Associations between COVID-19 symptoms, chest X-Ray, and patient characteristics: A Comprehensive Analysis

Associations between COVID-19 symptoms, chest X-Ray, and patient characteristics: A Comprehensive Analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Associations between COVID-19 symptoms, chest X-Ray, and patient characteristics: A Comprehensive Analysis Abdullah Awadh, Abdulrahman Alomari, Abdulrahman Almassrahy, Omar Hassan, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8125393/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background : COVID-19 pneumonia has diverse clinical, radiographic, and prognostic characteristics. Understanding the interactions between patient demographics, comorbidities, symptoms, imaging findings and outcomes is essential for clinical management. Objectives : This study explored the correlations between demographics, comorbidities, clinical presentation, chest imaging findings, and clinical outcomes in patients with COVID-19 pneumonia. Methods : This retrospective study included 293 patients with confirmed COVID-19 pneumonia. Clinical data and radiographic findings from initial and follow-up chest X-ray (CXR) images were analyzed, focusing on consolidation, ground-glass opacities, pleural effusion, and lobar distributions. Associations were examined using statistical tests, with p<0.05 considered to be significant. Results : Patients were predominantly male (57%) with a median age of 57 years. Common symptoms included fever (68%), cough (68%), and shortness of breath (62%). Diabetes (44%) and hypertension (45%) were the most common comorbidities. Initial radiographs showed consolidation (56%) and ground-glass opacities (51%), mainly in the bilateral lower lobes. Follow-up imaging revealed increased pleural effusion (9% to 85%) and bilateral involvement (37% to 53%). The ground-glass opacities increased to 62%. Significant associations were observed between higher BMI and multiple symptoms and between pneumonia severity and clinical symptoms (p<0.001). Diabetes was correlated with diarrhea (p=0.035), and asthma was correlated with headache (p=0.010). Severe pneumonia was correlated with increased radiographic abnormalities and worse outcomes, with a mortality rate of 14 %. Conclusion : This study examined the radiographic findings in COVID-19 pneumonia and their correlation with clinical manifestations and comorbidities. Chest imaging is crucial for monitoring disease progression in severe cases. COVID-19 pneumonia radiographic symptoms comorbidities Ches X-ray Introduction In late 2019, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) originated in China and swiftly spread across the globe, resulting in the coronavirus disease 19 (COVID-19) pandemic. The clinical manifestations of the disease vary from no symptoms to respiratory and/or systemic symptoms (Huang et al., 2020). COVID-19 is a severe acute respiratory syndrome that has caused a major ongoing global pandemic (Sharma et al., 2020). The COVID-19 pandemic has posed unprecedented challenges to healthcare systems worldwide, necessitating rapid advancements in diagnostic and prognostic tools (Filip et al., 2022). As of April 13, 2025, there have been over 777,720,205 confirmed cases and more than 7,094,447 deaths worldwide, ranking COVID-19 as the fifth deadliest pandemic in history (World Health Organization, 2025; Ding et al., 2025). Among these, chest X-rays (CXRs) have emerged as a valuable resource for the assessment and management of COVID-19 patients (Abougazia et al., 2021). Radiographic imaging allows healthcare providers to visualize the extent of lung involvement, which can be a key indicator of disease severity (Slika et al., 2024). While RT-PCR testing remains the gold standard for confirming COVID-19 infection, CXRs provide valuable supplementary information that can guide clinical decision-making, particularly in resource-limited settings where rapid testing may not be available (Loeffelholz and Tang, 2020; Ferrinho et al., 2020; Kevadiya et al., 2021). The role of CXRs in COVID-19 diagnosis extends beyond the initial detection. They are instrumental in monitoring disease progression and assessing treatment effectiveness (AIMohimeed et al., 2023). For patients presenting with respiratory symptoms, an initial CXR is crucial for identifying and evaluating the extent of pulmonary infiltrates indicative of viral pneumonia (Rousan et al., 2020). In cases of COVID-19, radiographic images display specific patterns that correspond to the severity and progression of the disease (Karacan and Aksoy, 2021). A commonly observed feature in these X-rays is bilateral peripheral ground-glass opacities (GGOs) (Cozzi et al., 2021). These opacities represent areas of increased lung attenuation, indicating inflammation and fluid accumulation (Cozzi et al., 2018). GGOs typically manifest in the early stages of infection and may progress to more extensive consolidation as the disease advances (Wang et al., 2020; Cozzi et al., 2021). In addition to ground-glass opacities (GGOs), CXRs can reveal patchy or confluent consolidations that appear as denser opaque regions (Wong et al., 2020). These consolidations are typically situated in the lower lung zones and indicate severe pulmonary involvement (Hatabu et al., 2020). The presence of such consolidations is associated with an increased likelihood of requiring mechanical ventilation and intensive care. It is imperative for radiologists and clinicians to recognize these patterns and understand their implications for patient management and prognosis (Brandi et al., 2022; Bianchini et al., 2025). The correlation between COVID-19 symptoms and CXR findings is a critical area of research that can provide valuable insights into disease severity and progression. Studies have demonstrated that patients with severe respiratory symptoms, such as dyspnea and hypoxemia, often present with more pronounced radiographic abnormalities (Santus et al., 2023). For instance, individuals experiencing significant shortness of breath are more likely to exhibit extensive GGOs and consolidation on CXRs, indicative of severe pulmonary involvement (Cozzi et al., 2021). Clinical and demographic factors are significantly associated with radiographic outcomes (AI-Smadi et al., 2021). Research indicates a correlation between abnormal CXRs findings and the presence of symptoms, with a substantial majority (92.3%) of patients with radiographic anomalies also exhibiting symptoms (Rousan et al., 2020). Further investigations have explored the relationship between deteriorating CXR results and prognostic outcomes, identifying radiographic progression as a potential indicator of disease severity and clinical trajectory (Wang et al., 2020; Rousan et al., 2020). Conversely, individuals with mild or asymptomatic COVID-19 may show minimal or no radiographic changes (Meng et al., 2020). This variability underscores the necessity of integrating clinical assessments with imaging findings to achieve a comprehensive understanding of a patient's condition (Huang et al., 2020). In certain cases, CXRs may reveal abnormalities even in the absence of severe symptoms, suggesting subclinical disease that could potentially progress without timely intervention if not detected. This underscores the importance of vigilant monitoring and a proactive approach to patient management (Yasin and Gouda, 2020). This study aimed to explore the intricate relationships between clinical symptoms, radiological findings, and individual patient characteristics in the context of COVID-19. Through this analysis, we sought to enhance our understanding of the manifestations of this disease and potentially improve patient care strategies. This comprehensive investigation may provide valuable insights for clinicians in their decision-making processes and contribute to the growing body of knowledge on this novel coronavirus. Methodology Study design The current retrospective cross-sectional study investigated the radiological outcomes of pneumonia in patients with RT-PCR-confirmed COVID-19 who were admitted to King Abdulaziz Medical City in Jeddah, Saudi Arabia. The study was conducted between March and October 2020 and included 1,215 patients. To be included, patients needed a positive COVID-19 RT-PCR test and more than one chest X-ray image. Patients were excluded if there was significant missing information or a lack of follow-up. The Raosoft sample size calculator was employed to determine the sample size, utilizing a 95% confidence level and a 5% margin of error, resulting in a sample size of 293 patients. A total of 802 patients were excluded because they did not meet the inclusion criteria, while 413 patients were included in the study. The charts of the 413 selected patients were sequentially numbered from 1 to 413 for entry into a random sample generator. A Research Randomizer was used to generate a random sample of 293 patients. Data collection Data collection was conducted by trained medical students following the approval of the ethical board at King Abdullah International Medical Research Center (KAIMRC) under approval number SP21J-125-03 and was supervised by the primary investigator (PI). Data collection from medical records was facilitated using a structured form created using Microsoft Excel. The data encompassed patient information and demographic details, including age, gender, BMI, education level, occupation, and travel history. Additionally, it included diagnostic information such as COVID-19 status and pneumonia severity, clinical presentation (symptomatic or asymptomatic), and symptoms (fever, headache, cough, shortness of breath, sore throat, general weakness, diarrhea, and vomiting). Comorbidities, including diabetes, hypertension, asthma, ischemic heart disease, and malignancy, were also recorded. Chest X-ray findings were documented, noting consolidation, ground-glass opacity, and pleural effusion, as well as the distribution of these findings (diffuse, right, left, or bilateral lung involvement, peripheral/perihilar/central predominant, and lobar involvement). Finally, clinical outcomes were assessed by categorizing patients as either discharged or deceased. Statistical analysis Parametric methods were used to describe the numerical data, such as age and BMI. Percentages were used to describe categorical variables, including sex, diagnosis, clinical presentation, symptoms, comorbidities, CXR findings, distribution of CXR findings, and clinical outcomes. The Chi-square test was used to compare categorical data, with a P-value of less than 0.05 considered statistically significant. Data analysis was conducted using JMP software (John's Macintosh Project), version 16.0 (SAS Institute Inc., Cary, NC, USA). The survival rate was calculated by dividing the percentage of infected patients who were discharged by the percentage of discharged patients in the general population of the same sex and age group during the same period. Results Baseline demographics characteristics outcome of patients with COVID-19 The demographic and clinical characteristics of 293 patients with COVID-19 pneumonia revealed a correlation between symptoms and chest radiographic disease progression (Table 1) . The cohort (median age 57 years, median BMI 30) comprised 57% males and 43% females. Most patients had mild-to-moderate pneumonia (73%), 21% developed severe forms, and 6% showed no initial radiographic evidence of pneumonia. The predominant symptoms were fever (68%), cough (68%), and shortness of breath (62%). Follow-up CXRs showed increased lobar involvement in patients with persistent respiratory symptoms, particularly in the lower and middle zones of the lungs. Disease progression was more frequent in patients with diabetes (44%) and hypertension (45%) than in those without. These comorbidities are correlated with extensive lung involvement and higher mortality (14%). Patients with ischemic heart disease (14%) and malignancy (9%) commonly presented with systemic symptoms, showing diffuse changes on follow-up radiography. Rare complications included pulmonary embolism (1%) and vein thromboembolism (0.3%), which contributed to worsening hypoxia and radiological deterioration. Symptomatology was strongly associated with radiographic progression, with second CXRs showing increased involvement in patients with persistent symptoms, particularly in those with comorbidities. Radiographic features and anatomical distribution in initial and follow-up chest imaging of patients with COVID-19 pneumonia The radiographic progression of COVID-19 pneumonia was assessed by comparing the first and second chest radiographs of 293 patients (Table 2) . Consolidation was higher in the second chest radiograph (60%) than in the first (56%), suggesting radiologic disease progression. Ground-glass opacities (GGO) increased from 51% to 62%, which is consistent with typical COVID-19 progression. Pleural effusion increased from 9% to 85% in the second radiograph, potentially reflecting disease severity progression or complications such as infections or heart failure. Peripheral predominance was slightly more common in the second chest radiograph (23%) than in the first (22%), whereas central and perihilar patterns remained rare. The diffuse infiltrates increased from 5% to 8%. Bilateral lung involvement increased from 37% to 53% on the second radiograph, showing the bilateral nature of advanced COVID-19 pneumonia. Lower lobe involvement increased from 16% to 24%, with the right lower lobe showing an increase from 7% to 9%. Middle and upper lobe involvement showed smaller increases, consistent with typical COVID-19 pneumonia patterns beginning in the lower lobes. CXR findings of interstitial lung disease were rare (2%) and stable between imaging points. Radiological findings demonstrated progression of pulmonary involvement, with increased consolidation, GGO, bilateral and lower lobe predominance, and pleural effusions, correlating with COVID-19 pneumonia progression. Correlation of COVID-19 Symptoms with Demographic Characteristics and Clinical Outcomes The correlation between COVID-19 symptoms and clinical characteristics revealed notable patterns (Table 3) . Fever, the most prevalent symptom (198 patients, 68%), showed no association with age, BMI, gender, or outcomes, but was significantly higher in severe pneumonia cases (79%) than non-pneumonic cases (37%) (p=0.003). Headache (17%) was more common in females (24%) than males (11%) (p=0.005) and was associated with a higher BMI. Cough (68%) correlated with higher BMI (p<0.001) and disease severity (74% severe cases vs. 26% non-pneumonic; p=0.001). Shortness of breath (62%) was associated with a higher BMI (p=0.001) and severe pneumonia (73% vs. 11% in non-pneumonic cases; p<0.001). Sore throat (21%) occurred more in females (27%) than males (16%) (p=0.017) but less in severe cases. Generalized weakness (30%) was more prevalent in severe pneumonia (47%) than in mild (27%) and non-pneumonic (5%) cases (p=0.001). Diarrhea (22%) was associated with younger age (median 53 years; p=0.039). Vomiting (17%) showed no significant difference across variables. No significant associations were found between the symptoms and radiologic findings of interstitial lung disease or rare complications. Symptoms did not significantly differ between the discharged and deceased patients. These findings indicate that cough, shortness of breath, and weakness reliably indicate severe pulmonary involvement, whereas sore throat and headache may reflect milder disease. BMI was a significant predictor of multiple symptoms. Comparison of Radiographic Progression Between First and Second Chest X-rays in Relation to Patient Characteristics A comparative analysis of the first and second CXRs of patients with COVID-19 pneumonia showed significant correlations between the radiological findings and clinical symptoms (Table 4) . Consolidation was the primary radiological feature, showing significant associations with fever (p = 0.004), cough (p = 0.001), shortness of breath (p = 0.001), and weakness (p = 0.005) on the first radiograph. These associations continued in the second radiograph, with consolidation correlating with fever (p < 0.001), cough (p = 0.004), and shortness of breath (p = 0.003), indicating persistent lung involvement. Ground-glass opacities (GGO) on the first radiograph were associated with cough (p = 0.022), shortness of breath (p = 0.004), and general weakness (p = 0.016); however, these diminished in the second radiograph, with only fever remaining significant (p = 0.013). Pleural effusion, although rare, appeared more frequently in the second radiograph and correlated with general weakness (p = 0.034). These findings demonstrate how initial GGO correlates with early respiratory symptoms, whereas consolidation becomes more prominent as the disease progresses. Correlations Between first and second chest X-ray lung and clinical symptoms in COVID-19 Pneumonia Patients A comparative analysis of the radiographic patterns in the first and second CXRs revealed important insights into disease distribution (Table 5) . Peripheral lung involvement, observed in 63 patients initially, correlated with cough (p = 0.012) and general weakness (p = 0.004), suggesting that early peripheral opacities are associated with respiratory and systemic symptoms. On the second X-ray, peripheral cases increased to 68, maintaining a correlation with general weakness (p = 0.001). Diffuse lung involvement was correlated with shortness of breath (p = 0.044) on the first radiograph. Bilateral lung involvement was significantly associated with multiple symptoms. Initially, bilateral changes correlated with cough (p = 0.012) and shortness of breath (p = 0.048), whereas in the second radiograph, associations included fever (p = 0.026), cough (p = 0.018), shortness of breath (p = 0.044), and sore throat (p = 0.029). The central, perihilar, and right lung distributions showed no significant correlation with symptoms. Left lung involvement was initially correlated with shortness of breath (p = 0.029) and general weakness (p = 0.008). The evolution of imaging findings, particularly peripheral and bilateral involvement, correlates with clinical deterioration and respiratory symptoms, indicating their value in monitoring disease progression. Correlations between first and second X-ray lobar and clinical symptoms in COVID-19 pneumonia patients Analysis of lobar involvement in chest radiographs of patients with COVID-19 pneumonia showed evolving patterns and symptom correlations (Table 6) . Middle lobe involvement increased from 11 to 20 cases between the first and second radiographs, significantly correlating with cough (p = 0.028) and shortness of breath (p = 0.029). The lower lobe was most frequently involved, increasing from 47 to 71 patients, with first scan involvement associated with sore throat (p = 0.009) and second scan involvement associated with vomiting (p = 0.012). The upper, right upper, and left upper lobes showed limited involvement with no significant symptom associations. Right lower lobe involvement (21 first, 20 cases in the follow-up) showed an inverse relationship with diarrhea in the second scan (p = 0.001). The findings showed increasing middle and lower lobe involvement over time, with the middle lobe particularly associated with respiratory symptoms in later stages, demonstrating COVID-19 the dynamic nature and the importance of serial radiographs in tracking disease progression and symptoms. Correlation of comorbidities and clinical symptoms among COVID-19 patients The analysis in Table 7 reveals associations between comorbidities and specific symptoms in patients with COVID-19 pneumonia. Although many associations were not statistically significant, notable patterns emerged in patients with diabetes, hypertension, asthma, and ischemic heart disease (IHD). Patients with diabetes (n = 130) showed a significant correlation with diarrhea (p = 0.035), suggesting a link between diabetes and systemic manifestations of COVID-19, possibly due to altered immune responses. Hypertension (132 patients) was significantly associated with shortness of breath (p = 0.015), potentially reflecting compromised cardiopulmonary interaction. Asthmatic patients (n = 26) were significantly more likely to experience headaches (p = 0.010), which may reflect underlying inflammatory mechanisms or medication effects. Patients with ischemic heart disease (n = 42) had a significantly lower prevalence of headache (p = 0.025). Other symptoms did not differ significantly between patients with and without IHD. Malignancy (27 patients) showed no statistically significant associations with any symptoms, possibly due to the small sample size. Among patients with COVID-19 pneumonia, diabetes was associated with increased diarrhea, hypertension with shortness of breath, and asthma with headache. These associations highlight the importance of individualized assessment in COVID-19 patients with underlying comorbidities, as they may present with varying symptom profiles. Discussion Chest X-Ray (CXR) imaging plays a vital role in assessing COVID-19 patients, given the constraints of other methods like computed topography (CT) scans. This study explored the connections between patient symptoms, characteristics, and examination timing with CXR-SS and CXR abnormality types. Chest CT is more sensitive than RT-PCR, with 98% sensitivity, even in asymptomatic patients (Fang et al., 2020). Some patients with positive RT-PCR results may have negative chest CT scans, while others with negative RT-PCR results may have positive CT scans (Ai et al., 2019; Bernheim et al., 2020). This study investigated the association between COVID-19 symptoms and factors such as age, sex, BMI, and disease severity. Fever was the most prevalent symptom (68%); however, it did not correlate with demographic factors. Notably, fever was more frequently observed in patients with severe pneumonia (79%) than in those without (37%) (p = 0.003). This finding is consistent with global data identifying fever as a common early symptom, particularly in severe cases (Guan et al., 2020; Huang et al., 2020). Cough (68%) and shortness of breath (62%) were associated with higher BMI and disease severity, corroborating previous studies that link obesity to severe respiratory symptoms in COVID-19 patients due to compromised respiratory function and immune dysregulation (Simonnet et al., 2020; Sattar et al., 2020). Our investigation into CXRs showed consolidation as the primary radiological finding that was significantly associated with fever, cough, shortness of breath, and weakness on initial and follow-up radiographs. These findings align with studies identifying consolidation, indicating alveolar exudation and advanced lung involvement, as a key feature of severe COVID-19 pneumonia (Shi et al., 2020; Bernheim et al., 2020). Ground-glass opacities (GGO) were linked to early symptoms such as cough, shortness of breath, and weakness in initial radiographs, representing early alveolar damage characteristic of viral pneumonia (Pan et al., 2020). The reduced GGO symptom association in subsequent radiographs, with only fever remaining significant, may indicate resolution or progression to consolidation (Wong et al., 2020). Although pleural effusion is uncommon in COVID-19, it is associated with severe disease or complications (Zhu et al., 2020). This study provides crucial insights into the radiographic patterns of patients with COVID-19 pneumonia. In subsequent radiographs, peripheral involvement increased to 68 patients and was correlated with general weakness (p = 0.001). These results align with those of studies identifying peripheral and subpleural opacities as typical features of COVID-19 lung pathology (Wong et al., 2020; Bernheim et al., 2020). The link with cough suggests airway irritation from subpleural inflammation, whereas general weakness may reflect systemic viral effects (Zhou et al., 2020). Diffuse lung involvement and shortness of breath on initial radiographs indicate extensive alveolar damage, resulting in impaired gas exchange. Similar patterns have been observed in severe disease and poor outcomes (Shi et al., 2020). Bilateral lung involvement emerged as a significant finding, aligning with the literature describing bilateral opacities as characteristics of COVID-19 pneumonia (Salehi et al., 2020). These findings emphasize the importance of serial CXRs in managing COVID-19. As peripheral and bilateral involvement increased, their association with symptoms highlighted their role in monitoring disease progression, supporting evidence that COVID-19 pneumonia evolves from focal to diffuse involvement (Pan et al., 2020). On further investigation, our study identified increased middle lobe involvement linked to cough and shortness of breath, aligning with studies suggesting that the middle lobe becomes more involved as the disease progresses (Zhao et al., 2020). In single-lobe involvement, the left upper and right middle lobes were the least affected at 10.3 and 13.8%, respectively. The right middle lobe is most often unaffected in four-lobe cases (65%) (Chung et al., 2020). The middle lobe is frequently associated with widespread lung involvement (Nardi et al. 2023). Cough and dyspnea's link to middle lobe pathology may indicate advancing bronchial involvement and worsening ventilation-perfusion mismatch (Wong et al., 2020). The early connection with sore throat suggests initial virus entry through the upper airway before descending to the lower lobes, consistent with the virus's preference for ACE2 receptors in the respiratory tract (Zhou et al., 2020). Later association with vomiting suggests systemic spread and gastrointestinal (GI) involvement, which is supported by the presence of SARS-CoV-2 RNA in GI tissues (Cheung et al., 2020). Right lower lobe involvement showed an inverse relationship with diarrhea during the second scan, possibly indicating either symptom prominence shifts or different inflammatory responses among patients (Huang et al., 2020). The link between diabetes and diarrhea (p = 0.035) in our study suggests that hyperglycemia affects the immune system and gut microbiota. Diabetes mellitus weakens both innate and adaptive immunity, potentially making patients more susceptible to severe GI symptoms during COVID-19 (Bornstein et al., 2020). Patients with COVID-19 often report GI symptoms, with a meta-analysis of 4,243 patients showing a 17.6% prevalence (Cheung et al., 2020). SARS-CoV-2 can invade the GI epithelium through ACE2, with high ACE2 expression found in the esophageal epithelium and absorptive enterocytes from the ileum and colon (Zhang et al., 2020). SARS-CoV-2's effects on the GI tract can cause diarrhea, bleeding, and inflammation, complicating COVID-19 in other organs (Kumar Durairajan et al., 2023). Hypertension was significantly linked to shortness of breath (p = 0.015), possibly due to cardiovascular dysfunction that hinders pulmonary circulation during pneumonia (Vaduganathan et al., 2020). Conclusion A comprehensive analysis of 293 patients with COVID-19 pneumonia revealed significant correlations between demographic characteristics, clinical symptoms, radiographic findings, and comorbidities. The study demonstrated that fever, cough, and shortness of breath were the predominant symptoms strongly associated with radiographic progression and disease severity. Radiographic features, including consolidation and ground-glass opacities, increased from the initial to follow-up CXRs, indicating disease progression. Bilateral lung involvement and lower lobe predominance became more prominent on subsequent imaging. This study identified associations between specific symptoms and patient characteristics, such as a higher BMI correlating with an increased prevalence of cough and shortness of breath. Furthermore, comorbidities such as diabetes and hypertension were correlated with particular symptoms. This study also revealed sex differences in symptom presentation. Radiographic progression, particularly in the middle and lower lobes, was consistently correlated with respiratory symptoms. These findings underscore the complex interplay between clinical presentation, radiographic findings, and patient characteristics in COVID-19 pneumonia, emphasizing the importance of comprehensive patient assessment and serial imaging for effective monitoring and management of the disease. Abbreviations SARS-CoV-2: severe acute respiratory syndrome coronavirus-2 COVID-19: coronavirus disease 19 GGO: ground-glass opacities CXR: chest X-rays RT-PCR: real-time polymerase chain reaction IHD: ischemic heart disease CT: computed topography ACE2: Angiotensin-converting enzyme 2 Declarations Ethical Approval: This study was approved by the institutional review board at King Abdullah International Medical Research Center (SP21J-125-03). Patient consent was waived due to the retrospective study design. Consent for publication Not applicable. Data Availability: Data supporting the findings of this study are available from the corresponding author upon reasonable request. Conflicts of Interest: The authors declare no conflicts of interest. Funding: This research received no specific grant from any funding agency. Author Contributions: AA conceived the study, collected clinical data, analyzed results, and drafted the manuscript. Co-authors contributed to data validation, critical revisions, and approval of the final manuscript. Acknowledgment The authors thank the Research Unit at the College of Medicine at KSAU-HS Jeddah for the support and guidance. References Abougazia, A., Alnuaimi, A., Mahran, A., Ali, T., Khedr, A., Qadourah, B., Shareef, A., Zitouni, S., Kahveci, S., Alqudah, B., Yassin, Y. A., Eldesoky, M., Abdelmoneim, A., & Youssef, R. (2021). Chest X-Ray Findings in COVID-19 Patients Presenting to Primary Care during the Peak of the First Wave of the Pandemic in Qatar: Their Association with Clinical and Laboratory Findings. Pulmonary Medicine , 2021 , 4496488. https://doi.org/10.1155/2021/4496488 Ai T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020;26:200642. AlMohimeed, A., Saleh, H., El-Rashidy, N., A Saad, R. M., El-Sappagh, S., & Mostafa, S. (2023). Diagnosis of COVID-19 Using Chest X-ray Images and Disease Symptoms Based on Stacking Ensemble Deep Learning. Diagnostics , 13 (11), 1968. https://doi.org/10.3390/diagnostics13111968 Al-Smadi AS, Bhatnagar A, Ali R, Lewis N, Johnson S. Correlation of chest radiography findings with the severity and progression of COVID-19 pneumonia. Clin Imaging. 2021 Mar;71:17-23. doi: 10.1016/j.clinimag.2020.11.004. Epub 2020 Nov 5. PMID: 33166898; PMCID: PMC7644185. Bernheim, A., Mei, X., Huang, M., et al. (2020). Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. Radiology , 295(3), 685–691. https://doi.org/10.1148/radiol.2020200463 Bianchini, A., Pintus, L., Vitale, G., Mazzotta, E., Felicani, C., Zangheri, E., Latrofa, M. E., Modolon, C., Pisano, R., & Siniscalchi, A. (2025). Lung Ultrasound in Mechanical Ventilation: A Purposive Review. Diagnostics , 15 (7), 870. https://doi.org/10.3390/diagnostics15070870 Bornstein, S. R., Rubino, F., Khunti, K., Mingrone, G., Hopkins, D., Birkenfeld, A. L., ... & Ludwig, B. (2020). Practical recommendations for the management of diabetes in patients with COVID-19. The lancet Diabetes & endocrinology , 8 (6), 546-550. Bourgonje, A. R., Abdulle, A. E., Timens, W., Hillebrands, L., Navis, G. J., Gordijn, S. J., Bolling, M. C., Dijkstra, G., Voors, A. A., Osterhaus, A. D., & Mulder, D. J. (2020). Angiotensin‐converting enzyme 2 (ACE2), SARS‐CoV‐2 and the pathophysiology of coronavirus disease 2019 (COVID‐19). The Journal of Pathology , 251 (3), 228. https://doi.org/10.1002/path.5471 Brandi, N., Ciccarese, F., Rimondi, M. R., Balacchi, C., Modolon, C., Sportoletti, C., Renzulli, M., Coppola, F., & Golfieri, R. (2022). An Imaging Overview of COVID-19 ARDS in ICU Patients and Its Complications: A Pictorial Review. Diagnostics , 12 (4), 846. https://doi.org/10.3390/diagnostics12040846 Cheung KS, Hung IF, Chan PP, et al . Gastrointestinal manifestations of SARS‐CoV‐2 infection and virus load in fecal samples from the Hong Kong cohort and systematic review and meta‐analysis. Gastroenterology 2020; 10.1053/j.gastro.2020.03.065 Chung, M., Bernheim, A., Mei, X., Zhang, N., Huang, M., Zeng, X., Cui, J., Xu, W., Yang, Y., Fayad, Z. A., Jacobi, A., Li, K., Li, S., & Shan, H. (2020). CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology, 200230. https://doi.org/10.1148/radiol.2020200230 Cozzi D, Moroni C, Addeo G, et al. Radiological patterns of lung involvement in inflammatory bowel disease. Gastroenterol Res Pract. 2018;5697846. Cozzi, D., Cavigli, E., Moroni, C., Smorchkova, O., Zantonelli, G., Pradella, S., & Miele, V. (2021). Ground-glass opacity (GGO): A review of the differential diagnosis in the era of COVID-19. Japanese Journal of Radiology , 39 (8), 721. https://doi.org/10.1007/s11604-021-01120-w Ding, X., Shang, B., Xie, C., Xin, J., & Yu, F. (2025). Artificial intelligence in the COVID-19 pandemic: Balancing benefits and ethical challenges in China’s response. Humanities and Social Sciences Communications , 12 (1), 1-19. https://doi.org/10.1057/s41599-025-04564-x Fang Y, Zhang H, Xie J, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020;19:200432. Ferrinho P., Sidat M., Leiras G., De Barros F.P.C., Arruda H. Principalism in public health decision making in the context of the COVID-19 pandemic. Int. J. Health Plan. Manag. 2020;35:997–1000. doi: 10.1002/hpm.3015 Filip, R., Puscaselu, R. G., Anchidin-Norocel, L., Dimian, M., & Savage, W. K. (2022). Global Challenges to Public Health Care Systems during the COVID-19 Pandemic: A Review of Pandemic Measures and Problems. Journal of Personalized Medicine , 12 (8), 1295. https://doi.org/10.3390/jpm12081295 Guan, W. J., Ni, Z. Y., Hu, Y., et al. (2020). Clinical characteristics of coronavirus disease 2019 in China. New England Journal of Medicine , 382(18), 1708–1720. https://doi.org/10.1056/NEJMoa2002032 Hatabu H, Hunninghake GM, Richeldi L, Brown KK, et al. Interstitial lung abnormalities detected incidentally on CT: a position paper from the Fleischner society. Lancet Respir Med. 2020;8:726–737. doi: 10.1016/S2213-2600(20)30168-5 Huang C., Wang Y., Li X., Ren L., Zhao J. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. 2020;395(10223):497–506. doi: 10.1016/S0140-6736(20)30183-5. KARACAN, A., & AKSOY, Y. E. (2021). The radiological findings of COVID-19. Turkish Journal of Medical Sciences , 51 (7), 3328. https://doi.org/10.3906/sag-2106-203 Kevadiya, B. D., Machhi, J., Herskovitz, J., Oleynikov, M. D., Blomberg, W. R., Bajwa, N., Soni, D., Das, S., Hasan, M., Patel, M., Senan, A. M., Gorantla, S., McMillan, J., Edagwa, B., Eisenberg, R., Gurumurthy, C. B., Reid, S. P., Punyadeera, C., Chang, L., . . . Gendelman, H. E. (2021). Diagnostics for SARS-CoV-2 infections. Nature Materials , 20 (5), 593-605. https://doi.org/10.1038/s41563-020-00906-z Kumar Durairajan, S. S., Singh, A. K., Saravanan, U. B., Namachivayam, M., Radhakrishnan, M., Huang, D., Dhodapkar, R., & Zhang, H. (2023). Gastrointestinal Manifestations of SARS-CoV-2: Transmission, Pathogenesis, Immunomodulation, Microflora Dysbiosis, and Clinical Implications. Viruses , 15 (6), 1231. https://doi.org/10.3390/v15061231 Loeffelholz M. J., Tang Y.-W. Laboratory diagnosis of emerging human coronavirus infections: the state of the art. Emerging Microbes & Infections . 2020;9(1):747–756. doi: 10.1080/22221751.2020.1745095. Meng H, Xiong R, He R, et al. CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China. J Inf Secur. 2020;12:S0163–S4453. doi: 10.1016/j.jinf.2020.04.004. Nardi, C., Magnini, A., Calistri, L., Cavigli, E., Peired, A. J., Rastrelli, V., Carlesi, E., Zantonelli, G., Smorchkova, O., Cinci, L., Orlandi, M., Landini, N., Berillo, E., Lorini, C., Mencarini, J., Colao, M. G., Gori, L., Luzzi, V., Lazzeri, C., . . . Colagrande, S. (2023). Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes. BMC Pulmonary Medicine , 23 , 472. https://doi.org/10.1186/s12890-023-02763-3 Pan, F., Ye, T., Sun, P., et al. (2020). Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia. Radiology , 295(3), 715–721. https://doi.org/10.1148/radiol.2020200370 Rousan, L. A., Elobeid, E., Karrar, M., & Khader, Y. (2020). Chest x-ray findings and temporal lung changes in patients with COVID-19 pneumonia. BMC Pulmonary Medicine , 20 , 245. https://doi.org/10.1186/s12890-020-01286-5 Salehi, S., Abedi, A., Balakrishnan, S., & Gholamrezanezhad, A. (2020). Coronavirus disease 2019 (COVID-19): A systematic review of imaging findings in 919 patients. AJR American Journal of Roentgenology , 215(1), 87–93. https://doi.org/10.2214/AJR.20.23034 Santus, P., Radovanovic, D., Saad, M. et al. Acute dyspnea in the emergency department: a clinical review. Intern Emerg Med 18 , 1491–1507 (2023). https://doi.org/10.1007/s11739-023-03322-8 Sattar, N., McInnes, I. B., & McMurray, J. J. V. (2020). Obesity is a risk factor for severe COVID-19 infection: multiple potential mechanisms. Circulation , 142(1), 4–6. https://doi.org/10.1161/CIRCULATIONAHA.120.047659 Sharma, A., Tiwari, S., Deb, M. K., & Marty, J. L. (2020). Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2): A global pandemic and treatment strategies. International Journal of Antimicrobial Agents , 56 (2), 106054. https://doi.org/10.1016/j.ijantimicag.2020.106054 Shi, H., Han, X., Jiang, N., et al. (2020). Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. The Lancet Infectious Diseases , 20(4), 425–434. https://doi.org/10.1016/S1473-3099(20)30086-4 Simonnet, A., Chetboun, M., Poissy, J., et al. (2020). High prevalence of obesity in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) requiring invasive mechanical ventilation. Obesity , 28(7), 1195–1199. https://doi.org/10.1002/oby.22831 Slika, B., Dornaika, F., Merdji, H. et al. Lung pneumonia severity scoring in chest X-ray images using transformers. Med Biol Eng Comput 62 , 2389–2407 (2024). https://doi.org/10.1007/s11517-024-03066-3 Vaduganathan, M., Vardeny, O., Michel, T., McMurray, J. J., Pfeffer, M. A., & Solomon, S. D. (2020). Renin–angiotensin–aldosterone system inhibitors in patients with Covid-19. New England Journal of Medicine , 382 (17), 1653-1659. Wang Y, Dong C, Hu Y, et al. (2020) Temporal Changes of CT Findings in 90 Patients with COVID-19 Pneumonia: A Longitudinal Study. Radiology doi: 10.1148/radiol.2020200843. Wong HYF, Lam HYS, Fong AH-T, Leung ST, Chin TW-Y, Lo CSY, Lui MM-S, Lee JCY, Chiu KW-H, Chung T, Lee EYP, Wan EYF, Hung FNI, Lam TPW, Kuo M, Ng M-Y. (2020) Frequency and distribution of chest radiographic findings in COVID-19 positive patients. Radiology;0(0):201160. doi: 10.1148/radiol.2020201160. World Health Organization (2025) Available online: https://covid19.who.int/. Accessed 7 Feb 2025 Yasin R, Gouda W. Chest X-ray findings monitoring COVID-19 disease course and severity. Egypt J Radiol Nucl Med. (2020) 51:193. 10.1186/s43055-020-00296-x Yoon, S. H., Lee, K. H., Kim, J. Y., et al. (2020). Chest radiographic and CT findings of the 2019 novel coronavirus disease (COVID-19): analysis of nine patients treated in Korea. Korean Journal of Radiology , 21(4), 494–500. https://doi.org/10.3348/kjr.2020.0132 Zhang H, Kang Z, Gong H, et al. Digestive system is a potential route of COVID‐19: an analysis of single‐cell coexpression pattern of key proteins in viral entry process. Gut 2020; 69 : 1010–1018. Zhao, W., Zhong, Z., Xie, X., Yu, Q., & Liu, J. (2020). Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: A multicenter study. American Journal of Roentgenology , 214(5), 1072–1077. https://doi.org/10.2214/AJR.20.22976 Zhou, F., Yu, T., Du, R., et al. (2020). Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The Lancet , 395(10229), 1054–1062. https://doi.org/10.1016/S0140-6736(20)30566-3 Zhou, P., Yang, X.-L., Wang, X.-G., et al. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature , 579(7798), 270–273. https://doi.org/10.1038/s41586-020-2012-7 Zhu, N., Zhang, D., Wang, W., et al. (2020). A novel coronavirus from patients with pneumonia in China, 2019. New England Journal of Medicine , 382(8), 727–733. https://doi.org/10.1056/NEJMoa2001017 Additional Declarations No competing interests reported. Supplementary Files TABLESANDFIGURES.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 09 Jan, 2026 Reviewers agreed at journal 22 Dec, 2025 Reviewers agreed at journal 14 Dec, 2025 Reviewers invited by journal 12 Dec, 2025 Editor invited by journal 20 Nov, 2025 Editor assigned by journal 19 Nov, 2025 Submission checks completed at journal 19 Nov, 2025 First submitted to journal 16 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. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8125393","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":560081744,"identity":"d1cad165-f238-444b-9375-2c29539d1321","order_by":0,"name":"Abdullah Awadh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYJACaQYGGwMQgxnMPUCcljTStRwmQQv/jOSHtwtqzhvLt58xYC74wyDHdyOB+cMPPFokbqQZW884dtvM4EyOAfPMNgZjyRsJbJI9+Ky5nWAmzcN2G+j/HPPfvA0MiRuAWhh48OiQv53+TZrn3zkb+f43Bsw8fxjqgVqYP/7Bo8Xgdo6ZNG/bATOGG0CH8bAxJBjcSGCQxmeL4f03xda8fcnGBjeeFTDztkkYzjzzsE1aBo8WuTPHN97m+WZnOL8/eQPQYTbyfMeTD398g8/7aEACiBkbSNAwCkbBKBgFowAbAABh1kmHqiOgHwAAAABJRU5ErkJggg==","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":true,"prefix":"","firstName":"Abdullah","middleName":"","lastName":"Awadh","suffix":""},{"id":560081745,"identity":"cefcf493-47e9-459a-80b7-cb8fe89f7823","order_by":1,"name":"Abdulrahman Alomari","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abdulrahman","middleName":"","lastName":"Alomari","suffix":""},{"id":560081746,"identity":"f5b40f7e-613d-4a06-87c9-4cdbb1a5427c","order_by":2,"name":"Abdulrahman Almassrahy","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Abdulrahman","middleName":"","lastName":"Almassrahy","suffix":""},{"id":560081747,"identity":"24badc3a-8e75-4083-8619-5d17798cf391","order_by":3,"name":"Omar Hassan","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"","lastName":"Hassan","suffix":""},{"id":560081748,"identity":"0c255657-07dd-40a5-b998-2ec0fe633cd1","order_by":4,"name":"Owais Kotbi","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Owais","middleName":"","lastName":"Kotbi","suffix":""},{"id":560081749,"identity":"cd1b11f4-2191-41e6-b204-cba4e9af2075","order_by":5,"name":"Moad Mohtasib","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Moad","middleName":"","lastName":"Mohtasib","suffix":""},{"id":560081751,"identity":"947c6594-0d40-4924-85f3-7c107094159e","order_by":6,"name":"Yazeed Alkheriji","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yazeed","middleName":"","lastName":"Alkheriji","suffix":""},{"id":560081752,"identity":"e9bbacc8-295b-4ce4-a88e-1495b5ee2240","order_by":7,"name":"Ziad Sijeeni","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ziad","middleName":"","lastName":"Sijeeni","suffix":""},{"id":560081756,"identity":"fc67a17d-c199-466d-9604-50714b533df8","order_by":8,"name":"Aws Kotbi","email":"","orcid":"","institution":"King Saud bin Abdulaziz University for Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Aws","middleName":"","lastName":"Kotbi","suffix":""},{"id":560081758,"identity":"1ac09caf-7e0c-4152-9cb7-c169dbaa44b9","order_by":9,"name":"Ali Alyami","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"","lastName":"Alyami","suffix":""},{"id":560081763,"identity":"c3471099-793b-46fa-bc7c-b193c17a39f7","order_by":10,"name":"Enas Ghulam","email":"","orcid":"","institution":"King Abdullah International Medical Research Center","correspondingAuthor":false,"prefix":"","firstName":"Enas","middleName":"","lastName":"Ghulam","suffix":""},{"id":560081764,"identity":"9a8f9d31-e7f6-4db8-bf0b-a959fe3e396f","order_by":11,"name":"Mohammed Khan","email":"","orcid":"","institution":"King Saud Bin Abdulaziz For Health Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mohammed","middleName":"","lastName":"Khan","suffix":""}],"badges":[],"createdAt":"2025-11-16 06:08:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8125393/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8125393/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98542835,"identity":"c0af7b97-21f8-4d02-be82-229785238c96","added_by":"auto","created_at":"2025-12-18 17:56:40","extension":"doc","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":117128,"visible":true,"origin":"","legend":"","description":"","filename":"MS1CO1.doc","url":"https://assets-eu.researchsquare.com/files/rs-8125393/v1/d46f685f1960b1bb4391e653.doc"},{"id":98626080,"identity":"47ad8cdc-4950-4369-b9e9-18225c9eec9c","added_by":"auto","created_at":"2025-12-19 17:09:30","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":12535,"visible":true,"origin":"","legend":"","description":"","filename":"b5cf4f50ba55497c81be391164f87580.json","url":"https://assets-eu.researchsquare.com/files/rs-8125393/v1/b0e68943cd5a75bcf87d211d.json"},{"id":98774939,"identity":"bee12c1f-67c2-4adb-a7c8-c9ac758c5007","added_by":"auto","created_at":"2025-12-22 12:17:20","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":810759,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8125393/v1/07e22424-6c93-4394-9376-a88cc24c7d57.pdf"},{"id":98542834,"identity":"44c66e2a-a5cc-461a-ba87-089e6acad154","added_by":"auto","created_at":"2025-12-18 17:56:40","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":70066,"visible":true,"origin":"","legend":"","description":"","filename":"TABLESANDFIGURES.docx","url":"https://assets-eu.researchsquare.com/files/rs-8125393/v1/99e9dcabd16cfe5a13baabab.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations between COVID-19 symptoms, chest X-Ray, and patient characteristics: A Comprehensive Analysis","fulltext":[{"header":"Introduction","content":"\u003cp\u003eIn late 2019, severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) originated in China and swiftly spread across the globe, resulting in the coronavirus disease 19 (COVID-19) pandemic. The clinical manifestations of the disease vary from no symptoms to respiratory and/or systemic symptoms (Huang et al., 2020). COVID-19 is a severe acute respiratory syndrome that has caused a major ongoing global pandemic (Sharma et al., 2020). The COVID-19 pandemic has posed unprecedented challenges to healthcare systems worldwide, necessitating rapid advancements in diagnostic and prognostic tools (Filip et al., 2022). As of April 13, 2025, there have been over 777,720,205 confirmed cases and more than 7,094,447 deaths worldwide, ranking COVID-19 as the fifth deadliest pandemic in history (World Health Organization, 2025; Ding et al., 2025). \u0026nbsp;Among these, chest X-rays (CXRs) have emerged as a valuable resource for the assessment and management of COVID-19 patients (Abougazia et al., 2021). Radiographic imaging allows healthcare providers to visualize the extent of lung involvement, which can be a key indicator of disease severity (Slika et al., 2024). While RT-PCR testing remains the gold standard for confirming COVID-19 infection, CXRs provide valuable supplementary information that can guide clinical decision-making, particularly in resource-limited settings where rapid testing may not be available (Loeffelholz and Tang, 2020; Ferrinho et al., 2020; Kevadiya et al., 2021).\u003c/p\u003e\n\u003cp\u003eThe role of CXRs in COVID-19 diagnosis extends beyond the initial detection. They are instrumental in monitoring disease progression and assessing treatment effectiveness (AIMohimeed et al., 2023). For patients presenting with respiratory symptoms, an initial CXR is crucial for identifying and evaluating the extent of pulmonary infiltrates indicative of viral pneumonia (Rousan et al., 2020). In cases of COVID-19, radiographic images display specific patterns that correspond to the severity and progression of the disease (Karacan and Aksoy, 2021). A commonly observed feature in these X-rays is bilateral peripheral ground-glass opacities (GGOs) (Cozzi et al., 2021). These opacities represent areas of increased lung attenuation, indicating inflammation and fluid accumulation (Cozzi et al., 2018). GGOs typically manifest in the early stages of infection and may progress to more extensive consolidation as the disease advances (Wang et al., 2020; Cozzi et al., 2021).\u003c/p\u003e\n\u003cp\u003eIn addition to ground-glass opacities (GGOs), CXRs can reveal patchy or confluent consolidations that appear as denser opaque regions (Wong et al., 2020). These consolidations are typically situated in the lower lung zones and indicate severe pulmonary involvement (Hatabu et al., 2020). The presence of such consolidations is associated with an increased likelihood of requiring mechanical ventilation and intensive care. It is imperative for radiologists and clinicians to recognize these patterns and understand their implications for patient management and prognosis (Brandi et al., 2022; Bianchini et al., 2025). The correlation between COVID-19 symptoms and CXR findings is a critical area of research that can provide valuable insights into disease severity and progression. Studies have demonstrated that patients with severe respiratory symptoms, such as dyspnea and hypoxemia, often present with more pronounced radiographic abnormalities (Santus et al., 2023). For instance, individuals experiencing significant shortness of breath are more likely to exhibit extensive GGOs and consolidation on CXRs, indicative of severe pulmonary involvement (Cozzi et al., 2021).\u003c/p\u003e\n\u003cp\u003eClinical and demographic factors are significantly associated with radiographic outcomes (AI-Smadi et al., 2021). Research indicates a correlation between abnormal CXRs findings and the presence of symptoms, with a substantial majority (92.3%) of patients with radiographic anomalies also exhibiting symptoms (Rousan et al., 2020). Further investigations have explored the relationship between deteriorating CXR results and prognostic outcomes, identifying radiographic progression as a potential indicator of disease severity and clinical trajectory (Wang et al., 2020; Rousan et al., 2020). Conversely, individuals with mild or asymptomatic COVID-19 may show minimal or no radiographic changes (Meng et al., 2020). This variability underscores the necessity of integrating clinical assessments with imaging findings to achieve a comprehensive understanding of a patient's condition (Huang et al., 2020). In certain cases,\u0026nbsp;CXRs may reveal abnormalities even in the absence of severe symptoms, suggesting subclinical disease that could potentially progress without timely intervention if not detected. This underscores the importance of vigilant monitoring and a proactive approach to patient management (Yasin and Gouda, 2020).\u003c/p\u003e\n\u003cp\u003eThis study aimed to explore the intricate relationships between clinical symptoms, radiological findings, and individual patient characteristics in the context of COVID-19. Through this analysis, we sought to enhance our understanding of the manifestations of this disease and potentially improve patient care strategies. This comprehensive investigation may provide valuable insights for clinicians in their decision-making processes and contribute to the growing body of knowledge on this novel coronavirus.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe current retrospective cross-sectional study investigated the radiological outcomes of pneumonia in patients with RT-PCR-confirmed COVID-19 who were admitted to King Abdulaziz Medical City in Jeddah, Saudi Arabia. The study was conducted between March and October 2020 and included 1,215 patients. To be included, patients needed a positive COVID-19 RT-PCR test and more than one chest X-ray image. Patients were excluded if there was significant missing information or a lack of follow-up. The Raosoft sample size calculator was employed to determine the sample size, utilizing a 95% confidence level and a 5% margin of error, resulting in a sample size of 293 patients. A total of 802 patients were excluded because they did not meet the inclusion criteria, while 413 patients were included in the study. The charts of the 413 selected patients were sequentially numbered from 1 to 413 for entry into a random sample generator. A Research Randomizer was used to generate a random sample of 293 patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData collection was conducted by trained medical students following the approval of the ethical board at King Abdullah International Medical Research Center (KAIMRC) under approval number SP21J-125-03 and was supervised by the primary investigator (PI). Data collection from medical records was facilitated using a structured form created using Microsoft Excel. The data encompassed patient information and demographic details, including age, gender, BMI, education level, occupation, and travel history. Additionally, it included diagnostic information such as COVID-19 status and pneumonia severity, clinical presentation (symptomatic or asymptomatic), and symptoms (fever, headache, cough, shortness of breath, sore throat, general weakness, diarrhea, and vomiting). Comorbidities, including diabetes, hypertension, asthma, ischemic heart disease, and malignancy, were also recorded. Chest X-ray findings were documented, noting consolidation, ground-glass opacity, and pleural effusion, as well as the distribution of these findings (diffuse, right, left, or bilateral lung involvement, peripheral/perihilar/central predominant, and lobar involvement). Finally, clinical outcomes were assessed by categorizing patients as either discharged or deceased.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParametric methods were used to describe the numerical data, such as age and BMI. Percentages were used to describe categorical variables, including sex, diagnosis, clinical presentation, symptoms, comorbidities, CXR findings, distribution of CXR findings, and clinical outcomes. The Chi-square test was used to compare categorical data, with a P-value of less than 0.05 considered statistically significant. Data analysis was conducted using JMP software (John's Macintosh Project), version 16.0 (SAS Institute Inc., Cary, NC, USA). The survival rate was calculated by dividing the percentage of infected patients who were discharged by the percentage of discharged patients in the general population of the same sex and age group during the same period.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eBaseline demographics characteristics outcome of patients with COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe demographic and clinical characteristics of 293 patients with COVID-19 pneumonia revealed a correlation between symptoms and chest radiographic disease progression \u003cstrong\u003e(Table 1)\u003c/strong\u003e. The cohort (median age 57 years, median BMI 30) comprised 57% males and 43% females. Most patients had mild-to-moderate pneumonia (73%), 21% developed severe forms, and 6% showed no initial radiographic evidence of pneumonia. The predominant symptoms were fever (68%), cough (68%), and shortness of breath (62%). Follow-up CXRs showed increased lobar involvement in patients with persistent respiratory symptoms, particularly in the lower and middle zones of the lungs. Disease progression was more frequent in patients with diabetes (44%) and hypertension (45%) than in those without. These comorbidities are correlated with extensive lung involvement and higher mortality (14%). Patients with ischemic heart disease (14%) and malignancy (9%) commonly presented with systemic symptoms, showing diffuse changes on follow-up radiography. Rare complications included pulmonary embolism (1%) and vein thromboembolism (0.3%), which contributed to worsening hypoxia and radiological deterioration. Symptomatology was strongly associated with radiographic progression, with second CXRs showing increased involvement in patients with persistent symptoms, particularly in those with comorbidities.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRadiographic features and anatomical distribution in initial and follow-up chest imaging of patients with COVID-19 pneumonia\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe radiographic progression of COVID-19 pneumonia was assessed by comparing the first and second chest radiographs of 293 patients \u003cstrong\u003e(Table 2)\u003c/strong\u003e. Consolidation was higher in the second chest radiograph (60%) than in the first (56%), suggesting radiologic disease progression. Ground-glass opacities (GGO) increased from 51% to 62%, which is consistent with typical COVID-19 progression. Pleural effusion increased from 9% to 85% in the second radiograph, potentially reflecting disease severity progression or complications such as infections or heart failure. Peripheral predominance was slightly more common in the second chest radiograph (23%) than in the first (22%), whereas central and perihilar patterns remained rare. The diffuse infiltrates increased from 5% to 8%. Bilateral lung involvement increased from 37% to 53% on the second radiograph, showing the bilateral nature of advanced COVID-19 pneumonia. Lower lobe involvement increased from 16% to 24%, with the right lower lobe showing an increase from 7% to 9%. Middle and upper lobe involvement showed smaller increases, consistent with typical COVID-19 pneumonia patterns beginning in the lower lobes. CXR findings of interstitial lung disease were rare (2%) and stable between imaging points. Radiological findings demonstrated progression of pulmonary involvement, with increased consolidation, GGO, bilateral and lower lobe predominance, and pleural effusions, correlating with COVID-19 pneumonia progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation of COVID-19 Symptoms with Demographic Characteristics and Clinical Outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe correlation between COVID-19 symptoms and clinical characteristics revealed notable patterns \u003cstrong\u003e(Table 3)\u003c/strong\u003e. Fever, the most prevalent symptom (198 patients, 68%), showed no association with age, BMI, gender, or outcomes, but was significantly higher in severe pneumonia cases (79%) than non-pneumonic cases (37%) (p=0.003). Headache (17%) was more common in females (24%) than males (11%) (p=0.005) and was associated with a higher BMI. Cough (68%) correlated with higher BMI (p\u0026lt;0.001) and disease severity (74% severe cases vs. 26% non-pneumonic; p=0.001). Shortness of breath (62%) was associated with a higher BMI (p=0.001) and severe pneumonia (73% vs. 11% in non-pneumonic cases; p\u0026lt;0.001). Sore throat (21%) occurred more in females (27%) than males (16%) (p=0.017) but less in severe cases. Generalized weakness (30%) was more prevalent in severe pneumonia (47%) than in mild (27%) and non-pneumonic (5%) cases (p=0.001). Diarrhea (22%) was associated with younger age (median 53 years; p=0.039). Vomiting (17%) showed no significant difference across variables. No significant associations were found between the symptoms and radiologic findings of interstitial lung disease or rare complications. Symptoms did not significantly differ between the discharged and deceased patients. These findings indicate that cough, shortness of breath, and weakness reliably indicate severe pulmonary involvement, whereas sore throat and headache may reflect milder disease. BMI was a significant predictor of multiple symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison of Radiographic Progression Between First and Second Chest X-rays in Relation to Patient Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comparative analysis of the first and second CXRs of patients with COVID-19 pneumonia showed significant correlations between the radiological findings and clinical symptoms \u003cstrong\u003e(Table 4)\u003c/strong\u003e. Consolidation was the primary radiological feature, showing significant associations with fever (p = 0.004), cough (p = 0.001), shortness of breath (p = 0.001), and weakness (p = 0.005) on the first radiograph. These associations continued in the second radiograph, with consolidation correlating with fever (p \u0026lt; 0.001), cough (p = 0.004), and shortness of breath (p = 0.003), indicating persistent lung involvement. Ground-glass opacities (GGO) on the first radiograph were associated with cough (p = 0.022), shortness of breath (p = 0.004), and general weakness (p = 0.016); however, these diminished in the second radiograph, with only fever remaining significant (p = 0.013). Pleural effusion, although rare, appeared more frequently in the second radiograph and correlated with general weakness (p = 0.034). These findings demonstrate how initial GGO correlates with early respiratory symptoms, whereas consolidation becomes more prominent as the disease progresses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations Between first and second chest X-ray lung and clinical symptoms in COVID-19 Pneumonia Patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA comparative analysis of the radiographic patterns in the first and second CXRs revealed important insights into disease distribution \u003cstrong\u003e(Table 5)\u003c/strong\u003e. Peripheral lung involvement, observed in 63 patients initially, correlated with cough (p = 0.012) and general weakness (p = 0.004), suggesting that early peripheral opacities are associated with respiratory and systemic symptoms. On the second X-ray, peripheral cases increased to 68, maintaining a correlation with general weakness (p = 0.001). Diffuse lung involvement was correlated with shortness of breath (p = 0.044) on the first radiograph. Bilateral lung involvement was significantly associated with multiple symptoms. Initially, bilateral changes correlated with cough (p = 0.012) and shortness of breath (p = 0.048), whereas in the second radiograph, associations included fever (p = 0.026), cough (p = 0.018), shortness of breath (p = 0.044), and sore throat (p = 0.029). The central, perihilar, and right lung distributions showed no significant correlation with symptoms. Left lung involvement was initially correlated with shortness of breath (p = 0.029) and general weakness (p = 0.008). The evolution of imaging findings, particularly peripheral and bilateral involvement, correlates with clinical deterioration and respiratory symptoms, indicating their value in monitoring disease progression.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelations between first and second X-ray lobar and clinical symptoms in COVID-19 pneumonia patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAnalysis of lobar involvement in chest radiographs of patients with COVID-19 pneumonia showed evolving patterns and symptom correlations \u003cstrong\u003e(Table 6)\u003c/strong\u003e. Middle lobe involvement increased from 11 to 20 cases between the first and second radiographs, significantly correlating with cough (p = 0.028) and shortness of breath (p = 0.029). The lower lobe was most frequently involved, increasing from 47 to 71 patients, with first scan involvement associated with sore throat (p = 0.009) and second scan involvement associated with vomiting (p = 0.012). The upper, right upper, and left upper lobes showed limited involvement with no significant symptom associations. Right lower lobe involvement (21 first, 20 cases in the follow-up) showed an inverse relationship with diarrhea in the second scan (p = 0.001). The findings showed increasing middle and lower lobe involvement over time, with the middle lobe particularly associated with respiratory symptoms in later stages, demonstrating COVID-19 the dynamic nature and the importance of serial radiographs in tracking disease progression and symptoms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation of comorbidities and clinical symptoms among COVID-19 patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe analysis in \u003cstrong\u003eTable 7\u003c/strong\u003e reveals associations between comorbidities and specific symptoms in patients with COVID-19 pneumonia. Although many associations were not statistically significant, notable patterns emerged in patients with diabetes, hypertension, asthma, and ischemic heart disease (IHD). Patients with diabetes (n = 130) showed a significant correlation with diarrhea (p = 0.035), suggesting a link between diabetes and systemic manifestations of COVID-19, possibly due to altered immune responses. Hypertension (132 patients) was significantly associated with shortness of breath (p = 0.015), potentially reflecting compromised cardiopulmonary interaction. Asthmatic patients (n = 26) were significantly more likely to experience headaches (p = 0.010), which may reflect underlying inflammatory mechanisms or medication effects. Patients with ischemic heart disease (n = 42) had a significantly lower prevalence of headache (p = 0.025). Other symptoms did not differ significantly between patients with and without IHD. Malignancy (27 patients) showed no statistically significant associations with any symptoms, possibly due to the small sample size. Among patients with COVID-19 pneumonia, diabetes was associated with increased diarrhea, hypertension with shortness of breath, and asthma with headache. These associations highlight the importance of individualized assessment in COVID-19 patients with underlying comorbidities, as they may present with varying symptom profiles.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eChest X-Ray (CXR) imaging plays a vital role in assessing COVID-19 patients, given the constraints of other methods like computed topography (CT) scans. This study explored the connections between patient symptoms, characteristics, and examination timing with CXR-SS and CXR abnormality types. Chest CT is more sensitive than RT-PCR, with 98% sensitivity, even in asymptomatic patients (Fang et al., 2020). Some patients with positive RT-PCR results may have negative chest CT scans, while others with negative RT-PCR results may have positive CT scans (Ai et al., 2019; Bernheim et al., 2020).\u003c/p\u003e\n\u003cp\u003eThis study investigated the association between COVID-19 symptoms and factors such as age, sex, BMI, and disease severity. Fever was the most prevalent symptom (68%); however, it did not correlate with demographic factors. Notably, fever was more frequently observed in patients with severe pneumonia (79%) than in those without (37%) (p = 0.003). This finding is consistent with global data identifying fever as a common early symptom, particularly in severe cases (Guan et al., 2020; Huang et al., 2020). Cough (68%) and shortness of breath (62%) were associated with higher BMI and disease severity, corroborating previous studies that link obesity to severe respiratory symptoms in COVID-19 patients due to compromised respiratory function and immune dysregulation (Simonnet et al., 2020; Sattar et al., 2020).\u003c/p\u003e\n\u003cp\u003eOur investigation into\u0026nbsp;CXRs\u0026nbsp;showed consolidation as the primary radiological finding that was significantly associated with fever, cough, shortness of breath, and weakness on initial and follow-up radiographs. These findings align with studies identifying consolidation, indicating alveolar exudation and advanced lung involvement, as a key feature of severe COVID-19 pneumonia (Shi et al., 2020; Bernheim et al., 2020). Ground-glass opacities (GGO) were linked to early symptoms such as cough, shortness of breath, and weakness in initial radiographs, representing early alveolar damage characteristic of viral pneumonia (Pan et al., 2020). The reduced GGO symptom association in subsequent radiographs, with only fever remaining significant, may indicate resolution or progression to consolidation (Wong et al., 2020). Although pleural effusion is uncommon in COVID-19, it is associated with severe disease or complications (Zhu et al., 2020).\u003c/p\u003e\n\u003cp\u003eThis study provides crucial insights into the radiographic patterns of patients with COVID-19 pneumonia. In subsequent radiographs, peripheral involvement increased to 68 patients and was correlated with general weakness (p = 0.001). These results align with those of studies identifying peripheral and subpleural opacities as typical features of COVID-19 lung pathology (Wong et al., 2020; Bernheim et al., 2020). The link with cough suggests airway irritation from subpleural inflammation, whereas general weakness may reflect systemic viral effects (Zhou et al., 2020). Diffuse lung involvement and shortness of breath on initial radiographs indicate extensive alveolar damage, resulting in impaired gas exchange. Similar patterns have been observed in severe disease and poor outcomes (Shi et al., 2020). Bilateral lung involvement emerged as a significant finding, aligning with the literature describing bilateral opacities as characteristics of COVID-19 pneumonia (Salehi et al., 2020). These findings emphasize the importance of serial CXRs in managing COVID-19. As peripheral and bilateral involvement increased, their association with symptoms highlighted their role in monitoring disease progression, supporting evidence that COVID-19 pneumonia evolves from focal to diffuse involvement (Pan et al., 2020).\u003c/p\u003e\n\u003cp\u003eOn further investigation, our study identified increased middle lobe involvement linked to cough and shortness of breath, aligning with studies suggesting that the middle lobe becomes more involved as the disease progresses (Zhao et al., 2020). In single-lobe involvement, the left upper and right middle lobes were the least affected at 10.3 and 13.8%, respectively. The right middle lobe is most often unaffected in four-lobe cases (65%) (Chung et al., 2020). The middle lobe is frequently associated with widespread lung involvement (Nardi et al. 2023). Cough and dyspnea's link to middle lobe pathology may indicate advancing bronchial involvement and worsening ventilation-perfusion mismatch (Wong et al., 2020). The early connection with sore throat suggests initial virus entry through the upper airway before descending to the lower lobes, consistent with the virus's preference for ACE2 receptors in the respiratory tract (Zhou et al., 2020). Later association with vomiting suggests systemic spread and gastrointestinal (GI) involvement, which is supported by the presence of SARS-CoV-2 RNA in GI tissues (Cheung et al., 2020). Right lower lobe involvement showed an inverse relationship with diarrhea during the second scan, possibly indicating either symptom prominence shifts or different inflammatory responses among patients (Huang et al., 2020).\u003c/p\u003e\n\u003cp\u003eThe link between diabetes and diarrhea (p = 0.035) in our study suggests that hyperglycemia affects the immune system and gut microbiota. Diabetes mellitus weakens both innate and adaptive immunity, potentially making patients more susceptible to severe GI symptoms during COVID-19 (Bornstein et al., 2020). Patients with COVID-19 often report GI symptoms, with a meta-analysis of 4,243 patients showing a 17.6% prevalence (Cheung et al., 2020). SARS-CoV-2 can invade the GI epithelium through ACE2, with high ACE2 expression found in the esophageal epithelium and absorptive enterocytes from the ileum and colon (Zhang et al., 2020). SARS-CoV-2's effects on the GI tract can cause diarrhea, bleeding, and inflammation, complicating COVID-19 in other organs (Kumar Durairajan et al., 2023). Hypertension was significantly linked to shortness of breath (p = 0.015), possibly due to cardiovascular dysfunction that hinders pulmonary circulation during pneumonia (Vaduganathan et al., 2020).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eA comprehensive analysis of 293 patients with COVID-19 pneumonia revealed significant correlations between demographic characteristics, clinical symptoms, radiographic findings, and comorbidities. The study demonstrated that fever, cough, and shortness of breath were the predominant symptoms strongly associated with radiographic progression and disease severity. Radiographic features, including consolidation and ground-glass opacities, increased from the initial to follow-up\u0026nbsp;CXRs, indicating disease progression. Bilateral lung involvement and lower lobe predominance became more prominent on subsequent imaging. This study identified associations between specific symptoms and patient characteristics, such as a higher BMI correlating with an increased prevalence of cough and shortness of breath. Furthermore, comorbidities such as diabetes and hypertension were correlated with particular symptoms. This study also revealed sex differences in symptom presentation. Radiographic progression, particularly in the middle and lower lobes, was consistently correlated with respiratory symptoms. These findings underscore the complex interplay between clinical presentation, radiographic findings, and patient characteristics in COVID-19 pneumonia, emphasizing the importance of comprehensive patient assessment and serial imaging for effective monitoring and management of the disease.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSARS-CoV-2: severe acute respiratory syndrome coronavirus-2\u003c/p\u003e\n\u003cp\u003eCOVID-19: coronavirus disease 19\u003c/p\u003e\n\u003cp\u003eGGO: ground-glass opacities\u003c/p\u003e\n\u003cp\u003eCXR: chest X-rays\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRT-PCR: real-time polymerase chain reaction\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIHD: ischemic heart disease\u003c/p\u003e\n\u003cp\u003eCT: computed topography\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eACE2: Angiotensin-converting enzyme 2\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Approval:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This study was approved by the institutional review board at King Abdullah International Medical Research Center (SP21J-125-03). Patient consent was waived due to the retrospective study design.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;Data supporting the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;This research received no specific grant from any funding agency.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;AA conceived the study, collected clinical data, analyzed results, and drafted the manuscript. Co-authors contributed to data validation, critical revisions, and approval of the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the Research Unit at the College of Medicine at KSAU-HS Jeddah for the support and guidance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAbougazia, A., Alnuaimi, A., Mahran, A., Ali, T., Khedr, A., Qadourah, B., Shareef, A., Zitouni, S., Kahveci, S., Alqudah, B., Yassin, Y. A., Eldesoky, M., Abdelmoneim, A., \u0026amp; Youssef, R. (2021). Chest X-Ray Findings in COVID-19 Patients Presenting to Primary Care during the Peak of the First Wave of the Pandemic in Qatar: Their Association with Clinical and Laboratory Findings. \u003cem\u003ePulmonary Medicine\u003c/em\u003e, \u003cem\u003e2021\u003c/em\u003e, 4496488. https://doi.org/10.1155/2021/4496488\u003c/li\u003e\n \u003cli\u003eAi T, Yang Z, Hou H, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020;26:200642.\u003c/li\u003e\n \u003cli\u003eAlMohimeed, A., Saleh, H., El-Rashidy, N., A Saad, R. M., El-Sappagh, S., \u0026amp; Mostafa, S. (2023). Diagnosis of COVID-19 Using Chest X-ray Images and Disease Symptoms Based on Stacking Ensemble Deep Learning. \u003cem\u003eDiagnostics\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(11), 1968. https://doi.org/10.3390/diagnostics13111968\u003c/li\u003e\n \u003cli\u003eAl-Smadi AS, Bhatnagar A, Ali R, Lewis N, Johnson S. Correlation of chest radiography findings with the severity and progression of COVID-19 pneumonia. Clin Imaging. 2021 Mar;71:17-23. doi: 10.1016/j.clinimag.2020.11.004. Epub 2020 Nov 5. PMID: 33166898; PMCID: PMC7644185.\u003c/li\u003e\n \u003cli\u003eBernheim, A., Mei, X., Huang, M., et al. (2020). Chest CT findings in coronavirus disease-19 (COVID-19): relationship to duration of infection. \u003cem\u003eRadiology\u003c/em\u003e, 295(3), 685\u0026ndash;691. https://doi.org/10.1148/radiol.2020200463\u003c/li\u003e\n \u003cli\u003eBianchini, A., Pintus, L., Vitale, G., Mazzotta, E., Felicani, C., Zangheri, E., Latrofa, M. E., Modolon, C., Pisano, R., \u0026amp; Siniscalchi, A. (2025). Lung Ultrasound in Mechanical Ventilation: A Purposive Review. \u003cem\u003eDiagnostics\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(7), 870. https://doi.org/10.3390/diagnostics15070870\u003c/li\u003e\n \u003cli\u003eBornstein, S. R., Rubino, F., Khunti, K., Mingrone, G., Hopkins, D., Birkenfeld, A. L., ... \u0026amp; Ludwig, B. (2020). Practical recommendations for the management of diabetes in patients with COVID-19. \u003cem\u003eThe lancet Diabetes \u0026amp; endocrinology\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(6), 546-550.\u003c/li\u003e\n \u003cli\u003eBourgonje, A. R., Abdulle, A. E., Timens, W., Hillebrands, L., Navis, G. J., Gordijn, S. J., Bolling, M. C., Dijkstra, G., Voors, A. A., Osterhaus, A. D., \u0026amp; Mulder, D. J. (2020). Angiotensin‐converting enzyme 2 (ACE2), SARS‐CoV‐2 and the pathophysiology of coronavirus disease 2019 (COVID‐19). \u003cem\u003eThe Journal of Pathology\u003c/em\u003e, \u003cem\u003e251\u003c/em\u003e(3), 228. https://doi.org/10.1002/path.5471\u003c/li\u003e\n \u003cli\u003eBrandi, N., Ciccarese, F., Rimondi, M. R., Balacchi, C., Modolon, C., Sportoletti, C., Renzulli, M., Coppola, F., \u0026amp; Golfieri, R. (2022). An Imaging Overview of COVID-19 ARDS in ICU Patients and Its Complications: A Pictorial Review. \u003cem\u003eDiagnostics\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(4), 846. https://doi.org/10.3390/diagnostics12040846\u003c/li\u003e\n \u003cli\u003eCheung KS, Hung IF, Chan PP, \u003cem\u003eet al\u003c/em\u003e. Gastrointestinal manifestations of SARS‐CoV‐2 infection and virus load in fecal samples from the Hong Kong cohort and systematic review and meta‐analysis. Gastroenterology 2020; 10.1053/j.gastro.2020.03.065\u003c/li\u003e\n \u003cli\u003eChung, M., Bernheim, A., Mei, X., Zhang, N., Huang, M., Zeng, X., Cui, J., Xu, W., Yang, Y., Fayad, Z. A., Jacobi, A., Li, K., Li, S., \u0026amp; Shan, H. (2020). CT Imaging Features of 2019 Novel Coronavirus (2019-nCoV). Radiology, 200230. https://doi.org/10.1148/radiol.2020200230\u003c/li\u003e\n \u003cli\u003eCozzi D, Moroni C, Addeo G, et al. Radiological patterns of lung involvement in inflammatory bowel disease. Gastroenterol Res Pract. 2018;5697846.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eCozzi, D., Cavigli, E., Moroni, C., Smorchkova, O., Zantonelli, G., Pradella, S., \u0026amp; Miele, V. (2021). Ground-glass opacity (GGO): A review of the differential diagnosis in the era of COVID-19. \u003cem\u003eJapanese Journal of Radiology\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(8), 721. https://doi.org/10.1007/s11604-021-01120-w\u003c/li\u003e\n \u003cli\u003eDing, X., Shang, B., Xie, C., Xin, J., \u0026amp; Yu, F. (2025). Artificial intelligence in the COVID-19 pandemic: Balancing benefits and ethical challenges in China\u0026rsquo;s response. \u003cem\u003eHumanities and Social Sciences Communications\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(1), 1-19. https://doi.org/10.1057/s41599-025-04564-x\u003c/li\u003e\n \u003cli\u003eFang Y, Zhang H, Xie J, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020;19:200432.\u003c/li\u003e\n \u003cli\u003eFerrinho P., Sidat M., Leiras G., De Barros F.P.C., Arruda H. Principalism in public health decision making in the context of the COVID-19 pandemic. Int. J. Health Plan. Manag. 2020;35:997\u0026ndash;1000. doi: 10.1002/hpm.3015\u003c/li\u003e\n \u003cli\u003eFilip, R., Puscaselu, R. G., Anchidin-Norocel, L., Dimian, M., \u0026amp; Savage, W. K. (2022). Global Challenges to Public Health Care Systems during the COVID-19 Pandemic: A Review of Pandemic Measures and Problems. \u003cem\u003eJournal of Personalized Medicine\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e(8), 1295. https://doi.org/10.3390/jpm12081295\u003c/li\u003e\n \u003cli\u003eGuan, W. J., Ni, Z. Y., Hu, Y., et al. (2020). Clinical characteristics of coronavirus disease 2019 in China. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e, 382(18), 1708\u0026ndash;1720. https://doi.org/10.1056/NEJMoa2002032\u003c/li\u003e\n \u003cli\u003eHatabu H, Hunninghake GM, Richeldi L, Brown KK, et al. Interstitial lung abnormalities detected incidentally on CT: a position paper from the Fleischner society. Lancet Respir Med. 2020;8:726\u0026ndash;737. doi: 10.1016/S2213-2600(20)30168-5\u003c/li\u003e\n \u003cli\u003eHuang C., Wang Y., Li X., Ren L., Zhao J. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. 2020;395(10223):497\u0026ndash;506. doi: 10.1016/S0140-6736(20)30183-5.\u003c/li\u003e\n \u003cli\u003eKARACAN, A., \u0026amp; AKSOY, Y. E. (2021). The radiological findings of COVID-19. \u003cem\u003eTurkish Journal of Medical Sciences\u003c/em\u003e, \u003cem\u003e51\u003c/em\u003e(7), 3328. https://doi.org/10.3906/sag-2106-203\u003c/li\u003e\n \u003cli\u003eKevadiya, B. D., Machhi, J., Herskovitz, J., Oleynikov, M. D., Blomberg, W. R., Bajwa, N., Soni, D., Das, S., Hasan, M., Patel, M., Senan, A. M., Gorantla, S., McMillan, J., Edagwa, B., Eisenberg, R., Gurumurthy, C. B., Reid, S. P., Punyadeera, C., Chang, L., . . . Gendelman, H. E. (2021). Diagnostics for SARS-CoV-2 infections. \u003cem\u003eNature Materials\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e(5), 593-605. https://doi.org/10.1038/s41563-020-00906-z\u003c/li\u003e\n \u003cli\u003eKumar Durairajan, S. S., Singh, A. K., Saravanan, U. B., Namachivayam, M., Radhakrishnan, M., Huang, D., Dhodapkar, R., \u0026amp; Zhang, H. (2023). Gastrointestinal Manifestations of SARS-CoV-2: Transmission, Pathogenesis, Immunomodulation, Microflora Dysbiosis, and Clinical Implications. \u003cem\u003eViruses\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(6), 1231. https://doi.org/10.3390/v15061231\u003c/li\u003e\n \u003cli\u003eLoeffelholz M. J., Tang Y.-W. Laboratory diagnosis of emerging human coronavirus infections: the state of the art. Emerging Microbes \u0026amp; Infections . 2020;9(1):747\u0026ndash;756. doi: 10.1080/22221751.2020.1745095.\u003c/li\u003e\n \u003cli\u003eMeng H, Xiong R, He R, et al. CT imaging and clinical course of asymptomatic cases with COVID-19 pneumonia at admission in Wuhan, China. J Inf Secur. 2020;12:S0163\u0026ndash;S4453. doi: 10.1016/j.jinf.2020.04.004.\u003c/li\u003e\n \u003cli\u003eNardi, C., Magnini, A., Calistri, L., Cavigli, E., Peired, A. J., Rastrelli, V., Carlesi, E., Zantonelli, G., Smorchkova, O., Cinci, L., Orlandi, M., Landini, N., Berillo, E., Lorini, C., Mencarini, J., Colao, M. G., Gori, L., Luzzi, V., Lazzeri, C., . . . Colagrande, S. (2023). Doubts and concerns about COVID-19 uncertainties on imaging data, clinical score, and outcomes. \u003cem\u003eBMC Pulmonary Medicine\u003c/em\u003e, \u003cem\u003e23\u003c/em\u003e, 472. https://doi.org/10.1186/s12890-023-02763-3\u003c/li\u003e\n \u003cli\u003ePan, F., Ye, T., Sun, P., et al. (2020). Time course of lung changes on chest CT during recovery from 2019 novel coronavirus (COVID-19) pneumonia. \u003cem\u003eRadiology\u003c/em\u003e, 295(3), 715\u0026ndash;721. https://doi.org/10.1148/radiol.2020200370\u003c/li\u003e\n \u003cli\u003eRousan, L. A., Elobeid, E., Karrar, M., \u0026amp; Khader, Y. (2020). Chest x-ray findings and temporal lung changes in patients with COVID-19 pneumonia. \u003cem\u003eBMC Pulmonary Medicine\u003c/em\u003e, \u003cem\u003e20\u003c/em\u003e, 245. https://doi.org/10.1186/s12890-020-01286-5\u003c/li\u003e\n \u003cli\u003eSalehi, S., Abedi, A., Balakrishnan, S., \u0026amp; Gholamrezanezhad, A. (2020). Coronavirus disease 2019 (COVID-19): A systematic review of imaging findings in 919 patients. \u003cem\u003eAJR American Journal of Roentgenology\u003c/em\u003e, 215(1), 87\u0026ndash;93. https://doi.org/10.2214/AJR.20.23034\u003c/li\u003e\n \u003cli\u003eSantus, P., Radovanovic, D., Saad, M. \u003cem\u003eet al.\u003c/em\u003e Acute dyspnea in the emergency department: a clinical review. \u003cem\u003eIntern Emerg Med\u003c/em\u003e \u003cstrong\u003e18\u003c/strong\u003e, 1491\u0026ndash;1507 (2023). https://doi.org/10.1007/s11739-023-03322-8\u003c/li\u003e\n \u003cli\u003eSattar, N., McInnes, I. B., \u0026amp; McMurray, J. J. V. (2020). Obesity is a risk factor for severe COVID-19 infection: multiple potential mechanisms. \u003cem\u003eCirculation\u003c/em\u003e, 142(1), 4\u0026ndash;6. https://doi.org/10.1161/CIRCULATIONAHA.120.047659\u003c/li\u003e\n \u003cli\u003eSharma, A., Tiwari, S., Deb, M. K., \u0026amp; Marty, J. L. (2020). Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2): A global pandemic and treatment strategies. \u003cem\u003eInternational Journal of Antimicrobial Agents\u003c/em\u003e, \u003cem\u003e56\u003c/em\u003e(2), 106054. https://doi.org/10.1016/j.ijantimicag.2020.106054\u003c/li\u003e\n \u003cli\u003eShi, H., Han, X., Jiang, N., et al. (2020). Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. \u003cem\u003eThe Lancet Infectious Diseases\u003c/em\u003e, 20(4), 425\u0026ndash;434. https://doi.org/10.1016/S1473-3099(20)30086-4\u003c/li\u003e\n \u003cli\u003eSimonnet, A., Chetboun, M., Poissy, J., et al. (2020). High prevalence of obesity in severe acute respiratory syndrome coronavirus‐2 (SARS‐CoV‐2) requiring invasive mechanical ventilation. \u003cem\u003eObesity\u003c/em\u003e, 28(7), 1195\u0026ndash;1199. https://doi.org/10.1002/oby.22831\u003c/li\u003e\n \u003cli\u003eSlika, B., Dornaika, F., Merdji, H. \u003cem\u003eet al.\u003c/em\u003e Lung pneumonia severity scoring in chest X-ray images using transformers. \u003cem\u003eMed Biol Eng Comput\u003c/em\u003e \u003cstrong\u003e62\u003c/strong\u003e, 2389\u0026ndash;2407 (2024). https://doi.org/10.1007/s11517-024-03066-3\u003c/li\u003e\n \u003cli\u003eVaduganathan, M., Vardeny, O., Michel, T., McMurray, J. J., Pfeffer, M. A., \u0026amp; Solomon, S. D. (2020). Renin\u0026ndash;angiotensin\u0026ndash;aldosterone system inhibitors in patients with Covid-19. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e, \u003cem\u003e382\u003c/em\u003e(17), 1653-1659.\u003c/li\u003e\n \u003cli\u003eWang Y, Dong C, Hu Y, et al. (2020) Temporal Changes of CT Findings in 90 Patients with COVID-19 Pneumonia: A Longitudinal Study. \u003cstrong\u003eRadiology\u003c/strong\u003e doi: 10.1148/radiol.2020200843.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWong HYF, Lam HYS, Fong AH-T, Leung ST, Chin TW-Y, Lo CSY, Lui MM-S, Lee JCY, Chiu KW-H, Chung T, Lee EYP, Wan EYF, Hung FNI, Lam TPW, Kuo M, Ng M-Y. (2020) Frequency and distribution of chest radiographic findings in COVID-19 positive patients. Radiology;0(0):201160. doi: 10.1148/radiol.2020201160.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eWorld Health Organization (2025) Available online: https://covid19.who.int/. Accessed 7 Feb 2025\u003c/li\u003e\n \u003cli\u003eYasin R, Gouda W. Chest X-ray findings monitoring COVID-19 disease course and severity. \u003cem\u003eEgypt J Radiol Nucl Med.\u003c/em\u003e (2020) 51:193. 10.1186/s43055-020-00296-x\u003c/li\u003e\n \u003cli\u003eYoon, S. H., Lee, K. H., Kim, J. Y., et al. (2020). Chest radiographic and CT findings of the 2019 novel coronavirus disease (COVID-19): analysis of nine patients treated in Korea. \u003cem\u003eKorean Journal of Radiology\u003c/em\u003e, 21(4), 494\u0026ndash;500. https://doi.org/10.3348/kjr.2020.0132\u003c/li\u003e\n \u003cli\u003eZhang H, Kang Z, Gong H, et al. Digestive system is a potential route of COVID‐19: an analysis of single‐cell coexpression pattern of key proteins in viral entry process. Gut 2020; 69 : 1010\u0026ndash;1018.\u003c/li\u003e\n \u003cli\u003eZhao, W., Zhong, Z., Xie, X., Yu, Q., \u0026amp; Liu, J. (2020). Relation between chest CT findings and clinical conditions of coronavirus disease (COVID-19) pneumonia: A multicenter study. \u003cem\u003eAmerican Journal of Roentgenology\u003c/em\u003e, 214(5), 1072\u0026ndash;1077. https://doi.org/10.2214/AJR.20.22976\u003c/li\u003e\n \u003cli\u003eZhou, F., Yu, T., Du, R., et al. (2020). Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. \u003cem\u003eThe Lancet\u003c/em\u003e, 395(10229), 1054\u0026ndash;1062. https://doi.org/10.1016/S0140-6736(20)30566-3\u003c/li\u003e\n \u003cli\u003eZhou, P., Yang, X.-L., Wang, X.-G., et al. (2020). A pneumonia outbreak associated with a new coronavirus of probable bat origin. \u003cem\u003eNature\u003c/em\u003e, 579(7798), 270\u0026ndash;273. https://doi.org/10.1038/s41586-020-2012-7\u003c/li\u003e\n \u003cli\u003eZhu, N., Zhang, D., Wang, W., et al. (2020). A novel coronavirus from patients with pneumonia in China, 2019. \u003cem\u003eNew England Journal of Medicine\u003c/em\u003e, 382(8), 727\u0026ndash;733. https://doi.org/10.1056/NEJMoa2001017\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-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, pneumonia, radiographic, symptoms, comorbidities, Ches X-ray","lastPublishedDoi":"10.21203/rs.3.rs-8125393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8125393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: COVID-19 pneumonia has diverse clinical, radiographic, and prognostic characteristics. Understanding the interactions between patient demographics, comorbidities, symptoms, imaging findings and outcomes is essential for clinical management.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: This study explored the correlations between demographics, comorbidities, clinical presentation, chest imaging findings, and clinical outcomes in patients with COVID-19 pneumonia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This retrospective study included 293 patients with confirmed COVID-19 pneumonia. Clinical data and radiographic findings from initial and follow-up chest X-ray (CXR) images were analyzed, focusing on consolidation, ground-glass opacities, pleural effusion, and lobar distributions. Associations were examined using statistical tests, with p\u0026lt;0.05 considered to be significant.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Patients were predominantly male (57%) with a median age of 57 years. Common symptoms included fever (68%), cough (68%), and shortness of breath (62%). Diabetes (44%) and hypertension (45%) were the most common comorbidities. Initial radiographs showed consolidation (56%) and ground-glass opacities (51%), mainly in the bilateral lower lobes. Follow-up imaging revealed increased pleural effusion (9% to 85%) and bilateral involvement (37% to 53%). The ground-glass opacities increased to 62%. Significant associations were observed between higher BMI and multiple symptoms and between pneumonia severity and clinical symptoms (p\u0026lt;0.001). Diabetes was correlated with diarrhea (p=0.035), and asthma was correlated with headache (p=0.010). Severe pneumonia was correlated with increased radiographic abnormalities and worse outcomes, with a mortality rate of 14 %.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: This study examined the radiographic findings in COVID-19 pneumonia and their correlation with clinical manifestations and comorbidities. Chest imaging is crucial for monitoring disease progression in severe cases.\u003c/p\u003e","manuscriptTitle":"Associations between COVID-19 symptoms, chest X-Ray, and patient characteristics: A Comprehensive Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-18 17:56:29","doi":"10.21203/rs.3.rs-8125393/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-01-09T23:10:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233569807703620128231386535066199178426","date":"2025-12-22T13:15:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337203472107863112339118564905849256361","date":"2025-12-14T15:14:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-12T14:36:10+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-20T05:03:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-19T08:22:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-19T08:20:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Infectious Diseases","date":"2025-11-16T05:52:11+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-infectious-diseases","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"infd","sideBox":"Learn more about [BMC Infectious Diseases](http://bmcinfectdis.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/infd","title":"BMC Infectious Diseases","twitterHandle":"#bmcinfectdis","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c7f89b81-14a9-4ece-867a-1a6b9c7b8334","owner":[],"postedDate":"December 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-12-18T17:56:29+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-18 17:56:29","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8125393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8125393","identity":"rs-8125393","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}