The Role of Geriatric Nutritional Risk Index in Predicting Adverse Outcomes of Bloodstream Infections: A Retrospective Study

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The adverse effects of bloodstream infections (BSIs) in elderly patients are severe when it occurs. The Geriatric Nutritional Risk Index (GNRI), specifically designed for the elderly, itsprediction value of adverse outcomes of BSIs patients is unclear. Methods: We conducted a two-year retrospective study in a large Chinese tertiary hospital, collecting surveillance data on patients with bloodstream infections (BSI). We utilized descriptive analysis to delineate the demographic and clinical characteristics of BSI patients across different GNRI levels. The relationship between GNRI and mortality in BSI patients was investigated using logistic regression and restricted cubic spline (RCS) analysis. Results: From 2020-2021, a total of 464 patients with BSI were identified. Among them, 203 (43.8%) were no risk, 70 (15.1%) at low risk, 118 (25.4%) at moderate risk and 73 (15.7%) at major risk for nutrition-related complications based on the GNRI classification of. Patients whose GNRI at higher risk had longer length of hospital stay (P< 0.001) and higher mortality (P< 0.001). After adjusting for other covariates by multivariate logistic regression analysis, GNRI at major risk (GNRI< 82) [odds ratio (OR): 3.16; 95% confidence interval (CI): 1.52-6.58; P= 0.002] and GNRI at moderate risk (82 to <92) (OR: 1.91; 95% CI: 1.00-3.62; P= 0.049) were associated with increased risk for mortality in patients with BSI, while GNRI score (per unit increase) had a protective effect (OR: 0.96; 95% CI: 0.94-0.98; P= 0.001). Furthermore, the RCS analysis shown that the risk of mortality decreased as GNRI scores increased and gradually became stable at GNRI scores above 96-98. Conclusions: There is an association between GNRI and mortality in patients with BSI. For those patients with a lower GNRI, clinicians need to provide more timely and rational nutritional intervention to reduce mortality. Geriatric Nutritional Risk Index bloodstream infections mortality Figures Figure 1 Figure 2 1 Background Bloodstream infections (BSIs) frequently impose detrimental effects on patients, characterized by elevated incidence rates and mortality [ 1 ]. Research from North America and Europe indicates that BSIs significantly contribute to morbidity and mortality in the general population, placing them among the top seven leading causes of death [ 2 ]. In China, the situation regarding healthcare-associated BSIs remains concerning. Surveillance data from a large general hospital reveal a rising trend in BSI incidence over the past five years [ 3 ]. Additionally, BSIs place an extra burden on patients, primarily by prolonging hospital stay and increasing healthcare costs [ 4 , 5 ]. Given the substantial social and economic toll of BSIs, it is imperative to preemptively identify patients at higher risk of poor outcomes and administer more targeted treatment to this group. The Geriatric Nutritional Risk Index (GNRI) is straightforward and accurate instrument for predicting morbidity and mortality risks in hospitalized elderly patients, and Olivier Bouillanne recommends its routine documentation upon the admission of elderly patients [ 6 ]. The GNRI, a practical and valuable tool for assessing a patient's nutritional status, can be derived from serum albumin, height, and weight measurements [ 6 ]. The GNRI has garnered popularity due to its proven high prognostic value in evaluating and assessing the nutritional status and nutrition-related complications of elderly patients [ 7 , 8 ]. While the GNRI has been applied in the context of healthcare-associated infections and has demonstrated robust predictive value, there is a paucity of research on its use in forecasting the prognosis of patients with BSIs [ 9 , 10 ]. Consequently, this study aims to determine whether the GNRI is correlated with the prognosis of patients with BSIs, potentially enabling the early identification of those at great risk of adverse outcomes and facilitating timely interventions to enhance the prognosis and quality of care. 2 Methods 2.1 Study design A retrospective study was conducted on elderly patients (see detailed criteria below) who developed healthcare-associated BSIs utilizing our hospital's proprietary real-time nosocomial infection surveillance system (RT-NISS) [ 11 ]. Through database queries, we retrospectively collected the medical records of all elderly inpatients with healthcare-associated BSIs admitted between January 2020 and December 2021 at a 3500-bed tertiary level healthcare hospital in Beijing, China. A total of 464 elderly inpatients who developed BSIs during their hospital stay were identified. This study was ethically approved by the Hospital Ethical Committee (S2019-142-02). All personal identifiers were removed to ensure patient confidentiality. 2.2 Study population The inclusion criteria were as follows: (1) age ≥ 60 years; (2)length of hospital stay > 2 days; (3) admissions between January 2020 and December 2021; (4) height, weight, and albumin levels documented at admission; (5) a diagnosis of bloodstream infection during hospitalization. Inpatients who did not meet these criteria were excluded (Fig. 1 ). For patients with persistent BSIs caused by the same pathogen, only the initial episode was considered for inclusion. 2.3 Definitions Healthcare-associated bloodstream infections (BSIs) were defined as the first positive blood culture obtained at least 48 hours after admission, with no evidence of infection present at the time of admission [ 12 ]. According to the United States Centers for Disease Control and Prevention, an episode of BSI was characterized by patients experiencing fever (axillary temperature of > 38°C for more than one hour),with or without chills, and at least one positive blood culture. The infection date was determined as the date confirmed by the physician in the RT-NISS. 2.4 Data collection and outcome measurements Demographic information of the inpatients were meticulously documented through the electronic medical record system and the RT-NISS, encompassing data such as age, gender, height, weight, admitting ward, body mass index (BMI), and histories of smoking and alcohol consumption. Additionally, we obtained the clinical data, including comorbidity (hypertension, diabetes, cerebral infarction, and coronary disease), surgical procedures, use of invasive devices, and laboratory results on admission (white blood cell, neutrophil percentage, red blood cell, hemoglobin, lymphocyte percentage, platelet count, albumin, C-reactive protein, procalcitonin, alanine aminotransferase [ALT], interleukin-6, and creatinine). Furthermore, the investigator also recorded the length of hospital stay, including both prior hospitalizations and the stay after the onset of BSIs, as well as the mortality of inpatients with BSIs during their hospitalization. We defined the death during hospitalization as a poor prognosis. The primary outcome was in-hospital mortality. 2.5 GNRI calculation The GNRI is an index calculated from height, weight, and albumin. It was developed based on the Nutritional Risk Index (NRI) and is specifically applied to the elderly [ 13 ]. The GNRI is calculated using the following formula: GNRI = [1.489×albumin (g/L)] + [41.7×(weight/WLo)] [ 6 ]. Here, WLo refers to the ideal body weight, which is calculated using the Lorentz equations. The formulas are as follows: (1)for males: WLo = height − 100 - [(height-150)/4]; (2)for females: WLo = height − 100 - [(height-150)/2.5]. Based on the GNRI values, patients are classified into four categories: no nutrition-related risk (GNRI > 98), low nutrition-related risk (92 ≤ GNRI ≤ 98), moderate nutrition-related risk (82 ≤ GNRI < 92), and major nutrition-related risk (GNRI < 82). 2.6 Statistical analysis Continuous variables were expressed as either mean with standard deviation or median with interquartile range (IQR), and comparisons were made using analysis of variance (ANOVA) or Kruskal-Wallis H test. Categorical variables were presented as frequencies and percentages, and comparisons were conducted using the chi-square test or Fisher's exact tests. Univariate logistic regression analysis was applied to identify potential associations with mortality. To investigate the impact of GNRI on mortality, GNRI was included as the independent variable (reference group: GNRI > 98) and mortality in elderly inpatients with BSIs as the dependent variable. Multivariate logistic regression with the forward stepwise method was used to adjust for the potential confounders. Factors with a p-value < 0.1 in the univariate analyses were included in the multivariate logistic regression model. A restricted cubic spline (RCS) with three knots (at the 5th, 50th, and 95th percentiles) was performed to clarify the pattern of the association between GNRI and mortality in elderly inpatients with BSIs. Results with a two-tailed p-value < 0.05 were considered statistically significant. All statistical analyses were performed using R (version 3.6.3). 3 Results 3.1 Demographic and clinical feature In total, 464 patients admitted with healthcare-associated bloodstream infections were included in the final analysis. The patients were categorized into four groups based on their GNRI scores, with 203 (43.8%) having normal nutritional status (GNRI > 98). The distribution of malnutrition inpatients was as follows: low malnutrition (92 ≤ GNRI ≤ 98) with 70 (15.1%), moderate malnutrition (82 ≤ GNRI < 92) with 118 (25.4%) and major malnutrition (GNRI < 82) with 73 (15.7%). The mean age (± SD) was 73.8 (± 9.9) years, and 323 (69.6%) of the patients were male (Table 1 ). Table 1 Demographic and clinical characteristics of patients with bloodstream infections. Variables Value (n = 464) Demographic characteristic Age, years, mean ± SD 73.8 ± 9.9 Gender, n (%) Male 323(69.6) Female 141(30.4) Height, cm 167.3 ± 7.3 Weight, kg 65.0 ± 12.1 BMI, mean ± SD 23.2 ± 3.9 Smoking history, n (%) 101(21.8) Drinking history, n (%) 105(22.6) Clinical characteristics Co-morbidity, n (%) Hypertension 240(51.7) Diabetes 150(32.3) Coronary disease 86(18.5) Cerebral infarction 46(9.9) Surgical procedure, n (%) 334(72.0) Use of invasive devices Indwelling urinary catheter 290(62.5) Central intravenous catheter 330(71.1) Using ventilator 171(36.9) GNRI, n (%) > 98 (no risk) 203(43.8) 92 to ≤ 98 (low risk) 70(15.1) 82 to < 92 (moderate risk) 118(25.4) < 82 (major risk) 73(15.7) GNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index. Patients with lower GNRI score were significantly older (P < 0.001) and had a lower BMI (P 98. Significant differences were observed in smoking and drinking histories across the groups (all P 0.05). Patients at higher nutritional risk had an increased in-hospital mortality rate (P = 0.007) (Table 2 ). Table 2 The comparison of the clinical characteristic and outcomes across different subgroups of GNRI in patients with bloodstream infections Variables < 82 (major risk) 82 to 98 (no risk) P Value (n = 73) (n = 118) (n = 70) (n = 203) Demographic characteristic Age, years 77.6 ± 10.5 75.9 ± 10.7 72.7 ± 9.6 71.6 ± 8.9 < 0.001 Gender, n (%) Male 52(71.2) 79(66.9) 51(72.9) 141(69.5) 0.841 Female 21(28.8) 39(33.1) 19(27.1) 62(30.5) Height, cm 167.5 ± 6.8 166.8 ± 7.5 166.8 ± 7.7 167.6 ± 7.2 0.707 Weight, kg 51.8 ± 8.4 61.3 ± 10.3 65.0 ± 9.7 71.8 ± 10.1 < 0.001 BMI 18.4 ± 2.5 21.9 ± 2.9 23.3 ± 2.9 25.5 ± 3.1 < 0.001 Smoking history, n (%) 13(17.8) 18(15.3) 13(18.6) 57(28.1) 0.032 Drinking history, n (%) 10(13.7) 20(16.9) 21(30.0) 54(26.6) 0.023 Clinical characteristics Co-morbidity, n (%) Hypertension 35(47.9) 60(50.8) 36(51.4) 109(53.7) 0.856 Diabetes 16(21.9) 39(33.1) 23(32.9) 72(35.5) 0.206 Coronary disease 11(15.1) 24(20.3) 9(12.9) 42(20.7) 0.399 Cerebral infarction 8(11.0) 16(13.6) 7(10.0) 15(7.4) 0.348 Surgical procedure, n (%) 46(63.0) 77(65.3) 55(78.6) 156(76.8) 0.024 Use of invasive devices Indwelling urinary catheter 47(64.4) 75(63.6) 46(65.7) 122(60.1) 0.807 Central intravenous catheter 53(72.6) 84(71.2) 52(74.3) 141(69.5) 0.875 Using ventilator 22(30.1) 43(36.4) 29(41.4) 77(37.9) 0.541 Outcomes Length of hospital stay(LOS), days 34.9(21.8,56.5) 29.7(18.4,47.0) 32.1(21.8,54.9) 33.1(20.6,45.7) 0.601 Prior hospital stay, days 14.6(5.9,26.8) 11.4(5.0,26.2) 17.8(8.0,27.4) 15.3(7.5,25.5) 0.175 Hospital stay after onset of BSIs, days 14.0(6.3,28.8) 13.5(5.6,24.9) 10.8(5.0,22.6) 11.9(6.6,22.8) 0.744 Mortality rate, n (%) 25(34.2) 33(28.0) 15(21.4) 33(16.3) 0.007 GNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index. 3.2 Univariate and multivariate analysis Univariate analysis revealed that GNRI, as a continuous variable, was significantly associated with mortality (P = 0.001). When GNRI scores were categorized into four groups, patients with GNRI 98 (P = 0.002; P = 0.013, respectively). After adjusting for covariates using multivariate logistic regression, a strong association was found between high-risk GNRI and mortality (OR: 3.16; 95% CI: 1.52–6.58; P = 0.002), as well as moderate-risk GNRI (82 to < 92) (OR: 1.91; 95% CI: 1.00-3.62; P = 0.049). Furthermore, each unit increase in GNRI score was associated with a reduced risk of mortality in patients with BSI (OR: 0.96; 95% CI: 0.94–0.98; P = 0.001) (Table 3 ). Table 3 Univariate and multivariate logistic regression for risk factors associated with mortality in patients with bloodstream infection Variable univariate analysis multivariate analysis OR(95%CI) P value OR(95%CI) P value Age 1.06(1.04,1.09) < 0.001 1.05(1.03,1.08) < 0.001 Gender Female ref. Male 0.96(0.60,1.53) 0.85 Smoking history 0.62(0.35,1.11) 0.106 Drinking history 0.69(0.40,1.20) 0.189 Hypertension 1.58(1.01,2.45) 0.043 Diabetes 1.16(0.74,1.84) 0.518 Coronary disease 2.28(1.37,3.78) 0.001 Cerebral infarction 2.41(1.28,4.56) 0.007 Surgical procedure 0.69(0.44,1.10) 0.122 Using indwelling urinary catheter 6.47(3.43,12.23) < 0.001 2.79(1.33,5.87) 0.007 Using central intravenous catheter 3.65(1.96,6.79) < 0.001 Using ventilator 7.46(4.58,12.14) < 0.001 5.86(3.30,10.42) 98 (no risk) ref. ref. < 82 (major risk) 2.68(1.46,4.94) 0.002 3.16(1.52,6.58) 0.002 82 to < 92 (moderate risk) 2(1.16,3.46) 0.013 1.91(1.00,3.62) 0.049 92 to ≤ 98 (low risk) 1.41(0.71,2.78) 0.328 1.27(0.59,2.72) 0.548 GNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index. 3.3 The nonlinear association between GNRI and mortality in patients with BSI The RCS analysis demonstrated that the risk of mortality decreased as GNRI scores increased, stabilizing at scores above 96–98. For the same GNRI score, male patients with BSI exhibited a lower risk of mortality compared to females (Fig. 2 ). 4 Discussion Nutritional status is widely recognized as a critical prognostic indicator, however, the role of GNRI in assessing malnutrition and its correlation with prognostic outcomes in patients with BSIs has not been previously explored. We conducted a retrospective study of 464 patients aged 60 years and older who developed BSIs between January 2020 and December 2021. Our findings reveal that GNRI can effectively quantify the severity of malnutrition and its impact on the prognosis of BSIs. This study is the first to assess the relationship between GNRI and mortality in BSI inpatients. We found that patients with lower GNRI scores are at a higher risk of mortality compared to those with higher GNRI scores. Additionally, we demonstrated that GNRI serves as an independent risk factor for predicting mortality in hospitalized BSI patients. Finally, a nonlinear relationship between GNRI and mortality was identified in BSI inpatients. Nutrition is essential for maintaining the normal physiological functions of the human body and for recover after illness, particularly in elderly patients [ 14 , 15 ]. Therefore, assessing the nutritional status of elderly inpatients at admission is crucial. The GNRI is a useful tool that can be easily calculated from medical records, providing a score that adjusts for hydration status and demonstrates its utility in evaluating the prognosis of elderly patients [ 16 ]. Jia Z et al. [ 16 ] found that GNRI is particularly valuable for assessing nutritional status and predicting the prognosis of nutrition-related complications in hospitalized elderly patients. Previous studies have showed that GNRI can predict both short-term and long-term outcomes in patients [ 17 – 20 ]. Our study found a significant correlation between GNRI and the prognosis of patients with BSIs. Bouillanne et al demonstrated that severe malnutrition, as defined by GNRI, is associated with a higher risk of complications, including infections and mortality from infectious complications in hospitalized elderly patients [ 6 ]. Mild malnutrition was found to have no significantly impact on the mortality risk of elderly BSIs patients during hospitalization; however, patients with moderate to severe malnutrition patients faced a significantly higher risk of mortality, highlighting the importance of nutritional status assessment in hospitalized patients. Assessing baseline nutritional status can help physicians identify which elderly BSI patients require nutritional support. This study clearly demonstratess that GNRI is a predictor of mortality in patients with BSIs during hospitalization, and that there is a nonlinear relationship between GNRI and mortality. As GNRI decreases, the risk of death increases steeply. Previous studies [ 21 – 24 ] have shown that malnutrition could elevate the risk of adverse outcomes, including immune system impairment and a reduced ability of the body to adapt, recover, or survive. Patients with BSIs are already in a compromised physiological state, and malnutrition further hinders their ability to acquire the necessary nutrients for healing and maintenance. These patients often have a weakened immune response, which may contribute to the high mortality rate. Malnutrition is closely associated with the mortality of elderly patients and is believed to worsen infections, thereby exacerbating the impact of BSIs on elderly individuals [ 25 – 28 ]. Therefore, timely assessment of nutritional status is essential for elder patients with BSIs. GNRI can help clinicians identify the risk of mortality in these patients and facilitate providing prompt intervention, which can reduce BSI-related mortality. This study also found that using of indwelling urinary catheter or central intravenous catheter was associated with mortality of elderly patients with BSIs. Previous studies have shown that invasive procedures are not only associated with BSIs, but also with the prognosis of patients with BSIs [ 29 , 30 ]. Mellinghoff SC et al. [ 31 ] noted that central venous catheters and other indwelling devices are critical in the management of Candida BSIs, and invasive procedures should be used with caution. Invasive procedures can lead to disruption of the skin-mucosal barrier, reduce immune function in the elderly, and cause multiple complications secondary to poor prognosis [ 32 ]. Therefore, it is necessary to assess the necessity of invasive procedures in elderly patients with BSIs and to manage invasive procedures properly. The present study also has several limitations. First, as a single-center retrospective study, the generalizability of our findings is limited, and further data from multi-center studies are needed to confirm these results in broader populations. Second, we measured GNRI only at the time of admission. Future longitudinal studies are required to track changes in GNRI over time, which would provide deeper insights into its long-term effects. 5 Conclusions There is a robust correlation between GNRI and mortality in inpatients with BSI, establishing GNRI as a significant independent predictor of death. Clinicians should maintain heightened vigilance for patients who present with a reduced GNRI score at the onset of BSI. Declarations Ethics approval and consent to participate Not applicable. Clinical trial number Not applicable. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This work is financially supported by the Foundation of State Key Laboratory of Pathogen and Biosecurity of China (Grant No. SKLPBS2443) and Infection Prevention and Control Research Project of “Gan•Dong China” (Grant No.GY2023022-A). Authors' contributions HW-Y, ML-L, YX-L and MM-D conceived, designed and supervised the study. XL-L, ZH-Y and WH-Z collected, cleaned and analyzed the data. XL-L, ZH-Y, WH-Z, YL-B, BW-L, XM-Z, HL, JX-L, and XX-M wrote the draft of the manuscript and interpreted the findings. HW-Y, ML-L, YX-L and MM-D commented on and revised drafts of the manuscript. All authors read and approved the final report. References Goto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect. 2013;19(6):501–9. Bloodstream infections in. the elderly: what is the real goal. 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Cite Share Download PDF Status: Published Journal Publication published 01 Oct, 2025 Read the published version in BMC Geriatrics → Version 1 posted Editorial decision: Revision requested 17 Feb, 2025 Editor assigned by journal 14 Feb, 2025 Submission checks completed at journal 14 Feb, 2025 First submitted to journal 04 Feb, 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5962030","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":415813039,"identity":"ac2fc54d-b248-467b-9d06-aa660f5bf7dd","order_by":0,"name":"Xin-Lou Li","email":"","orcid":"","institution":"Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xin-Lou","middleName":"","lastName":"Li","suffix":""},{"id":415813040,"identity":"76b6f613-a7a7-4933-b629-fbce6a820248","order_by":1,"name":"Zheng-Hao Yu","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Zheng-Hao","middleName":"","lastName":"Yu","suffix":""},{"id":415813041,"identity":"63c22ff8-bb1d-4e1d-90ef-b35a55c90c0c","order_by":2,"name":"Wu-Hong Zhou","email":"","orcid":"","institution":"984th Hospital of Joint Logistic Support Force of Chinese People's Liberation Army","correspondingAuthor":false,"prefix":"","firstName":"Wu-Hong","middleName":"","lastName":"Zhou","suffix":""},{"id":415813042,"identity":"73a0524f-f5dd-445c-b762-5d353cfa7ee8","order_by":3,"name":"Yan-Ling Bai","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan-Ling","middleName":"","lastName":"Bai","suffix":""},{"id":415813043,"identity":"45c29454-01c0-4610-b274-21f90b8e1650","order_by":4,"name":"Bo-Wei Liu","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Bo-Wei","middleName":"","lastName":"Liu","suffix":""},{"id":415813044,"identity":"7fbf0dd9-a079-4543-846d-966b8a8893f9","order_by":5,"name":"Xiao-Ming Zhang","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiao-Ming","middleName":"","lastName":"Zhang","suffix":""},{"id":415813045,"identity":"98299b67-0d4c-45b8-8bf5-65dd5a9d008e","order_by":6,"name":"Huan Li","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Huan","middleName":"","lastName":"Li","suffix":""},{"id":415813046,"identity":"00a5e644-9961-4224-9181-d19a8f7f8c49","order_by":7,"name":"Jia-Xi Li","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jia-Xi","middleName":"","lastName":"Li","suffix":""},{"id":415813047,"identity":"8d2457a1-043c-41eb-8397-d5c53e0e1696","order_by":8,"name":"Cheng-Xue Ma","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Xue","middleName":"","lastName":"Ma","suffix":""},{"id":415813048,"identity":"2e7dfc7c-f3e6-44d5-a227-30c10784af24","order_by":9,"name":"Ming-Mei Du","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ming-Mei","middleName":"","lastName":"Du","suffix":""},{"id":415813049,"identity":"31d766d8-d04a-4a35-90f2-3e61e09bba3e","order_by":10,"name":"Yun-Xi Liu","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yun-Xi","middleName":"","lastName":"Liu","suffix":""},{"id":415813050,"identity":"6f1ddcef-9466-4455-aeea-b9c5546e143d","order_by":11,"name":"Meng-Lin Liu","email":"","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meng-Lin","middleName":"","lastName":"Liu","suffix":""},{"id":415813051,"identity":"0e666492-2e79-46bf-bf08-57df905cbe02","order_by":12,"name":"Hong-Wu Yao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYBADOTb29gOkaTHm4zmTQJqWxHkSDgbEKeWfffjYg49th9PbJBgSGH5UbCOsReJcWrrhzLbDuW3SjQcYe87cJsKaMzxm0rzbgFpkDiQwM7YRoUX+DP836b/bDqezSSQYEKfF4AwPmzTjtsMJxGsxPMNmJtn7L92wDRjIB4nyi9wZ5mcSP85Yy8u3tx988KOCGO8jgwMkqh8Fo2AUjIJRgAsAAG+jOfFVVtMaAAAAAElFTkSuQmCC","orcid":"","institution":"the First Medical Center, Chinese PLA General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Hong-Wu","middleName":"","lastName":"Yao","suffix":""}],"badges":[],"createdAt":"2025-02-05 03:53:25","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5962030/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5962030/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12877-025-06387-6","type":"published","date":"2025-10-01T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76578141,"identity":"6e8e4236-6702-43d7-a2dc-27f013eeae63","added_by":"auto","created_at":"2025-02-18 14:35:30","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":241354,"visible":true,"origin":"","legend":"\u003cp\u003eThe flowchat of study.\u003c/p\u003e","description":"","filename":"figure11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5962030/v1/922ffc4d9fe283ac7e76f3f9.jpg"},{"id":76579444,"identity":"c377fb85-3bcf-4779-a033-0f75a715e3ce","added_by":"auto","created_at":"2025-02-18 14:43:31","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":835908,"visible":true,"origin":"","legend":"\u003cp\u003eRCS analysis of association between GNRI and mortality in patients with BSIs. (A) Association between GNRI and mortality in total patients with BSIs. (B) Association between GNRI and mortality in patients with BSIs stratified by gender from RCS analysis. GNRI: Geriatric Nutritional Risk Index; BSI, bloodstream infections; RCS, restricted cubic spline.\u003c/p\u003e","description":"","filename":"figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5962030/v1/ca4151e5a21882ef6485b4d5.jpg"},{"id":92883642,"identity":"2cbee5a0-d3af-4582-ab57-898efc2bfede","added_by":"auto","created_at":"2025-10-06 16:07:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1961180,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5962030/v1/ba28ad58-f19a-4170-9a8c-c0a7cc30e432.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Role of Geriatric Nutritional Risk Index in Predicting Adverse Outcomes of Bloodstream Infections: A Retrospective Study","fulltext":[{"header":"1 Background","content":"\u003cp\u003eBloodstream infections (BSIs) frequently impose detrimental effects on patients, characterized by elevated incidence rates and mortality [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Research from North America and Europe indicates that BSIs significantly contribute to morbidity and mortality in the general population, placing them among the top seven leading causes of death [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. In China, the situation regarding healthcare-associated BSIs remains concerning. Surveillance data from a large general hospital reveal a rising trend in BSI incidence over the past five years [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, BSIs place an extra burden on patients, primarily by prolonging hospital stay and increasing healthcare costs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Given the substantial social and economic toll of BSIs, it is imperative to preemptively identify patients at higher risk of poor outcomes and administer more targeted treatment to this group.\u003c/p\u003e \u003cp\u003eThe Geriatric Nutritional Risk Index (GNRI) is straightforward and accurate instrument for predicting morbidity and mortality risks in hospitalized elderly patients, and Olivier Bouillanne recommends its routine documentation upon the admission of elderly patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The GNRI, a practical and valuable tool for assessing a patient's nutritional status, can be derived from serum albumin, height, and weight measurements [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The GNRI has garnered popularity due to its proven high prognostic value in evaluating and assessing the nutritional status and nutrition-related complications of elderly patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While the GNRI has been applied in the context of healthcare-associated infections and has demonstrated robust predictive value, there is a paucity of research on its use in forecasting the prognosis of patients with BSIs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Consequently, this study aims to determine whether the GNRI is correlated with the prognosis of patients with BSIs, potentially enabling the early identification of those at great risk of adverse outcomes and facilitating timely interventions to enhance the prognosis and quality of care.\u003c/p\u003e"},{"header":"2 Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design\u003c/h2\u003e \u003cp\u003eA retrospective study was conducted on elderly patients (see detailed criteria below) who developed healthcare-associated BSIs utilizing our hospital's proprietary real-time nosocomial infection surveillance system (RT-NISS) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Through database queries, we retrospectively collected the medical records of all elderly inpatients with healthcare-associated BSIs admitted between January 2020 and December 2021 at a 3500-bed tertiary level healthcare hospital in Beijing, China. A total of 464 elderly inpatients who developed BSIs during their hospital stay were identified. This study was ethically approved by the Hospital Ethical Committee (S2019-142-02). All personal identifiers were removed to ensure patient confidentiality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study population\u003c/h2\u003e \u003cp\u003eThe inclusion criteria were as follows: (1) age\u0026thinsp;\u0026ge;\u0026thinsp;60 years; (2)length of hospital stay\u0026thinsp;\u0026gt;\u0026thinsp;2 days; (3) admissions between January 2020 and December 2021; (4) height, weight, and albumin levels documented at admission; (5) a diagnosis of bloodstream infection during hospitalization. Inpatients who did not meet these criteria were excluded (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For patients with persistent BSIs caused by the same pathogen, only the initial episode was considered for inclusion.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Definitions\u003c/h2\u003e \u003cp\u003eHealthcare-associated bloodstream infections (BSIs) were defined as the first positive blood culture obtained at least 48 hours after admission, with no evidence of infection present at the time of admission [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. According to the United States Centers for Disease Control and Prevention, an episode of BSI was characterized by patients experiencing fever (axillary temperature of \u0026gt;\u0026thinsp;38\u0026deg;C for more than one hour),with or without chills, and at least one positive blood culture. The infection date was determined as the date confirmed by the physician in the RT-NISS.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data collection and outcome measurements\u003c/h2\u003e \u003cp\u003eDemographic information of the inpatients were meticulously documented through the electronic medical record system and the RT-NISS, encompassing data such as age, gender, height, weight, admitting ward, body mass index (BMI), and histories of smoking and alcohol consumption. Additionally, we obtained the clinical data, including comorbidity (hypertension, diabetes, cerebral infarction, and coronary disease), surgical procedures, use of invasive devices, and laboratory results on admission (white blood cell, neutrophil percentage, red blood cell, hemoglobin, lymphocyte percentage, platelet count, albumin, C-reactive protein, procalcitonin, alanine aminotransferase [ALT], interleukin-6, and creatinine). Furthermore, the investigator also recorded the length of hospital stay, including both prior hospitalizations and the stay after the onset of BSIs, as well as the mortality of inpatients with BSIs during their hospitalization. We defined the death during hospitalization as a poor prognosis. The primary outcome was in-hospital mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 GNRI calculation\u003c/h2\u003e \u003cp\u003eThe GNRI is an index calculated from height, weight, and albumin. It was developed based on the Nutritional Risk Index (NRI) and is specifically applied to the elderly [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The GNRI is calculated using the following formula: GNRI = [1.489\u0026times;albumin (g/L)] + [41.7\u0026times;(weight/WLo)] [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Here, WLo refers to the ideal body weight, which is calculated using the Lorentz equations. The formulas are as follows: (1)for males: WLo\u0026thinsp;=\u0026thinsp;height \u0026minus;\u0026thinsp;100 - [(height-150)/4]; (2)for females: WLo\u0026thinsp;=\u0026thinsp;height \u0026minus;\u0026thinsp;100 - [(height-150)/2.5]. Based on the GNRI values, patients are classified into four categories: no nutrition-related risk (GNRI\u0026thinsp;\u0026gt;\u0026thinsp;98), low nutrition-related risk (92\u0026thinsp;\u0026le;\u0026thinsp;GNRI\u0026thinsp;\u0026le;\u0026thinsp;98), moderate nutrition-related risk (82\u0026thinsp;\u0026le;\u0026thinsp;GNRI\u0026thinsp;\u0026lt;\u0026thinsp;92), and major nutrition-related risk (GNRI\u0026thinsp;\u0026lt;\u0026thinsp;82).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were expressed as either mean with standard deviation or median with interquartile range (IQR), and comparisons were made using analysis of variance (ANOVA) or Kruskal-Wallis H test. Categorical variables were presented as frequencies and percentages, and comparisons were conducted using the chi-square test or Fisher's exact tests. Univariate logistic regression analysis was applied to identify potential associations with mortality. To investigate the impact of GNRI on mortality, GNRI was included as the independent variable (reference group: GNRI\u0026thinsp;\u0026gt;\u0026thinsp;98) and mortality in elderly inpatients with BSIs as the dependent variable. Multivariate logistic regression with the forward stepwise method was used to adjust for the potential confounders. Factors with a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.1 in the univariate analyses were included in the multivariate logistic regression model. A restricted cubic spline (RCS) with three knots (at the 5th, 50th, and 95th percentiles) was performed to clarify the pattern of the association between GNRI and mortality in elderly inpatients with BSIs. Results with a two-tailed p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant. All statistical analyses were performed using R (version 3.6.3).\u003c/p\u003e \u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic and clinical feature\u003c/h2\u003e \u003cp\u003eIn total, 464 patients admitted with healthcare-associated bloodstream infections were included in the final analysis. The patients were categorized into four groups based on their GNRI scores, with 203 (43.8%) having normal nutritional status (GNRI\u0026thinsp;\u0026gt;\u0026thinsp;98). The distribution of malnutrition inpatients was as follows: low malnutrition (92\u0026thinsp;\u0026le;\u0026thinsp;GNRI\u0026thinsp;\u0026le;\u0026thinsp;98) with 70 (15.1%), moderate malnutrition (82\u0026thinsp;\u0026le;\u0026thinsp;GNRI\u0026thinsp;\u0026lt;\u0026thinsp;92) with 118 (25.4%) and major malnutrition (GNRI\u0026thinsp;\u0026lt;\u0026thinsp;82) with 73 (15.7%). The mean age (\u0026plusmn;\u0026thinsp;SD) was 73.8 (\u0026plusmn;\u0026thinsp;9.9) years, and 323 (69.6%) of the patients were male (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\u003eDemographic and clinical characteristics of patients with bloodstream infections.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eValue (n\u0026thinsp;=\u0026thinsp;464)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge, years, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.8\u0026thinsp;\u0026plusmn;\u0026thinsp;9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323(69.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e141(30.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHeight, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167.3\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWeight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65.0\u0026thinsp;\u0026plusmn;\u0026thinsp;12.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101(21.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDrinking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e105(22.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCo-morbidity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e240(51.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150(32.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoronary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86(18.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCerebral infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(9.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSurgical procedure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e334(72.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUse of invasive devices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndwelling urinary catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e290(62.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral intravenous catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e330(71.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUsing ventilator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e171(36.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGNRI, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;98 (no risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203(43.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 to \u0026le;\u0026thinsp;98 (low risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e70(15.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 to \u0026lt;\u0026thinsp;92 (moderate risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118(25.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;82 (major risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73(15.7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eGNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePatients with lower GNRI score were significantly older (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and had a lower BMI (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those with GNRI\u0026thinsp;\u0026gt;\u0026thinsp;98. Significant differences were observed in smoking and drinking histories across the groups (all P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). No significant variation was found in the length of stay among patients in different GNRI subgroups, nor in the duration of stay before and after infection (all P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Patients at higher nutritional risk had an increased in-hospital mortality rate (P\u0026thinsp;=\u0026thinsp;0.007) (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\u003eThe comparison of the clinical characteristic and outcomes across different subgroups of GNRI in patients with bloodstream infections\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;82 \u003c/p\u003e \u003cp\u003e(major risk)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 to \u0026lt;\u0026thinsp;92 \u003c/p\u003e \u003cp\u003e(moderate risk)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e92 to \u0026le;\u0026thinsp;98 \u003c/p\u003e \u003cp\u003e(low risk)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;98 \u003c/p\u003e \u003cp\u003e(no risk)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;73)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;118)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;70)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;203)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic characteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77.6\u0026thinsp;\u0026plusmn;\u0026thinsp;10.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.9\u0026thinsp;\u0026plusmn;\u0026thinsp;10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72.7\u0026thinsp;\u0026plusmn;\u0026thinsp;9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.6\u0026thinsp;\u0026plusmn;\u0026thinsp;8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52(71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79(66.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e51(72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e141(69.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.841\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21(28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19(27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e62(30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHeight, cm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e167.5\u0026thinsp;\u0026plusmn;\u0026thinsp;6.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e166.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e166.8\u0026thinsp;\u0026plusmn;\u0026thinsp;7.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e167.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWeight, kg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.8\u0026thinsp;\u0026plusmn;\u0026thinsp;8.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.3\u0026thinsp;\u0026plusmn;\u0026thinsp;10.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e65.0\u0026thinsp;\u0026plusmn;\u0026thinsp;9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e71.8\u0026thinsp;\u0026plusmn;\u0026thinsp;10.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.4\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e25.5\u0026thinsp;\u0026plusmn;\u0026thinsp;3.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13(17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18(15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57(28.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDrinking history, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20(16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21(30.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e54(26.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical characteristics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCo-morbidity, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(47.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60(50.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36(51.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e109(53.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16(21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39(33.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23(32.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e72(35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.206\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCoronary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(15.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24(20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9(12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e42(20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCerebral infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16(13.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7(10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15(7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.348\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSurgical procedure, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e46(63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77(65.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55(78.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e156(76.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.024\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUse of invasive devices\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndwelling urinary catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47(64.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75(63.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46(65.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e122(60.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral intravenous catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53(72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84(71.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52(74.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e141(69.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUsing ventilator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22(30.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43(36.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29(41.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e77(37.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLength of hospital stay(LOS), days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.9(21.8,56.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.7(18.4,47.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e32.1(21.8,54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33.1(20.6,45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.601\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePrior hospital stay, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.6(5.9,26.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4(5.0,26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.8(8.0,27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.3(7.5,25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHospital stay after onset of BSIs, days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0(6.3,28.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.5(5.6,24.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.8(5.0,22.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.9(6.6,22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.744\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMortality rate, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25(34.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33(28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e33(16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eGNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Univariate and multivariate analysis\u003c/h2\u003e \u003cp\u003eUnivariate analysis revealed that GNRI, as a continuous variable, was significantly associated with mortality (P\u0026thinsp;=\u0026thinsp;0.001). When GNRI scores were categorized into four groups, patients with GNRI\u0026thinsp;\u0026lt;\u0026thinsp;82 and those at moderate nutritional risk showed a significant association with mortality compared to those with GNRI\u0026thinsp;\u0026gt;\u0026thinsp;98 (P\u0026thinsp;=\u0026thinsp;0.002; P\u0026thinsp;=\u0026thinsp;0.013, respectively). After adjusting for covariates using multivariate logistic regression, a strong association was found between high-risk GNRI and mortality (OR: 3.16; 95% CI: 1.52\u0026ndash;6.58; P\u0026thinsp;=\u0026thinsp;0.002), as well as moderate-risk GNRI (82 to \u0026lt;\u0026thinsp;92) (OR: 1.91; 95% CI: 1.00-3.62; P\u0026thinsp;=\u0026thinsp;0.049). Furthermore, each unit increase in GNRI score was associated with a reduced risk of mortality in patients with BSI (OR: 0.96; 95% CI: 0.94\u0026ndash;0.98; P\u0026thinsp;=\u0026thinsp;0.001) (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\u003eUnivariate and multivariate logistic regression for risk factors associated with mortality in patients with bloodstream infection\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eunivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003emultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.06(1.04,1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.05(1.03,1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.96(0.60,1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSmoking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.62(0.35,1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDrinking history\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69(0.40,1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58(1.01,2.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDiabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16(0.74,1.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCoronary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.28(1.37,3.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCerebral infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.41(1.28,4.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSurgical procedure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.69(0.44,1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUsing indwelling urinary catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.47(3.43,12.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.79(1.33,5.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUsing central intravenous catheter\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.65(1.96,6.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eUsing ventilator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.46(4.58,12.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.86(3.30,10.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eGNRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eper unit increase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.97(0.95,0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96(0.94,0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;98 (no risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eref.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;82 (major risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.68(1.46,4.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.16(1.52,6.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82 to \u0026lt;\u0026thinsp;92 (moderate risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(1.16,3.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.91(1.00,3.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.049\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 to \u0026le;\u0026thinsp;98 (low risk)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.41(0.71,2.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.27(0.59,2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.548\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eGNRI, Geriatric Nutritional Risk Index; BMI, Body Mass Index.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.3 The nonlinear association between GNRI and mortality in patients with BSI\u003c/h2\u003e \u003cp\u003eThe RCS analysis demonstrated that the risk of mortality decreased as GNRI scores increased, stabilizing at scores above 96\u0026ndash;98. For the same GNRI score, male patients with BSI exhibited a lower risk of mortality compared to females (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eNutritional status is widely recognized as a critical prognostic indicator, however, the role of GNRI in assessing malnutrition and its correlation with prognostic outcomes in patients with BSIs has not been previously explored. We conducted a retrospective study of 464 patients aged 60 years and older who developed BSIs between January 2020 and December 2021. Our findings reveal that GNRI can effectively quantify the severity of malnutrition and its impact on the prognosis of BSIs. This study is the first to assess the relationship between GNRI and mortality in BSI inpatients. We found that patients with lower GNRI scores are at a higher risk of mortality compared to those with higher GNRI scores. Additionally, we demonstrated that GNRI serves as an independent risk factor for predicting mortality in hospitalized BSI patients. Finally, a nonlinear relationship between GNRI and mortality was identified in BSI inpatients.\u003c/p\u003e \u003cp\u003eNutrition is essential for maintaining the normal physiological functions of the human body and for recover after illness, particularly in elderly patients [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Therefore, assessing the nutritional status of elderly inpatients at admission is crucial. The GNRI is a useful tool that can be easily calculated from medical records, providing a score that adjusts for hydration status and demonstrates its utility in evaluating the prognosis of elderly patients [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Jia Z et al. [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] found that GNRI is particularly valuable for assessing nutritional status and predicting the prognosis of nutrition-related complications in hospitalized elderly patients. Previous studies have showed that GNRI can predict both short-term and long-term outcomes in patients [\u003cspan additionalcitationids=\"CR18 CR19\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Our study found a significant correlation between GNRI and the prognosis of patients with BSIs. Bouillanne et al demonstrated that severe malnutrition, as defined by GNRI, is associated with a higher risk of complications, including infections and mortality from infectious complications in hospitalized elderly patients [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Mild malnutrition was found to have no significantly impact on the mortality risk of elderly BSIs patients during hospitalization; however, patients with moderate to severe malnutrition patients faced a significantly higher risk of mortality, highlighting the importance of nutritional status assessment in hospitalized patients. Assessing baseline nutritional status can help physicians identify which elderly BSI patients require nutritional support.\u003c/p\u003e \u003cp\u003eThis study clearly demonstratess that GNRI is a predictor of mortality in patients with BSIs during hospitalization, and that there is a nonlinear relationship between GNRI and mortality. As GNRI decreases, the risk of death increases steeply. Previous studies [\u003cspan additionalcitationids=\"CR22 CR23\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] have shown that malnutrition could elevate the risk of adverse outcomes, including immune system impairment and a reduced ability of the body to adapt, recover, or survive. Patients with BSIs are already in a compromised physiological state, and malnutrition further hinders their ability to acquire the necessary nutrients for healing and maintenance. These patients often have a weakened immune response, which may contribute to the high mortality rate. Malnutrition is closely associated with the mortality of elderly patients and is believed to worsen infections, thereby exacerbating the impact of BSIs on elderly individuals [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Therefore, timely assessment of nutritional status is essential for elder patients with BSIs. GNRI can help clinicians identify the risk of mortality in these patients and facilitate providing prompt intervention, which can reduce BSI-related mortality.\u003c/p\u003e \u003cp\u003eThis study also found that using of indwelling urinary catheter or central intravenous catheter was associated with mortality of elderly patients with BSIs. Previous studies have shown that invasive procedures are not only associated with BSIs, but also with the prognosis of patients with BSIs [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Mellinghoff SC et al. [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] noted that central venous catheters and other indwelling devices are critical in the management of Candida BSIs, and invasive procedures should be used with caution. Invasive procedures can lead to disruption of the skin-mucosal barrier, reduce immune function in the elderly, and cause multiple complications secondary to poor prognosis [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Therefore, it is necessary to assess the necessity of invasive procedures in elderly patients with BSIs and to manage invasive procedures properly.\u003c/p\u003e \u003cp\u003eThe present study also has several limitations. First, as a single-center retrospective study, the generalizability of our findings is limited, and further data from multi-center studies are needed to confirm these results in broader populations. Second, we measured GNRI only at the time of admission. Future longitudinal studies are required to track changes in GNRI over time, which would provide deeper insights into its long-term effects.\u003c/p\u003e"},{"header":"5 Conclusions","content":"\u003cp\u003eThere is a robust correlation between GNRI and mortality in inpatients with BSI, establishing GNRI as a significant independent predictor of death. Clinicians should maintain heightened vigilance for patients who present with a reduced GNRI score at the onset of BSI.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.\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\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work is financially supported by the Foundation of State Key Laboratory of Pathogen and Biosecurity of China (Grant No. SKLPBS2443) and Infection Prevention and Control Research Project of \u0026ldquo;Gan\u0026bull;Dong China\u0026rdquo; (Grant No.GY2023022-A).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHW-Y, ML-L, YX-L and MM-D conceived, designed and supervised the study. XL-L, ZH-Y and WH-Z collected, cleaned and analyzed the data. XL-L, ZH-Y, WH-Z, YL-B, BW-L, XM-Z, HL, JX-L, and XX-M wrote the draft of the manuscript and interpreted the findings. HW-Y, ML-L, YX-L and MM-D commented on and revised drafts of the manuscript. All authors read and approved the final report.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGoto M, Al-Hasan MN. Overall burden of bloodstream infection and nosocomial bloodstream infection in North America and Europe. Clin Microbiol Infect. 2013;19(6):501\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBloodstream infections in. the elderly: what is the real goal. AGING CLINICAL AND EXPERIMENTAL RESEARCH; 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKaye KS, Marchaim D, Chen TY, Baures T, Anderson DJ, Choi Y, et al. Effect of nosocomial bloodstream infections on mortality, length of stay, and hospital costs in older adults. 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Nutr Cancer. 2021;73(3):391\u0026ndash;403.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYenibertiz D, Cirik MO. The comparison of GNRI and other nutritional indexes on short-term survival in geriatric patients treated for respiratory failure. Aging Clin Exp Res. 2021;33(3):611\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang W, Xiao Y, Wang H, Li K. Association of geriatric nutritional risk index with the risk of osteoporosis in the elderly population in the NHANES. Front Endocrinol (Lausanne). 2022;13:965487.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Z, Hao Q, Sun R, Zhang Y, Fu H, Liu S, et al. Predictive value of the geriatric nutrition risk index for postoperative delirium in elderly patients undergoing cardiac surgery. CNS Neurosci Ther. 2024;30(2):e14343.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKeusch GT. The history of nutrition: malnutrition, infection and immunity. J Nutr. 2003;133(1):S336\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBourke CD, Berkley JA, Prendergast AJ. Immune Dysfunction as a Cause and Consequence of Malnutrition. Trends Immunol. 2016;37(6):386\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFelblinger DM. Malnutrition, infection, and sepsis in acute and chronic illness. Crit Care Nurs Clin North Am. 2003;15(1):71\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShiroma K, Tanabe H, Takiguchi Y, Yamaguchi M, Sato M, Saito H, et al. A nutritional assessment tool, GNRI, predicts sarcopenia and its components in type 2 diabetes mellitus: A Japanese cross-sectional study. Front Nutr. 2023;10:1087471.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGavazzi G, Krause KH. Ageing and infection. Lancet Infect Dis. 2002;2(11):659\u0026ndash;66.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchaible UE, Kaufmann SH. Malnutrition and infection: complex mechanisms and global impacts. PLoS Med. 2007;4(5):e115.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorreia MI, Waitzberg DL. The impact of malnutrition on morbidity, mortality, length of hospital stay and costs evaluated through a multivariate model analysis. Clin Nutr. 2003;22(3):235\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi Z, Zhang L, Yang Q, Zhou X, Yang M, Zhang Y, et al. Association between geriatric nutritional risk index and depression prevalence in the elderly population in NHANES. BMC Public Health. 2024;24(1):469.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlves P, Melo S, Bessa M, Brito MO, Menezes RP, Ara\u0026uacute;jo LB, et al. Risk factors associated with mortality among patients who had candidemia in a university hospital. Rev Soc Bras Med Trop. 2020;53:e20190206.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLou T, Du X, Zhang P, Shi Q, Han X, Lan P, et al. Risk factors for infection and mortality caused by carbapenem-resistant Klebsiella pneumoniae: A large multicentre case-control and cohort study. J Infect. 2022;84(5):637\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMellinghoff SC, Cornely OA, Jung N. Essentials in Candida bloodstream infection. Infection. 2018;46(6):897\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou HY, Yuan Z, Du YP. Prior use of four invasive procedures increases the risk of Acinetobacter baumannii nosocomial bacteremia among patients in intensive care units: a systematic review and meta-analysis. Int J Infect Dis. 2014;22:25\u0026ndash;30.\u003c/span\u003e\u003c/li\u003e\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":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Geriatric Nutritional Risk Index, bloodstream infections, mortality","lastPublishedDoi":"10.21203/rs.3.rs-5962030/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5962030/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eNutritional deficiencies have been associated with the high prevalence of healthcare-associated infections (HAIs), which is particularly severe in elderly patients. The adverse effects of bloodstream infections (BSIs) in elderly patients are severe when it occurs. The Geriatric Nutritional Risk Index (GNRI), specifically designed for the elderly, itsprediction value of adverse outcomes of BSIs patients is unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We conducted a two-year retrospective study in a large Chinese tertiary hospital, collecting surveillance data on patients with bloodstream infections (BSI). We utilized descriptive analysis to delineate the demographic and clinical characteristics of BSI patients across different GNRI levels. The relationship between GNRI and mortality in BSI patients was investigated using logistic regression and restricted cubic spline (RCS) analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e From 2020-2021, a total of 464 patients with BSI were identified. Among them, 203 (43.8%) were no risk, 70 (15.1%) at low risk, 118 (25.4%) at moderate risk and 73 (15.7%) at major risk for nutrition-related complications based on the GNRI classification of. Patients whose GNRI at higher risk had longer length of hospital stay (P\u0026lt; 0.001) and higher mortality (P\u0026lt; 0.001). After adjusting for other covariates by multivariate logistic regression analysis, GNRI at major risk (GNRI\u0026lt; 82) [odds ratio (OR): 3.16; 95% confidence interval (CI): 1.52-6.58; P= 0.002] and GNRI at moderate risk (82 to \u0026lt;92) (OR: 1.91; 95% CI: 1.00-3.62; P= 0.049) were associated with increased risk for mortality in patients with BSI, while GNRI score (per unit increase) had a protective effect (OR: 0.96; 95% CI: 0.94-0.98; P= 0.001). Furthermore, the RCS analysis shown that the risk of mortality decreased as GNRI scores increased and gradually became stable at GNRI scores above 96-98.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e There is an association between GNRI and mortality in patients with BSI. For those patients with a lower GNRI, clinicians need to provide more timely and rational nutritional intervention to reduce mortality.\u003c/p\u003e","manuscriptTitle":"The Role of Geriatric Nutritional Risk Index in Predicting Adverse Outcomes of Bloodstream Infections: A Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-18 14:27:26","doi":"10.21203/rs.3.rs-5962030/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-17T07:32:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-02-14T11:37:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-02-14T11:37:32+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Geriatrics","date":"2025-02-05T03:49:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-geriatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bgtc","sideBox":"Learn more about [BMC Geriatrics](http://bmcgeriatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bgtc/default.aspx","title":"BMC Geriatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b104b0d-3a20-4f1c-b48a-273a8b3ebaca","owner":[],"postedDate":"February 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T15:59:55+00:00","versionOfRecord":{"articleIdentity":"rs-5962030","link":"https://doi.org/10.1186/s12877-025-06387-6","journal":{"identity":"bmc-geriatrics","isVorOnly":false,"title":"BMC Geriatrics"},"publishedOn":"2025-10-01 15:57:09","publishedOnDateReadable":"October 1st, 2025"},"versionCreatedAt":"2025-02-18 14:27:26","video":"","vorDoi":"10.1186/s12877-025-06387-6","vorDoiUrl":"https://doi.org/10.1186/s12877-025-06387-6","workflowStages":[]},"version":"v1","identity":"rs-5962030","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5962030","identity":"rs-5962030","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}