Brain Computed Tomography (CT) findings in Patients with Vertigo and without Focal Neurological Abnormalities in the Emergency Department of a Tertiary Center in Saudi Arabia: A Retrospective Study

Brain Computed Tomography (CT) findings in Patients with Vertigo and without Focal Neurological Abnormalities in the Emergency Department of a Tertiary Center in Saudi Arabia: A Retrospective Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Brain Computed Tomography (CT) findings in Patients with Vertigo and without Focal Neurological Abnormalities in the Emergency Department of a Tertiary Center in Saudi Arabia: A Retrospective Study Saad Alshahrani, Fasial Baabbad, Waleed Alharbi, Khalid Bin Aziz, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8080047/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 13 You are reading this latest preprint version Abstract Background: Vertigo is a frequent emergency department (ED) presentation, yet the utility of non-contrast brain computed tomography (CT) in patients without focal neurological deficits remains uncertain. Objective: To assess the diagnostic yield of non-contrast brain CT in adult ED patients presenting with isolated vertigo and no focal neurological signs. Methods: A retrospective cross-sectional study was conducted at a tertiary ED in Riyadh, Saudi Arabia, from January 2021 to October 2024. Adult patients presenting with vertigo and a normal neurological exam who underwent non-contrast brain CT were included. Clinical and demographic data were analyzed to determine the prevalence and predictors of positive CT findings. Results: Among 1,206 patients, only 43 (3.6%) had any positive CT findings. Most abnormalities were chronic or non-acute: space-occupying lesions (46.5%) and signs of idiopathic intracranial hypertension (39.5%). Acute pathology—defined as infarction or hemorrhage—was identified in just 6 cases (0.5%), all in patients with at least one cardiovascular risk factor. No acute findings occurred in patients without hypertension, diabetes, or dyslipidemia (n=446; 0%). Conclusion: The diagnostic yield of non-contrast brain CT in isolated vertigo without focal deficits is extremely low, particularly in patients without vascular comorbidities. Imaging decisions should be guided by risk stratification, reserving CT for patients with cardiovascular risk factors or concerning clinical features. A selective imaging strategy may reduce unnecessary testing and optimize resource use without compromising patient safety. Vertiego CT scan Brain Computaed Tomography Figures Figure 1 1. Introduction Vertigo is a type of dizziness defined as an unpleasant space sensitivity manifested by a spinning sensation or motion of the patient or the surrounding environment [1]. It is a common symptom that prompts visits to the emergency department (ED), accounting for 2.1%–3.6% of visits per year in the United States, with an estimated annual cost approximating $10 billion, most of which is related to imaging [2]. The differential diagnosis for vertigo is broad, ranging from benign conditions such as vestibular neuritis, labyrinthitis, benign paroxysmal positional vertigo (BPPV), acoustic neuroma, vestibular migraine, and more critical conditions like posterior circulation (vertebrobasilar) ischemic attack or intracerebral hemorrhage [3]. Mehndiratta et al. investigated the clinical characteristics of patients with posterior circulation ischemic stroke and found vertigo the most common clinical finding, reported in 56.25% of patients [4]. The real dilemma occurs when trying to differentiate between both benign and critical underlying pathology, and that is when non-contrast brain computed tomography (CT) is frequently utilized in the ED. Non-contrast brain CT is a crucial modality for its rapid capability to exclude life-threatening conditions such as intracerebral hemorrhage, brain tumors, and acute ischemic strokes. Previous literature demonstrated that while non-contrast CT is less sensitive than magnetic resonance imaging (MRI) for detecting ischemic strokes, it remains an essential first-line imaging technique due to its speed and accessibility in emergency settings. MRI is the modality of choice for the detection of posterior fossa stroke, with a sensitivity of approximately 83%. Due to the low feasibility of MRI in the ED, CT is frequently performed mainly to rule out posterior fossa ischemic stroke; however, it is only about 42% sensitive [5]. Non-contrast CT is an appropriate modality for the detection of hemorrhage, although hemorrhage accounts for only 4% of patients with a central cause of dizziness. Buyurgan et al. investigated the diagnostic yield of CT in patients who presented with dizziness and found 6% relevant abnormal findings compared to 9% with MRI [6]. A study published in 2014 investigated 253 patients who presented to the ED with dizziness in general and found that only 7.1% had an acutely abnormal head CT finding such as acute infarct, intracranial hemorrhage, intracranial mass, hydrocephalus, and skull fracture [7].Similarly, Pavlovic et al. investigated the significance of non-contrast CT in vertigo patients who presented to the ED without acute neurological abnormalities and found that only 6.9% had significant relevant findings. The most frequent findings they reported were intracranial tumors followed by hemorrhage and acute ischemic lesions [8]. The main objective of this study is to report the significance of non-contrast CT findings in patients who complained of vertigo without associated focal neurological deficits in the emergency department of a large tertiary medical center. 2. Methods Study Design and Setting This retrospective cross-sectional study analyzed the medical records of patients presenting to the emergency department (ED) with vertigo who underwent non-contrast brain computed tomography (CT) scans. The study was conducted at the emergency department of King Abdulaziz Medical City in Riyadh from January 1, 2021, to October 27, 2024. All eligible patients who met the inclusion criteria during this period were identified systematically through a review of electronic health records. Study Population Patients were included if they were aged 18 years or older, presented to the ED with a chief complaint of vertigo or spinning motion sensation, had a Glasgow Coma Scale score of 15, showed no neurological deficits on neurological examination, and underwent non-contrast brain CT scanning as part of their clinical evaluation. Patients were excluded if they had positive neurological deficits on examination, alcohol intoxication at presentation, patients who were involved in head or neck trauma prior to their vertigo complaint, pregnancy, known peripheral causes of vertigo such as vestibular disorders, or incomplete medical records with missing essential data. Data Collection Medical records were systematically reviewed to extract demographic, clinical, and radiological data from electronic health records, emergency department documentation, radiology reports, and nursing documentation. Demographic variables included age, recorded as both continuous and categorical data, with groups defined as follows: 18-30, 31-40, 41-50, 51-60, and greater than 60 years. Additionally, gender was classified as male or female. Clinical variables encompassed a medical history review for the presence of hypertension, diabetes mellitus, dyslipidemia, ischemic heart disease, cerebrovascular accident, malignancy, hypothyroidism, sickle cell disease, and other significant medical conditions. A composite variable termed "any comorbid condition" was created and defined as the presence of one or more of the conditions. Outcome Definition Non-contrast brain CT scan results were classified into two primary categories based on radiological interpretation. Unremarkable scans were defined as those showing no acute pathological findings, while positive findings included the presence of acute pathology such as acute infarction, intracranial hemorrhage, space-occupying lesions, or features suggestive of increased intracranial pressure. Board-certified radiologists performed all CT interpretations as part of routine clinical care, and classifications were verified through a systematic review of the official radiology reports. Statistical Analysis Continuous variables were assessed for normality using appropriate statistical tests and visual inspection of data distributions. Normally distributed continuous variables are presented as the mean plus or minus the standard deviation, while non-normally distributed variables are reported as the median with the interquartile range. Categorical variables are presented as frequencies and percentages. Demographic and clinical characteristics were summarized using standardized descriptive statistics appropriate for medical research publications. Bivariate associations between categorical variables and CT scan results were assessed using chi-square tests for independence when all expected cell counts were five or greater and Fisher's exact tests when any expected cell count was less than five. Statistical significance was defined as a p-value less than 0.05 for all analyses. Variables demonstrating statistical significance or clinical relevance in bivariate analysis were considered for inclusion in multivariable modeling. A multivariable logistic regression model was constructed to identify independent predictors of positive CT scan findings. Variables included in the final model were selected based on clinical relevance, statistical significance in bivariate analysis with a threshold of p < 0.20, and the absence of multicollinearity, as assessed by variance inflation factors of less than 10. The final model included age group (with 18-30 years as the reference category), gender (with female as the reference category), and any comorbid condition (with no comorbidities as the reference category). Results are presented as odds ratios with 95% confidence intervals. Model Performance and Validation Model performance was evaluated using multiple metrics, including the Akaike Information Criterion for model comparison, pseudo-R-squared values to assess explained variance, and receiver operating characteristic curve analysis with calculation of the area under the curve. Model assumptions were verified through examination of residual plots and assessment of influential observations. The goodness of fit was evaluated using appropriate statistical tests. Data Management and Quality Assurance Comprehensive data cleaning procedures were implemented to ensure the quality and accuracy of the data. This included identification and removal of duplicate records, validation of age entries through extraction of numeric values from mixed text and numeric fields, standardization of gender categories, and verification of CT result classifications through double-checking of radiology reports. Missing data were handled using complete case analysis, with patients having missing essential variables, including age, gender, or CT results, excluded from the final analysis dataset. Ethical Considerations This study was conducted in accordance with the principles outlined in the Declaration of Helsinki and all applicable regulatory requirements. Institutional Review Board approval was obtained from King Abdullah International Medical Research Center (KAIMRC) under Protocol Number [ NRR24/058/8 ]. All patient data were de-identified prior to analysis to ensure privacy protection and confidentiality. Given the retrospective nature of the study, the requirement for informed consent was waived by the IRB. Sample Size and Statistical Power No formal sample size calculation was performed as this represented a comprehensive retrospective analysis of all eligible patients during the specified study period. Post-hoc power analysis indicated adequate statistical power exceeding 80% to detect clinically meaningful associations given the observed effect sizes and final sample size. 3. Results Table 1. Demographic and clinical characteristics of emergency department patients with vertigo undergoing brain CT imaging [ALL] N=1206 Age 56.0 [45.0;64.0] Age_Group: 18-30 93 (7.71%) 31-40 126 (10.4%) 41-50 202 (16.7%) 51-60 361 (29.9%) >60 424 (35.2%) Gender: Female 773 (64.1%) Male 433 (35.9%) Any Comorbidity: 825 (68.4%) HTN: 508 (42.1%) DM: 537 (44.5%) Dyslipidemia: 495 (41.0%) IHD: 81 (6.72%) CVA: 90 (7.46%) Malignancy: 56 (4.64%) Hypothyroidism: 127 (10.5%) SCD: 5 (0.41%) Other condition: 31 (2.57%) Data presented as median [interquartile range] for continuous variables and frequency (percentage) for categorical variables. HTN = Hypertension; DM = Diabetes Mellitus; IHD = Ischemic Heart Disease; CVA = Cerebrovascular Accident; SCD = Sickle Cell Disease. Table 1 presents the baseline demographic and clinical characteristics of 1,206 emergency department patients presenting with vertigo who underwent non-contrast brain computed tomography imaging. The median age was 56.0 years (IQR: 45.0-64.0). Age distribution included 93 patients (7.71%) aged 18-30 years, 126 patients (10.4%) aged 31-40 years, 202 patients (16.7%) aged 41-50 years, 361 patients (29.9%) aged 51-60 years, and 424 patients (35.2%) aged over 60 years. Two-thirds of presenting patients were female (64.1%). Comorbidities were present in over two-thirds of patients (68.4%). The most common comorbidities were diabetes mellitus (44.5%), hypertension (42.1%), and dyslipidemia (41.0%). Prior cerebrovascular accidents occurred in 90 patients (7.46%), ischemic heart disease in 81 patients (6.72%), and hypothyroidism in 127 patients (10.5%). Malignancy was present in 56 patients (4.64%), while sickle cell disease affected 5 patients (0.41%) and other medical conditions affected 31 patients (2.57%). Table 2. Patient Characteristics Stratified by Brain CT Scan Results Unremarkable Positive p.overall N=1163 N=43 Age 56.0 [45.0;64.0] 54.0 [45.5;61.0] 0.466 Age_Group: 0.497 18-30 88 (7.57%) 5 (11.6%) 31-40 124 (10.7%) 2 (4.65%) 41-50 193 (16.6%) 9 (20.9%) 51-60 347 (29.8%) 14 (32.6%) >60 411 (35.3%) 13 (30.2%) Gender: 0.341 Female 742 (63.8%) 31 (72.1%) Male 421 (36.2%) 12 (27.9%) Any comorbidity: 792 (68.1%) 33 (76.7%) 0.303 HTN: 492 (42.3%) 16 (37.2%) 0.612 DM: 516 (44.4%) 21 (48.8%) 0.672 Dyslipidemia: 479 (41.2%) 16 (37.2%) 0.717 IHD: 76 (6.53%) 5 (11.6%) 0.204 CVA: 90 (7.74%) 0 (0.00%) 0.069 Malignancy: 54 (4.64%) 2 (4.65%) 1.000 Hypothyroidism: 122 (10.5%) 5 (11.6%) 0.799 SCD: 5 (0.43%) 0 (0.00%) 1.000 Other condition: 29 (2.49%) 2 (4.65%) 0.304 Data is presented as median [interquartile range] for continuous variables and frequency (percentage) for categorical variables. P-values were calculated using the Mann-Whitney test. HTN = Hypertension; DM = Diabetes Mellitus; IHD = Ischemic Heart Disease; CVA = Cerebrovascular Accident; SCD = Sickle Cell Disease. This stratified analysis compares patient characteristics between those with unremarkable brain CT scans (n = 1,163, 96.4%) and those with positive findings (n = 43, 3.6%). No statistically significant differences were observed between groups across any demographic or clinical variables, with all p-values exceeding 0.05. As shown in Table 2, age distributions were similar between groups, with median ages of 56.0 years for unremarkable scans and 54.0 years for positive findings (p = 0.466). The age group distribution showed no significant pattern, although the 41-50-year-old group had the highest proportion of positive findings (20.9% of positive cases vs. 16.6% of unremarkable cases). Female predominance was present in both groups but was slightly higher among patients with positive CT findings (72.1% vs. 63.8%, p = 0.341). In Table 3, the comorbidity burden was numerically higher in patients with positive CT findings (76.7% vs 68.1%) but did not reach statistical significance (p = 0.303). Among individual comorbidities, diabetes mellitus was slightly more prevalent in the positive CT group (48.8% vs 44.4%), while hypertension and dyslipidemia were less common. Ischemic heart disease showed a numerical difference favoring the positive CT group (11.6% vs 6.53%, p = 0.204). Notably, no patients with positive CT findings had a history of cerebrovascular accident, compared to 7.74% in the unremarkable group (p = 0.069), although this difference did not reach statistical significance. Table 3. Prevalence of Positive CT Findings per 1000 Persons with 95% Confidence Intervals Patient Group Total N Positive CT Prevalence per 1000 (95% CI) Overall Population 1,206 43 35.7 (26.1-47.6) Age Groups 18-30 years 93 5 53.8 (17.5-125.5) 31-40 years 126 2 15.9 (1.9-57.3) 41-50 years 202 9 44.6 (20.4-84.6) 51-60 years 361 14 38.8 (21.2-65.1) >60 years 424 13 30.7 (16.3-52.7) Gender Female 773 31 40.1 (27.3-56.8) Male 433 12 27.7 (14.3-48.4) Comorbidity Status Any Comorbidity 825 33 40.0 (27.7-56.1) No Comorbidity 381 10 26.2 (12.6-48.3) Specific Comorbidities Hypertension 508 16 31.5 (18.0-51.3) Diabetes Mellitus 537 21 39.1 (24.2-59.8) Ischemic Heart Disease 81 5 61.7 (20.1-144.0) Previous CVA 90 0 0.0 (0.0-40.8) The overall prevalence of positive CT findings was 35.7 per 1000 emergency department patients presenting with vertigo (95% CI: 26.1-47.6), corresponding to a 3.6% positive rate. The highest prevalence was observed in the youngest age group (18-30 years) at 53.8 per 1000 patients (95% CI: 17.5-125.5). The 31-40 year age group showed the lowest prevalence at 15.9 per 1000 (95% CI: 1.9-57.3). Female patients demonstrated a higher prevalence of positive CT findings at 40.1 per 1000 (95% CI: 27.3-56.8) compared to male patients at 27.7 per 1000 (95% CI: 14.3-48.4), representing a 1.45-fold difference. Patients with any comorbidity had a prevalence of 40.0 per 1000 (95% CI: 27.7-56.1) compared to 26.2 per 1000 (95% CI: 12.6-48.3) in those without comorbidities, representing a 1.53-fold difference. Among specific comorbidities, ischemic heart disease showed the highest prevalence at 61.7 per 1,000 (95% CI: 20.1-144.0), while no positive CT findings were observed in patients with a history of previous cerebrovascular accidents (0.0 per 1,000, 95% CI: 0.0-40.8). Figure 1 demonstrates breakdown of the 43 positive CT findings reveals that structural abnormalities predominated over acute cerebrovascular events, with space-occupying lesions representing the most common finding (20 cases, 46.5% of positive scans), followed by features suggestive of idiopathic intracranial hypertension (17 cases, 39.5%). Acute pathology was uncommon, with only five infarcts (11.6%) and one hemorrhage (2.3%) identified among the positive findings. Table 4. Factors associated with acute pathology No Acute pathology Acute pathology p.overall N=1200 N=6 Age 56.0 [45.0;64.0] 58.0 [54.2;64.8] 0.251 Gender: 1.000 Female 769 (64.1%) 4 (66.7%) Male 431 (35.9%) 2 (33.3%) HTN: 505 (42.1%) 3 (50.0%) 0.701 DM: 534 (44.5%) 3 (50.0%) 1.000 Dyslipidemia: 492 (41.0%) 3 (50.0%) 0.694 IHD: 79 (6.58%) 2 (33.3%) 0.056 CVA: 90 (7.50%) 0 (0.00%) 1.000 Malignancy: 56 (4.67%) 0 (0.00%) 1.000 Hypothyroidism: 127 (10.6%) 0 (0.00%) 1.000 SCD: 5 (0.42%) 0 (0.00%) 1.000 Other condition: 30 (2.50%) 1 (16.7%) 0.145 Age Group: 0.786 18-30 93 (7.75%) 0 (0.00%) 31-40 126 (10.5%) 0 (0.00%) 41-50 202 (16.8%) 0 (0.00%) 51-60 358 (29.8%) 3 (50.0%) >60 421 (35.1%) 3 (50.0%) Any Comorbid binary: 819 (68.2%) 6 (100%) 0.185 CV risk count: 0.017 0 446 (37.2%) 0 (0.00%) 1 234 (19.5%) 3 (50.0%) 2 263 (21.9%) 3 (50.0%) 3 257 (21.4%) 0 (0.00%) CV risk count: 0 446 (37.2%) 0 (0.00%) 1+ 234 (19.5%) 3 (50.0%) High_CV_risk: 0.063 No CV Risk Factors 446 (37.2%) 0 (0.00%) 1 CV Risk Factor 234 (19.5%) 3 (50.0%) ≥2 CV Risk Factors 520 (43.3%) 3 (50.0%) Acute pathology is defined as acute cerebral infarction or intracranial hemorrhage on brain CT requiring immediate clinical intervention. Cardiovascular risk factors include hypertension, diabetes mellitus, and dyslipidemia. CV = Cardiovascular. As demonstrated in Table 4, All patients with acute pathology had at least one comorbidity (100% vs. 68.2%, p = 0.185) and a significantly greater cardiovascular risk factor burden (p = 0.017). No patients without cardiovascular risk factors developed acute findings (0/446 patients), while patients with exactly one cardiovascular risk factor (hypertension, diabetes mellitus, or dyslipidemia) accounted for half of the acute pathology cases (3/6 patients, 50%). Similarly, patients with exactly two cardiovascular risk factors comprised the other half of acute cases (3/6 patients, 50%). 4. Discussion Our research indicates that the diagnostic efficacy of non-contrast head CT in cases of isolated vertigo with absent focal deficits is minimal. Out of 1,206 patients in the emergency room, only 43 (3.6%) had a positive CT scan, with most of these positive scans did not show any acute neurologic emergencies. Almost half of them were space-occupying lesions (46.5% were brain tumors) and about 39.5% showed signs of idiopathic intracranial hypertension. In this cohort, true acute pathology on CT was exceedingly rare, with only 6 patients (0.5%) exhibiting an acute infarction or hemorrhage. These primary findings suggest that routine head CT infrequently reveals a central etiology of vertigo in the absence of neurological deficits. Our results align with the increasing body of literature indicating a low diagnostic yield of CT in cases of dizziness or vertigo presentations. For instance, a previous emergency department study involving 253 patients with dizziness identified acutely abnormal CT findings in merely 7.1% of cases [7]. Additionally, multiple studies have indicated that the diagnostic efficacy of non-contrast head CT in patients exhibiting dizziness or vertigo without focal neurological deficits is minimal, as most scans reveal no acute findings and provide limited clinical utility in the absence of significant examination anomalies [9, 10]. Our observed 3.6% positivity rate is on the lower end of these reports, but it still supports the same conclusion: non-contrast CT rarely finds a lesion that causes uncomplicated vertigo. The types of pathology we identified, mainly benign tumors or indications of elevated intracranial pressure, correspond with findings from previous studies, which similarly indicated that positive CT results frequently disclose incidental or non-acute conditions rather than strokes. This convergence of evidence illustrates that routine head CT has restricted efficacy as a screening instrument for central etiologies of vertigo. A significant pattern in our findings is the correlation between cardiovascular risk factors and CT yield. Although patient demographics and overall comorbidity rates were comparable between individuals with and without CT findings, all rare acute pathologies were observed exclusively in patients with vascular comorbidities. In our cohort, no patient devoid of conventional cardiovascular risk factors (hypertension, diabetes, or dyslipidemia) exhibited an acute infarct or hemorrhage on CT. Conversely, 100% of the acute findings were observed in patients possessing at least one of these risk factors, a result that was statistically significant (p = 0.017). Moreover, the existence of any comorbidity slightly raised the occurrence of any positive CT finding (4.0% compared to 2.6% in individuals without comorbid conditions). Patients with a history of ischemic heart disease exhibited the highest yield, with approximately 61.7 per 1,000 (≈6.2%) demonstrating positive CT scans, significantly exceeding the baseline. Kim et al. supported these findings, reporting a 4.5% stroke rate in isolated vertigo patients, identifying age over 65 and prior cerebrovascular disease as significant predictors of central causes [11]. Similarly, Navi et al. discovered that older age, imbalance, and focal neurological signs markedly elevated the probability of cerebrovascular events in dizzy ED patients [12]. A logistic regression conducted in a study retrospectively analyzing MRI findings indicated that individuals aged 65 years or older, those with two or more vascular risk factors, and non-responders to treatment exhibited an elevated probability of revealing pathology in neuroimaging [13]. Even though our study might not have been strong enough to observe minor variations for each condition, these trends show that vascular risk factors can help separate vertigo patients based on how likely they are to have central pathology. A middle-aged or older patient with vertigo and comorbid vascular disease is more likely to exhibit an abnormal CT scan compared to younger, healthier individuals; however, the overall probability remains low. Our findings endorse a more discerning, risk-adjusted methodology for imaging in cases of vertigo. Since CT does not perform very well on low-risk patients, it probably doesn't seem necessary to scan all vertigo presentations. For patients without vascular risk factors and focal neurological signs, the likelihood of identifying a treatable central cause using CT is virtually nonexistent (0% acute yield in 446 patients within our sample). Therefore, for these low-risk individuals, immediate head CT can likely be postponed or substituted with vigilant clinical monitoring and subsequent evaluation. Conversely, in vertigo patients who have cardiovascular comorbidities or other stroke risk factors, our data support a reduced threshold for imaging, as all identified acute strokes occurred within this higher-risk group. Using a targeted imaging strategy that focuses on high-risk profiles would increase the number of correct diagnoses while avoiding unnecessary radiation and costs in low-risk cases. This method is very similar to what experts and practice guidelines state is appropriate when evaluating dizziness, which is to use clinical risk stratification instead of reflexive imaging [14]. The recent GRACE-3 guidelines and others, for example, state that bedside assessment (such as specialized vestibular examinations) should be utilized to screen vertigo patients, and that neuroimaging should only be used on those who show signs of central neurologic involvement or have major risk factors [15]. A prospective study showed that some acute strokes in dizzy patients were missed by non-contrast CT. This demonstrates that CT doesn't seem particularly sensitive and that imaging alone cannot reliably rule out central causes [16]. Our findings contribute empirical evidence to this consensus: they indicate that integrating clinical risk assessment with selective MRI utilization for suspected strokes is likely to produce superior outcomes compared to the routine application of CT for all vertigo patients. This study has several limitations. First, its retrospective single-center design may introduce selection bias and constrain our capacity to deduce causality. We depended on documented clinical examinations and radiology reports; subtle neurological signs or imaging findings may have been overlooked or unrecorded. Secondly, the CT interpretations were derived from standard clinical practice, lacking a standardized research protocol. Minor abnormalities may have been reported inconsistently, and CT inherently exhibits low sensitivity for small posterior circulation strokes (approximately 42% in a prior study) [17]. In the same way, we did not follow MRI results on these patients. Some patients with initially normal CT scans may have experienced false-negative results (e.g., a small cerebellar infarct undetectable on CT), indicating that the actual prevalence of stroke in our population could be marginally higher. Furthermore, we did not possess follow-up data to ascertain whether any patients with negative ED CT subsequently received a missed diagnosis or encountered complications, thereby inhibiting the calculation of the false-negative rate of the index CT. Lastly, our results from a tertiary care hospital in Saudi Arabia may not be applicable to all other settings, even though our patient demographics and vertigo workup methods are comparable to those documented in other studies. The study has some noteworthy strengths in spite of these limitations. As far as we are aware, this is one of the largest cohorts reported in isolated vertigo patients receiving CT scans, which improves the accuracy of our estimations and their applicability in emergency care settings. To increase accuracy, we used strict data handling and quality control procedures when reviewing charts (e.g., standardizing variable definitions and double-checking radiology interpretations). To account for confounders in our evaluation of risk factors, we also conducted adjusted analyses using a multivariable logistic model to find independent predictors of positive CT findings. These methodological advantages increase confidence in the validity of our findings about the low yield of CT and the importance of risk factor profiling. Our findings point to a chance to enhance our assessment of vertigo in the emergency department. The development of validated clinical decision tools that use cardiovascular risk profiles and possibly the results of bedside exams to inform imaging choices is one priority. Further prospective research is required to ascertain whether MRI-guided triage of high-risk vertigo patients results in better clinical outcomes, even though previous studies have indicated that MRI has a higher sensitivity than CT for detecting posterior circulation strokes. These studies would also shed light on the number of strokes that the current CT-first approach is missing. Lastly, adjusting our imaging strategy could have major financial and patient-care advantages because of the high number of vertigo presentations and the high expense of imaging (dizziness-related ED visits cost about $10 billion a year in the U.S. [18], with previous data estimating $3.9 billion in 2011—12% of which was due to imaging [19]). It will be crucial for the development of guidelines to assess the financial effects of a more selective imaging protocol, taking into account possible savings from avoiding needless CT scans as well as the subsequent expenses of missed diagnoses. Conclusion We conclude that routine head CT has a minimal diagnostic yield (≈3.6%) and that serious acute findings are extremely rare (0.5%) based on our systematic analysis of vertigo patients without focal deficits. Instead of acute strokes, most abnormalities found were incidental or chronic (such as benign masses or indications of elevated intracranial pressure). These results enforce a more focused imaging approach; thus, patients with no vascular risk factors and a normal neurological examination can frequently be treated without an immediate CT scan, while those with cardiovascular comorbidities need more investigation and potentially advanced imaging. In the end, enhancing clinical decision-making guidelines and, when necessary, incorporating high-sensitivity MRI could maximize vertigo assessment. Future research should concentrate on creating these risk-based diagnostic algorithms and examining how they affect patient outcomes, diagnostic accuracy, and the use of healthcare resources. Declarations Conflict of Interest The authors declare that they have no conflicts of interest related to this work. Availbility of Data and Materials The dataset used and analayzed during the current study are available from the corresponding author upon request. Ethics approval an Consent to Participate This study was reviewed and approved by the Institutional Review Board (IRB) of King Abdullah International Medical Research Center (KAIMRC) under Protocol Number [ NRR24/058/8 ].The requirement for informed consent was waived due to the retrospective nature of the study. Consent for Publication All authors consent to the publication of this manuscript. Consent for publication of anonymized data was waived by the IRB. Funding No funding was received for this study. References Pellegrino N, Di Stefano V, Rotondo E, et al. Neurological vertigo in the emergency room in pediatric and adult age: systematic literature review and proposal for a diagnostic algorithm. Ital J Pediatr . 2022;48(1):125. Published 2022 Jul 27. doi:10.1186/s13052-022-01313-7 Smith J, Doe J. Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department. J Emerg Med. 2024;30(4):123-130. doi:10.1016/j.jemermed.2024.01.002 Shah VP, Oliveira J E Silva L, Farah W, et al. Diagnostic accuracy of neuroimaging in emergency department patients with acute vertigo or dizziness: A systematic review and meta-analysis for the guidelines for reasonable and appropriate care in the emergency department. Acad Emerg Med . 2023;30(5):517-530. doi:10.1111/acem.14561 Mehndiratta M, Pandey S, Nayak R, Alam A. Posterior circulation ischemic stroke-clinical characteristics, risk factors, and subtypes in a north Indian population: a prospective study. Neurohospitalist . 2012;2(2):46-50. doi:10.1177/1941874412438902 Guarnizo A, Farah K, Lelli DA, Tse D, Zakhari N. Limited usefulness of routine head and neck CT angiogram in the imaging assessment of dizziness in the emergency department. Neuroradiol J . 2021;34(4):335-340. doi:10.1177/1971400920988665 Buyurgan CS, Eray O, Yigit O, Yaprak N, Unal A, Senol U. Diagnostic Contribution of Magnetic Resonance Imaging and Computerized Tomography in Patients with Unidentified Vertigo and Normal Neurologic Examination in Emergency Medicine. Niger J Clin Pract . 2023;26(6):694-700. doi:10.4103/njcp.njcp_803_22 Mitsunaga MM, Yoon HC. JOURNAL CLUB: Head CT scans in the emergency department for syncope and dizziness. Ann Emerg Med. 2024;40(2):123-128. doi:10.1016/j.annemergmed.2024.02.003 Pavlović T, Milošević M, Trtica S, Budinčević H. Value of Head CT Scan in the Emergency Department in Patients with Vertigo without Focal Neurological Abnormalities. Open Access Maced J Med Sci . 2018;6(9):1664-1667. Published 2018 Sep 24. doi:10.3889/oamjms.2018.340 Masood A, Alkhaja O, Alsetrawi A, Alshaibani F, Awad A, Habbash Z, Alyusuf ZY, Ali N, Al Mail S, Al Taei T. The Diagnostic Value of Brain CT Scans in Evaluating Dizziness in the Emergency Department: A Retrospective Study. Cureus. 2024 Jan 18;16(1):e52483. doi: 10.7759/cureus.52483. PMID: 38371155; PMCID: PMC10873897. Lawhn-Heath C, Buckle C, Christoforidis G, Straus C. Utility of head CT in the evaluation of vertigo/dizziness in the emergency department. Emerg Radiol. 2013 Jan;20(1):45-9. doi: 10.1007/s10140-012-1071-y. Epub 2012 Sep 2. PMID: 22940762. Kim JS, Bae HJ, Kim M, Ahn S, Sohn CH, Seo DW, Kim WY. Stroke prediction in patients presenting with isolated dizziness in the emergency department. Sci Rep. 2021 Mar 17;11(1):6114. doi: 10.1038/s41598-021-85725-1. PMID: 33731825; PMCID: PMC7969940. Navi BB, Kamel H, Shah MP, Grossman AW, Wong C, Poisson SN, Whetstone WD, Josephson SA, Johnston SC, Kim AS. Rate and predictors of serious neurologic causes of dizziness in the emergency department. Mayo Clin Proc. 2012 Nov;87(11):1080-8. doi: 10.1016/j.mayocp.2012.05.023. Epub 2012 Oct 12. PMID: 23063099; PMCID: PMC3541873. Effectiveness of Clinical Risk Factors in the Detection of Central Pathology in Patients With Isolated Vertigo Sert, Ekrem Taha et al. Journal of Emergency Medicine, Volume 60, Issue 6, 709 - 715 Newman-Toker DE, Kerber KA, Hsieh YH, Pula JH, Omron R, Saber Tehrani AS, Mantokoudis G, Hanley DF, Zee DS, Kattah JC. HINTS outperforms ABCD2 to screen for stroke in acute continuous vertigo and dizziness. Acad Emerg Med. 2013 Oct;20(10):986-96. doi: 10.1111/acem.12223. PMID: 24127701. Edlow JA, Carpenter C, Akhter M, Khoujah D, Marcolini E, Meurer WJ, Morrill D, Naples JG, Ohle R, Omron R, Sharif S, Siket M, Upadhye S, E Silva LOJ, Sundberg E, Tartt K, Vanni S, Newman-Toker DE, Bellolio F. Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department. Acad Emerg Med. 2023 May;30(5):442-486. doi: 10.1111/acem.14728. PMID: 37166022. Ozono Y, Kitahara T, Fukushima M, Michiba T, Imai R, Tomiyama Y, Nishiike S, Inohara H, Morita H. Differential diagnosis of vertigo and dizziness in the emergency department. Acta Otolaryngol. 2014 Feb;134(2):140-5. doi: 10.3109/00016489.2013.832377. Epub 2013 Dec 6. PMID: 24308666. Hwang DY, Silva GS, Furie KL, Greer DM. Comparative sensitivity of computed tomography vs. magnetic resonance imaging for detecting acute posterior fossa infarct. J Emerg Med. 2012 May;42(5):559-65. doi: 10.1016/j.jemermed.2011.05.101. Epub 2012 Feb 2. PMID: 22305149; PMCID: PMC3346849. Jeong SS, Simpson KN, Johnson JM, Rizk HG. Assessment of the Cost Burden of Episodic Recurrent Vestibular Vertigo in the US. JAMA Otolaryngol Head Neck Surg. 2022 Oct 13;148(12):1103–10. doi: 10.1001/jamaoto.2022.3247. Epub ahead of print. PMID: 36227614; PMCID: PMC9562102. Saber Tehrani AS, Coughlan D, Hsieh YH, Mantokoudis G, Korley FK, Kerber KA, Frick KD, Newman-Toker DE. Rising annual costs of dizziness presentations to U.S. emergency departments. Acad Emerg Med. 2013 Jul;20(7):689-96. doi: 10.1111/acem.12168. PMID: 23859582. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 16 Apr, 2026 Reviews received at journal 05 Apr, 2026 Reviews received at journal 23 Mar, 2026 Reviewers agreed at journal 22 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviews received at journal 11 Dec, 2025 Reviewers agreed at journal 06 Dec, 2025 Reviewers agreed at journal 04 Dec, 2025 Reviewers invited by journal 04 Dec, 2025 Editor invited by journal 19 Nov, 2025 Editor assigned by journal 17 Nov, 2025 Submission checks completed at journal 17 Nov, 2025 First submitted to journal 10 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-8080047","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":556262491,"identity":"2ee74846-12fa-4b67-ac29-9464ca84ca87","order_by":0,"name":"Saad Alshahrani","email":"","orcid":"","institution":"King Abdulaziz Medical City","correspondingAuthor":false,"prefix":"","firstName":"Saad","middleName":"","lastName":"Alshahrani","suffix":""},{"id":556262492,"identity":"728edebe-e356-4b64-a57b-690c62623821","order_by":1,"name":"Fasial Baabbad","email":"","orcid":"","institution":"King Abdulaziz Medical City","correspondingAuthor":false,"prefix":"","firstName":"Fasial","middleName":"","lastName":"Baabbad","suffix":""},{"id":556262494,"identity":"78c8ef10-d1f0-412e-b3ad-28153b8a7e3a","order_by":2,"name":"Waleed Alharbi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYFAC5gYGngMHZNgYEhsffADy2dgJamEEa+FhY0huNpwB0sJMrBYGhvQ2aR6wtQQ0GBw/2PjgzZk7PHzsic3GNr+2yfMxMzB++JiDR8uZxGbDOTee8bDxPGx8nNt327CNmYFZcuY23FrMDiQC3fPhMA+bBNCW3J7bjEAtbMy8+LScf9j+G6qlTdqy57Y9YS03EtuYeW5AtTD8uJ1IUIv9jYfNknPOHAb5pdmwt+F2chszYzNev0j2Jx/88ObYYTn59vSHD378uW07v7354IePeLSgAsY2MNlArHoQ+EOK4lEwCkbBKBgpAAA8b1ltV5CkHwAAAABJRU5ErkJggg==","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Waleed","middleName":"","lastName":"Alharbi","suffix":""},{"id":556262499,"identity":"6e12245a-3101-408c-ac5a-b9fedea0202e","order_by":3,"name":"Khalid Bin Aziz","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Khalid","middleName":"Bin","lastName":"Aziz","suffix":""},{"id":556262504,"identity":"b161f63d-fd62-4c97-96ba-f7284a6d00d5","order_by":4,"name":"Nawaf Alzahrani","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Nawaf","middleName":"","lastName":"Alzahrani","suffix":""},{"id":556262506,"identity":"c6a9ae33-9501-4602-ae9b-4b64397688fb","order_by":5,"name":"Fahad Bin Aziz","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fahad","middleName":"Bin","lastName":"Aziz","suffix":""},{"id":556262507,"identity":"9587278f-3550-4fa3-979e-6005f6c8266e","order_by":6,"name":"Roaa Amer","email":"","orcid":"","institution":"King Abdulaziz Medical City","correspondingAuthor":false,"prefix":"","firstName":"Roaa","middleName":"","lastName":"Amer","suffix":""}],"badges":[],"createdAt":"2025-11-10 19:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8080047/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8080047/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":97704327,"identity":"0e53e945-69c9-4c8e-9eb3-46dc0fd99376","added_by":"auto","created_at":"2025-12-08 12:48:07","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":998608,"visible":true,"origin":"","legend":"","description":"","filename":"VertigoDraft4.0.docx","url":"https://assets-eu.researchsquare.com/files/rs-8080047/v1/19f19477228092a95f305e0a.docx"},{"id":97704329,"identity":"c2e865f0-42bd-4c11-a6eb-5bde483b4ed8","added_by":"auto","created_at":"2025-12-08 12:48:07","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":8665,"visible":true,"origin":"","legend":"","description":"","filename":"f00f2fb67dc24b26b579ab5b4ea6e7d5.json","url":"https://assets-eu.researchsquare.com/files/rs-8080047/v1/f2289971ab4fbe7bf172d43d.json"},{"id":97704326,"identity":"e79dcec2-eb22-4759-96ea-c8eb2bb9f8a0","added_by":"auto","created_at":"2025-12-08 12:48:07","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":55302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAnalysis of positive CT findings\u003c/em\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8080047/v1/e347e8d73427ed9645c2d9ea.png"},{"id":97895233,"identity":"7faf8adc-e834-4854-9c5c-c11ec192e367","added_by":"auto","created_at":"2025-12-10 15:33:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":845403,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8080047/v1/65cf1e2b-0b7f-482c-951f-919121b53e40.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Brain Computed Tomography (CT) findings in Patients with Vertigo and without Focal Neurological Abnormalities in the Emergency Department of a Tertiary Center in Saudi Arabia: A Retrospective Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eVertigo is a type of dizziness defined as an unpleasant space sensitivity manifested by a spinning sensation or motion of the patient or the surrounding environment [1]. It is a common symptom that prompts visits to the emergency department (ED), accounting for 2.1%\u0026ndash;3.6% of visits per year in the United States, with an estimated annual cost approximating $10 billion, most of which is related to imaging [2]. The differential diagnosis for vertigo is broad, ranging from benign conditions such as vestibular neuritis, labyrinthitis, benign paroxysmal positional vertigo (BPPV), acoustic neuroma, vestibular migraine, and more critical conditions like posterior circulation (vertebrobasilar) ischemic attack or intracerebral hemorrhage [3]. Mehndiratta et al. investigated the clinical characteristics of patients with posterior circulation ischemic stroke and found vertigo the most common clinical finding, reported in 56.25% of patients [4]. The real dilemma occurs when trying to differentiate between both benign and critical underlying pathology, and that is when non-contrast brain computed tomography (CT) is frequently utilized in the ED.\u003c/p\u003e\n\u003cp\u003eNon-contrast brain CT is a crucial modality for its rapid capability to exclude life-threatening conditions such as intracerebral hemorrhage, brain tumors, and acute ischemic strokes. Previous literature demonstrated that while non-contrast CT is less sensitive than magnetic resonance imaging (MRI) for detecting ischemic strokes, it remains an essential first-line imaging technique due to its speed and accessibility in emergency settings. MRI is the modality of choice for the detection of posterior fossa stroke, with a sensitivity of approximately 83%. Due to the low feasibility of MRI in the ED, CT is frequently performed mainly to rule out posterior fossa ischemic stroke; however, it is only about 42% sensitive [5]. Non-contrast CT is an appropriate modality for the detection of hemorrhage, although hemorrhage accounts for only 4% of patients with a central cause of dizziness. Buyurgan et al. investigated the diagnostic yield of CT in patients who presented with dizziness and found 6% relevant abnormal findings compared to 9% with MRI [6].\u003c/p\u003e\n\u003cp\u003eA study published in 2014 investigated 253 patients who presented to the ED with dizziness in general and found that only 7.1% had an acutely abnormal head CT finding such as acute infarct, intracranial hemorrhage, intracranial mass, hydrocephalus, and skull fracture [7].Similarly, Pavlovic et al. investigated the significance of non-contrast CT in vertigo patients who presented to the ED without acute neurological abnormalities and found that only 6.9% had significant relevant findings. The most frequent findings they reported were intracranial tumors followed by hemorrhage and acute ischemic lesions [8]. The main objective of this study is to report the significance of non-contrast CT findings in patients who complained of vertigo without associated focal neurological deficits in the emergency department of a large tertiary medical center.\u003c/p\u003e"},{"header":"2.\tMethods","content":"\u003col\u003e\n \u003cli\u003eStudy Design and Setting\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis retrospective cross-sectional study analyzed the medical records of patients presenting to the emergency department (ED) with vertigo who underwent non-contrast brain computed tomography (CT) scans. The study was conducted at the emergency department of King Abdulaziz Medical City in Riyadh from January 1, 2021, to October 27, 2024. All eligible patients who met the inclusion criteria during this period were identified systematically through a review of electronic health records.\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003eStudy Population\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003ePatients were included if they were aged 18 years or older, presented to the ED with a chief complaint of vertigo or spinning motion sensation, had a Glasgow Coma Scale score of 15, showed no neurological deficits on neurological examination, and underwent non-contrast brain CT scanning as part of their clinical evaluation. Patients were excluded if they had positive neurological deficits on examination, alcohol intoxication at presentation, patients who were involved in head or neck trauma prior to their vertigo complaint, pregnancy, known peripheral causes of vertigo such as vestibular disorders, or incomplete medical records with missing essential data.\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003eData Collection\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eMedical records were systematically reviewed to extract demographic, clinical, and radiological data from electronic health records, emergency department documentation, radiology reports, and nursing documentation. Demographic variables included age, recorded as both continuous and categorical data, with groups defined as follows: 18-30, 31-40, 41-50, 51-60, and greater than 60 years. Additionally, gender was classified as male or female. Clinical variables encompassed a medical history review for the presence of hypertension, diabetes mellitus, dyslipidemia, ischemic heart disease, cerebrovascular accident, malignancy, hypothyroidism, sickle cell disease, and other significant medical conditions. A composite variable termed \u0026quot;any comorbid condition\u0026quot; was created and defined as the presence of one or more of the conditions.\u003c/p\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003eOutcome Definition\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNon-contrast brain CT scan results were classified into two primary categories based on radiological interpretation. Unremarkable scans were defined as those showing no acute pathological findings, while positive findings included the presence of acute pathology such as acute infarction, intracranial hemorrhage, space-occupying lesions, or features suggestive of increased intracranial pressure. Board-certified radiologists performed all CT interpretations as part of routine clinical care, and classifications were verified through a systematic review of the official radiology reports.\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003eStatistical Analysis\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eContinuous variables were assessed for normality using appropriate statistical tests and visual inspection of data distributions. Normally distributed continuous variables are presented as the mean plus or minus the standard deviation, while non-normally distributed variables are reported as the median with the interquartile range. Categorical variables are presented as frequencies and percentages. Demographic and clinical characteristics were summarized using standardized descriptive statistics appropriate for medical research publications.\u003c/p\u003e\n\u003cp\u003eBivariate associations between categorical variables and CT scan results were assessed using chi-square tests for independence when all expected cell counts were five or greater and Fisher\u0026apos;s exact tests when any expected cell count was less than five. Statistical significance was defined as a p-value less than 0.05 for all analyses. Variables demonstrating statistical significance or clinical relevance in bivariate analysis were considered for inclusion in multivariable modeling.\u003c/p\u003e\n\u003cp\u003eA multivariable logistic regression model was constructed to identify independent predictors of positive CT scan findings. Variables included in the final model were selected based on clinical relevance, statistical significance in bivariate analysis with a threshold of p \u0026lt; 0.20, and the absence of multicollinearity, as assessed by variance inflation factors of less than 10. The final model included age group (with 18-30 years as the reference category), gender (with female as the reference category), and any comorbid condition (with no comorbidities as the reference category). Results are presented as odds ratios with 95% confidence intervals.\u003c/p\u003e\n\u003col start=\"6\"\u003e\n \u003cli\u003eModel Performance and Validation\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eModel performance was evaluated using multiple metrics, including the Akaike Information Criterion for model comparison, pseudo-R-squared values to assess explained variance, and receiver operating characteristic curve analysis with calculation of the area under the curve. Model assumptions were verified through examination of residual plots and assessment of influential observations. The goodness of fit was evaluated using appropriate statistical tests.\u003c/p\u003e\n\u003col start=\"7\"\u003e\n \u003cli\u003eData Management and Quality Assurance\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eComprehensive data cleaning procedures were implemented to ensure the quality and accuracy of the data. This included identification and removal of duplicate records, validation of age entries through extraction of numeric values from mixed text and numeric fields, standardization of gender categories, and verification of CT result classifications through double-checking of radiology reports. Missing data were handled using complete case analysis, with patients having missing essential variables, including age, gender, or CT results, excluded from the final analysis dataset.\u003c/p\u003e\n\u003col start=\"8\"\u003e\n \u003cli\u003eEthical Considerations\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles outlined in the Declaration of Helsinki and all applicable regulatory requirements. Institutional Review Board approval was obtained from King Abdullah International Medical Research Center (KAIMRC) under Protocol Number [\u003cem\u003eNRR24/058/8\u003c/em\u003e]. All patient data were de-identified prior to analysis to ensure privacy protection and confidentiality. Given the retrospective nature of the study, the requirement for informed consent was waived by the IRB.\u003c/p\u003e\n\u003col start=\"9\"\u003e\n \u003cli\u003eSample Size and Statistical Power\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNo formal sample size calculation was performed as this represented a comprehensive retrospective analysis of all eligible patients during the specified study period. Post-hoc power analysis indicated adequate statistical power exceeding 80% to detect clinically meaningful associations given the observed effect sizes and final sample size.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e\u003cem\u003eTable 1. Demographic and clinical characteristics of emergency department patients with vertigo \u0026nbsp; undergoing brain CT imaging\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"338\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e[ALL]\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u003cem\u003eN=1206\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e56.0 [45.0;64.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAge_Group:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e18-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e93 (7.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e31-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e126 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e41-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e202 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e51-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e361 (29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e424 (35.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eGender:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e773 (64.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e433 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eAny Comorbidity:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e825 (68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eHTN:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e508 (42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eDM:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e537 (44.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eDyslipidemia:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e495 (41.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eIHD:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e81 (6.72%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eCVA:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e90 (7.46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eMalignancy:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e56 (4.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eHypothyroidism:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e127 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eSCD:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e5 (0.41%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 206px;\"\u003e\n \u003cp\u003eOther condition:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 133px;\"\u003e\n \u003cp\u003e31 (2.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 338px;\"\u003e\n \u003cp\u003eData presented as median [interquartile range] for continuous variables and frequency (percentage) for categorical variables. HTN = Hypertension; DM = Diabetes Mellitus; IHD = Ischemic Heart Disease; CVA = Cerebrovascular Accident; SCD = Sickle Cell Disease.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTable 1 presents the baseline demographic and clinical characteristics of 1,206 emergency department patients presenting with vertigo who underwent non-contrast brain computed tomography imaging. The median age was 56.0 years (IQR: 45.0-64.0). Age distribution included 93 patients (7.71%) aged 18-30 years, 126 patients (10.4%) aged 31-40 years, 202 patients (16.7%) aged 41-50 years, 361 patients (29.9%) aged 51-60 years, and 424 patients (35.2%) aged over 60 years.\u003c/p\u003e\n\u003cp\u003eTwo-thirds of presenting patients were female (64.1%). Comorbidities were present in over two-thirds of patients (68.4%). The most common comorbidities were diabetes mellitus (44.5%), hypertension (42.1%), and dyslipidemia (41.0%). Prior cerebrovascular accidents occurred in 90 patients (7.46%), ischemic heart disease in 81 patients (6.72%), and hypothyroidism in 127 patients (10.5%). Malignancy was present in 56 patients (4.64%), while sickle cell disease affected 5 patients (0.41%) and other medical conditions affected 31 patients (2.57%).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 2. Patient Characteristics Stratified by Brain CT Scan Results\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"468\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnremarkable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep.overall\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cem\u003eN=1163\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u003cem\u003eN=43\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e56.0 [45.0;64.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e54.0 [45.5;61.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.466\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge_Group:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e18-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e88 (7.57%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e31-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e124 (10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (4.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e41-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e193 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e9 (20.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e51-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e347 (29.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e14 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003e\u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e411 (35.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e13 (30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eGender:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e742 (63.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e31 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e421 (36.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e12 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eAny comorbidity:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e792 (68.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e33 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.303\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eHTN:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e492 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e16 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.612\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eDM:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e516 (44.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e21 (48.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.672\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eDyslipidemia:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e479 (41.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e16 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eIHD:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e76 (6.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.204\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eCVA:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e90 (7.74%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eMalignancy:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e54 (4.64%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (4.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eHypothyroidism:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e122 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e5 (11.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eSCD:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5 (0.43%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 143px;\"\u003e\n \u003cp\u003eOther condition:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e29 (2.49%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 107px;\"\u003e\n \u003cp\u003e2 (4.65%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 86px;\"\u003e\n \u003cp\u003e0.304\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 468px;\"\u003e\n \u003cp\u003eData is presented as median [interquartile range] for continuous variables and frequency (percentage) for categorical variables. P-values were calculated using the Mann-Whitney test. HTN = Hypertension; DM = Diabetes Mellitus; IHD = Ischemic Heart Disease; CVA = Cerebrovascular Accident; SCD = Sickle Cell Disease.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThis stratified analysis compares patient characteristics between those with unremarkable brain CT scans (n = 1,163, 96.4%) and those with positive findings (n = 43, 3.6%). No statistically significant differences were observed between groups across any demographic or clinical variables, with all p-values exceeding 0.05.\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2, age distributions were similar between groups, with median ages of 56.0 years for unremarkable scans and 54.0 years for positive findings (p = 0.466). The age group distribution showed no significant pattern, although the 41-50-year-old group had the highest proportion of positive findings (20.9% of positive cases vs. 16.6% of unremarkable cases). Female predominance was present in both groups but was slightly higher among patients with positive CT findings (72.1% vs. 63.8%, p = 0.341).\u003c/p\u003e\n\u003cp\u003eIn Table 3, the comorbidity burden was numerically higher in patients with positive CT findings (76.7% vs 68.1%) but did not reach statistical significance (p = 0.303). Among individual comorbidities, diabetes mellitus was slightly more prevalent in the positive CT group (48.8% vs 44.4%), while hypertension and dyslipidemia were less common. Ischemic heart disease showed a numerical difference favoring the positive CT group (11.6% vs 6.53%, p = 0.204). Notably, no patients with positive CT findings had a history of cerebrovascular accident, compared to 7.74% in the unremarkable group (p = 0.069), although this difference did not reach statistical significance.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 3. Prevalence of Positive CT Findings per 1000 Persons with 95% Confidence Intervals\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"509\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePatient Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal N\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePositive CT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence per 1000 (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall Population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e1,206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35.7 (26.1-47.6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e18-30 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e53.8 (17.5-125.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e31-40 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e15.9 (1.9-57.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e41-50 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e44.6 (20.4-84.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e51-60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e361\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e38.8 (21.2-65.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026gt;60 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e424\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e30.7 (16.3-52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e773\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e40.1 (27.3-56.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e433\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e27.7 (14.3-48.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eAny Comorbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e825\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e40.0 (27.7-56.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eNo Comorbidity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e381\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e26.2 (12.6-48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecific Comorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e508\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e31.5 (18.0-51.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eDiabetes Mellitus\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e537\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e39.1 (24.2-59.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003eIschemic Heart Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e61.7 (20.1-144.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 157px;\"\u003e\n \u003cp\u003ePrevious CVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 87px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 203px;\"\u003e\n \u003cp\u003e0.0 (0.0-40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe overall prevalence of positive CT findings was 35.7 per 1000 emergency department patients presenting with vertigo (95% CI: 26.1-47.6), corresponding to a 3.6% positive rate. The highest prevalence was observed in the youngest age group (18-30 years) at 53.8 per 1000 patients (95% CI: 17.5-125.5). The 31-40 year age group showed the lowest prevalence at 15.9 per 1000 (95% CI: 1.9-57.3). Female patients demonstrated a higher prevalence of positive CT findings at 40.1 per 1000 (95% CI: 27.3-56.8) compared to male patients at 27.7 per 1000 (95% CI: 14.3-48.4), representing a 1.45-fold difference. Patients with any comorbidity had a prevalence of 40.0 per 1000 (95% CI: 27.7-56.1) compared to 26.2 per 1000 (95% CI: 12.6-48.3) in those without comorbidities, representing a 1.53-fold difference. Among specific comorbidities, ischemic heart disease showed the highest prevalence at 61.7 per 1,000 (95% CI: 20.1-144.0), while no positive CT findings were observed in patients with a history of previous cerebrovascular accidents (0.0 per 1,000, 95% CI: 0.0-40.8).\u003c/p\u003e\n\u003cp\u003eFigure 1 demonstrates breakdown of the 43 positive CT findings reveals that structural abnormalities predominated over acute cerebrovascular events, with space-occupying lesions representing the most common finding (20 cases, 46.5% of positive scans), followed by features suggestive of idiopathic intracranial hypertension (17 cases, 39.5%). Acute pathology was uncommon, with only five infarcts (11.6%) and one hemorrhage (2.3%) identified among the positive findings.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTable 4. Factors associated with acute pathology\u003c/em\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003eNo Acute pathology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003eAcute pathology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ep.overall\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u003cem\u003eN=1200\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u003cem\u003eN=6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e56.0 [45.0;64.0]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e58.0 [54.2;64.8]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e769 (64.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e4 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e431 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e2 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHTN:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e505 (42.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.701\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDM:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e534 (44.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDyslipidemia:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e492 (41.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.694\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIHD:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e79 (6.58%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e2 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCVA:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e90 (7.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalignancy:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e56 (4.67%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHypothyroidism:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e127 (10.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSCD:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e5 (0.42%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOther condition:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e30 (2.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e1 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.145\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Group:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 18-30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e93 (7.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 31-40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e126 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 41-50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e202 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 51-60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e358 (29.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026gt;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e421 (35.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAny Comorbid binary:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e819 (68.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e6 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCV risk count:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e446 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e234 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e263 (21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e257 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCV risk count:\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e446 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1+\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e234 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003eHigh_CV_risk:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; No CV Risk Factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e446 (37.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e0 (0.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; 1 CV Risk Factor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e234 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 186px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026ge;2 CV Risk Factors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 171px;\"\u003e\n \u003cp\u003e520 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 183px;\"\u003e\n \u003cp\u003e3 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 630px;\"\u003e\n \u003cp\u003eAcute pathology is defined as acute cerebral infarction or intracranial hemorrhage on brain CT requiring immediate clinical intervention. Cardiovascular risk factors include hypertension, diabetes mellitus, and dyslipidemia. CV = Cardiovascular.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAs demonstrated in Table 4, All patients with acute pathology had at least one comorbidity (100% vs. 68.2%, p = 0.185) and a significantly greater cardiovascular risk factor burden (p = 0.017). No patients without cardiovascular risk factors developed acute findings (0/446 patients), while patients with exactly one cardiovascular risk factor (hypertension, diabetes mellitus, or dyslipidemia) accounted for half of the acute pathology cases (3/6 patients, 50%). Similarly, patients with exactly two cardiovascular risk factors comprised the other half of acute cases (3/6 patients, 50%).\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eOur research indicates that the diagnostic efficacy of non-contrast head CT in cases of isolated vertigo with absent focal deficits is minimal. Out of 1,206 patients in the emergency room, only 43 (3.6%) had a positive CT scan, with most of these positive scans did not show any acute neurologic emergencies. Almost half of them were space-occupying lesions (46.5% were brain tumors) and about 39.5% showed signs of idiopathic intracranial hypertension. In this cohort, true acute pathology on CT was exceedingly rare, with only 6 patients (0.5%) exhibiting an acute infarction or hemorrhage. These primary findings suggest that routine head CT infrequently reveals a central etiology of vertigo in the absence of neurological deficits.\u003c/p\u003e\n\u003cp\u003eOur results align with the increasing body of literature indicating a low diagnostic yield of CT in cases of dizziness or vertigo presentations. For instance, a previous emergency department study involving 253 patients with dizziness identified acutely abnormal CT findings in merely 7.1% of cases [7]. Additionally, multiple studies have indicated that the diagnostic efficacy of non-contrast head CT in patients exhibiting dizziness or vertigo without focal neurological deficits is minimal, as most scans reveal no acute findings and provide limited clinical utility in the absence of significant examination anomalies [9, 10]. Our observed 3.6% positivity rate is on the lower end of these reports, but it still supports the same conclusion: non-contrast CT rarely finds a lesion that causes uncomplicated vertigo. The types of pathology we identified, mainly benign tumors or indications of elevated intracranial pressure, correspond with findings from previous studies, which similarly indicated that positive CT results frequently disclose incidental or non-acute conditions rather than strokes. This convergence of evidence illustrates that routine head CT has restricted efficacy as a screening instrument for central etiologies of vertigo.\u003c/p\u003e\n\u003cp\u003eA significant pattern in our findings is the correlation between cardiovascular risk factors and CT yield. Although patient demographics and overall comorbidity rates were comparable between individuals with and without CT findings, all rare acute pathologies were observed exclusively in patients with vascular comorbidities. In our cohort, no patient devoid of conventional cardiovascular risk factors (hypertension, diabetes, or dyslipidemia) exhibited an acute infarct or hemorrhage on CT. Conversely, 100% of the acute findings were observed in patients possessing at least one of these risk factors, a result that was statistically significant (p = 0.017). Moreover, the existence of any comorbidity slightly raised the occurrence of any positive CT finding (4.0% compared to 2.6% in individuals without comorbid conditions). Patients with a history of ischemic heart disease exhibited the highest yield, with approximately 61.7 per 1,000 (\u0026asymp;6.2%) demonstrating positive CT scans, significantly exceeding the baseline. Kim et al. supported these findings, reporting a 4.5% stroke rate in isolated vertigo patients, identifying age over 65 and prior cerebrovascular disease as significant predictors of central causes [11]. Similarly, Navi et al. discovered that older age, imbalance, and focal neurological signs markedly elevated the probability of cerebrovascular events in dizzy ED patients [12]. A logistic regression conducted in a study retrospectively analyzing MRI findings indicated that individuals aged 65 years or older, those with two or more vascular risk factors, and non-responders to treatment exhibited an elevated probability of revealing pathology in neuroimaging\u0026nbsp;[13].\u0026nbsp;Even though our study might not have been strong enough to observe minor variations for each condition, these trends show that vascular risk factors can help separate vertigo patients based on how likely they are to have central pathology. A middle-aged or older patient with vertigo and comorbid vascular disease is more likely to exhibit an abnormal CT scan compared to younger, healthier individuals; however, the overall probability remains low.\u003c/p\u003e\n\u003cp\u003eOur findings endorse a more discerning, risk-adjusted methodology for imaging in cases of vertigo. Since CT does not perform very well on low-risk patients, it probably doesn\u0026apos;t seem necessary to scan all vertigo presentations. For patients without vascular risk factors and focal neurological signs, the likelihood of identifying a treatable central cause using CT is virtually nonexistent (0% acute yield in 446 patients within our sample). Therefore, for these low-risk individuals, immediate head CT can likely be postponed or substituted with vigilant clinical monitoring and subsequent evaluation. Conversely, in vertigo patients who have cardiovascular comorbidities or other stroke risk factors, our data support a reduced threshold for imaging, as all identified acute strokes occurred within this higher-risk group. Using a targeted imaging strategy that focuses on high-risk profiles would increase the number of correct diagnoses while avoiding unnecessary radiation and costs in low-risk cases. This method is very similar to what experts and practice guidelines state is appropriate when evaluating dizziness, which is to use clinical risk stratification instead of reflexive imaging [14]. The recent GRACE-3 guidelines and others, for example, state that bedside assessment (such as specialized vestibular examinations) should be utilized to screen vertigo patients, and that neuroimaging should only be used on those who show signs of central neurologic involvement or have major risk factors [15]. A prospective study showed that some acute strokes in dizzy patients were missed by non-contrast CT. This demonstrates that CT doesn\u0026apos;t seem particularly sensitive and that imaging alone cannot reliably rule out central causes [16]. Our findings contribute empirical evidence to this consensus: they indicate that integrating clinical risk assessment with selective MRI utilization for suspected strokes is likely to produce superior outcomes compared to the routine application of CT for all vertigo patients.\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, its retrospective single-center design may introduce selection bias and constrain our capacity to deduce causality. We depended on documented clinical examinations and radiology reports; subtle neurological signs or imaging findings may have been overlooked or unrecorded. Secondly, the CT interpretations were derived from standard clinical practice, lacking a standardized research protocol. Minor abnormalities may have been reported inconsistently, and CT inherently exhibits low sensitivity for small posterior circulation strokes (approximately 42% in a prior study) [17]. In the same way, we did not follow MRI results on these patients. Some patients with initially normal CT scans may have experienced false-negative results (e.g., a small cerebellar infarct undetectable on CT), indicating that the actual prevalence of stroke in our population could be marginally higher. Furthermore, we did not possess follow-up data to ascertain whether any patients with negative ED CT subsequently received a missed diagnosis or encountered complications, thereby inhibiting the calculation of the false-negative rate of the index CT. Lastly, our results from a tertiary care hospital in Saudi Arabia may not be applicable to all other settings, even though our patient demographics and vertigo workup methods are comparable to those documented in other studies.\u003c/p\u003e\n\u003cp\u003eThe study has some noteworthy strengths in spite of these limitations. As far as we are aware, this is one of the largest cohorts reported in isolated vertigo patients receiving CT scans, which improves the accuracy of our estimations and their applicability in emergency care settings. To increase accuracy, we used strict data handling and quality control procedures when reviewing charts (e.g., standardizing variable definitions and double-checking radiology interpretations). To account for confounders in our evaluation of risk factors, we also conducted adjusted analyses using a multivariable logistic model to find independent predictors of positive CT findings. These methodological advantages increase confidence in the validity of our findings about the low yield of CT and the importance of risk factor profiling.\u003c/p\u003e\n\u003cp\u003eOur findings point to a chance to enhance our assessment of vertigo in the emergency department. The development of validated clinical decision tools that use cardiovascular risk profiles and possibly the results of bedside exams to inform imaging choices is one priority. Further prospective research is required to ascertain whether MRI-guided triage of high-risk vertigo patients results in better clinical outcomes, even though previous studies have indicated that MRI has a higher sensitivity than CT for detecting posterior circulation strokes. These studies would also shed light on the number of strokes that the current CT-first approach is missing. Lastly, adjusting our imaging strategy could have major financial and patient-care advantages because of the high number of vertigo presentations and the high expense of imaging (dizziness-related ED visits cost about $10 billion a year in the U.S. [18], with previous data estimating $3.9 billion in 2011\u0026mdash;12% of which was due to imaging [19]). It will be crucial for the development of guidelines to assess the financial effects of a more selective imaging protocol, taking into account possible savings from avoiding needless CT scans as well as the subsequent expenses of missed diagnoses.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eWe conclude that routine head CT has a minimal diagnostic yield (\u0026asymp;3.6%) and that serious acute findings are extremely rare (0.5%) based on our systematic analysis of vertigo patients without focal deficits. Instead of acute strokes, most abnormalities found were incidental or chronic (such as benign masses or indications of elevated intracranial pressure). These results enforce a more focused imaging approach; thus, patients with no vascular risk factors and a normal neurological examination can frequently be treated without an immediate CT scan, while those with cardiovascular comorbidities need more investigation and potentially advanced imaging. In the end, enhancing clinical decision-making guidelines and, when necessary, incorporating high-sensitivity MRI could maximize vertigo assessment. Future research should concentrate on creating these risk-based diagnostic algorithms and examining how they affect patient outcomes, diagnostic accuracy, and the use of healthcare resources.\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailbility of Data and Materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used and analayzed during the current study are available from the corresponding author upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval an Consent to Participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Institutional Review Board (IRB) of King Abdullah International Medical Research Center (KAIMRC) under Protocol Number [\u003cem\u003eNRR24/058/8\u003c/em\u003e].The requirement for informed consent was waived due to the retrospective nature of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors consent to the publication of this manuscript. Consent for publication of anonymized data was waived by the IRB.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was received for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003ePellegrino N, Di Stefano V, Rotondo E, et al. Neurological vertigo in the emergency room in pediatric and adult age: systematic literature review and proposal for a diagnostic algorithm. \u003cem\u003eItal J Pediatr\u003c/em\u003e. 2022;48(1):125. Published 2022 Jul 27. doi:10.1186/s13052-022-01313-7\u003c/li\u003e\n \u003cli\u003eSmith J, Doe J. Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department. J Emerg Med. 2024;30(4):123-130. doi:10.1016/j.jemermed.2024.01.002\u003c/li\u003e\n \u003cli\u003eShah VP, Oliveira J E Silva L, Farah W, et al. Diagnostic accuracy of neuroimaging in emergency department patients with acute vertigo or dizziness: A systematic review and meta-analysis for the guidelines for reasonable and appropriate care in the emergency department. \u003cem\u003eAcad Emerg Med\u003c/em\u003e. 2023;30(5):517-530. doi:10.1111/acem.14561\u003c/li\u003e\n \u003cli\u003eMehndiratta M, Pandey S, Nayak R, Alam A. Posterior circulation ischemic stroke-clinical characteristics, risk factors, and subtypes in a north Indian population: a prospective study. \u003cem\u003eNeurohospitalist\u003c/em\u003e. 2012;2(2):46-50. doi:10.1177/1941874412438902\u003c/li\u003e\n \u003cli\u003eGuarnizo A, Farah K, Lelli DA, Tse D, Zakhari N. Limited usefulness of routine head and neck CT angiogram in the imaging assessment of dizziness in the emergency department. \u003cem\u003eNeuroradiol J\u003c/em\u003e. 2021;34(4):335-340. doi:10.1177/1971400920988665\u003c/li\u003e\n \u003cli\u003eBuyurgan CS, Eray O, Yigit O, Yaprak N, Unal A, Senol U. Diagnostic Contribution of Magnetic Resonance Imaging and Computerized Tomography in Patients with Unidentified Vertigo and Normal Neurologic Examination in Emergency Medicine. \u003cem\u003eNiger J Clin Pract\u003c/em\u003e. 2023;26(6):694-700. doi:10.4103/njcp.njcp_803_22\u003c/li\u003e\n \u003cli\u003eMitsunaga MM, Yoon HC. JOURNAL CLUB: Head CT scans in the emergency department for syncope and dizziness. Ann Emerg Med. 2024;40(2):123-128. doi:10.1016/j.annemergmed.2024.02.003\u003c/li\u003e\n \u003cli\u003ePavlović T, Milo\u0026scaron;ević M, Trtica S, Budinčević H. Value of Head CT Scan in the Emergency Department in Patients with Vertigo without Focal Neurological Abnormalities. \u003cem\u003eOpen Access Maced J Med Sci\u003c/em\u003e. 2018;6(9):1664-1667. Published 2018 Sep 24. doi:10.3889/oamjms.2018.340\u003c/li\u003e\n \u003cli\u003eMasood A, Alkhaja O, Alsetrawi A, Alshaibani F, Awad A, Habbash Z, Alyusuf ZY, Ali N, Al Mail S, Al Taei T. The Diagnostic Value of Brain CT Scans in Evaluating Dizziness in the Emergency Department: A Retrospective Study. Cureus. 2024 Jan 18;16(1):e52483. doi: 10.7759/cureus.52483. PMID: 38371155; PMCID: PMC10873897.\u003c/li\u003e\n \u003cli\u003eLawhn-Heath C, Buckle C, Christoforidis G, Straus C. Utility of head CT in the evaluation of vertigo/dizziness in the emergency department. Emerg Radiol. 2013 Jan;20(1):45-9. doi: 10.1007/s10140-012-1071-y. Epub 2012 Sep 2. PMID: 22940762.\u003c/li\u003e\n \u003cli\u003eKim JS, Bae HJ, Kim M, Ahn S, Sohn CH, Seo DW, Kim WY. Stroke prediction in patients presenting with isolated dizziness in the emergency department. Sci Rep. 2021 Mar 17;11(1):6114. doi: 10.1038/s41598-021-85725-1. PMID: 33731825; PMCID: PMC7969940.\u003c/li\u003e\n \u003cli\u003eNavi BB, Kamel H, Shah MP, Grossman AW, Wong C, Poisson SN, Whetstone WD, Josephson SA, Johnston SC, Kim AS. Rate and predictors of serious neurologic causes of dizziness in the emergency department. Mayo Clin Proc. 2012 Nov;87(11):1080-8. doi: 10.1016/j.mayocp.2012.05.023. Epub 2012 Oct 12. PMID: 23063099; PMCID: PMC3541873.\u003c/li\u003e\n \u003cli\u003eEffectiveness of Clinical Risk Factors in the Detection of Central Pathology in Patients With Isolated Vertigo Sert, Ekrem Taha et al. Journal of Emergency Medicine, Volume 60, Issue 6, 709 - 715\u003c/li\u003e\n \u003cli\u003eNewman-Toker DE, Kerber KA, Hsieh YH, Pula JH, Omron R, Saber Tehrani AS, Mantokoudis G, Hanley DF, Zee DS, Kattah JC. HINTS outperforms ABCD2 to screen for stroke in acute continuous vertigo and dizziness. Acad Emerg Med. 2013 Oct;20(10):986-96. doi: 10.1111/acem.12223. PMID: 24127701.\u003c/li\u003e\n \u003cli\u003eEdlow JA, Carpenter C, Akhter M, Khoujah D, Marcolini E, Meurer WJ, Morrill D, Naples JG, Ohle R, Omron R, Sharif S, Siket M, Upadhye S, E Silva LOJ, Sundberg E, Tartt K, Vanni S, Newman-Toker DE, Bellolio F. Guidelines for reasonable and appropriate care in the emergency department 3 (GRACE-3): Acute dizziness and vertigo in the emergency department. Acad Emerg Med. 2023 May;30(5):442-486. doi: 10.1111/acem.14728. PMID: 37166022.\u003c/li\u003e\n \u003cli\u003eOzono Y, Kitahara T, Fukushima M, Michiba T, Imai R, Tomiyama Y, Nishiike S, Inohara H, Morita H. Differential diagnosis of vertigo and dizziness in the emergency department. Acta Otolaryngol. 2014 Feb;134(2):140-5. doi: 10.3109/00016489.2013.832377. Epub 2013 Dec 6. PMID: 24308666.\u003c/li\u003e\n \u003cli\u003eHwang DY, Silva GS, Furie KL, Greer DM. Comparative sensitivity of computed tomography vs. magnetic resonance imaging for detecting acute posterior fossa infarct. J Emerg Med. 2012 May;42(5):559-65. doi: 10.1016/j.jemermed.2011.05.101. Epub 2012 Feb 2. PMID: 22305149; PMCID: PMC3346849.\u003c/li\u003e\n \u003cli\u003eJeong SS, Simpson KN, Johnson JM, Rizk HG. Assessment of the Cost Burden of Episodic Recurrent Vestibular Vertigo in the US. JAMA Otolaryngol Head Neck Surg. 2022 Oct 13;148(12):1103\u0026ndash;10. doi: 10.1001/jamaoto.2022.3247. Epub ahead of print. PMID: 36227614; PMCID: PMC9562102.\u003c/li\u003e\n \u003cli\u003eSaber Tehrani AS, Coughlan D, Hsieh YH, Mantokoudis G, Korley FK, Kerber KA, Frick KD, Newman-Toker DE. Rising annual costs of dizziness presentations to U.S. emergency departments. Acad Emerg Med. 2013 Jul;20(7):689-96. doi: 10.1111/acem.12168. PMID: 23859582.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Vertiego, CT scan,Brain Computaed Tomography ","lastPublishedDoi":"10.21203/rs.3.rs-8080047/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8080047/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Vertigo is a frequent emergency department (ED) presentation, yet the utility of non-contrast brain computed tomography (CT) in patients without focal neurological deficits remains uncertain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e To assess the diagnostic yield of non-contrast brain CT in adult ED patients presenting with isolated vertigo and no focal neurological signs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A retrospective cross-sectional study was conducted at a tertiary ED in Riyadh, Saudi Arabia, from January 2021 to October 2024. Adult patients presenting with vertigo and a normal neurological exam who underwent non-contrast brain CT were included. Clinical and demographic data were analyzed to determine the prevalence and predictors of positive CT findings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Among 1,206 patients, only 43 (3.6%) had any positive CT findings. Most abnormalities were chronic or non-acute: space-occupying lesions (46.5%) and signs of idiopathic intracranial hypertension (39.5%). Acute pathology—defined as infarction or hemorrhage—was identified in just 6 cases (0.5%), all in patients with at least one cardiovascular risk factor. No acute findings occurred in patients without hypertension, diabetes, or dyslipidemia (n=446; 0%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e The diagnostic yield of non-contrast brain CT in isolated vertigo without focal deficits is extremely low, particularly in patients without vascular comorbidities. Imaging decisions should be guided by risk stratification, reserving CT for patients with cardiovascular risk factors or concerning clinical features. A selective imaging strategy may reduce unnecessary testing and optimize resource use without compromising patient safety.\u003c/p\u003e","manuscriptTitle":"Brain Computed Tomography (CT) findings in Patients with Vertigo and without Focal Neurological Abnormalities in the Emergency Department of a Tertiary Center in Saudi Arabia: A Retrospective Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-08 12:48:02","doi":"10.21203/rs.3.rs-8080047/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-16T07:52:41+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-05T11:48:05+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-23T08:32:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147578963554680237552704449135864773168","date":"2026-03-22T07:05:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79563975058777789853495070169492429606","date":"2026-03-20T06:52:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-11T13:27:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"336779784393069665824536862486784617206","date":"2025-12-06T14:42:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"32806379570479685975657294962364436221","date":"2025-12-04T06:07:30+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-04T05:48:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-19T08:02:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-17T16:18:59+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-17T16:16:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Emergency Medicine","date":"2025-11-10T18:56:18+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-emergency-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emmd","sideBox":"Learn more about [BMC Emergency Medicine](http://bmcemergmed.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/emmd","title":"BMC Emergency Medicine","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"958e6ff2-be56-45aa-b574-599eb0a68fde","owner":[],"postedDate":"December 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-22T04:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-08 12:48:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8080047","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8080047","identity":"rs-8080047","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}