003e+\u003c/sup\u003e, CD8\u003csup\u003e+\u003c/sup\u003e and Treg subgroups was positively correlated with the NRS-2002 score. The higher NRS-2002 score, the higher PD-1/CTLA-4 levels. Similar results were obtained for the relationship between PD-1/CTLA-4 levels with ALB concentration and BMI, which are essential for the evaluation of nutritional status. (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e)\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eCD4\u003csup\u003e+\u003c/sup\u003e PD-1, CD4\u003csup\u003e+\u003c/sup\u003e CTLA-4, CD8\u003csup\u003e+\u003c/sup\u003e PD-1, CD8\u003csup\u003e+\u003c/sup\u003e CTLA-4, Tregs PD-1 and Tregs CTLA-4 were subjected to a correlation analysis with the NRS-2002 score, BMI and ALB level, and the P values were statistically significant. (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eConsidering the interaction between nutritional status with prognosis and mortality of cardiovascular disease, cancer, et al, an increasing number of studies concerned the importance of nutritional status screening \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Yanagita Y\u003csup\u003e21\u003c/sup\u003e used the Geriatric Nutritional Risk Index (GNRI) as a tool to distinguish the relationship between nutritional status and aspiration pneumonia risk then concluded that the GNRI scores were greater in the survivor group than in the nonsurvivor group (78.1 vs. 68.6, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), the same result also put forward in the fields of the total protein (6.7 g/dL vs. 6.2 g/dL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and serum albumin (3.1 g/dL vs. 2.5 g/dL, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) levels among different groups. He also reported that the GNRI was an independent early predictor of mortality (OR\u0026thinsp;=\u0026thinsp;0.383; 95% CI, 0.178\u0026ndash;0.824; P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). We obtained similar results when we used the NRS-2002 score as a tool to assess nutritional status in our study. The number of hospital-free days (t\u0026thinsp;=\u0026thinsp;450, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01), mortality and occurrence of SCAP (X\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;10.6, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) were lower in the no-risk group than in the malnutrition risk group. Furthermore, we also found that the nutritional status, as indicated by the NRS-2002 score, was a risk factor for SCAP development. Even though Both Iddir M and Yanagita Y emphasized the influence of ALB level on the prognosis of pneumonia patients, there were no distinctions between the two groups when focused on the serum ALB concentration and BMI in our research. Many studies have shown that ALB concentration was related to infectious disease risk. In combination with our previous study\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, it indicated that nutritional risk screening score and the level of ALB were correlated with the prognosis of elder with severe pneumonia. The study also revealed that shock, invasive mechanical ventilation (IMV) or renal replacement therapy and the costs associated with the malnutrition risk group increased more severely than those of the no-risk group. Therefore, we conclude that the NRS-2002 score influences the prognosis of CAP patients. Most studies focus on the effect of nutritional status on the prognosis of infection (such as pneumonia), but limited studies have addressed the effect of infection on nutrition satues.We only discussed the impact of nutritional status on the prognosis of patients with pneumonia. Even whether severe CAP could itself worsen nutritional status haven\u0026rsquo;t clarified in our research, many studies have suggested that the increased consumption of carbohydrate, fat, and protein caused by severe infections may lead to malnutrition\u003csup\u003e\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eT cells, including CD4\u003csup\u003e+\u003c/sup\u003e T cells, CD8\u003csup\u003e+\u003c/sup\u003e T cells and Tregs, are foundational to the immune system. PD-1 is often expressed on activated T lymphocytes and regulates T-cell activation. It can lead to immune tolerance by binding to antigen-presenting cell (APC) ligands, which results in T lymphocyte dysfunction, apoptosis and cytokine damage. CTLA-4 is an immunosuppressive factor that is expressed on the surface of activated T lymphocytes where it generates signals that prevent T lymphocyte activation through competitively inhibiting ligand binding to CD28 and APCs. CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells and Tregs, which affected by PD-1 and CTLA-4, are decreased in sepsis, whereas PD-1 and CTLA-4 are upregulated.\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Gong investigated the expression of PD-1 and CTLA-4 in CAP patients and reported that the percentages of Tregs with PD-1 and CTLA-4 expression were significantly greater than those in healthy controls. However, for both the CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T-cell cell groups, no differences were observed between healthy individuals and CAP patients\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Unlike in Gong\u0026rsquo;s study, PD-1 and CTLA-4 expressed on CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e T cells and on Tregs were related to the occurrence of SCAP and mortality in our study. However, when we performed a correlation analysis between PD-1/CTLA-4 and the PSI score, we found that the results were positive, as higher PD-1 and CTLA-4 percentages indicated higher PSI scores. PSI is an important tool to evaluate and predict the severity and prognosis of CAP. Therefore, we concluded that the percentage of cells with PD-1/CTLA-4 was associated with the severity of CAP.\u003c/p\u003e\u003cp\u003eMalnutrition interferes with the suppression of immune reactions, but few studies have demonstrated this process at the molecular level. We investigated this process in patients with CAP and reported that PD-1 and CTLA-4 expression was greater in the malnutrition risk group than in the no-risk group. Furthermore, we also demonstrated that the percentages of PD-1 and CTLA-4 cells were positively correlated to the NRS-2002 score. The ALB concentration and BMI are important indicators for the evaluation of nutritional status and are used to evaluate malnutrition\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In our research, the level of ALB was also related to PD-1 and CTLA-4 levels, whereas BMI was not correlated with these parameters. Patients who had higher NRS-2002 scores or lower ALB levels presented higher PD-1 and CTLA-4 levels. Therefore, we proposed that CAP patients who present with malnutrition or hypoalbuminemia may also have a high risk of immunosuppression. However, this was a single-center study and the number of enrollment was not very large, which may lead to confounding and sampling bias. Tang W\u003csup\u003e25\u003c/sup\u003e reported that the NRS-2002 score can predict the efficacy and prognosis of immunotherapy in patients with solid tumors treated with immune checkpoint inhibitor therapy. It is difficult to evaluate the immunosuppression status in an effective and precise methods during clinical practice. According to our research, the NRS-2002 score could also be an indicator of immunosuppression in patients with CAP and may be a prognostic factor in the treatment of CAP or other diseases.It can help us acknowledge the immune status in time and may provide new ideas for the immunosuppression therapies for severe pneumonia in future.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eMalnutrition, as assessed by NRS-2002, is associated with prolonged hospitalization, higher SCAP incidence, and elevated PD-1/CTLA-4 levels. Higher PD-1 and CTLA-4 levels which regulate the immunosupression process were associated with a higher PSI score. Nutritional status influences the occurrence of immunosuppression, which is associated with the prognosis of CAP. Malnutrition statues may increase the risk of immunosuppression, which is regulated by PD-1 and CTLA-4.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eChenguang Zhang was responsible for data collection, literature review and writing the manuscript. Mingqiang Zhang and Xiangdong Mu conducted the experiments and tested the levels of PD-1 and CTLA-4 in different T-cell subgroups. Sheng Wu and Xuyan Chen was responsible for writing and reviewing the manuscript. Hao Yang were engaged in data collection and figure drawing. Jingjing Li contributed to the collection, preservation and transportation of blood samples.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the Special Program of Major Epidemic Prevention and Control in Beijing (XKB2022B101).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn accordance with the International Ethical Guidelines for Biomedical Research Involving Human Subjects (2002) and the Declaration of Helsinki (2013), the Ethics Committee of the Beijing Tsinghua Changgung Hospital approved this research(18190-0-02, Sep 7,2021), and all patients provided informed consent and agreed to participate in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated or analyzed during the current study are not publicly available because the data will be used for further research but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eFern\u0026aacute;ndez-L\u0026aacute;zaro D, Seco-Calvo J. Nutrition, Nutritional Status and Functionality. Nutrients. 2023 Apr 18;15(8):1944. doi: 10.3390/nu15081944. PMID: 37111162; PMCID: PMC10142726.\u003c/li\u003e\n \u003cli\u003eMohajeri MH. Nutrition and Aging. Int J Mol Sci. 2023 May 25;24(11):9265. doi: 10.3390/ijms24119265. PMID: 37298216; PMCID: PMC10253359.\u003c/li\u003e\n \u003cli\u003eFrederiks P, Peetermans M, Wilmer A. Nutritional support in the cardiac intensive care unit. Eur Heart J Acute Cardiovasc Care. 2024 May 7;13(4):373-379. doi: 10.1093/ehjacc/zuae018. PMID: 38333990.\u003c/li\u003e\n \u003cli\u003eChen LK, Arai H, Assantachai P, Akishita M, Chew STH, Dumlao LC, Duque G, Woo J. Roles of nutrition in muscle health of community-dwelling older adults: evidence-based expert consensus from Asian Working Group for Sarcopenia. J Cachexia Sarcopenia Muscle. 2022 Jun;13(3):1653-1672. doi: 10.1002/jcsm.12981. Epub 2022 Mar 20. 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Epub 2011 Dec 14. PMID: 22196799.\u003c/li\u003e\n \u003cli\u003eS\u0026uuml;mer A, Uzun LN, \u0026Ouml;zbek YD, Tok HH, Altınsoy C. Nutrition improves COVID-19 clinical progress. Ir J Med Sci. 2022 Oct;191(5):1967-1972. doi: 10.1007/s11845-021-02868-w. Epub 2022 Jan 15. PMID: 35031937; PMCID: PMC8760115.\u003c/li\u003e\n \u003cli\u003eWu L, Liu H, Liu H. Prognostic significance of PD-1, CTLA-4, CD4, and CD8 expression in olfactory neuroblastoma. Clin Neuropathol. 2023 Mar-Apr;42(2):47-53. doi: 10.5414/NP301519. PMID: 36708210.\u003c/li\u003e\n \u003cli\u003eRowshanravan B, Halliday N, Sansom DM. CTLA-4: a moving target in immunotherapy. Blood. 2018 Jan 4;131(1):58-67. doi: 10.1182/blood-2017-06-741033. Epub 2017 Nov 8. PMID: 29118008; PMCID: PMC6317697.\u003c/li\u003e\n \u003cli\u003eGao DN, Yang ZX, Qi QH. Roles of PD-1, Tim-3 and CTLA-4 in immunoregulation in regulatory T cells among patients with sepsis. Int J Clin Exp Med. 2015 Oct 15;8(10):18998-9005. PMID: 26770525; PMCID: PMC4694425.\u003c/li\u003e\n \u003cli\u003eGong H, Zhao J, Xu W, Wan Y, Mu X, Zhang M. The distribution of myeloid-derived suppressor cells subsets and up-regulation of programmed death-1/PD-L1 axis in peripheral blood of adult CAP patients. PLoS One. 2023 Sep 27;18(9):e0291455. doi: 10.1371/journal.pone.0291455. PMID: 37756307; PMCID: PMC10529571.\u003c/li\u003e\n \u003cli\u003ePletz MW, Blasi F, Chalmers JD, Dela Cruz CS, Feldman C, Luna CM, Ramirez JA, Shindo Y, Stolz D, Torres A, Webb B, Welte T, Wunderink R, Aliberti S. International Perspective on the New 2019 American Thoracic Society/Infectious Diseases Society of America Community-Acquired Pneumonia Guideline: A Critical Appraisal by a Global Expert Panel. Chest. 2020 Nov;158(5):1912-1918. doi: 10.1016/j.chest.2020.07.089. Epub 2020 Aug 25. PMID: 32858009; PMCID: PMC7445464.\u003c/li\u003e\n \u003cli\u003eNair GB, Niederman MS. Updates on community acquired pneumonia management in the ICU. 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Prevalence of malnutrition comparing NRS2002, MUST, and PG-SGA with the GLIM criteria in adults with cancer: A multi-center study. Nutrition. 2021 Mar;83:111072. doi: 10.1016/j.nut.2020.111072. Epub 2020 Nov 19. PMID: 33360034.\u003c/li\u003e\n \u003cli\u003eKondrup J, Allison SP, Elia M, Vellas B, Plauth M; Educational and Clinical Practice Committee, European Society of Parenteral and Enteral Nutrition (ESPEN). ESPEN guidelines for nutrition screening 2002. Clin Nutr. 2003 Aug;22(4):415-21. doi: 10.1016/s0261-5614(03)00098-0. PMID: 12880610.\u003c/li\u003e\n \u003cli\u003eMirizzi, A.; Aballay, L.R.; Misciagna, G.; Caruso, M.G.; Bonfiglio, C.; Sorino, P.; Bianco, A.; Campanella, A.; Franco, I.; Curci, R.; et al. Modified WCRF/AICR Score and All-Cause, Digestive System, Cardiovascular, Cancer and Other-Cause-Related Mortality: A Competing Risk Analysis of Two Cohort Studies Conducted in Southern Italy. Nutrients 2021, 13, 4002.\u003c/li\u003e\n \u003cli\u003eMugica-Errazquin, I.; Zarrazquin, I.; Seco-Calvo, J.; Gil-Goikouria, J.; Rodriguez-Larrad, A.; Virgala, J.; Arizaga, N.; Matilla-Alejos, B.; Irazusta, J.; Kortajarena, M. The Nutritional Status of Long-Term Institutionalized Older Adults Is Associated with Functional Status, Physical Performance and Activity, and Frailty. Nutrients 2021, 13, 3716.\u003c/li\u003e\n \u003cli\u003eYanagita Y, Arizono S, Tawara Y, Oomagari M, Machiguchi H, Yokomura K, Katagiri N, Iida Y. The severity of nutrition and pneumonia predicts survival in patients with aspiration pneumonia: A retrospective observational study. Clin Respir J. 2022 Jul;16(7):522-532. doi: 10.1111/crj.13521. Epub 2022 Jul 5. PMID: 35789107; PMCID: PMC9329015.\u003c/li\u003e\n \u003cli\u003eZhang CG, Chen XY, Zhang XY,et al. Correlation between nutritional risk screening and the prognosis of elderly severe pneumonia. Chin J Crit Care Med, 2023, 43 (03): 175-179.\u003c/li\u003e\n \u003cli\u003eCollins K, Huen SC. Metabolism and Nutrition in Sepsis: In Need of a Paradigm Shift. Nephron. 2023;147(12):733-736. doi: 10.1159/000534074. Epub 2023 Sep 13. PMID: 37703850; PMCID: PMC11098033.\u003c/li\u003e\n \u003cli\u003eDe Waele E, Malbrain MLNG, Spapen H. Nutrition in Sepsis: A Bench-to-Bedside Review. Nutrients. 2020 Feb 2;12(2):395. doi: 10.3390/nu12020395. PMID: 32024268; PMCID: PMC7071318.\u003c/li\u003e\n \u003cli\u003eTang W, Li C, Huang D, Zhou S, Zheng H, Wang Q, Zhang X, Fu J. NRS2002 score as a prognostic factor in solid tumors treated with immune checkpoint inhibitor therapy: a real-world evidence analysis. Cancer Biol Ther. 2024 Dec 31;25(1):2358551. doi: 10.1080/15384047.2024.2358551. Epub 2024 May 30. PMID: 38813753; PMCID: PMC11141475.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"NRS-2002, PD-1, CTLA-4, CAP, Malnutrition","lastPublishedDoi":"10.21203/rs.3.rs-8228282/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8228282/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aimed to investigate the association between nutritional status, immunosuppression mediated by PD-1/CTLA-4 which expressed on T cells and prognosis in patients with community-acquired pneumonia (CAP).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003e According to the enrollment strategy, we enrolled 60 participants and collected their medical records. Collecting their blood samples, and exploring the distributions of PD-1 and CTLA-4 in different T-cell subgroups.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eElevated levels of PD-1 and CTLA-4 on CD4\u003csup\u003e+\u003c/sup\u003e T cells (CD4\u003csup\u003e+\u003c/sup\u003e), CD8\u003csup\u003e+\u003c/sup\u003e T cells (CD8\u003csup\u003e+\u003c/sup\u003e) and regulatory T cells (Tregs) cells were associated with the occurrance of SCAP, higher mortality, and increased Pneumonia Severity Index (PSI) scores. The malnutrition risk group (nutritional risk scring(NRS)-2002 score\u0026thinsp;\u0026ge;\u0026thinsp;3) exhibited a higher proportion of SCAP cases, prolonged hospital stays, and higher mortality when compared with the no-risk group. Higher PD-1/CTLA-4 levels were observed in the malnutrition risk group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eMalnutrition status prolonged hospitalization and increased the risk of severe CAP (SCAP). Higher PD-1 and CTLA-4 levels were associated with a higher PSI score. Nutritional status influences the occurrence of immunosuppression, and malnutrition status may increase the risk of immunosuppression, which is regulated by PD-1 and CTLA-4.\u003c/p\u003e","manuscriptTitle":"Correlation between the NRS-2002 score and PD-1/CTLA-4 levels in patients with CAP","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-11 14:24:30","doi":"10.21203/rs.3.rs-8228282/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-24T05:28:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-21T02:06:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-17T13:04:37+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62223848174922618842939051688839792087","date":"2026-02-11T18:31:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"21376157366819502567873737906966693528","date":"2026-02-11T18:31:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4281073321639387933550979398559223120","date":"2026-02-11T18:27:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-08T20:08:17+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-05T18:25:45+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-03T09:24:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-03T09:23:58+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-11-28T08:28:58+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9973a3d6-b789-47b8-b891-688eaa996bda","owner":[],"postedDate":"December 11th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":59449687,"name":"Health sciences/Biomarkers"},{"id":59449688,"name":"Health sciences/Diseases"},{"id":59449689,"name":"Biological sciences/Immunology"},{"id":59449690,"name":"Health sciences/Medical research"},{"id":59449691,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2026-04-20T02:24:55+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-11 14:24:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8228282","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8228282","identity":"rs-8228282","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}