The clinical profile and symptomatology of Guillain-Barre Syndrome: a retrospective analysis

The clinical profile and symptomatology of Guillain-Barre Syndrome: a retrospective analysis | 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 The clinical profile and symptomatology of Guillain-Barre Syndrome: a retrospective analysis İsmail Ataş, Mümin Murat Yazıcı, Bünyamin Onur Harmancı, Enes Güler, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6406596/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background : The aim of the study was to evaluate the clinical profile, factors associated with mortality, and hospital outcomes of adult patients diagnosed with Guillain-Barre syndrome (GBS) in the ED and to identify the factors involved in early diagnosis. Methods : This retrospective study reviewed patients diagnosed with GBS in the ED between 2015 and 2023. GBS prognostic scoring systems were utilized, including the Medical Research Council (MRC) score at admission and discharge, the Hughes Functional Rating Scale (HFGS) for functional disability, and the modified Erasmus GBS outcome score (mEGOS). Results : The study included 98 patients. Significant differences in mEGOS, MRC, HFGS, and discharge MRC scores were observed between the living and deceased patient groups. Based on Brighton diagnostic criteria, 54.1% (n = 53) of patients were classified as level 2, 30.6% (n = 30) as level 3, and 15.3% (n = 15) as level 1. Biomarkers analysis showed significantly higher glucose, urea, neutrophil count, and the neutrophil-to-lymphocyte ratio (NLR) values (p = 0.034, p = 0.042, p = 0.014, p = 0.037, respectively) and significantly lower albumin levels (p = 0.002) in deceased patients compared to survivors. Conclusion : Neutrophil count, NLR, glucose, urea, and albumin levels, alongside scoring systems such as mEGOS, MRC, and HFGS, may be effective in determining prognosis when applied at initial presentation. Guillain-Barre Syndrome Medical Research Council Hughes Functional Rating Scale modified Erasmus GBS outcome score biomarkers Introduction Guillain Barre syndrome (GBS) is an acute-onset inflammatory polyradiculoneuropathy that progresses rapidly. While it can affect individuals of all ages, it exhibits a bimodal distribution, particularly among young adults and the elderly [ 1 ]. Its etiology involves multiple factors, including bacterial and viral pathogens, vaccines, genetic predisposition, and abnormal immune responses [ 2 ]. Pathophysiologically, autoimmune events—often triggered by infections—target the peripheral nervous system, leading to demyelination or axon damage [ 3 ]. Clinical manifestations range from motor and sensory dysfunctions to cranial nerve involvement, respiratory failure, and autonomic dysfunction, potentially progressing to life-threatening conditions [ 4 ]. The hallmark symptom is flaccid paralysis, characterized by symmetrical and increasing weakness that typically begins in the lower extremities and ascends proximally. In addition to loss of sensory and motor function, autonomic dysfunction—including cardiovascular instability, respiratory distress, and gastrointestinal dysmotility—may occur [ 5 ]. GBS is classified into subtypes based on clinical, pathophysiologic, and electrophysiologic findings. Acute inflammatory demyelinating polyradiculoneuropathy (AIDP), acute motor axonal neuropathy (AMAN), and acute motor-sensory axonal neuropathy (AMSAN) are common subtypes, although their prevalence differs regionally [ 6 ]. Identifying the subtype is crucial for assessing mortality, morbidity, and treatment strategies [ 7 ]. GBS is frequently underdiagnosed in EDs, which can significantly increase mortality [ 8 ]. While laboratory and imaging tests play a key role in diagnosis, a thorough history and physical examination remain fundamental diagnostic steps [ 9 ]. This study aimed to assess factors involved in early diagnosis by evaluating the clinical profile, mortality-related factors, and hospital outcomes of adult patients diagnosed with GBS in the ED. Methods Study design and setting The study was a retrospective review of patients who presented to the ED of a tertiary hospital between January 2015 and December 2023 with symptoms of motor, sensory or autonomic dysfunction related to GBS. Approval was obtained from the local ethics committee prior to its initiation (Date: 06.03.2025, No: 2025/81). Patient selection Clinical and radiological data were collected using the local computer-based Hospital Information Management System (HIMS) program and ED patient files. Patients were excluded if they were younger than 18 years of age, had symptoms that could be explained by an alternative diagnosis, or had missing clinical and laboratory data. The inclusion criteria, based on Brighton criteria [ 10 ], included acute or subacute flaccid paralysis involving the lower or upper extremities, peak weakness occurring between 12 hours and four weeks, and the presence of at least one of the following: hyporeflexia or areflexia in the extremities, cerebrospinal fluid (CSF) protein level > 0.45g/L with a cell count < 50 cells/µ (cytoalbuminologic dissociation), or electrophysiologic study results consistent with one of the GBS subtypes. Patients were classified according to Hadden’s criteria [ 11 ], based on electroneurophysiological studies, as AIDP, AMAN, or AMSAN. Patients with Miller-Fischer syndrome (MFS) were also included based on clinical evaluation [ 12 ]. Data collection The study form included demographic characteristics, admission symptoms and onset time, antecedent focus of infection, hospital admission within four–eight weeks prior to ED admission, electrophysiological classification, radiological characteristics, CSF profile, treatment given, area of hospitalization (clinic or intensive care unit), duration of inpatient treatment, use of mechanical ventilation, hospital outcome, laboratory findings (neutrophil-to-lymphocyte ratio [NLR], lymphocyte-to-monocyte ratio [LMR], platelet-to-lymphocyte ratio [TLR], systemic immune inflammation index, and systemic inflammation response index). It also incorporated the following GBS prognostic scoring systems: the Medical Research Council (MRC) score at admission and discharge, the Hughes Functional Grading Scale (HFGS) for assessing functional disability, and the modified Erasmus GBS outcome score (mEGOS) [ 9 , 13 , 14 ]. Statistical methods All analyses were performed using Jamovi v.1.6 software (The Jamovi Project (2021) Computer Software, version 1.6. Sydney, Australia). Categorical data are expressed as frequency (n) and percentage. Normally distributed continuous variable data are expressed as mean plus standard deviation (SD), while non-normally distributed data are presented as medians and interquartile range (IQR). Normality of distribution was assessed using the Shapiro–Wilk test. Two-group comparisons were made using either the Student’s t-test or Mann–Whitney U test, depending on the data distribution. P-values < 0.05 were considered statistically significant. Results The study included 98 patients who presented to the ED with symptoms of GBS between 2015 and 2023 and whose diagnoses were confirmed. Of these, 68.4% (n = 67) were male, with a mean age of 66.0 ± 18.3 years (range: 21–94). Of the patients, 50% (n = 49) had previously presented to the ED with symptoms such as limb or back pain before the GBS diagnosis. The median time from illness onset to hospitalization was seven days (IQR 2–10), and the most common presenting complaint was difficulty walking (52%, n = 51). A history of infection was reported in 58.2% of patients, with 21.4% having diarrhea, 18.4% having an upper respiratory tract infection, and 11.2% having a lower respiratory tract infection. The main demographic characteristics of the patients are presented in Table 1 . Table 1. The patients’ demographic data and baseline characteristics Characteristics All Patients (N=98) Gender Male, n (%) Female, n (%) 67 (68.4) 31 (31.6) Age (years), mean ± sd 66.0 ± 18.3 Comorbidities Hypertension, n (%) Diabetes, n (%) CAD, n (%) COPD, n (%) 61 (62.2) 30 (30.6) 17 (17.3) 15 (15.3) Duration of complaint before ED (days), median (IQR) 7 (2-10) Application complaint Walking difficulty, n (%) Weakness in the legs, n (%) Weakness in hands and feet n (%) 51 (52.0) 24 (24.5) 16 (16.3) History of infection Acute gastroenteritis, n (%) Upper respiratory tract infection, n (%) Lower respiratory tract infection, n (%) Urinary tract infection, n (%) Soft tissue infection, n (%) 21 (21.4%) 18 (18.4%) 11 (11.2%) 4 (4.1%) 3 (3.1%) Outcome Clinical hospitalisation, n (%) ICU hospitalisation, n (%) 94 (95.9%) 4 (4.1%) Number of days of hospitalisation, median (IQR) 5.0 (5.0-7.0) Number of ICU hospitalisation days, mean ± sd 1.92 ± 9.08 Number of patients followed up in MV, n (%) 7 (7.1) Days in MV, mean ± sd 0.90 ± 6.1 Hospital outcome Discharged, n (%) Death, n (%) 89 (90.8%) 9 (9.2%) IQR: Interquartile Range (25p, 75p), sd: standard deviation, CAD: Coronary Artery Disease , COPD: Chronic Obstructive Pulmonary Disease, ED: Emergency Department, ICU : Intensive Care Unit, MV: Mechanical Ventilator, Neurological examination in the ED revealed that 72.4% (n = 71) had only lower extremity weakness, while 27.6% (n = 27) had both upper and lower extremity weakness. Ataxia was present in 93.9% (n = 92) of patients, and limb areflexia was present in 80.6% (n = 79). Sensory dysfunction was observed in 52% (n = 51), while pharyngeal, cervical, and brachial muscle weakness was observed in 23.5% (n = 23). Bilateral facial muscle weakness was observed in 10.2% (n = 10), ophthalmoplegia in 8.2% (n = 8), and pyramidal system findings in 4.1% (n = 4). Electroneurophysiological studies were performed on all patients, with 40.8% (n = 40) classified as AIDP, 34.7% (n = 34) as AMSAN, and 20.4% (n = 20) as AMAN. Additionally, two patients were diagnosed with MFS based on clinical examination. To exclude other causes of weakness and sensory changes, all patients underwent brain computed tomography as part of their ED management. Lumbar puncture was performed on 24.5% (n = 24) of the patients, and albuminocytologic dissociation (high protein levels with a normal cell count) was observed in 20.4% (n = 20). Laboratory tests, including basic metabolic and inflammatory markers, were also conducted (Table 2 ). When biomarkers were evaluated, glucose, urea, neutrophils, and NLR were significantly higher in the deceased than in the living ( p = 0.034, p = 0.042, p = 0.014, and p = 0.037, respectively), while albumin levels were significantly lower in the deceased ( p = 0.002). Table 2 Evaluation of biomarkers according to alive and deaded patient groups Biomarkers All Patients (N = 98) Patients Alive (N = 89) Patients Deaded (N = 9) p-Value Glucose (mg/dl) , median (IQR) 121 (102–161) 118 (100–158) 153 (125–163) 0.034 Urea (mg/dl) , median (IQR) 37 (29.3–57) 37 (29–52.0) 73 (31–107) 0.042 Albumin (g/L) , mean ± sd 38.2 ± 6.53 38.82 ± 6.13 32 ± 7.50 0.002 ALT (U/L) , median (IQR) 21 (15–31) 21.0 (15–31) 27 (18–32) 0.053 AST (U/L) , median (IQR) 28 (20-36.5) 28.0 (28–35) 25 (25–37) 0.721 Sodium (mmol/L) , mean ± sd 136 ± 4.34 136 ± 4.16 136 ± 6.13 0.788 Leukocytes (103/µl) , median (IQR) 8.015 (6.390-10.673) 5.470 (6.150–1.260) 10.770 (7.840–12.700) 0.053 Neutrophils (103/µl) , median (IQR) 5.630 (4.140–7.468) 5.470 (3.990–7.110) 7.720 (6.660–9.230) 0.014 Lymphocytes (103/µl) , median (IQR) 1.645 (1.148–2.358) 1.710 (1.230–2.360) 1.520 (836 − 2.280) 0.460 Monocytes (103/µl) , median (IQR) 585 (440–817) 580 (440–740) 740 (423–954) 0.645 Platelets (103/µl) , median (IQR) 247 (195–315) 251 (199–318) 177 (145–260) 0.051 NLR , median (IQR) 3.31 (2-5.95) 3.02 (198 − 5.31) 6.33 (3.55–8.81) 0.037 LMR , median (IQR) 2.80 (1.68–4.03) 2.88 (1.75–3.98) 1.78 (1.50–6.14) 0.749 PLR , median (IQR) 155 (104–229) 155 (105–232) 173 (73.8–183) 0.597 SII , median (IQR) 791 (517–1573) 778 (516–1509) 880 (628–2741) 0.676 SIRI , median (IQR) 2.21 (1.19–4.53) 2.09 (1.17–4.21) 3.95 (1.50–6.46) 0.325 IQR : Interquartile Range (25p, 75p) , sd : standard deviation , AST : Aspartate Aminotransferase , ALT : Alanine Aminotransferase , NLR : Neutrophil Lymphocyte Ratio , LMR : Lymphocyte Monocyte Ratio , PLR : Platelet Lymphocyte Ratio , SII : Systemic Immune Inflammation Index , SIRI : Systemic Inflammation Response Index HFGS, mEGOS, and MRC (admission and discharge) scores were calculated at the time of admission to the ED, where patients were evaluated during the acute phase. Statistically significant differences were observed between living and deceased patient groups across all prognostic scoring systems (Table 3). When evaluated according to the clinical and laboratory findings required for the Brighton diagnostic criteria, 54.1% (n = 53) were classified as level 2, 30.6% (n = 30) as level 3, and 15.3% (n = 15) as level 1. However, no statistically significant difference was found between the living and deceased patient groups in terms of these criteria ( p = 0.838). Tablo 3 Evaluation of prognostic scoring systems in patient groups Score All Patients (N = 98) Patients Alive (N = 89) Patients Deaded (N = 9) p-Value mEGOS , mean ± sd 10.6 ± 0.812 10.5 ± 0.771 5.00 ± 0.707 0.001 MRCS*, mean ± sd 19.5 ± 5.75 20.4 ± 4.91 10.6 ± 5.94 0.001 MRCS” , mean ± sd 25.4 ± 5.40 26.8 ± 2.20 11.1 ± 6.94 0.001 HFGS , mean ± sd 3.7 ± 0.606 3.61 ± 0.596 5.00 ± 0.707 0.001 sd : standard deviation , mEGOS : modified Erasmus GBS Outcome Score , MRCS : Medical Research Council Score , HFGS : Hughes Functional Grading Score , * : Admission , ” : Discharge. Discussion Although GBS is a treatable condition, it is associated with both mortality and morbidity. It should be included in the differential diagnosis of patients presenting to the ED with an acute onset of neurologic deficits. However, due to the heterogeneity of its clinical presentation, diagnosing GBS can be challenging, and delays in diagnosis may lead to mortality. Therefore, scoring systems with proven efficacy in early diagnosis and prognostic determination, based on clinical and laboratory data, are used. mEGOS, MRC, HFGS, and Brighton criteria, especially in rural hospitals with limited resources, have proven effective in diagnosing GBS and identifying high-risk patient groups, thereby improving the predictability of prognosis [ 12 , 15 , 16 ]. In our retrospective study, which included data from 98 GBS patients, significant differences in prognosis and mortality were found when comparing the mEGOS, MRC, and HFG scores between the living and deceased groups. However, no statistically significant differences were observed when comparing the Brighton criteria between the groups. We believe this may be attributed to the relatively low mortality rate (9.2%) and the limited study population. There is no sensitive or specific laboratory test that can definitively diagnose GBS. However, laboratory evaluations—including complete blood count, electrolytes, renal and liver function, and thyroid stimulating hormone—are recommended to exclude other conditions in the differential diagnosis [ 17 – 19 ]. Based on the pathogenesis of the disease, neutrophils and NLR, which are simple indicators of immune function and inflammatory processes, have been linked to the incidence and severity of the disease [ 20 , 21 ]. In our study, neutrophils and NLR showed statistical significance between the living and deceased patient groups, which is important for determining prognosis and guiding treatment strategies. Additionally, among the biochemical markers checked in the ED at the time of diagnosis, elevated glucose and urea levels, along with low albumin levels, were found to be prognostically significant in the deceased patient group compared to the living patients. Furthermore, cytologic examination of CSF obtained through lumbar puncture is a useful test that may support the diagnosis of GBS. The classic finding in CSF analysis is a high protein level with a normal cell count [ 1 , 10 ]. Pathological findings consistent with GBS were observed in 20.4% of the 24.5% patients who underwent CSF examination. GBS typically presents with symmetrical, ascending flaccid paralysis, beginning in the lower extremities, along with decreased or absent reflexes. It may also involve diaphragmatic weakness or respiratory distress, which can lead to hemodynamic instability, depending on the variant [ 22 , 23 ]. In our study, the presence of symmetrical and bilateral weakness in the lower extremities (72.4%), ataxia (93.9%), sensory symptoms (52%), and areflexia (80.6%) were identified as key findings during the physical examination at the time of presentation to the ED. However, the disease can also manifest with atypical symptoms, which may lead to repeated ED visits [ 23 ]. Previous studies have shown that patients often have at least one ED visit before diagnosis [ 24 , 25 ]. In our study, 50% of the patients had visited the ED for nonspecific complaints, such as back or extremity pain, prior to diagnosis. The clinical presentation of GBS varies according to its sub-variants and shows regional differences [ 7 ]. AIDP is the most common form of GBS and classically presents with ascending weakness and decreased reflexes [ 22 , 26 ]. This variant was also the most common in our study, accounting for 40.8% of cases. Electromyographic (EMG) features are useful for distinguishing different sub-variants, but limited access to the test restricts its use. In our study, diagnostic accuracy was ensured by performing EMG on all patients, allowing for determination of the sub-variant. A history of a precipitating event, such as gastroenteritis or upper respiratory tract infection (URTI), is common prior to the onset of GBS [ 8 , 27 ]. In our study, a history of infection, particularly diarrhea and URTI, was present in 58.2% of the cases before the diagnosis. One of the primary limitations of this study is its retrospective design and the relatively small sample size. Specifically, the exclusion of patients with missing data reduced the number of patients. Conclusion Although GBS is a rare presentation, it should be considered in patients presenting to the ED with complaints of weakness and paresthesia. Laboratory values, including neutrophil count, NLR, glucose, urea, and albumin levels, in conjunction with scoring systems such as mEGOS, MRC, and HFGS, may be effective in determining prognosis. This approach allows for the early diagnosis of patients who are hemodynamically unstable or experiencing respiratory issues and helps establish an appropriate roadmap for observation. It also provides a practical method for identifying high-risk groups, particularly in hospitals located in rural areas with limited diagnostic resources. Declarations Author Contribution İ.A. writing – review & editing, writing – original draft, visualization, validation, supervision, software, resources, project administration, methodology, investigation, funding acquisition, formal analysis, data curation, conceptualization. M.M.Y. validation, supervision, project administration, methodology, conceptualization. B.O.H. supervision, project administration, investigation. E.G. software, project administration, investigation. Ö.B. writing – review & editing, validation, formal analysis, conceptualization. Acknowledgement We want to thank the Department of Emergency Medicine for their hard work on their help in data collection. References Bellanti R, Rinaldi S. Guillain-Barre syndrome: a comprehensive review. Eur J Neurol. 2024;13(8):e16365. Habib AA, Waheed W. Guillain-Barre Syndrome. Continuum (Minneap Minn). 2023;29:1327–56. Elendu C, et al. Clinical presentation and symptomatology of Guillain-Barre syndrome: A literatüre review. Med (Baltim). 2024;103(30):e38890. van Doorn PA, et al. European Academy of Neurology/Peripheral Nerve Society Guideline on diagnosis and treatment of Guillain-Barre syndrome. Eur J Neurol. 2023;30(12):3646–74. Ogawara K, et al. Axonal Guillain-Barre syndrome: relation to anti-ganglioside antibodies and Campylobacter jejuni infection in Japan. Ann Neurol. 2000;48(4):624–31. Malek E, Salameh J. Guillain-Barre Syndrome. Semin Neurol. 2019;39(5):589–95. Alanazy MH, et al. 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Electrophysiological Subtypes and Prognostic Factors of Guillain-Barre Syndrome in Northern China. Front Neurol. 2019;10:714. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 18 Apr, 2025 Editor assigned by journal 16 Apr, 2025 Submission checks completed at journal 16 Apr, 2025 First submitted to journal 08 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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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-6406596","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":440352735,"identity":"097bbc57-45f9-480c-ac69-8aafcc87ddf9","order_by":0,"name":"İsmail Ataş","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDCCA4wNQFJCBsz5AMRs7ERq4WFgY2BgnAHSwkxQC4QCa2HmATEJaeG7fbj5040aCx7++c2PP9v82ibPx8zA+OFjDm4tkucS26RzjknwSBxjM5PO7btt2MbMwCw5cxtuLQZnGNuYc9iAfjnGYMac23MbyAV6hxe/lubPOf8keOSPsX/+bNlz254YLQ3SuW0SPAbHeAykGX7cTiSoRRLoMKAXJHgMj+WUSfY23E5uY2ZsxusXvjPsjz/nfKuTkzt8fPOHH39u285vbz744SMeLaiAsQ1MNhCrHgT+kKJ4FIyCUTAKRgoAANMlTTeMMGHxAAAAAElFTkSuQmCC","orcid":"","institution":"Recep Tayyip Erdoğan University Training and Research Hospital, Department of Emergency Medicine","correspondingAuthor":true,"prefix":"","firstName":"İsmail","middleName":"","lastName":"Ataş","suffix":""},{"id":440352736,"identity":"331421b9-e093-4591-835d-fab507d9aff1","order_by":1,"name":"Mümin Murat Yazıcı","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University Training and Research Hospital, Department of Emergency Medicine","correspondingAuthor":false,"prefix":"","firstName":"Mümin","middleName":"Murat","lastName":"Yazıcı","suffix":""},{"id":440352737,"identity":"7f21ff05-61cd-475f-841b-1ad8b66b02bb","order_by":2,"name":"Bünyamin Onur Harmancı","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University Training and Research Hospital, Department of Emergency Medicine","correspondingAuthor":false,"prefix":"","firstName":"Bünyamin","middleName":"Onur","lastName":"Harmancı","suffix":""},{"id":440352738,"identity":"8e06bf99-4fbb-40fb-8989-9dcd895afede","order_by":3,"name":"Enes Güler","email":"","orcid":"","institution":"Ministry of Health Kırklareli Provincial Health Directorate, Department of Emergency Medicine","correspondingAuthor":false,"prefix":"","firstName":"Enes","middleName":"","lastName":"Güler","suffix":""},{"id":440352739,"identity":"3bae2c57-79ce-46d7-8741-13d791c9114c","order_by":4,"name":"Özlem Bilir","email":"","orcid":"","institution":"Recep Tayyip Erdoğan University Training and Research Hospital, Department of Emergency Medicine","correspondingAuthor":false,"prefix":"","firstName":"Özlem","middleName":"","lastName":"Bilir","suffix":""}],"badges":[],"createdAt":"2025-04-08 22:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6406596/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6406596/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":80280547,"identity":"2ec2df2e-254d-483a-80ab-a257ad8a8a4a","added_by":"auto","created_at":"2025-04-10 05:42:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":775515,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6406596/v1/8671e5f8-e9ef-4d9c-a7ac-b64632442b78.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The clinical profile and symptomatology of Guillain-Barre Syndrome: a retrospective analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGuillain Barre syndrome (GBS) is an acute-onset inflammatory polyradiculoneuropathy that progresses rapidly. While it can affect individuals of all ages, it exhibits a bimodal distribution, particularly among young adults and the elderly [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its etiology involves multiple factors, including bacterial and viral pathogens, vaccines, genetic predisposition, and abnormal immune responses [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Pathophysiologically, autoimmune events\u0026mdash;often triggered by infections\u0026mdash;target the peripheral nervous system, leading to demyelination or axon damage [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eClinical manifestations range from motor and sensory dysfunctions to cranial nerve involvement, respiratory failure, and autonomic dysfunction, potentially progressing to life-threatening conditions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The hallmark symptom is flaccid paralysis, characterized by symmetrical and increasing weakness that typically begins in the lower extremities and ascends proximally. In addition to loss of sensory and motor function, autonomic dysfunction\u0026mdash;including cardiovascular instability, respiratory distress, and gastrointestinal dysmotility\u0026mdash;may occur [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGBS is classified into subtypes based on clinical, pathophysiologic, and electrophysiologic findings. Acute inflammatory demyelinating polyradiculoneuropathy (AIDP), acute motor axonal neuropathy (AMAN), and acute motor-sensory axonal neuropathy (AMSAN) are common subtypes, although their prevalence differs regionally [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Identifying the subtype is crucial for assessing mortality, morbidity, and treatment strategies [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGBS is frequently underdiagnosed in EDs, which can significantly increase mortality [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While laboratory and imaging tests play a key role in diagnosis, a thorough history and physical examination remain fundamental diagnostic steps [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This study aimed to assess factors involved in early diagnosis by evaluating the clinical profile, mortality-related factors, and hospital outcomes of adult patients diagnosed with GBS in the ED.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThe study was a retrospective review of patients who presented to the ED of a tertiary hospital between January 2015 and December 2023 with symptoms of motor, sensory or autonomic dysfunction related to GBS. Approval was obtained from the local ethics committee prior to its initiation (Date: 06.03.2025, No: 2025/81).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003ePatient selection\u003c/h3\u003e\n\u003cp\u003e Clinical and radiological data were collected using the local computer-based Hospital Information Management System (HIMS) program and ED patient files. Patients were excluded if they were younger than 18 years of age, had symptoms that could be explained by an alternative diagnosis, or had missing clinical and laboratory data. The inclusion criteria, based on Brighton criteria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], included acute or subacute flaccid paralysis involving the lower or upper extremities, peak weakness occurring between 12 hours and four weeks, and the presence of at least one of the following: hyporeflexia or areflexia in the extremities, cerebrospinal fluid (CSF) protein level\u0026thinsp;\u0026gt;\u0026thinsp;0.45g/L with a cell count\u0026thinsp;\u0026lt;\u0026thinsp;50 cells/\u0026micro; (cytoalbuminologic dissociation), or electrophysiologic study results consistent with one of the GBS subtypes.\u003c/p\u003e \u003cp\u003ePatients were classified according to Hadden\u0026rsquo;s criteria [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], based on electroneurophysiological studies, as AIDP, AMAN, or AMSAN. Patients with Miller-Fischer syndrome (MFS) were also included based on clinical evaluation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eData collection\u003c/h3\u003e\n\u003cp\u003eThe study form included demographic characteristics, admission symptoms and onset time, antecedent focus of infection, hospital admission within four\u0026ndash;eight weeks prior to ED admission, electrophysiological classification, radiological characteristics, CSF profile, treatment given, area of hospitalization (clinic or intensive care unit), duration of inpatient treatment, use of mechanical ventilation, hospital outcome, laboratory findings (neutrophil-to-lymphocyte ratio [NLR], lymphocyte-to-monocyte ratio [LMR], platelet-to-lymphocyte ratio [TLR], systemic immune inflammation index, and systemic inflammation response index). It also incorporated the following GBS prognostic scoring systems: the Medical Research Council (MRC) score at admission and discharge, the Hughes Functional Grading Scale (HFGS) for assessing functional disability, and the modified Erasmus GBS outcome score (mEGOS) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eStatistical methods\u003c/h3\u003e\n\u003cp\u003eAll analyses were performed using Jamovi v.1.6 software (The Jamovi Project (2021) Computer Software, version 1.6. Sydney, Australia). Categorical data are expressed as frequency (n) and percentage. Normally distributed continuous variable data are expressed as mean plus standard deviation (SD), while non-normally distributed data are presented as medians and interquartile range (IQR). Normality of distribution was assessed using the Shapiro\u0026ndash;Wilk test. Two-group comparisons were made using either the Student\u0026rsquo;s t-test or Mann\u0026ndash;Whitney U test, depending on the data distribution. P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe study included 98 patients who presented to the ED with symptoms of GBS between 2015 and 2023 and whose diagnoses were confirmed. Of these, 68.4% (n\u0026thinsp;=\u0026thinsp;67) were male, with a mean age of 66.0\u0026thinsp;\u0026plusmn;\u0026thinsp;18.3 years (range: 21\u0026ndash;94). Of the patients, 50% (n\u0026thinsp;=\u0026thinsp;49) had previously presented to the ED with symptoms such as limb or back pain before the GBS diagnosis. The median time from illness onset to hospitalization was seven days (IQR 2\u0026ndash;10), and the most common presenting complaint was difficulty walking (52%, n\u0026thinsp;=\u0026thinsp;51). A history of infection was reported in 58.2% of patients, with 21.4% having diarrhea, 18.4% having an upper respiratory tract infection, and 11.2% having a lower respiratory tract infection. The main demographic characteristics of the patients are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eThe patients\u0026rsquo; demographic data and baseline characteristics\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" title=\"Table 1 - \" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Patients (N=98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eMale, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Female, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e67 (68.4)\u003c/p\u003e\n \u003cp\u003e31 (31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e(years), mean \u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e66.0 \u0026plusmn; 18.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Hypertension, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; Diabetes,\u0026nbsp;n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; CAD, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;COPD, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e61 (62.2)\u003c/p\u003e\n \u003cp\u003e30 (30.6)\u003c/p\u003e\n \u003cp\u003e17 (17.3)\u003c/p\u003e\n \u003cp\u003e15 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of complaint before ED\u0026nbsp;\u003c/strong\u003e(days), median (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e7 (2-10)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eApplication complaint\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eWalking difficulty, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Weakness in the legs, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Weakness in hands and feet n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e51 (52.0)\u003c/p\u003e\n \u003cp\u003e24 (24.5)\u003c/p\u003e\n \u003cp\u003e16 (16.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of infection\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAcute gastroenteritis, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Upper respiratory tract infection, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Lower respiratory tract infection, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Urinary tract infection, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Soft tissue infection, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21 (21.4%)\u003c/p\u003e\n \u003cp\u003e18 (18.4%)\u003c/p\u003e\n \u003cp\u003e11 (11.2%)\u003c/p\u003e\n \u003cp\u003e4 (4.1%)\u003c/p\u003e\n \u003cp\u003e3 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOutcome\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eClinical hospitalisation, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;ICU hospitalisation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e94 (95.9%)\u003c/p\u003e\n \u003cp\u003e4 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of days of hospitalisation,\u0026nbsp;\u003c/strong\u003emedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e5.0 (5.0-7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of ICU hospitalisation days,\u0026nbsp;\u003c/strong\u003emean\u0026nbsp;\u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e1.92 \u0026plusmn; 9.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of patients followed up in MV,\u0026nbsp;\u003c/strong\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e7 (7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDays in MV,\u0026nbsp;\u003c/strong\u003emean\u0026nbsp;\u0026plusmn; sd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e0.90 \u0026plusmn; 6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 66.1238%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital outcome\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eDischarged, n (%)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Death, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 33.8762%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e89 (90.8%)\u003c/p\u003e\n \u003cp\u003e9 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 100%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eIQR:\u003c/em\u003e\u003c/strong\u003e \u003cem\u003eInterquartile Range (25p, 75p),\u003cstrong\u003e\u0026nbsp;sd:\u003c/strong\u003e\u003c/em\u003e \u003cem\u003estandard deviation, \u003cstrong\u003eCAD:\u0026nbsp;\u003c/strong\u003eCoronary Artery Disease\u003cstrong\u003e, COPD:\u0026nbsp;\u003c/strong\u003eChronic Obstructive Pulmonary Disease,\u003cstrong\u003e\u0026nbsp;ED:\u0026nbsp;\u003c/strong\u003eEmergency Department, \u003cstrong\u003eICU\u003c/strong\u003e: Intensive Care Unit, \u003cstrong\u003eMV:\u0026nbsp;\u003c/strong\u003eMechanical Ventilator,\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\u003c/br\u003e\u003cp\u003eNeurological examination in the ED revealed that 72.4% (n\u0026thinsp;=\u0026thinsp;71) had only lower extremity weakness, while 27.6% (n\u0026thinsp;=\u0026thinsp;27) had both upper and lower extremity weakness. Ataxia was present in 93.9% (n\u0026thinsp;=\u0026thinsp;92) of patients, and limb areflexia was present in 80.6% (n\u0026thinsp;=\u0026thinsp;79). Sensory dysfunction was observed in 52% (n\u0026thinsp;=\u0026thinsp;51), while pharyngeal, cervical, and brachial muscle weakness was observed in 23.5% (n\u0026thinsp;=\u0026thinsp;23). Bilateral facial muscle weakness was observed in 10.2% (n\u0026thinsp;=\u0026thinsp;10), ophthalmoplegia in 8.2% (n\u0026thinsp;=\u0026thinsp;8), and pyramidal system findings in 4.1% (n\u0026thinsp;=\u0026thinsp;4).\u003c/p\u003e \u003cp\u003eElectroneurophysiological studies were performed on all patients, with 40.8% (n\u0026thinsp;=\u0026thinsp;40) classified as AIDP, 34.7% (n\u0026thinsp;=\u0026thinsp;34) as AMSAN, and 20.4% (n\u0026thinsp;=\u0026thinsp;20) as AMAN. Additionally, two patients were diagnosed with MFS based on clinical examination.\u003c/p\u003e \u003cp\u003eTo exclude other causes of weakness and sensory changes, all patients underwent brain computed tomography as part of their ED management. Lumbar puncture was performed on 24.5% (n\u0026thinsp;=\u0026thinsp;24) of the patients, and albuminocytologic dissociation (high protein levels with a normal cell count) was observed in 20.4% (n\u0026thinsp;=\u0026thinsp;20). Laboratory tests, including basic metabolic and inflammatory markers, were also conducted (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). When biomarkers were evaluated, glucose, urea, neutrophils, and NLR were significantly higher in the deceased than in the living (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.034, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.042, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.014, and \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037, respectively), while albumin levels were significantly lower in the deceased (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002).\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\u003eEvaluation of biomarkers according to alive and deaded patient groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBiomarkers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll Patients (N\u0026thinsp;=\u0026thinsp;98)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients Alive (N\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients Deaded (N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose (mg/dl)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (102\u0026ndash;161)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118 (100\u0026ndash;158)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153 (125\u0026ndash;163)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.034\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUrea (mg/dl)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (29.3\u0026ndash;57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (29\u0026ndash;52.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73 (31\u0026ndash;107)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.042\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAlbumin (g/L)\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e38.2\u0026thinsp;\u0026plusmn;\u0026thinsp;6.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.82\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32\u0026thinsp;\u0026plusmn;\u0026thinsp;7.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eALT (U/L)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (15\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.0 (15\u0026ndash;31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (18\u0026ndash;32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAST (U/L)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (20-36.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.0 (28\u0026ndash;35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25 (25\u0026ndash;37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.721\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSodium (mmol/L)\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136\u0026thinsp;\u0026plusmn;\u0026thinsp;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e136\u0026thinsp;\u0026plusmn;\u0026thinsp;4.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e136\u0026thinsp;\u0026plusmn;\u0026thinsp;6.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.788\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLeukocytes (103/\u0026micro;l)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.015 (6.390-10.673)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.470 (6.150\u0026ndash;1.260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.770 (7.840\u0026ndash;12.700)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNeutrophils (103/\u0026micro;l)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.630 (4.140\u0026ndash;7.468)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.470 (3.990\u0026ndash;7.110)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.720 (6.660\u0026ndash;9.230)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLymphocytes (103/\u0026micro;l)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.645 (1.148\u0026ndash;2.358)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.710 (1.230\u0026ndash;2.360)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.520 (836\u0026thinsp;\u0026minus;\u0026thinsp;2.280)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.460\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMonocytes (103/\u0026micro;l)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e585 (440\u0026ndash;817)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e580 (440\u0026ndash;740)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e740 (423\u0026ndash;954)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.645\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlatelets (103/\u0026micro;l)\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e247 (195\u0026ndash;315)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e251 (199\u0026ndash;318)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e177 (145\u0026ndash;260)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNLR\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.31 (2-5.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.02 (198\u0026thinsp;\u0026minus;\u0026thinsp;5.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.33 (3.55\u0026ndash;8.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.037\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLMR\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.80 (1.68\u0026ndash;4.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88 (1.75\u0026ndash;3.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.78 (1.50\u0026ndash;6.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.749\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePLR\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e155 (104\u0026ndash;229)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155 (105\u0026ndash;232)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173 (73.8\u0026ndash;183)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.597\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSII\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e791 (517\u0026ndash;1573)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e778 (516\u0026ndash;1509)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e880 (628\u0026ndash;2741)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSIRI\u003c/b\u003e, median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.21 (1.19\u0026ndash;4.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.09 (1.17\u0026ndash;4.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.95 (1.50\u0026ndash;6.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.325\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIQR\u003c/b\u003e: \u003cem\u003eInterquartile Range (25p, 75p)\u003c/em\u003e, \u003cb\u003esd\u003c/b\u003e: \u003cem\u003estandard deviation\u003c/em\u003e, \u003cb\u003eAST\u003c/b\u003e: \u003cem\u003eAspartate Aminotransferase\u003c/em\u003e, \u003cb\u003eALT\u003c/b\u003e: \u003cem\u003eAlanine Aminotransferase\u003c/em\u003e, \u003cb\u003eNLR\u003c/b\u003e: \u003cem\u003eNeutrophil Lymphocyte Ratio\u003c/em\u003e, \u003cb\u003eLMR\u003c/b\u003e: \u003cem\u003eLymphocyte Monocyte Ratio\u003c/em\u003e, \u003cb\u003ePLR\u003c/b\u003e: \u003cem\u003ePlatelet Lymphocyte Ratio\u003c/em\u003e, \u003cb\u003eSII\u003c/b\u003e: \u003cem\u003eSystemic Immune Inflammation Index\u003c/em\u003e, \u003cb\u003eSIRI\u003c/b\u003e: \u003cem\u003eSystemic Inflammation Response Index\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eHFGS, mEGOS, and MRC (admission and discharge) scores were calculated at the time of admission to the ED, where patients were evaluated during the acute phase. Statistically significant differences were observed between living and deceased patient groups across all prognostic scoring systems (Table\u0026nbsp;3). When evaluated according to the clinical and laboratory findings required for the Brighton diagnostic criteria, 54.1% (n\u0026thinsp;=\u0026thinsp;53) were classified as level 2, 30.6% (n\u0026thinsp;=\u0026thinsp;30) as level 3, and 15.3% (n\u0026thinsp;=\u0026thinsp;15) as level 1. However, no statistically significant difference was found between the living and deceased patient groups in terms of these criteria (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.838).\u003c/p\u003e \u003cp\u003e \u003cb\u003eTablo 3\u003c/b\u003e Evaluation of prognostic scoring systems in patient groups\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScore\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll Patients (N\u0026thinsp;=\u0026thinsp;98)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatients Alive (N\u0026thinsp;=\u0026thinsp;89)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePatients Deaded (N\u0026thinsp;=\u0026thinsp;9)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ep-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003emEGOS\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.6\u0026thinsp;\u0026plusmn;\u0026thinsp;0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMRCS*, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.5\u0026thinsp;\u0026plusmn;\u0026thinsp;5.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.4\u0026thinsp;\u0026plusmn;\u0026thinsp;4.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMRCS\u0026rdquo;\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26.8\u0026thinsp;\u0026plusmn;\u0026thinsp;2.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.1\u0026thinsp;\u0026plusmn;\u0026thinsp;6.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHFGS\u003c/b\u003e, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;sd\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.7\u0026thinsp;\u0026plusmn;\u0026thinsp;0.606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.61\u0026thinsp;\u0026plusmn;\u0026thinsp;0.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.00\u0026thinsp;\u0026plusmn;\u0026thinsp;0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003esd\u003c/b\u003e: \u003cem\u003estandard deviation\u003c/em\u003e, \u003cb\u003emEGOS\u003c/b\u003e: \u003cem\u003emodified Erasmus GBS Outcome Score\u003c/em\u003e, \u003cb\u003eMRCS\u003c/b\u003e: \u003cem\u003eMedical Research Council Score\u003c/em\u003e, \u003cb\u003eHFGS\u003c/b\u003e: \u003cem\u003eHughes Functional Grading Score\u003c/em\u003e, \u003cb\u003e*\u003c/b\u003e: \u003cem\u003eAdmission\u003c/em\u003e, \u003cb\u003e\u0026rdquo;\u003c/b\u003e:\u003cem\u003eDischarge.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAlthough GBS is a treatable condition, it is associated with both mortality and morbidity. It should be included in the differential diagnosis of patients presenting to the ED with an acute onset of neurologic deficits. However, due to the heterogeneity of its clinical presentation, diagnosing GBS can be challenging, and delays in diagnosis may lead to mortality. Therefore, scoring systems with proven efficacy in early diagnosis and prognostic determination, based on clinical and laboratory data, are used. mEGOS, MRC, HFGS, and Brighton criteria, especially in rural hospitals with limited resources, have proven effective in diagnosing GBS and identifying high-risk patient groups, thereby improving the predictability of prognosis [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. In our retrospective study, which included data from 98 GBS patients, significant differences in prognosis and mortality were found when comparing the mEGOS, MRC, and HFG scores between the living and deceased groups. However, no statistically significant differences were observed when comparing the Brighton criteria between the groups. We believe this may be attributed to the relatively low mortality rate (9.2%) and the limited study population.\u003c/p\u003e \u003cp\u003eThere is no sensitive or specific laboratory test that can definitively diagnose GBS. However, laboratory evaluations\u0026mdash;including complete blood count, electrolytes, renal and liver function, and thyroid stimulating hormone\u0026mdash;are recommended to exclude other conditions in the differential diagnosis [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Based on the pathogenesis of the disease, neutrophils and NLR, which are simple indicators of immune function and inflammatory processes, have been linked to the incidence and severity of the disease [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In our study, neutrophils and NLR showed statistical significance between the living and deceased patient groups, which is important for determining prognosis and guiding treatment strategies. Additionally, among the biochemical markers checked in the ED at the time of diagnosis, elevated glucose and urea levels, along with low albumin levels, were found to be prognostically significant in the deceased patient group compared to the living patients. Furthermore, cytologic examination of CSF obtained through lumbar puncture is a useful test that may support the diagnosis of GBS. The classic finding in CSF analysis is a high protein level with a normal cell count [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Pathological findings consistent with GBS were observed in 20.4% of the 24.5% patients who underwent CSF examination.\u003c/p\u003e \u003cp\u003eGBS typically presents with symmetrical, ascending flaccid paralysis, beginning in the lower extremities, along with decreased or absent reflexes. It may also involve diaphragmatic weakness or respiratory distress, which can lead to hemodynamic instability, depending on the variant [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our study, the presence of symmetrical and bilateral weakness in the lower extremities (72.4%), ataxia (93.9%), sensory symptoms (52%), and areflexia (80.6%) were identified as key findings during the physical examination at the time of presentation to the ED. However, the disease can also manifest with atypical symptoms, which may lead to repeated ED visits [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Previous studies have shown that patients often have at least one ED visit before diagnosis [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In our study, 50% of the patients had visited the ED for nonspecific complaints, such as back or extremity pain, prior to diagnosis.\u003c/p\u003e \u003cp\u003eThe clinical presentation of GBS varies according to its sub-variants and shows regional differences [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. AIDP is the most common form of GBS and classically presents with ascending weakness and decreased reflexes [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This variant was also the most common in our study, accounting for 40.8% of cases. Electromyographic (EMG) features are useful for distinguishing different sub-variants, but limited access to the test restricts its use. In our study, diagnostic accuracy was ensured by performing EMG on all patients, allowing for determination of the sub-variant.\u003c/p\u003e \u003cp\u003eA history of a precipitating event, such as gastroenteritis or upper respiratory tract infection (URTI), is common prior to the onset of GBS [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. In our study, a history of infection, particularly diarrhea and URTI, was present in 58.2% of the cases before the diagnosis.\u003c/p\u003e \u003cp\u003eOne of the primary limitations of this study is its retrospective design and the relatively small sample size. Specifically, the exclusion of patients with missing data reduced the number of patients.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough GBS is a rare presentation, it should be considered in patients presenting to the ED with complaints of weakness and paresthesia. Laboratory values, including neutrophil count, NLR, glucose, urea, and albumin levels, in conjunction with scoring systems such as mEGOS, MRC, and HFGS, may be effective in determining prognosis. This approach allows for the early diagnosis of patients who are hemodynamically unstable or experiencing respiratory issues and helps establish an appropriate roadmap for observation. It also provides a practical method for identifying high-risk groups, particularly in hospitals located in rural areas with limited diagnostic resources.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eİ.A. writing \u0026ndash; review \u0026amp; editing, writing \u0026ndash; original draft, visualization, validation, supervision, software, resources, project administration, methodology, investigation, funding acquisition, formal analysis, data curation, conceptualization. M.M.Y. validation, supervision, project administration, methodology, conceptualization. B.O.H. supervision, project administration, investigation. E.G. software, project administration, investigation. \u0026Ouml;.B. writing \u0026ndash; review \u0026amp; editing, validation, formal analysis, conceptualization.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe want to thank the Department of Emergency Medicine for their hard work on their help in data collection.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBellanti R, Rinaldi S. Guillain-Barre syndrome: a comprehensive review. Eur J Neurol. 2024;13(8):e16365.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHabib AA, Waheed W. Guillain-Barre Syndrome. Continuum (Minneap Minn). 2023;29:1327\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eElendu C, et al. Clinical presentation and symptomatology of Guillain-Barre syndrome: A literat\u0026uuml;re review. Med (Baltim). 2024;103(30):e38890.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan Doorn PA, et al. European Academy of Neurology/Peripheral Nerve Society Guideline on diagnosis and treatment of Guillain-Barre syndrome. Eur J Neurol. 2023;30(12):3646\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOgawara K, et al. Axonal Guillain-Barre syndrome: relation to anti-ganglioside antibodies and Campylobacter jejuni infection in Japan. Ann Neurol. 2000;48(4):624\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMalek E, Salameh J. Guillain-Barre Syndrome. Semin Neurol. 2019;39(5):589\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlanazy MH, et al. Clinical features and outcome of Guillain Barre syndrome in Saudi Arabia: a multicenter retrospective study. BMC Neurol. 2021;21(1):275.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeonhard SE, et al. Diagnosis and management of Guillain-Barr\u0026eacute; syndrome in ten steps. Nat Rev Neurol. 2019;15:671\u0026ndash;83.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evan der Berg B, et al. Guillain-Barr\u0026eacute; syndrome: pathogenesis, diagnosis, treatment and prognosis. Nat Rev Neurol. 2014;10(8):469\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFokke C, et al. Diagnosis of Guillain Barre syndrome and validation of Brighton criteria. Brain. 2014;137:33\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHadden RD, et al. Electrophysiological classification of Guillain-Barr\u0026eacute; syndrome: clinical associations and outcome. Plasma Exchange/Sandoglobulin Guillain-Barr\u0026eacute; Syndrome Trial Group. Ann Neurol. 1998;44(5):780\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCovino M, et al. Guillain-Barr\u0026eacute; syndrome from an emergency department view: how to better predict the outcome? Neurol Res. 2022;44(11):964\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Zhao Y, Wang Y. Prognostic factors of Guillain-Barr\u0026eacute; syndrome: a 111-case retrospective review. Chin Neurosurg J. 2018;4:14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePapri N, et al. Validation and adjustment of modified Erasmus GBS outcome score in Bangladesh. Ann Clin Transl Neurol. 2022;9(8):1264\u0026ndash;75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWen P, et al. Risk factors for the severity of Guillain-Barre syndrome and predictors of short-term prognosis of severe Guillain-Barre syndrome. Sci Rep. 2021;11(1):11578.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGhazanfar H, et al. Significance of Brighton Criteria in the Early Diagnosis and Management of Guillain-Barr\u0026eacute; Syndrome. Cureus. 2020;12(5):e8318.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGillicuddy DC, et al. Guillain-Barr\u0026eacute; syndrome in the emergency department. Ann Emerg Med. 2006;47(4):390\u0026ndash;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGarg SK, et al. Hyperkalemia: A rare cause of acute flaccid quadriparesis. Indian J Crit Care Med. 2014;18(1):46\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLu R, et al. Myopathy after rapid correction of hyperthyroidism: A case report and review of literature. Med (Baltim). 2020;99(3):e18878.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun, Shujun, et al. Neutrophil-to-lymphocyte ratio is a risk indicator of Guillain-Barr\u0026eacute; syndrome and is associated with severity and short-term prognosis. Heliyon. 2023;9(3):e14321.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao Y, et al. Antecedent infections in Guillain-Barre syndrome: a single-center, prospective study. Ann Clin Transl Neurol. 2019;6(12):2510\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMadden J, et al. High risk and low prevalence diseases: Guillain-Barr\u0026eacute; syndrome. Am J Emerg Med. 2024;75:90\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSun J, et al. Case Report: Early-Onset Guillain-Barre Syndrome Mimicking Stroke. Front Neurol. 2021;12:525699.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePathikonda C, et al. Disease and Patient Characteristics Contributing to Diagnostic Delays in Patients With Guillain-Barr\u0026eacute; Syndrome. Front Neurol. 2021;12:684847.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDubey D, et al. Factors contributing to delay in diagnosis of Guillain-Barr\u0026eacute; syndrome and impact on clinical outcome. Muscle Nerve. 2016;53(3):384\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKhedr EM, et al. Early electrophysiological study variants and their relationship with clinical presentation and outcomes of patients with Guillain-Barr\u0026eacute; syndrome. Sci Rep. 2023;13(1):14000.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian J, et al. Electrophysiological Subtypes and Prognostic Factors of Guillain-Barre Syndrome in Northern China. Front Neurol. 2019;10:714.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"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":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Guillain-Barre Syndrome, Medical Research Council, Hughes Functional Rating Scale, modified Erasmus GBS outcome score, biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-6406596/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6406596/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: The aim of the study was to evaluate the clinical profile, factors associated with mortality, and hospital outcomes of adult patients diagnosed with Guillain-Barre syndrome (GBS) in the ED and to identify the factors involved in early diagnosis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This retrospective study reviewed patients diagnosed with GBS in the ED between 2015 and 2023. GBS prognostic scoring systems were utilized, including the Medical Research Council (MRC) score at admission and discharge, the Hughes Functional Rating Scale (HFGS) for functional disability, and the modified Erasmus GBS outcome score (mEGOS).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: The study included 98 patients. Significant differences in mEGOS, MRC, HFGS, and discharge MRC scores were observed between the living and deceased patient groups. Based on Brighton diagnostic criteria, 54.1% (n = 53) of patients were classified as level 2, 30.6% (n = 30) as level 3, and 15.3% (n = 15) as level 1. Biomarkers analysis showed significantly higher glucose, urea, neutrophil count, and the neutrophil-to-lymphocyte ratio (NLR) values (p = 0.034, p = 0.042, p = 0.014, p = 0.037, respectively) and significantly lower albumin levels (p = 0.002) in deceased patients compared to survivors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Neutrophil count, NLR, glucose, urea, and albumin levels, alongside scoring systems such as mEGOS, MRC, and HFGS, may be effective in determining prognosis when applied at initial presentation.\u003c/p\u003e","manuscriptTitle":"The clinical profile and symptomatology of Guillain-Barre Syndrome: a retrospective analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-10 05:34:07","doi":"10.21203/rs.3.rs-6406596/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-18T10:57:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-16T23:10:08+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-16T23:09:15+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neurology","date":"2025-04-08T22:51:02+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d9c5284c-1e86-4b98-8b72-d59b7f7552c2","owner":[],"postedDate":"April 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-06-14T23:08:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-10 05:34:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6406596","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6406596","identity":"rs-6406596","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}