Association of body mass index and hypoglycemia with mortality rates among sepsis patients: a retrospective sub-analysis of the FORECAST Study

Association of body mass index and hypoglycemia with mortality rates among sepsis patients: a retrospective sub-analysis of the FORECAST Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Association of body mass index and hypoglycemia with mortality rates among sepsis patients: a retrospective sub-analysis of the FORECAST Study Atsushi Tanikawa, Daisuke Kudo, Hiroyuki Ohbe, Shigeki Kushimoto This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-643582/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract We assessed the influence of admission hypoglycemia on mortality in sepsis patients according to body mass index (BMI). We included 1,184 patients (age ≥ 16 years) with severe sepsis diagnosed using Sepsis-2 criteria. The outcome was in-hospital mortality. Using multivariate logistic regression, we examined the association between hypoglycemia and in-hospital mortality. Overall, 1,103 patients were analyzed. Patients were divided into groups according to the initial blood glucose level, i.e., < 70 (hypoglycemia) or ≥ 70 (non-hypoglycemia) mg/dL, and BMI, i.e., < 18.5 (low), 18.5–24.9 (normal), or ≥ 25 (high) kg/m 2 . Hypoglycemia was noted in 65 patients, with low (n = 13), normal (n = 38), and high BMI (n = 14). Hypoglycemia patients showed higher in-hospital mortality than those without in the normal BMI group but not in the low and high BMI groups. In multivariate logistic regression, hypoglycemia was non-significantly associated with higher mortality in all patients ( p = 0.268). However, there was a significant interaction between normal BMI patients and hypoglycemia on in-hospital mortality but not between low or high BMI patients and hypoglycemia ( p = 0.0476). Hypoglycemia at admission in sepsis patients was associated with high mortality in normal BMI patients but not in low or high BMI patients. This association may be used as a prognostic marker in sepsis patients. Critical Care & Emergency Medicine Molecular Epidemiology Epidemiology Blood glucose body mass index mortality sepsis Figures Figure 1 Figure 2 Introduction Sepsis is a life-threatening syndrome characterized by organ dysfunction due to infection [ 1 , 2 ]. It is estimated that more than 10 million sepsis patients die each year, and the number of deaths is increasing [ 1 , 3 ]. Previous reports showed that hypoglycemia at admission is associated with high mortality in sepsis patients [ 4 – 7 ]. The association of body mass index (BMI) with sepsis-related mortality has also been investigated. Studies from North America and Europe demonstrated that a higher BMI was associated with lower mortality rates, while a report from China indicated that a higher BMI was not significantly associated with lower mortality rates, but a lower BMI was associated with a high risk of death [ 8 – 11 ]. In addition to these inconsistent results, it remains unclear whether hypoglycemia is associated with survival outcomes regardless of BMI or in a particular BMI category. This study aimed to assess the association between hypoglycemia at admission and mortality in sepsis patients according to BMI categories. Methods Design, setting, and participants This is a retrospective secondary analysis of the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma (FORECAST) study, which described the incidence, clinical characteristics, and evolving management of sepsis in Japan. The FORECAST study was a multicenter, prospective cohort study of sepsis patients at 59 intensive care units (ICUs), and it was conducted between January 2016 and March 2017 [ 12 ]. The subjects were patients (age ≥ 16 years) diagnosed with severe sepsis based on the Sepsis-2 criteria in 2003 [ 13 ] because the FORECAST sepsis study was planned before the announcement of the Sepsis-3 criteria. All the patients were admitted to the ICU. Severe sepsis was defined as a diagnosis or suspicion of new-onset infection based on the history of present illness, meeting at least two criteria for systemic inflammatory response syndrome [ 14 ] and at least one criterion for organ dysfunction. Exclusion criteria included the limitation of sustained life care or post-cardiopulmonary arrest resuscitation status at the time of sepsis diagnosis. In this secondary analysis, we screened all patients included in the FORECAST study. We excluded patients with missing data of initial blood glucose level, BMI, or survival at discharge. Because only few data were missing, we did not make any assumptions for missing data. The FORECAST study protocol was reviewed and approved by the ethics committee of all participating institutes in the FORECAST Study Group, Japan (IRB number 014–0306, Hokkaido University the presentative for FORECAST). Data collection was performed as a part of routine clinical workup without any interventions, and data management and statistical analyses were performed anonymously. Hence, the need for informed consent was waived by the ethics committee of all participating institutes in the FORECAST Study Group ( Appendix ). All methods were performed in accordance with the relevant guidelines and regulations. Data collection Data were compiled by the FORECAST investigators and obtained from the FORECAST database. We collected data of patient characteristics, admission source, pre-existing comorbidities assessed using the Charlson comorbidity index, activities of daily living, suspected sites of infection, organ dysfunction, sepsis-related severity scores, duration of mechanical ventilation and ICU stays, and survival information 28 days after ICU admission and at hospital discharge. The Sequential Organ Failure Assessment (SOFA) [ 15 ] and the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores [ 16 ] were calculated using physiological and laboratory data obtained at the initial examination as a part of the routine medical workup. Blood glucose levels were measured using a blood gas analyzer, as recommended by the international sepsis guidelines [ 17 ], and not using a glucometer. All glucose levels were measured before corticosteroid administration, if possible. Date definitions Patients were divided into two groups depending on their initial blood glucose levels: <70 mg/dL (hypoglycemia) or ≥ 70 mg/dL (non-hypoglycemia). Although not universally defined, blood glucose levels of < 70 mg/dL are widely accepted as the definition of hypoglycemia [ 18 ]. BMI classification was made based on the definition of the Japan Society for the Study of Obesity [ 19 ]: <18.5 kg/m 2 (low BMI), 18.5–24.9 kg/m 2 (normal BMI), and ≥ 25 kg/m 2 (high BMI). Septic shock and organ dysfunction were defined using the Sepsis-2 criteria [ 13 ]. The Charlson comorbidity index was classified into four groups as previously defined: 0 (none), 1–2 (low), 3–4 (moderate), and ≥ 5 (high) points [ 20 ]. Outcome The primary outcome measure was in-hospital mortality. Statistical analysis Descriptive statistics included counts (proportions) for categorical variables and medians (interquartile range, IQR) for continuous variables, as not all variables had normal distribution. Categorical variables were compared using chi-square tests, and continuous variables were compared using the Mann-Whitney U test. We performed a multivariable logistic regression analysis using in-hospital mortality as the objective variable and blood glucose level of < 70 mg/dL or not, three BMI category groups, age, SOFA score, and Charlson comorbidity index, as explanatory variables. To examine the heterogeneity of the impact of hypoglycemia on in-hospital mortality across each BMI category, we performed a multivariable logistic regression analysis including the interaction term between BMI category and hypoglycemia in each BMI category. Statistical significance was defined as p < 0.05, and statistical analyses were performed using JMP® 15 (SAS Institute Inc., Cary, NC, USA). Results The FORECAST study registered 1,184 patients. Eighty-one patients were excluded because of missing data regarding the initial blood glucose level, BMI, or survival at hospital discharge. Finally, we analyzed data from 1,103 patients with severe sepsis. The patients were divided into two groups according to blood glucose levels: 65 patients with hypoglycemia and 1,038 patients without hypoglycemia. Furthermore, patients with hypoglycemia were divided according to BMI categories: 13/1,103 (1% of all included patients) with a low BMI, 38/1,103 (2%) with a normal BMI, and 14/1,103 (1%) with a high BMI. Patients without hypoglycemia were also divided similarly: 210/1,103 (19%), 584/1,103 (53%), and 244/1,103 (22%), respectively (Fig. 1 ). Patient characteristics and clinical outcomes Patient characteristics are shown in Table 1 (detailed characteristics are shown in Supplemental Digital Content 1 ). Median patient age was 73 (64–81) years, and median BMI was 21.7 kg/m 2 (19.0–24.7). Of the 1,038 patients, 23.3% were diagnosed with diabetes mellitus before admission. The proportion of patients with pre-existing diabetes was similar between patients with and without hypoglycemia in all BMI categories. The most suspected site of infection was the lung (31.1%), followed by the abdomen (25.7%). SOFA score, APACHE II score, and lactate levels tended to be higher in patients with hypoglycemia than in those without hypoglycemia in all BMI categories. Table 1 Characteristics of patients classified by body mass index category and glucose levels on admission All patients BMI low (n = 223) BMI normal (n = 622) BMI high (n = 258) (n = 1,103) Glucose <70 mg/dL Glucose ≥ 70 mg/dL p value Glucose < 70 mg/dL Glucose ≥ 70 mg/dL p value Glucose < 70 mg/dL Glucose ≥ 70 mg/dL p value (n = 13) (n = 210) (n = 38) (n = 584) (n = 14) (n = 244) Age (years) 73 (64–81) 71 (58.0–79.5) 75 (67–83) 0.224 74 (69.5–80) 73 (64–82) 0.297 68 (64–72.5) 69 (61–80) 0.581 Sex, male 664 (60.2) 6 (46.2) 114 (54.3) 0.568 19 (50.0) 368 (63.0) 0.109 6 (42.8) 151 (61.9) 0.156 BMI (kg/m 2 ) 21.7 (19.0–24.7) 15.6 (14.9–17.4) 16.8 (15.2–17.8) 0.429 21.2 (19.7–23.2) 21.5 (19.9–23.1) 0.722 29.8 (26.4–31.8) 27.0 (25.8–30.4) 0.123 Glucose (mg/dL) 136 (104–188) 40 (25.5–61) 133.5 (105–179) < .0001 51.5 (36–63) 139 (110–192) < .0001 59 (47–53) 146.5 (116.5–199) < 0.0001 SOFA score 9 (6–11) 10 (7–14) 9 (6–11) 0.177 11 (9–14.5) 8 (6–11) < .0001 12 (10–13) 8 (5–12) 0.00168 APACHE II score 22 (17–29) 26 (20–31) 22 (17–30) 0.433 29 (21–38.5) 22 (17–29) 0.0003 29.5 (23–35.5) 22 (16–30) 0.087 Pre-existing diabetes mellitus 257 (23.3) 2 (15.4) 34 (15.7) 0.975 7 (18.4) 129 (22.1) 0.596 4 (28.6) 82 (33.6) 0.698 Charlson Comorbidity Index 1 (0–2) 1 (0–2) 1 (0–2) 0.710 1 (0–2) 1 (0–2) 0.629 1 (0–3.5) 1 (0–2) 0.947 Septic shock 684 (62.0) 11 (84.6) 137 (65.2) 0.151 31 (81.6) 359 (61.5) 0.0130 12 (85.7) 134 (54.9) 0.0238 Number of patients with missing data: SOFA score, 158; APACHE II score, 112 APACHE, Acute Physiology and Chronic Health Evaluation; BMI, body mass index; SOFA, Sequential Organ Failure Assessment The clinical outcomes are shown in Table 2 (detailed results of outcome measures are shown in Supplemental Digital Content 2 ). In all patients, the in-hospital and 28-day mortality rates were 253/1103 (22.9%) and 200/1093 (18.3%), respectively. The in-hospital and 28-day mortality rates were higher in patients with hypoglycemia than in those without hypoglycemia in the normal BMI group (18/38 [47.4%] vs. 119/584 [20.4%], p = 0.0001, and 16/38 [42.1%] vs. 89/577 [15.4%], p < 0.0001, respectively). However, these rates were similar in the low and high BMI groups. Table 2 Clinical outcomes in patients with or without hypoglycemia classified by body mass index All patients BMI low (n = 223) BMI normal (n = 622) BMI high (n = 258) (n = 1,103) Glucose < 70 mg/dL Glucose ≥ 70 mg/dL p value Glucose < 70 mg/dL Glucose ≥ 70 mg/dL p value Glucose < 70 mg/dL Glucose ≥ 70 mg/dL p value (n = 13) (n = 210) (n = 38) (n = 584) (n = 14) (n = 244) In-hospital mortality 253/1103 (22.9) 3/13 (23.1) 53/210 (25.2) 0.862 18/38 (47.4) 119/584 (20.4) 0.0001 3/14 (21.4) 57/244 (23.4) 0.868 28-day mortality 200/1093 (18.3) 3/13 (23.1) 43/209 (20.6) 0.829 16/38 (42.1) 89/577 (15.4) < .0001 3/14 (21.4) 46/242 (19.0) 0.823 ICU-free days 19 (11–24) 16.5 (10–24) 20 (13–25) 0.355 17 (9.5–22) 19 (10–24) 0.437 13 (4–20) 20 (11–24) 0.097 Length of hospital stay 24 (12–46) 22 (5.5–40) 24 (14–45) 0.524 27 (4–44) 25.5 (13–47) 0.260 23.5 (19–52.5) 21 (11–46) 0.200 Number of patients with missing data: 28-day mortality, 10; ICU-free days, 210 BMI, body mass index; ICU, intensive care unit Interaction between hypoglycemia and BMI category for in-hospital mortality In the multivariate logistic regression model, hypoglycemia was not significantly associated with higher mortality in all patients (Table 3 ). However, there was a significant interaction between patients with normal BMI and hypoglycemia on in-hospital mortality (OR 2.32, 95% CI 1.05–5.07, p value for interaction = 0.0476), whereas there was no interaction between patients with low or high BMI and hypoglycemia (Fig. 2 ). Table 3 Odds ratios for in-hospital mortality Variables Odds ratio 95% CI p value Glucose level < 70 mg/dL 1.41 0.77–2.58 0.268 BMI low vs. normal 1.19 0.78–1.81 0.407 BMI high vs. normal 1.09 0.73–1.62 0.662 BMI high vs. low 0.92 0.56–1.50 0.724 Age 1.02 1.00–1.03 0.0189 SOFA 1.18 1.13–1.23 < 0.0001 Charlson Comorbidity Index 1.22 1.12–1.34 < 0.0001 BMI, body mass index; CI, confidence interval; SOFA, Sequential Organ Failure Assessment Discussion We found that hypoglycemia at admission in sepsis patients was associated with high mortality in patients with normal BMI but not in those with low and high BMI. To the best of our knowledge, this is the first study to examine the association between hypoglycemia at admission and mortality in sepsis patients according to BMI categories. Hypoglycemia is associated with a high mortality rate in sepsis patients and critically ill patients [ 5 – 7 ]. The NICE-SUGAR study demonstrated that hypoglycemia was associated with an increased risk of death, especially among patients with distributive shock [ 6 ]. Patients with both septic shock and hypoglycemia on the day of enrolment had a 2.5-fold higher mortality rate than those without septic shock and hypoglycemia in a multicenter observational study of sepsis patients in Japan [ 5 ]. The distribution of BMI in the population varies widely across countries and regions. A population-based study of adults was conducted in 200 countries, and it revealed that the proportions of high BMI (BMI ≥ 25), normal BMI, and low BMI (BMI < 18.5) were 50–60%, 30%, and < 5%, respectively, in Western countries, and 30%, 50%, and 10–20%, respectively, in East Asian countries [ 20 ]. Observational studies in sepsis patients of Western countries showed that the population with high BMI accounted for more than 50% and that of low BMI accounted for less than 10%, and sepsis patients with high BMI had better survival outcomes, suggesting an “obesity paradox” [ 8 – 10 ]. By contrast, a study conducted in China reported that low BMI was an independent factor associated with reduced 90-day survival [ 11 ]. In addition, a retrospective observational study using two cohorts in Japan (including cohort of the FORECAST study) showed that patients with low BMI had a significantly higher 28-day mortality than those without low BMI [ 21 ]. However, previous studies did not address the association between hypoglycemia and mortality in sepsis patients according to BMI categories. The mechanism by which a low BMI and high BMI were not associated with worse mortality in patients with hypoglycemia was not clear. Adipose tissue and lipoproteins are related to BMI [ 22 ] as well as inflammation [ 23 , 24 ]. The amount of adipose tissue and lipoproteins may depend on host defense in patients with sepsis and hypoglycemia. Further studies should be conducted to elucidate the mechanisms underlying the biological reactions of adipose tissue and lipoproteins to hypoglycemia in sepsis patients. This study has some limitations. First, because these data were collected before the sepsis-3 criteria were published, the definition of sepsis used in this study was different from the latest definition. Second, the number of patients with hypoglycemia was too small to be assessed with sufficient statistical power. Third, all of our participants were Japanese; thus, generalizability might be limited to East Asians. Fourth, we could use few explanatory variables in the multivariate analysis because not many patients died. In conclusion, hypoglycemia at admission in sepsis patients was associated with high mortality in patients with normal BMI, but not in those with low and high BMI. This association may be used as a prognostic marker in sepsis patients. In the future, larger cohort studies are needed to confirm this finding. Declarations Acknowledgements We thank the core investigators of the FORECAST sepsis study (Appendix) for providing the dataset. We are grateful to all investigators involved in the FORECAST sepsis study for contributing to data collection and assessment. Authors’ contributions All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by AT and DK. Statistical analysis was reviewed by DK and HO. The first draft of the manuscript was written by AT. The manuscript was reviewed and edited by DK and SK, and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript. Conflict of Interest and Source of Funding This work was supported by grants from JSPS KAKENHI [grant number JP 19H03755] for language editing. The authors declare that they have no competing interests. Availability of data and materials The dataset of the FORECAST sepsis study is not publicly available, based on the decision by the Japanese Association for Acute Medicine. Ethics approval and consent to participate The study protocol was reviewed and approved by the ethics committee of all participant institutes in the Japanese Association for Acute Medicine (JAAM) study group, Japan. (IRB number 014–0306 on Hokkaido University, the representative for FORECAST). References Singer, M. et al. The third international consensus definitions for sepsis and septic shock (sepsis-3). JAMA , 315 , 801–810 (2016). Rudd, K. E. et al. Global, regional, and national sepsis incidence and mortality, 1990–2017: analysis for the Global Burden of Disease Study. Lancet , 395 , 200–211 (2020). Gaieski, D. F., Edwards, J. M., Kallan, M. J. & Carr, B. G. Benchmarking the incidence and mortality of severe sepsis in the United States. Crit. Care Med , 41 , 1167–1174 (2013). Plummer, M. P. et al. Dysglycaemia in the critically ill and the interaction of chronic and acute glycaemia with mortality. Intensive Care Med , 40 , 973–980 (2014). Kushimoto, S. et al. Impact of blood glucose abnormalities on outcomes and disease severity in patients with severe sepsis: an analysis from a multicenter, prospective survey of severe sepsis. PLOS ONE , 15 , e0229919 (2020). NICE-SUGAR Study Investigators. Hypoglycemia and risk of death in critically ill patients. N. Engl. J. Med , 367 , 1108–1118 (2012). Hermanides, J. et al. Hypoglycemia is associated with intensive care unit mortality. Crit. Care Med , 38 , 1430–1434 (2010). Prescott, H. C., Chang, V. W., O’Brien, J. M. Jr, Langa, K. M. & Iwashyna, T. J. Obesity and 1-year outcomes in older Americans with severe sepsis. Crit. Care Med , 42 , 1766–1774 (2014). Sakr, Y. et al. Obesity is associated with increased morbidity but not mortality in critically ill patients. Intensive Care Med , 34 , 1999–2009 (2008). Pepper, D. J. et al. Does obesity protect against death in sepsis? A retrospective cohort study of 55,038 adult patients. Crit. Care Med , 47 , 643–650 (2019). Zhou, Q. et al. Impact of body mass index on survival of medical patients with sepsis: a prospective cohort study in a university hospital in China. BMJ. Open , 8 , e021979 (2018). Abe, T. et al. Characteristics, management, and in-hospital mortality among patients with severe sepsis in intensive care units in Japan: the FORECAST study. Crit. Care , 22 , 322 (2018). Levy, M. M. et al. 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Crit. Care. Med. 31, 1250–1256(2003). Bone, R. C. et al. Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 101, 1644–1655(1992). Vincent, J. L. et al. Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on “sepsis-related problems” of the European Society of Intensive Care Medicine. Crit. Care. Med , 26 , 1793–1800 (1998). Knaus, W. A., Draper, E. A., Wagner, D. P. & Zimmerman, J. E. Apache II: a severity of disease classification system. Crit. Care. Med , 13 , 818–829 (1985). Dellinger, R. P. et al. Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. Crit. Care Med , 41 , 580–637 (2013). Seaquist, E. R. et al. Hypoglycemia and diabetes: a report of a workgroup of the American Diabetes Association and the Endocrine Society. J. Clin. Endocrinol. Metab , 98 , 1845–1859 (2013). Examination Committee of Criteria for 'Obesity Disease' in Japan; Japan Society for the Study of Obesity. New criteria for “obesity disease” in. Jpn. Circ. J , 66 , 987–992 (2002). Yang, Y., Yang, K. S., Hsann, Y. M., Lim, V. & Ong, B. C. The effect of comorbidity and age on hospital mortality and length of stay in patients with sepsis. J. Crit. Care , 25 , 398–405 (2010). Oami, T. et al. Association between low body mass index and increased 28-day mortality of severe sepsis in Japanese cohorts. Sci. Rep , 11 , 1615 (2021). Bastien, M., Poirier, P., Lemieux, I. & Després, J. P. Overview of epidemiology and contribution of obesity to cardiovascular disease. Prog. Cardiovasc. Dis , 56 , 369–381 (2014). McGown, C., Birerdinc, A. & Younossi, Z. M. Adipose tissue as an endocrine organ. Clin. Liver. Dis , 18 , 41–58 (2014). Murch, O., Collin, M., Hinds, C. J. & Thiemermann, C. Lipoproteins in inflammation and sepsis. I. Basic science. Intensive Care Med , 33 , 13–24 (2007). Additional Declarations No competing interests reported. Supplementary Files Forecastsupplementaltable2AT0621.docx Forecastsupplementaltable1AT0621.docx Appendix0506.docx Cite Share Download PDF Status: Posted Version 1 posted 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-643582","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":35948891,"identity":"708e0ee5-2684-4070-aa48-9f639e124a2c","order_by":0,"name":"Atsushi Tanikawa","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/ElEQVRIiWNgGAWjYLACxgYJBgZm5gMHPlQwgBgN+JWzQbXwsLclPpxxBqSFkSgtDAw8PGeMjXnbGKBcPIB/fvszyZ87LBjsJXLMpHnn1UbztwO1/KjYhlOLxDEeoMozQIdJpJVJzt12PHfGYcYGxp4zt3Fbc4yHTZqxDaQleZvE223HchuAWpgZ23BrkT/GDnQYWEuCmQTvnGO58wlpMTjGAFQJ0sJzxNiQt6EmdwMhLYbHcoytgVp4eI6DAvnYgdyNQC0H8flF7vDxhzd/ttXJsTeDorKmLnfe+cMHH/yowON9KOCB0ofB5AGC6pFAHSmKR8EoGAWjYIQAACgNWB95YgREAAAAAElFTkSuQmCC","orcid":"","institution":"Tohoku University Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Atsushi","middleName":"","lastName":"Tanikawa","suffix":""},{"id":35948892,"identity":"ad8ac68d-e584-4022-ab97-fd7edff0cb17","order_by":1,"name":"Daisuke Kudo","email":"","orcid":"","institution":"Tohoku University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daisuke","middleName":"","lastName":"Kudo","suffix":""},{"id":35948893,"identity":"6b4c5489-4f0a-43de-b95e-c854c228ca8f","order_by":2,"name":"Hiroyuki Ohbe","email":"","orcid":"","institution":"The University of Tokyo","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hiroyuki","middleName":"","lastName":"Ohbe","suffix":""},{"id":35948894,"identity":"7140e1a4-ad83-4185-b271-aeb6abce6513","order_by":3,"name":"Shigeki Kushimoto","email":"","orcid":"","institution":"Tohoku University Graduate School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Shigeki","middleName":"","lastName":"Kushimoto","suffix":""}],"badges":[],"createdAt":"2021-06-20 23:44:01","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-643582/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-643582/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":10969185,"identity":"d47b6a30-8932-4f2f-8543-bab0178d0817","added_by":"auto","created_at":"2021-06-30 17:13:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":134278,"visible":true,"origin":"","legend":"Flowchart of the patient selection process","description":"","filename":"Onlinefigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/2121223cb6b88f9fe503828f.png"},{"id":10969186,"identity":"5562e999-562e-4c5f-906e-a8ddfdaa23ba","added_by":"auto","created_at":"2021-06-30 17:13:36","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":93650,"visible":true,"origin":"","legend":"Interaction between body mass index category and hypoglycemia for in-hospital morality\nOdds ratios of hypoglycemia for in-hospital mortality in each BMI category are shown. Odds ratios and 95% CIs were obtained using a multivariable logistic regression model. Squares indicate odds ratios. Horizontal bars indicate 95% confidence intervals. The dotted vertical line indicates the odds ratio of hypoglycemia for in-hospital mortality in all patients.\nLow BMI, \u003c18.5 kg/m2; normal BMI, 18.5–24.9 kg/m2; high BMI, ≥25 kg/m2.\nBMI, body mass index; CI, confidence interval\n","description":"","filename":"Onlinefigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/1503172b2d42acbf0c7e026b.png"},{"id":15302056,"identity":"0c4c2324-bcee-4a06-921c-64f70fd679f4","added_by":"auto","created_at":"2021-11-08 09:29:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":535999,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/3f3e3a3a-76f2-4386-86f7-86d69a0814c2.pdf"},{"id":10969024,"identity":"9ae90ff0-3dc6-44a8-904f-94cd1b42e453","added_by":"auto","created_at":"2021-06-30 17:10:36","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":28328,"visible":true,"origin":"","legend":"","description":"","filename":"Forecastsupplementaltable2AT0621.docx","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/4b68bd135d7021cec6850d57.docx"},{"id":10969022,"identity":"98fb0a2f-eabf-4a1f-9910-187839499896","added_by":"auto","created_at":"2021-06-30 17:10:36","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":33908,"visible":true,"origin":"","legend":"","description":"","filename":"Forecastsupplementaltable1AT0621.docx","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/425fdc828057f33b4b9384cc.docx"},{"id":10969537,"identity":"c1c864bc-5daf-4dc3-bd6b-3083ef8313b6","added_by":"auto","created_at":"2021-06-30 17:16:36","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":14955,"visible":true,"origin":"","legend":"","description":"","filename":"Appendix0506.docx","url":"https://assets-eu.researchsquare.com/files/rs-643582/v1/5e93fc803acd9f5e68854924.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Association of body mass index and hypoglycemia with mortality rates among sepsis patients: a retrospective sub-analysis of the FORECAST Study","fulltext":[{"header":"Introduction","content":" \u003cp\u003eSepsis is a life-threatening syndrome characterized by organ dysfunction due to infection [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It is estimated that more than 10\u0026nbsp;million sepsis patients die each year, and the number of deaths is increasing [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious reports showed that hypoglycemia at admission is associated with high mortality in sepsis patients [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The association of body mass index (BMI) with sepsis-related mortality has also been investigated. Studies from North America and Europe demonstrated that a higher BMI was associated with lower mortality rates, while a report from China indicated that a higher BMI was not significantly associated with lower mortality rates, but a lower BMI was associated with a high risk of death [\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn addition to these inconsistent results, it remains unclear whether hypoglycemia is associated with survival outcomes regardless of BMI or in a particular BMI category. This study aimed to assess the association between hypoglycemia at admission and mortality in sepsis patients according to BMI categories.\u003c/p\u003e "},{"header":"Methods","content":" \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDesign, setting, and participants\u003c/h2\u003e \u003cp\u003e This is a retrospective secondary analysis of the Focused Outcomes Research in Emergency Care in Acute Respiratory Distress Syndrome, Sepsis, and Trauma (FORECAST) study, which described the incidence, clinical characteristics, and evolving management of sepsis in Japan. The FORECAST study was a multicenter, prospective cohort study of sepsis patients at 59 intensive care units (ICUs), and it was conducted between January 2016 and March 2017 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The subjects were patients (age\u0026thinsp;\u0026ge;\u0026thinsp;16 years) diagnosed with severe sepsis based on the Sepsis-2 criteria in 2003 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] because the FORECAST sepsis study was planned before the announcement of the Sepsis-3 criteria. All the patients were admitted to the ICU. Severe sepsis was defined as a diagnosis or suspicion of new-onset infection based on the history of present illness, meeting at least two criteria for systemic inflammatory response syndrome [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and at least one criterion for organ dysfunction. Exclusion criteria included the limitation of sustained life care or post-cardiopulmonary arrest resuscitation status at the time of sepsis diagnosis.\u003c/p\u003e \u003cp\u003eIn this secondary analysis, we screened all patients included in the FORECAST study. We excluded patients with missing data of initial blood glucose level, BMI, or survival at discharge. Because only few data were missing, we did not make any assumptions for missing data.\u003c/p\u003e \u003cp\u003eThe FORECAST study protocol was reviewed and approved by the ethics committee of all participating institutes in the FORECAST Study Group, Japan (IRB number 014\u0026ndash;0306, Hokkaido University the presentative for FORECAST). Data collection was performed as a part of routine clinical workup without any interventions, and data management and statistical analyses were performed anonymously. Hence, the need for informed consent was waived by the ethics committee of all participating institutes in the FORECAST Study Group (\u003cb\u003eAppendix\u003c/b\u003e). All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eData were compiled by the FORECAST investigators and obtained from the FORECAST database. We collected data of patient characteristics, admission source, pre-existing comorbidities assessed using the Charlson comorbidity index, activities of daily living, suspected sites of infection, organ dysfunction, sepsis-related severity scores, duration of mechanical ventilation and ICU stays, and survival information 28 days after ICU admission and at hospital discharge. The Sequential Organ Failure Assessment (SOFA) [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] were calculated using physiological and laboratory data obtained at the initial examination as a part of the routine medical workup. Blood glucose levels were measured using a blood gas analyzer, as recommended by the international sepsis guidelines [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and not using a glucometer. All glucose levels were measured before corticosteroid administration, if possible.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eDate definitions\u003c/h2\u003e \u003cp\u003ePatients were divided into two groups depending on their initial blood glucose levels: \u0026lt;70 mg/dL (hypoglycemia) or \u0026ge;\u0026thinsp;70 mg/dL (non-hypoglycemia). Although not universally defined, blood glucose levels of \u0026lt;\u0026thinsp;70 mg/dL are widely accepted as the definition of hypoglycemia [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBMI classification was made based on the definition of the Japan Society for the Study of Obesity [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]: \u0026lt;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e (low BMI), 18.5\u0026ndash;24.9 kg/m\u003csup\u003e2\u003c/sup\u003e (normal BMI), and \u0026ge;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e (high BMI). Septic shock and organ dysfunction were defined using the Sepsis-2 criteria [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The Charlson comorbidity index was classified into four groups as previously defined: 0 (none), 1\u0026ndash;2 (low), 3\u0026ndash;4 (moderate), and \u0026ge;\u0026thinsp;5 (high) points [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eOutcome\u003c/h2\u003e \u003cp\u003eThe primary outcome measure was in-hospital mortality.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics included counts (proportions) for categorical variables and medians (interquartile range, IQR) for continuous variables, as not all variables had normal distribution. Categorical variables were compared using chi-square tests, and continuous variables were compared using the Mann-Whitney U test. We performed a multivariable logistic regression analysis using in-hospital mortality as the objective variable and blood glucose level of \u0026lt;\u0026thinsp;70 mg/dL or not, three BMI category groups, age, SOFA score, and Charlson comorbidity index, as explanatory variables. To examine the heterogeneity of the impact of hypoglycemia on in-hospital mortality across each BMI category, we performed a multivariable logistic regression analysis including the interaction term between BMI category and hypoglycemia in each BMI category. Statistical significance was defined as \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, and statistical analyses were performed using JMP\u0026reg; 15 (SAS Institute Inc., Cary, NC, USA).\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":" \u003cp\u003eThe FORECAST study registered 1,184 patients. Eighty-one patients were excluded because of missing data regarding the initial blood glucose level, BMI, or survival at hospital discharge. Finally, we analyzed data from 1,103 patients with severe sepsis. The patients were divided into two groups according to blood glucose levels: 65 patients with hypoglycemia and 1,038 patients without hypoglycemia. Furthermore, patients with hypoglycemia were divided according to BMI categories: 13/1,103 (1% of all included patients) with a low BMI, 38/1,103 (2%) with a normal BMI, and 14/1,103 (1%) with a high BMI. Patients without hypoglycemia were also divided similarly: 210/1,103 (19%), 584/1,103 (53%), and 244/1,103 (22%), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003ePatient characteristics and clinical outcomes\u003c/h2\u003e \u003cp\u003ePatient characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (detailed characteristics are shown in \u003cb\u003eSupplemental Digital Content 1\u003c/b\u003e). Median patient age was 73 (64\u0026ndash;81) years, and median BMI was 21.7 kg/m\u003csup\u003e2\u003c/sup\u003e (19.0\u0026ndash;24.7). Of the 1,038 patients, 23.3% were diagnosed with diabetes mellitus before admission. The proportion of patients with pre-existing diabetes was similar between patients with and without hypoglycemia in all BMI categories. The most suspected site of infection was the lung (31.1%), followed by the abdomen (25.7%). SOFA score, APACHE II score, and lactate levels tended to be higher in patients with hypoglycemia than in those without hypoglycemia in all BMI categories.\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\u003eCharacteristics of patients classified by body mass index category and glucose levels on admission\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBMI low (n\u0026thinsp;=\u0026thinsp;223)\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\u003eBMI normal (n\u0026thinsp;=\u0026thinsp;622)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eBMI high (n\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;584)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (64\u0026ndash;81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (58.0\u0026ndash;79.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75 (67\u0026ndash;83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74 (69.5\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e73 (64\u0026ndash;82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e68 (64\u0026ndash;72.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e69 (61\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.581\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, male\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e664 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (46.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e368 (63.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.109\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e6 (42.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e151 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21.7 (19.0\u0026ndash;24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6 (14.9\u0026ndash;17.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.8 (15.2\u0026ndash;17.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.429\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.2 (19.7\u0026ndash;23.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e21.5 (19.9\u0026ndash;23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.722\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.8 (26.4\u0026ndash;31.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e27.0 (25.8\u0026ndash;30.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.123\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose (mg/dL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136 (104\u0026ndash;188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (25.5\u0026ndash;61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e133.5 (105\u0026ndash;179)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e51.5 (36\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e139 (110\u0026ndash;192)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e59 (47\u0026ndash;53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e146.5 (116.5\u0026ndash;199)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (6\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (7\u0026ndash;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (6\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11 (9\u0026ndash;14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 (6\u0026ndash;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12 (10\u0026ndash;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8 (5\u0026ndash;12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.00168\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPACHE II score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (17\u0026ndash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (20\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (17\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.433\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29 (21\u0026ndash;38.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22 (17\u0026ndash;29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e29.5 (23\u0026ndash;35.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e22 (16\u0026ndash;30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.087\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-existing diabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e257 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (15.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.975\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7 (18.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e129 (22.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e4 (28.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e82 (33.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.698\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.710\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.629\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (0\u0026ndash;3.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e684 (62.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (84.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e137 (65.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e31 (81.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e359 (61.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e12 (85.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e134 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.0238\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNumber of patients with missing data: SOFA score, 158; APACHE II score, 112\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eAPACHE, Acute Physiology and Chronic Health Evaluation; BMI, body mass index; SOFA, Sequential Organ Failure Assessment\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe clinical outcomes are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e (detailed results of outcome measures are shown in \u003cb\u003eSupplemental Digital Content 2\u003c/b\u003e). In all patients, the in-hospital and 28-day mortality rates were 253/1103 (22.9%) and 200/1093 (18.3%), respectively. The in-hospital and 28-day mortality rates were higher in patients with hypoglycemia than in those without hypoglycemia in the normal BMI group (18/38 [47.4%] vs. 119/584 [20.4%], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0001, and 16/38 [42.1%] vs. 89/577 [15.4%], \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0001, respectively). However, these rates were similar in the low and high BMI groups.\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\u003eClinical outcomes in patients with or without hypoglycemia classified by body mass index\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eBMI low (n\u0026thinsp;=\u0026thinsp;223)\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\u003eBMI normal (n\u0026thinsp;=\u0026thinsp;622)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c10\" namest=\"c9\"\u003e \u003cp\u003eBMI high (n\u0026thinsp;=\u0026thinsp;258)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1,103)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eGlucose\u003c/p\u003e \u003cp\u003e\u0026ge;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;210)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;584)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;244)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-hospital mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e253/1103 (22.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/13 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53/210 (25.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18/38 (47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e119/584 (20.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3/14 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e57/244 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.868\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28-day mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200/1093 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3/13 (23.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43/209 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.829\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16/38 (42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e89/577 (15.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.0001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3/14 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e46/242 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.823\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICU-free days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (11\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.5 (10\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (13\u0026ndash;25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17 (9.5\u0026ndash;22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19 (10\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.437\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e13 (4\u0026ndash;20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e20 (11\u0026ndash;24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of hospital stay\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (12\u0026ndash;46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (5.5\u0026ndash;40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (14\u0026ndash;45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.524\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e27 (4\u0026ndash;44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e25.5 (13\u0026ndash;47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23.5 (19\u0026ndash;52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21 (11\u0026ndash;46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.200\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eNumber of patients with missing data: 28-day mortality, 10; ICU-free days, 210\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"11\"\u003eBMI, body mass index; ICU, intensive care unit\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eInteraction between hypoglycemia and BMI category for in-hospital mortality\u003c/h2\u003e \u003cp\u003eIn the multivariate logistic regression model, hypoglycemia was not significantly associated with higher mortality in all patients (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). However, there was a significant interaction between patients with normal BMI and hypoglycemia on in-hospital mortality (OR 2.32, 95% CI 1.05\u0026ndash;5.07, \u003cem\u003ep\u003c/em\u003e value for interaction\u0026thinsp;=\u0026thinsp;0.0476), whereas there was no interaction between patients with low or high BMI and hypoglycemia (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\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\u003eOdds ratios for in-hospital mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOdds ratio\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGlucose level\u0026thinsp;\u0026lt;\u0026thinsp;70 mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.77\u0026ndash;2.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.268\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI low vs. normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.78\u0026ndash;1.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.407\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI high vs. normal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.73\u0026ndash;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.662\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI high vs. low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.56\u0026ndash;1.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.00\u0026ndash;1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0189\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.13\u0026ndash;1.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharlson Comorbidity Index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.12\u0026ndash;1.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.0001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eBMI, body mass index; CI, confidence interval; SOFA, Sequential Organ Failure Assessment\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e "},{"header":"Discussion","content":" \u003cp\u003eWe found that hypoglycemia at admission in sepsis patients was associated with high mortality in patients with normal BMI but not in those with low and high BMI. To the best of our knowledge, this is the first study to examine the association between hypoglycemia at admission and mortality in sepsis patients according to BMI categories.\u003c/p\u003e \u003cp\u003eHypoglycemia is associated with a high mortality rate in sepsis patients and critically ill patients [\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The NICE-SUGAR study demonstrated that hypoglycemia was associated with an increased risk of death, especially among patients with distributive shock [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Patients with both septic shock and hypoglycemia on the day of enrolment had a 2.5-fold higher mortality rate than those without septic shock and hypoglycemia in a multicenter observational study of sepsis patients in Japan [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe distribution of BMI in the population varies widely across countries and regions. A population-based study of adults was conducted in 200 countries, and it revealed that the proportions of high BMI (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25), normal BMI, and low BMI (BMI\u0026thinsp;\u0026lt;\u0026thinsp;18.5) were 50\u0026ndash;60%, 30%, and \u0026lt;\u0026thinsp;5%, respectively, in Western countries, and 30%, 50%, and 10\u0026ndash;20%, respectively, in East Asian countries [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Observational studies in sepsis patients of Western countries showed that the population with high BMI accounted for more than 50% and that of low BMI accounted for less than 10%, and sepsis patients with high BMI had better survival outcomes, suggesting an \u0026ldquo;obesity paradox\u0026rdquo; [\u003cspan additionalcitationids=\"CR9\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. By contrast, a study conducted in China reported that low BMI was an independent factor associated with reduced 90-day survival [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In addition, a retrospective observational study using two cohorts in Japan (including cohort of the FORECAST study) showed that patients with low BMI had a significantly higher 28-day mortality than those without low BMI [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, previous studies did not address the association between hypoglycemia and mortality in sepsis patients according to BMI categories.\u003c/p\u003e \u003cp\u003eThe mechanism by which a low BMI and high BMI were not associated with worse mortality in patients with hypoglycemia was not clear. Adipose tissue and lipoproteins are related to BMI [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e] as well as inflammation [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The amount of adipose tissue and lipoproteins may depend on host defense in patients with sepsis and hypoglycemia. Further studies should be conducted to elucidate the mechanisms underlying the biological reactions of adipose tissue and lipoproteins to hypoglycemia in sepsis patients.\u003c/p\u003e \u003cp\u003eThis study has some limitations. First, because these data were collected before the sepsis-3 criteria were published, the definition of sepsis used in this study was different from the latest definition. Second, the number of patients with hypoglycemia was too small to be assessed with sufficient statistical power. Third, all of our participants were Japanese; thus, generalizability might be limited to East Asians. Fourth, we could use few explanatory variables in the multivariate analysis because not many patients died.\u003c/p\u003e \u003cp\u003eIn conclusion, hypoglycemia at admission in sepsis patients was associated with high mortality in patients with normal BMI, but not in those with low and high BMI. This association may be used as a prognostic marker in sepsis patients. In the future, larger cohort studies are needed to confirm this finding.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank the core investigators of the FORECAST sepsis study (Appendix) for providing the dataset. We are grateful to all investigators involved in the FORECAST sepsis study for contributing to data collection and assessment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by AT and DK. Statistical analysis was reviewed by DK and HO. The first draft of the manuscript was written by AT. The manuscript was reviewed and edited by DK and SK, and all authors commented on the previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest and Source of Funding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by grants from JSPS KAKENHI [grant number JP 19H03755] for language editing. The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset of the FORECAST sepsis study is not publicly available, based on the decision by the Japanese Association for Acute Medicine.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study protocol was reviewed and approved by the ethics committee of all participant institutes in the Japanese Association for Acute Medicine (JAAM) study group, Japan. (IRB number 014\u0026ndash;0306 on Hokkaido University, the representative for FORECAST).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSinger, M. \u003cem\u003eet al.\u003c/em\u003e The third international consensus definitions for sepsis and septic shock (sepsis-3). \u003cem\u003eJAMA\u003c/em\u003e, \u003cb\u003e315\u003c/b\u003e, 801\u0026ndash;810 (2016).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRudd, K. E. \u003cem\u003eet al.\u003c/em\u003e Global, regional, and national sepsis incidence and mortality, 1990\u0026ndash;2017: analysis for the Global Burden of Disease Study. \u003cem\u003eLancet\u003c/em\u003e, \u003cb\u003e395\u003c/b\u003e, 200\u0026ndash;211 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGaieski, D. F., Edwards, J. M., Kallan, M. J. \u0026amp; Carr, B. G. Benchmarking the incidence and mortality of severe sepsis in the United States. \u003cem\u003eCrit. Care Med\u003c/em\u003e, \u003cb\u003e41\u003c/b\u003e, 1167\u0026ndash;1174 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePlummer, M. P. \u003cem\u003eet al.\u003c/em\u003e Dysglycaemia in the critically ill and the interaction of chronic and acute glycaemia with mortality. \u003cem\u003eIntensive Care Med\u003c/em\u003e, \u003cb\u003e40\u003c/b\u003e, 973\u0026ndash;980 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKushimoto, S. \u003cem\u003eet al.\u003c/em\u003e Impact of blood glucose abnormalities on outcomes and disease severity in patients with severe sepsis: an analysis from a multicenter, prospective survey of severe sepsis. \u003cem\u003ePLOS ONE\u003c/em\u003e, \u003cb\u003e15\u003c/b\u003e, e0229919 (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNICE-SUGAR Study Investigators. Hypoglycemia and risk of death in critically ill patients. \u003cem\u003eN. Engl. J. Med\u003c/em\u003e, \u003cb\u003e367\u003c/b\u003e, 1108\u0026ndash;1118 (2012).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHermanides, J. \u003cem\u003eet al.\u003c/em\u003e Hypoglycemia is associated with intensive care unit mortality. \u003cem\u003eCrit. Care Med\u003c/em\u003e, \u003cb\u003e38\u003c/b\u003e, 1430\u0026ndash;1434 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePrescott, H. C., Chang, V. W., O\u0026rsquo;Brien, J. M. Jr, Langa, K. M. \u0026amp; Iwashyna, T. J. Obesity and 1-year outcomes in older Americans with severe sepsis. \u003cem\u003eCrit. Care Med\u003c/em\u003e, \u003cb\u003e42\u003c/b\u003e, 1766\u0026ndash;1774 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSakr, Y. \u003cem\u003eet al.\u003c/em\u003e Obesity is associated with increased morbidity but not mortality in critically ill patients. \u003cem\u003eIntensive Care Med\u003c/em\u003e, \u003cb\u003e34\u003c/b\u003e, 1999\u0026ndash;2009 (2008).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePepper, D. J. \u003cem\u003eet al.\u003c/em\u003e Does obesity protect against death in sepsis? A retrospective cohort study of 55,038 adult patients. \u003cem\u003eCrit. Care Med\u003c/em\u003e, \u003cb\u003e47\u003c/b\u003e, 643\u0026ndash;650 (2019).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhou, Q. \u003cem\u003eet al.\u003c/em\u003e Impact of body mass index on survival of medical patients with sepsis: a prospective cohort study in a university hospital in China. \u003cem\u003eBMJ. Open\u003c/em\u003e, \u003cb\u003e8\u003c/b\u003e, e021979 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbe, T. \u003cem\u003eet al.\u003c/em\u003e Characteristics, management, and in-hospital mortality among patients with severe sepsis in intensive care units in Japan: the FORECAST study. \u003cem\u003eCrit. Care\u003c/em\u003e, \u003cb\u003e22\u003c/b\u003e, 322 (2018).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevy, M. M. \u003cem\u003eet al.\u003c/em\u003e 2001 SCCM/ESICM/ACCP/ATS/SIS international sepsis definitions conference. Crit. Care. Med. 31, 1250\u0026ndash;1256(2003).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBone, R. C. \u003cem\u003eet al.\u003c/em\u003e Definitions for sepsis and organ failure and guidelines for the use of innovative therapies in sepsis. The ACCP/SCCM Consensus Conference Committee. American College of Chest Physicians/Society of Critical Care Medicine. Chest. 101, 1644\u0026ndash;1655(1992).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVincent, J. L. \u003cem\u003eet al.\u003c/em\u003e Use of the SOFA score to assess the incidence of organ dysfunction/failure in intensive care units: results of a multicenter, prospective study. Working group on \u0026ldquo;sepsis-related problems\u0026rdquo; of the European Society of Intensive Care Medicine. \u003cem\u003eCrit. Care. Med\u003c/em\u003e, \u003cb\u003e26\u003c/b\u003e, 1793\u0026ndash;1800 (1998).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKnaus, W. A., Draper, E. A., Wagner, D. P. \u0026amp; Zimmerman, J. E. Apache II: a severity of disease classification system. \u003cem\u003eCrit. Care. Med\u003c/em\u003e, \u003cb\u003e13\u003c/b\u003e, 818\u0026ndash;829 (1985).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDellinger, R. P. \u003cem\u003eet al.\u003c/em\u003e Surviving sepsis campaign: international guidelines for management of severe sepsis and septic shock: 2012. \u003cem\u003eCrit. Care Med\u003c/em\u003e, \u003cb\u003e41\u003c/b\u003e, 580\u0026ndash;637 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeaquist, E. R. \u003cem\u003eet al.\u003c/em\u003e Hypoglycemia and diabetes: a report of a workgroup of the American Diabetes Association and the Endocrine Society. \u003cem\u003eJ. Clin. Endocrinol. Metab\u003c/em\u003e, \u003cb\u003e98\u003c/b\u003e, 1845\u0026ndash;1859 (2013).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eExamination Committee of Criteria for 'Obesity Disease' in Japan; Japan Society for the Study of Obesity. New criteria for \u0026ldquo;obesity disease\u0026rdquo; in. \u003cem\u003eJpn. Circ. J\u003c/em\u003e, \u003cb\u003e66\u003c/b\u003e, 987\u0026ndash;992 (2002).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang, Y., Yang, K. S., Hsann, Y. M., Lim, V. \u0026amp; Ong, B. C. The effect of comorbidity and age on hospital mortality and length of stay in patients with sepsis. \u003cem\u003eJ. Crit. Care\u003c/em\u003e, \u003cb\u003e25\u003c/b\u003e, 398\u0026ndash;405 (2010).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOami, T. \u003cem\u003eet al.\u003c/em\u003e Association between low body mass index and increased 28-day mortality of severe sepsis in Japanese cohorts. \u003cem\u003eSci. Rep\u003c/em\u003e, \u003cb\u003e11\u003c/b\u003e, 1615 (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBastien, M., Poirier, P., Lemieux, I. \u0026amp; Despr\u0026eacute;s, J. P. Overview of epidemiology and contribution of obesity to cardiovascular disease. \u003cem\u003eProg. Cardiovasc. Dis\u003c/em\u003e, \u003cb\u003e56\u003c/b\u003e, 369\u0026ndash;381 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGown, C., Birerdinc, A. \u0026amp; Younossi, Z. M. Adipose tissue as an endocrine organ. \u003cem\u003eClin. Liver. Dis\u003c/em\u003e, \u003cb\u003e18\u003c/b\u003e, 41\u0026ndash;58 (2014).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMurch, O., Collin, M., Hinds, C. J. \u0026amp; Thiemermann, C. Lipoproteins in inflammation and sepsis. I. Basic science. \u003cem\u003eIntensive Care Med\u003c/em\u003e, \u003cb\u003e33\u003c/b\u003e, 13\u0026ndash;24 (2007).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Blood glucose, body mass index, mortality, sepsis","lastPublishedDoi":"10.21203/rs.3.rs-643582/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-643582/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eWe assessed the influence of admission hypoglycemia on mortality in sepsis patients according to body mass index (BMI). We included 1,184 patients (age\u0026thinsp;\u0026ge;\u0026thinsp;16 years) with severe sepsis diagnosed using Sepsis-2 criteria. The outcome was in-hospital mortality. Using multivariate logistic regression, we examined the association between hypoglycemia and in-hospital mortality. Overall, 1,103 patients were analyzed. Patients were divided into groups according to the initial blood glucose level, i.e., \u0026lt;\u0026thinsp;70 (hypoglycemia) or \u0026ge;\u0026thinsp;70 (non-hypoglycemia) mg/dL, and BMI, i.e., \u0026lt;\u0026thinsp;18.5 (low), 18.5\u0026ndash;24.9 (normal), or \u0026ge;\u0026thinsp;25 (high) kg/m\u003csup\u003e2\u003c/sup\u003e. Hypoglycemia was noted in 65 patients, with low (n\u0026thinsp;=\u0026thinsp;13), normal (n\u0026thinsp;=\u0026thinsp;38), and high BMI (n\u0026thinsp;=\u0026thinsp;14). Hypoglycemia patients showed higher in-hospital mortality than those without in the normal BMI group but not in the low and high BMI groups. In multivariate logistic regression, hypoglycemia was non-significantly associated with higher mortality in all patients (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.268). However, there was a significant interaction between normal BMI patients and hypoglycemia on in-hospital mortality but not between low or high BMI patients and hypoglycemia (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0476). Hypoglycemia at admission in sepsis patients was associated with high mortality in normal BMI patients but not in low or high BMI patients. This association may be used as a prognostic marker in sepsis patients.\u003c/p\u003e","manuscriptTitle":"Association of body mass index and hypoglycemia with mortality rates among sepsis patients: a retrospective sub-analysis of the FORECAST Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-06-30 17:10:34","doi":"10.21203/rs.3.rs-643582/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d031777c-6653-49dc-9691-8ccdffde0316","owner":[],"postedDate":"June 30th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":5372129,"name":"Critical Care \u0026 Emergency Medicine"},{"id":5372130,"name":"Molecular Epidemiology"},{"id":5372131,"name":"Epidemiology"}],"tags":[],"updatedAt":"2021-11-08T09:29:15+00:00","versionOfRecord":[],"versionCreatedAt":"2021-06-30 17:10:34","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-643582","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-643582","identity":"rs-643582","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}