Archives of Academic Emergency Medicine. 2022; 10(1): e10 OR I G I N A L RE S E A RC H Clinical, Laboratory and Imaging Characteristics of Hos- pitalized COVID-19 Patients with Neurologic Involvement; a Cross-Sectional Study Ali Zare Dehnavi1, Mohammadreza Salehi2, Mehran Arab Ahmadi3, Mohammad Hossein Asgardoon4, Farzad Ashrafi5, Nasrin Ahmadinejad3, Atefeh Behkar4, Ramin Hamidi Farahani6, Hassan Hashemi3, Abbas Tafakhori7, Hamze Shahali8, Mohammad Rahmani7, Alireza Ranjbar Naeini1∗ 1. Department of Neurology, School of Medicine, AJA University of Medical Sciences, Tehran, Iran. 2. Infectious Diseases and Tropical Medicines Department, Tehran University of Medical Sciences, Tehran, Iran. 3. Advanced Diagnostic and Interventional Radiology Research Center, Tehran University of Medical Sciences, Tehran, Iran. 4. School of Medicine, Tehran University of Medical Sciences, Tehran, Iran. 5. Functional Neurosurgery Research Center, Shohadaye Tajrish Neurosurgical Center of Excellence, Shahid Beheshti University of Medical Sciences, Tehran, Iran. 6. Department of Infectious Disease, AJA University of Medical Sciences, Tehran, Iran. 7. Department of Neurology, School of Medicine, Imam Khomeini Hospital, Tehran University of Medical Sciences, Tehran, Iran. 8. Department of Aerospace and Sub Aquatic Medicine, AJA University of Medical Sciences, Tehran, Iran. Received: December 2021; Accepted: December 2021; Published online: 30 January 2022 Abstract: Introduction: Although neurologic involvement and neuroimaging abnormalities have been frequently identi- fied in COVID-19 patients, the underlying factors remain unclear. In this study, we assessed the association of the neurological manifestations and neuroimaging features of hospitalized COVID-19 patients with their clin- ical, laboratory, and imaging characteristics. Methods: This multicenter cross-sectional study was conducted between September 2020 and March 2021 at two large academic hospitals in Tehran, Iran. We used census sam- pling from medical records to enroll hospitalized patients with a positive COVID-19 Polymerase chain reaction (PCR) test who underwent brain imaging due to presenting any acute neurologic symptom during hospital stay. Results: Of the 4372 hospitalized patients with COVID-19, only 211 met the inclusion criteria (35.5% with severe infection). Central nervous system and psychiatric manifestations were significantly more common in severe cases (p ≤ 0.044). Approximately, 30% had a new abnormality on their neuroimaging, with ischemic (38/63) and hemorrhagic (16/63) insults being the most common. The most frequent reasons that provoked cranial imaging were headache (27%), altered consciousness (25.6%), focal neurologic signs (19.9%), and delirium (18%). Analy- sis revealed a positive correlation for age, neutrophilia, lymphopenia, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) with the emergence of neuroimaging abnormalities (p ≤ 0.018). In addition, patients with new neuroimaging abnormalities had a significantly higher lung CT score than those without any patho- logic findings (11.1 ± 4.8 vs. 5.9 ± 4.8, p < 0.001). Conclusion: Approximately 30% of the study population had various acute neuroimaging findings. The lung CT score, neutrophil count, and age were strong predictors of acute neuroimaging abnormalities in hospitalized COVID-19 patients. Keywords: COVID-19; Neurology; Neurologic Manifestations; Neuroimaging; Tomography, X-ray computed; Magnetic Resonance Imaging; Risk Factors Cite this article as: Zare Dehnavi A, Salehi M, Arab Ahmadi M, Asgardoon M H, Ashrafi F, Ahmadinejad N, Behkar A, Hamidi Fara- hani R, Hashemi H, Tafakhori A, Shahali H, Rahmani M, Ranjbar Naeini A. Clinical, Laboratory and Imaging Characteristics of Hos- pitalized COVID-19 Patients with Neurologic Involvement; a Cross-Sectional Study. Arch Acad Emerg Med. 2022; 10(1): e10. https://doi.org/10.22037/aaem.v10i1.1507. ∗Corresponding Author: Alireza Ranjbar naeini; AJA University of medical sci- ences, Etemad zadeh street, Fatemi-Gharbi Street, Tehran, Iran. / Postal Code: 1411718541, E-mail: a.ranjbar.naeini@ajaums.ac.ir, Tell: 021- 86096350, OR- CID: http://orcid.org/0000-0002-3150-6093. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Zare Dehnavi et al. 2 1. Introduction COVID-19 has been declared a public health emergency of international concern by the World Health Organization (WHO)(1). According to WHO statistics, to date (December 20, 2021), this disease has infected roughly 272 million peo- ple worldwide and has led to more than 5 million deaths (2). According to WHO statistics, Iran is one of the top 20 na- tions with the highest prevalence of COVID-19, with approx- imately 6.2 million individuals infected and 130,000 deaths documented so far (December 20, 2021) (2). COVID-19 can have a variety of clinical manifestations, from asymptomatic to death (3). With the increase in COVID-19 cases globally, many extra-pulmonary manifestations of this disease, such as neurologic ones, have been documented (3, 4). Differ- ent investigations have found that the prevalence of at least one new-onset neurological manifestation linked to COVID- 19 infection is highly variable, ranging from around 10% to more than 80% (5-7). In addition, neuropsychiatric prob- lems such as delirium have been frequently documented in hospitalized patients, and linked to a higher mortality rate in COVID-19 cases (8, 9). Several studies have also documented neuroimaging abnormalities in patients with COVID-19, including ischemic and hemorrhagic infarction, cerebral venous thrombosis, demyelinating disorders such as acute disseminated encephalomyelitis (ADEM), menin- gitis, encephalomyelitis, acute hemorrhagic necrotizing en- cephalopathy (ANE), and hemorrhagic posterior reversible encephalopathy syndrome (PRES)(4, 10-12). Due to the neurological symptoms that emerge through- out the disease period, the potential effects of SARS-COV- 2 on the nervous system has attracted remarkable atten- tion, and several possible mechanisms of neurological in- jury have been postulated (13). This virus can affect the central nervous system via olfactory nerves or, enter brain cells by binding to angiotensin-converting enzyme-2 (ACE- 2) or cause neuroinflammation following a cytokine storm (3, 14). COVID-19 can affect the central nervous system, periph- eral nervous system, and musculoskeletal system, leading to various neurological manifestations including headache, anosmia, ageusia, dizziness, altered consciousness, myalgia, myelopathy, encephalopathy, meningitis, seizure, syncope, hemorrhage, and stroke (15, 16). Despite the rapidly growing literature on this subject, corre- lations between neurological symptoms and/or neuroimag- ing findings in COVID-19 and other variables are still mostly unknown. Only a few studies have investigated the as- sociation between neurological symptoms and other vari- ables. Our objective in this study is to evaluate COVID-19- related neurological and neuroimaging findings in hospital- ized patients, while investigating their relationship with var- ious clinical, laboratory, and lung CT score characteristics. 2. Methods 2.1. Study design and setting This cross-sectional study was conducted between Septem- ber 22, 2020 and March 30, 2021 at Imam Khomeini Hos- pital Complex and Shohadaye Tajrish Medical Center in Tehran, Iran. We used the STROBE checklist as the re- porting guideline for this study. This was a retrospective study and all admission, discharge, diagnostic, and thera- peutic decisions were made based on the latest version of the national COVID-19 protocol during the study, and we did not interfere with the patient’s diagnostic process and didn’t charge the patient or the system anything. The study pro- tocol was approved by the ethics committee of AJA Univer- sity of Medical Sciences, receiving the ethics code number (IR.AJAUMS.REC.1399.163). 2.2. Study population All adult (≥18 years old) hospitalized COVID-19 patients with positive real-time reverse transcription-polymerase chain re- action (RT -PCR) test and a neuroimaging study (including brain and/or spine imaging) following the emergence of any acute neurologic manifestation during hospital stay were in- cluded in the study. Exclusion criteria were: (a) known his- tory of previous neurological disorders; (b) previous neu- roimaging abnormalities; (c) neurologic manifestation with non-COVID-19 etiology; and (d) incomplete medical records, which failed to meet the requirements for our checklist. Acute neurologic manifestations included: headache, dizzi- ness, altered consciousness, seizure, any focal neurologic symptoms, delirium, psychosis, and any other type of neu- ropathy. 2.3. Outcomes and measurements A checklist was designed and developed to extract patients’ data. The collected data included demographic character- istics (age, gender, and underlying disease), clinical features (degree of severity on admission (measured using American Thoracic Society guidelines for community-acquired pneu- monia (17), severe or non-severe), outcome (death or dis- charge), neurologic/psychiatric manifestations, and indica- tion for neuroimaging), initial laboratory data (included a complete blood cell count (CBC), and assessment of renal function, C - reactive protein (CRP), erythrocyte sedimenta- tion rate (ESR), creatine kinase (CK), and lactate dehydroge- nase (LDH) according to the clinical care needs of the pa- tient), chest CT scan, and neuroimaging findings. All neu- rological symptoms in this study were evaluated by an ex- pert neurologist after suspicion of a clinician during daily routine practice in the mentioned centres. Neurologic man- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 3 Archives of Academic Emergency Medicine. 2022; 10(1): e10 Figure 1: (a, b, c) Acute infarct in posterior cerebral artery (PCA) territory with restriction on diffusion-weighted magnetic resonance imaging (DWI) in a 53-year-old female with COVID-19 on the ninth day of admission; (d) hyper dense materials in brain sulci more prominent on left peritoneal lobe in favor of Subarachnoid hemorrhage (SAH). Figure 2: (a, b) Large hyper dense heterogeneous lesion in right temporal lobe with peripheral edema, more evaluated with brain magnetic resonance imaging/venography (MRI/MRV ), which showed abnormal signal in right sigmoid sinus compatible with cerebral venous throm- bosis; (c) T2 Flair images in a 39-year-old female with COVID-19 shows some hyper intense predominantly subcortical and deep white matter lesions without periventricular and corpus callosum involvement suggestive of acute disseminated encephalomyelitis (ADEM). ifestations were divided into three groups: central nervous system (CNS) manifestations (dizziness, headache, impaired consciousness, acute cerebrovascular disease, ataxia, and seizure), peripheral nervous system (PNS) manifestations (taste impairment, smell impairment, vision impairment, and nerve pain), and acute psychiatric manifestations (psy- chosis and delirium). Both neurological and psychiatric symptoms were extracted from the consultation notes of ex- perienced neurologists and psychiatrists. Acute cerebrovas- cular disorders including ischemic or hemorrhagic insults were diagnosed by clinical symptoms and brain imaging. Seizure was diagnosed based on clinical symptoms at the time of presentation. Indications for neuroimaging were also extracted from medical records and were categorized into six groups: 1) focal neurologic signs (including stroke, tran- sient ischemic attack (TIA) and all possible forms); 2) altered consciousness / reduced GCS; 3) delirium; 4) headache; 5) seizure; and 6) miscellaneous. 2.4. Image acquisition and interpretation We obtained all the images in our study as per standard of care protocols. 1.5-T scanners (Siemens Avanto, Germany) with standardized protocols were utilized for brain and spine magnetic resonance imaging (MRI) scans. All CT and MRI images were initially reviewed by two experienced neurora- diologists (each having at least ten years of neuroradiology experience), and any disagreements were settled by consen- sus. All available chest CT scans were evaluated for CT lung sever- ity score via lobar based assessment (18). Each of the five lung lobes was subjectively graded from 0 to 5 (0, no involve- ment; 1, involvement<5%; 2, involvement 6–25%; 3, involve- ment 26–50%; 4, involvement 51–75%; 5, involvement>75%) in lobar based evaluation. The total score was the sum of the individual lobar scores and ranged from 0 to 25. All neu- roimaging was analysed for the following characteristics: 1) ischemic insults; 2) haemorrhagic insults; 3) leptomeningeal or cranial nerves enhancement; 4) cerebral venous throm- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Zare Dehnavi et al. 4 Figure 3: Distribution of neuroimaging findings based on neuroimaging indications. CVT: cerebral venous thrombosis. bosis; 5) acute encephalopathy; 6) white matter involvement and any other new abnormal findings. 2.5. Statistical analysis All statistical analyses were conducted using SPSS version 20. Mean and standard deviation were used for reporting normally distributed quantitative variables; Median and in- terquartile range (IQR) were used for reporting quantitative variables that were not normally distributed, and frequency (percentage) was used to report categorical variables. Independent sample t-test or Mann Whitney test was used for comparing two quantitative groups based on the result of Shapiro-Wilks for normality. Chi square test, and if needed Fisher’s exact test was used to evaluate the association be- tween two categorical variables. We also performed mul- tivariate binary logistic regression analysis on factors that significantly correlated with neuroimaging abnormality. P- values < 0.05 were considered statistically significant. 3. Results 3.1. Demographic, clinical and laboratory char- acteristics During the study period, a total of 4372 hospitalized pa- tients with SARS-CoV-2 infection were identified. Of these, 211 patients met our inclusion criteria (52.6% male). Their mean age was 60.7 (standard deviation (SD) =15.8) years (age range, 18-94 years). Based on American Thoracic Society guidelines for community-acquired pneumonia, 75 (35.5%) of cases were categorized as severe COVID-19 infections and 136 (64.5%) of them were non-severe. Patients’ characteris- tics are presented in Table 1. 84.4%, 19.4%, and 35.1% of the patients showed at least one CNS, PNS, and neuropsychiatric manifestation, respectively. CNS findings were the most prevalent neurologic symptoms overall, with a significantly higher prevalence in the severe group (93.3% vs. 80.1%, p = 0.011). The most frequently recorded CNS man- ifestations were: headache (40.3%), reduced consciousness (36%), and focal neurologic symptoms (18%). Altered con- sciousness, focal neurologic findings, and seizures were more prevalent in severe infections compared to non-severe infec- tions; headache was significantly higher in non-severe infec- tions (29.3% vs. 46.3%, p = 0.016). Neuropsychiatric mani- festations were also fairly common, with a total prevalence of around 35%, and were significantly associated with in- fection severity (severe (44.0%) vs. non-severe (30.1%), p = 0.044). PNS manifestations were the least common among these three categories, with an overall prevalence of about 20% and no remarkable difference between severe and non- severe groups. In the PNS group, 2 cases were also diagnosed with Guillain-Barre syndrome. Clinical manifestations of pa- tients are detailed in Table 1. In the comparison of various factors between severe and non-severe cases, patients with severe infection were signif- icantly older (64.5±14.2 vs. 58.6±16.4, p = 0.010), and had a higher mortality rate (p <0.001). In addition, past medical history of hypertension (54.7% vs. 39.7%, p = 0.037) also as- sociated with severity. However, no other difference was ob- served between these two groups. Regarding laboratory tests, patients with a severe infection had a higher inflammatory response, including higher neutrophil counts, lower lympho- cyte counts, increased C-reactive protein levels, elevated ery- throcyte sedimentation rate, and higher lactate dehydroge- nase levels (p ≤ 0.010) compared to those with non-severe infection. During the study, 13 patients underwent lumbar This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 5 Archives of Academic Emergency Medicine. 2022; 10(1): e10 Table 1: Clinical and laboratory findings of patients based on severity of infection Characteristics Total (N= 211) Severity of infection P Severe n=75 Non-severe n=136 Age (year) 60.7±15.8 64.5±14.2 58.6±16.4 0.010 Neuroimaging abnormality 63(29.9) 39(52) 24(17.6) <0.001 Gender Male 111(52.6) 39 (52) 72(52.9) 0.896 Female 100 (47.4) 36 (48) 64(47.1) Comorbidities Hypertension 95(45) 41(54.7) 54(39.7) 0.037 Diabetes mellitus 81(38.4) 26(34.7) 55(40.4) 0.409 Heart disease 51(24.2) 17(22.7) 34(25.0) 0.705 COPD 10(4.7) 4(5.3) 6(4.4) 0.763 CKD 14(6.6) 8(10.7) 6(4.4) 0.081 Liver disease 7(3.3) 3(4.0) 4(2.9) 0.681 Malignancy 18(8.5) 8(10.7) 10(7.4) 0.409 Tobacco smoking 26(12.3) 9(12.2) 17(12.5) 0.916 Outcome Discharged 158(74.9) 38(50.7) 120(88.2) <0.001 Expired 53(25.1) 37(49.3) 16(11.8) CNS Total 179(84.4) 70(93.3) 109(80.1) 0.011 Dizziness 33(15.7) 15(20) 18(13.2) 0.195 Headache 85(40.3) 22(29.3) 63(46.3) 0.016 LOC 76(36.0) 46(61.3) 30(22.1) <0.001 Ataxia 22(10.4) 9(12.0) 13(9.6) 0.579 Seizure 11(5.2) 9(12.0) 2(1.5) 0.001 Focal neurologic findings 38(18.0) 23(30.7) 15(11.0) <0.001 Encephalopathy 4(1.9) 3(4.0) 1(0.7) 0.096 PNS Taste impairment 23(10.9) 3(4.0) 20(14.7) 0.017 Smell impairment 24(11.4) 3(4.0) 21(15.4) 0.012 Visual impairment 10(4.7) 5(6.7) 5(3.7) 0.328 Guillain-Barre syndrome 2(0.9) 1(1.3) 1(0.7) 0.668 Psychiatric Total 74(35.1) 33(44.0) 41(30.1) 0.044 Laboratory WBC (cells /µL) 10219±4932 10930±6344 9827±3917 0.174 Neutrophil (cells /µL) 7904±4353 9271±5569 7150±3295 0.003 Lymphocyte (cells /µL) 1586±963 933±643 1945±921 <0.001 Platelet (cells /µL) 235004±114506 212413±102995 247463±118935 0.033 ESR (mm/hr) 43.0±33.1 62.1±26.9 32.4±31.4 <0.001 C-reactive protein (mg/L) 37.4±29.0 55.4±23.9 28.0±27.3 <0.001 CPK (U/L) 151.1±345.9 192.8±183.7 128.6±406.3 0.001 Lactate dehydrogenase (U/L) 543.2±436.9 661.3±585.4 478.7±313.7 0.01 Blood urea nitrogen (mg/dL) 56.3±49.2 70.8±53.1 48.3±45.2 0.002 Creatinine (mg/dL) 1.5±1.0 1.6±1.1 1.3±0.9 0.075 CSF High WBC (cells/mm3 ) 4/13 —- —- Increased Protein (mg/dL) 5/13 —- —- Data presented as mean ± standard deviation (SD) or number (%). ESR: Erythrocyte sedimentation rate; LOC: loss of consciousness; CPK: Creatine phosphor Kinase; WBC: White blood cell; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease. puncture and their cerebrospinal fluid findings are shown in Table 1. 3.2. Neuroimaging findings In the study population, 160 (75.8%) were examined using brain CT, 5 (2.4%) underwent brain and/or spine MRI, and 46 (21.8%) underwent both CT and MRI. Apart from changes commonly found in elderly patients, neuroimaging indicated no major abnormalities in 148 (70.1%) participants. Abnor- mal findings were seen in 63 (29.9%) cases, with the rate of abnormality being significantly higher in patients with severe COVID-19 infection (52 % (severe) vs. 17.6% (non-severe), p < 0.001). The main neurologic imaging hallmark was acute ischemic infarcts, found in 38 (18%) of the 211 individuals. Of these, 35 (92%) had territorial infarction and 3 (8%) had non-territorial infarcts. Ischemia in the territory supplied by the middle cerebral artery (MCA) (27/35, 77%) was the most prevalent among territorial infarcts. The rest included: 3 posterior cerebral artery (PCA), 1 anterior cerebral artery (ACA), 2 in- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Zare Dehnavi et al. 6 Table 2: Summary of patients’ neuroimaging (computed tomogra- phy scan or magnetic resonance imaging) findings Variables Values n (%) Indication for neuroimaging Headache 57 (27.0) Altered consciousness 54 (25.6) Focal neurologic signs 42 (19.9) Delirium 38 (18.0) Seizure 11 (5.2) Miscellaneous 9 (4.3) Ischemic insult Territorial 35 (16.6) Non-territorial 3 (1.4) Hemorrhagic insult Large intracranial and intraventricular 5 (2.4) Microhemorrhage 8 (3.8) Subarachnoid hemorrhage (SAH) 3(1.4) Territory of ischemic insult Middle cerebellar artery (MCA) 27(12.8) Posterior cerebellar artery (PCA) 5(2.4) Anterior cerebellar artery (ACA) 2(0.9) Infratentorial 3(1.4) Other findings Acute encephalopathy 2 (0.9) Leptomeningeal enhancement 1 (0.5) Pituitary apoplexy 1(0.5) Cranial nerves 0 (0.00) Cerebral venous thrombosis (CVT) 7 (3.3) Transverse myelitis 1 (0.5) Demyelination (white matter involvement) 1 (0.5) fratentorial, 1 PCA+ACA, and 1 PCA +infratentorial (figure 1). Intracranial hemorrhages (ICHs) were the second most com- mon finding (16/211), with micro-hemorrhages being the most common (8/16, 50%), followed by 5 large cranial hem- orrhages and 3 cases of subarachnoid hemorrhage (SAH) (fig- ure 1). Of these, one was a 27-year-old female with no re- markable past medical history surveyed with complaints of severe headache and altered mental status approximately one week after the beginning of COVID-19 symptoms who underwent brain CT and MRI. Cranial imaging revealed brain edema and a 12×9×8mm mass in the left aspect of the pitu- itary fossa with a hemorrhagic appearance suggestive of pi- tuitary adenoma apoplexy. Seven cases were diagnosed with cerebral venous thrombo- sis (CVT), one of which had superior sagittal sinus throm- bosis accompanied by leptomeningeal enhancement. An- other case was a 66-year-old man with hypertension, clas- sified as a severe infection, who underwent cranial imaging due to decreased consciousness and seizure. His brain MRI showed an abnormal signal area with hemorrhagic change in the right temporal lobe and an abnormal signal in the right sigmoid sinus favoring venous infarct due to dural venous si- nus thrombosis. In MRV (Magnetic Resonance Venography), transverse and sigmoid sinus was not seen, and abnormal signals in T2/W sequences consistent with venous thrombo- sis were present (figure2). Details of neuroimaging charac- teristics are summarized in Table 2. 3.3. Neuroimaging indications Among reasons for undergoing imaging, the most common indications were headache (27%), impaired mental status (25.6%), and focal neurologic signs (19.9%) (Table2). Indi- cations for neuroimaging matched with neuroimaging char- acteristics are presented in figure 3. Most of the patients with headache (52/57, 91%) and delirium (32/38, 84%) had no abnormal findings on neuroimaging, but most of those who had seizures (7/11, 64%) had pathologic findings on neuroimaging. Most ischemic or hemorrhagic insults were seen among patients who underwent neuroimaging due to altered consciousness or focal neurology (42/55, 76%). On the other hand, all CVT cases were detected in people who had headaches and/or seizures. 3.4. Association of neuroimaging with clinical, laboratory features, and lung CT score Table 3 presents the characteristics of patients with and with- out neuroimaging abnormalities. We found that individuals with abnormal findings in neuroimaging studies were signif- icantly older (p = 0.009) and had a higher level of ESR, CRP, and neutrophil count (p ≤ 0.018). The analysis also revealed that chest CT score of patients with COVID-19 who had new abnormalities on neuroimaging was significantly higher than those who didn’t have any pathologic neuroimaging findings (mean CT score±SD, 11.1±4.8 vs. 5.9±4.8, p < 0.001). How- ever, no other related factor was detected. 3.5. Predictors of neuroimaging abnormality The multivariate logistic regression on the factors influenc- ing neuroimaging abnormality is presented in Table 4. This analysis showed that age (B=0.041, SE=0.013, Exp(B)=1.042, p = 0.002), neutrophil count (B=0.000, SE=0.000, Exp(B)=1, p = 0.039) and lung CT Score (B=-0.181, SE=0.045, Exp(B)=0.834, p = 0.000) were strong predictors of neuroimaging abnormal- ity. However, ESR, CRP, and lymphocyte count showed no sig- nificant prediction ability for neuroimaging abnormality (p ≥ 0.116). 4. Discussion In this study, we surveyed hospitalized patients with COVID- 19-related neurologic symptoms requiring neuroimaging, fo- cusing on their clinical, laboratory, and chest CT scan charac- teristics. Our patients had a wide range of neurologic symp- toms as well as neuroimaging indications and findings. We This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 7 Archives of Academic Emergency Medicine. 2022; 10(1): e10 Table 3: Comparing the patients’ characteristics between cases with and without acute neuroimaging abnormality Characteristics Total (n= 211) Neuroimaging abnormality P With n=63 Without n=148 Age (years) Mean ± SD 60.7 ± 15.8 56.3 ± 16.1 62.6 ± 15.4 0.009 Gender Male 111 (52.6) 28 (44.4) 83 (56.1) 0.121 Female 100 (47.4) 35 (55.6) 65 (43.9) Comorbidities Hypertension 95 (45.0) 30 (47.6) 65 (43.9) 0.621 Diabetes 81 (38.4) 22 (34.9) 59 (39.9) 0.499 Heart disease 51 (24.2) 13 (20.6) 38 (25.7) 0.434 COPD 10 (4.7) 1 (1.6) 9 (6.1) 0.160 Chronic kidney disease 14 (6.6) 6 (9.5) 8 (5.4) 0.271 Liver disease 7 (3.3) 0 (0.00) 7 (4.6) 0.079 Malignancy 18 (8.5) 4 (6.3) 14 (9.5) 0.459 Tobacco smoking 26 (12.3) 10 (15.9) 16 (10.8) 0.306 Outcome Discharged 158 (74.9) 42 (66.7) 116 (78.4) 0.073 Expired 53 (25.1) 21 (33.3) 32 (21.6) Laboratory findings WBC (cells/µL) 10219±4932 11090±5806 9849±4480 0.094 Neutrophil (cells /µL) 7904 ± 4353 9158 ± 5094 7371 ± 3894 0.006 Lymphocyte (cells /µL) 1586 ± 963 1238 ± 714 1733 ± 1017 <0.001 Platelet (cells /µL) 235004±114506 247349±105979 229750±117901 0.308 ESR (mm/hr) 43.0 ± 33.1 52.7 ± 27.5 39.0 ± 34.3 <0.001 CRP (mg/L) 37.4 ± 29.0 44.3±26.3 34.4 ± 29.7 0.018 CPK (U/L) 151.1 ± 345.9 214.7±592.2 121.5 ± 107.3 0.235 LDH (U/L) 543.2 ± 436.9 518.1±358.0 554.0 ± 467.5 0.632 BUN (mg/dL) 56.3 ± 49.2 50.0±37.3 59.0 ± 53.4 0.166 Creatinine (mg/dL) 1.5 ± 1.0 1.2 ± 0.6 1.5 ± 1.1 0.027 CT lung severity score (0-25) Mean ± SD 7.4 ± 5.3 11.1 ± 4.8 5.9 ± 4.8 <0.001 Data presented as mean ± standard deviation (SD) or number (%). WBC: White blood cell; CT: computed tomography scan; ESR: Erythrocyte sedimentation rate; CRP: C-reactive protein; CPK: Creatine Phosphokinase; LDH: Lactate dehydrogenase; BUN: Blood urea nitrogen; COPD: Chronic obstructive pulmonary disease. Table 4: The multivariate binary logistic regression of the potential factors predicting neuroimaging abnormality Parameters B Standard error EXP (B) P value Constant -0.175 0.954 0.839 0.854 Age 0.041 0.013 1.042 0.002 Neutrophil 0.000 0.000 1.000 0.039 Lymphocyte 0.000 0.000 1.000 0.116 Erythrocyte sedimentation rate (ESR) -0.006 0.009 0.994 0.486 C reactive protein (CRP) 0.004 0.010 1.004 0.685 Creatinine 0.369 0.318 1.446 0.246 CT lung severity score -0.181 0.045 0.834 0.000 CT: computed tomography. discovered that nearly 30% of COVID-19 patients with neuro- logical involvement had an abnormality in their neuroimag- ing, with the most commonly reported abnormality being acute ischemic infarcts, followed by ICH. Analysis showed that the emergence of acute neuroimaging findings was re- lated to a higher lung CT severity score as well as age, neu- trophil count, lymphocyte count, ESR, and CRP level. Mul- tivariate logistic regression on the factors influencing neu- This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem A. Zare Dehnavi et al. 8 roimaging abnormality identified age, neutrophil count, and lung CT score as strong predictors of new abnormal neu- roimaging findings. We also found that being old; having a past medical history of HTN, having a CNS manifestation, and having neuropsychiatric symptoms are associated with disease severity. Patients with hypertension in our study were more likely to have severe COVID-19 infection; similar to the findings of several previous papers (19-22) which found that hyperten- sion is related to a greater risk of mortality. So, this underlying condition should be considered by clinicians as a predictor of progression of COVID-19 to severe status and poor outcome. Patients with severe infection were found to be older. Accord- ing to some studies (19, 21, 22), older patients had a greater mortality rate. Patients with abnormal neuroimaging were also found to be older, which is consistent with the findings of Chen et al., who reported that age is associated with acute cerebrovascular events in COVID-19 patients (20). This is im- portant because in elderly patients with COVID-19, who have nonspecific symptoms of neurological involvement, the like- lihood of neurological involvement should always be consid- ered, and the threshold for neurological imaging should be lower. However, in contrast to some investigations that found a higher prevalence of severe cases in men, no gender differ- ence was observed between these two groups in our study (23-25). CNS manifestations were shown to be the most prevalent neurological manifestation, with headache being the most common (40.3%). This finding is in agreement with previous studies, which found headache to be one of the most common neurological manifestations, with a frequency ranging from 4 to more than 40% (6, 7, 16, 19, 21, 22, 26). We found that almost 30% of COVID-19 patients with neurologic manifestations had abnormal neuroimaging. This number has been observed to range from 20% to more than 80% in different studies (26-32). The disparities could be due to the lower threshold for undergoing brain imaging in Iran’s health system setting, sample-size differences, or differences in the characteristics of the sample groups. For example, in the study that reported this number to be above 80%, a greater percentage of the sample experienced more serious neuro- logical symptoms, such as paresis or loss of consciousness, or had more comorbidities. Like Mahammedi et al.(32), we observed that patients who had acute abnormalities on neu- roimaging had a significantly higher CT lung severity score. Although further research is needed to verify this associa- tion, it suggests that any neurological symptoms in COVID- 19 patients with a high CT lung severity score should be taken seriously. In addition, we can employ the CT lung severity score as a prognostic tool in managing COVID-19 patients with neurological manifestations. Ischemia and infarction were the most common imaging ab- normalities, as they had been in many earlier studies (19, 28, 30, 33, 34). However, we have an inadequate understand- ing of the mechanisms of the neurologic manifestations pre- sented in COVID-19 patients, and we don’t know whether they were caused by direct invasion of the coronavirus to the central nervous system (35). SARS-CoV-2 has been demon- strated to enhance coagulopathy in previous investigations (36, 37), thus finding ischemia and infarction in neuroimag- ing appears to be a possibility that should be considered. We also reported four cases of encephalopathy, two of which dis- played encephalopathy features on brain imaging. Both were in the severe group and had to undergo neuroimaging due to delirium and focal neurologic signs; tragically, one of them passed away during the hospital stay. We also described a case of pituitary apoplexy in a young woman, which has been recorded in only a few cases in the COVID-19 setting (38). There are some limitations to this study that should be high- lighted. Even though our sample was large and multi-center, we only investigated hospitalized patients in two large hos- pitals. Our study was retrospective, which can contribute to an underestimation of variable frequency. Multinational and outpatient studies on long-term outcomes as well as other study designs should be considered. Due to the subjective nature of neuroimaging and chest CT scan findings, it was challenging to standardize them. We overcame this con- straint by having two expert neuroradiologists review all CT and MRI images and reaching a consensus on any disputes. Another major limitation was that we only enrolled COVID- 19 patients with neurologic manifestations who underwent neuroimaging. Because performing neuroimaging on all pa- tients as a routine is unnecessary and immoral, increasing the probability of exposure to the virus during a pandemic, imaging was done selectively in patients with more serious and significant neurologic symptoms. 5. Conclusion Our study demonstrates that roughly 30% of the studied cases had various new neuroimaging abnormalities, which should not be dismissed during the COVID-19 pandemic. Furthermore, age, neutrophil count, and lung CT score were shown to be strong predictors for the emergence of neu- roimaging pathologic findings. 6. Declarations 6.1. Acknowledgments We thank all the medical team at the neurology, radiology, infectious disease, and emergency medicine departments of both hospitals, including doctors, nurses, the health care ex- perts, and the staff. We also thank the patients and their fam- ilies for their cooperation. This open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 3.0 License (CC BY-NC 3.0). Downloaded from: http://journals.sbmu.ac.ir/aaem 9 Archives of Academic Emergency Medicine. 2022; 10(1): e10 6.2. Authors’ contributions Design of the study by AZ, MS, A.R and F.A; Data acquisition by AZ, MA, MR and A.T; Images review by HH, NA, and MA, Data analysis and interpretation by MHA; AR, FA, and RH; drafting the manuscript by AZ, MHA, HS, and AB; Revision of the manuscript by MS, AR, FA, MA, and AT; the final version of the manuscript is approved by all the authors. 6.3. Funding and supports None. 6.4. Conflict of Interest The authors declare no conflict of interest 6.5. Data Availability The datasets generated and analyzed during the current study are available from the corresponding author on reason- able request. References 1. Team EE. Note from the editors: World Health Organiza- tion declares novel coronavirus (2019-nCoV ) sixth public health emergency of international concern. Eurosurveil- lance. 2020;25(5):200131e. 2. World Health Organization. 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