The role of inferior vena cava diameter and collapsibility index assessment of fluid status among hemodialysis dependent patients : A cross sectional comparative study

The role of inferior vena cava diameter and collapsibility index assessment of fluid status among hemodialysis dependent patients : A cross sectional comparative study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The role of inferior vena cava diameter and collapsibility index assessment of fluid status among hemodialysis dependent patients : A cross sectional comparative study Naveed Ahmed Shah, Sundus Ali, Harmla Hussain, Muhammad Omer Amir, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7874240/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Accurate assessment of fluid status in hemodialysis dependent patients to achieve a euvolumic state remains the cornerstone of Chronic Kidney disease management. There are various clinical and physical examination parameters for optimal estimation of fluid status in CKD patients. This research focuses on studying the comparison between inferior vena cava diameter and compressibility index with physical signs for fluid manage in pre and post dialysis patients. Methods and results: A cross sectional comparative study was conducted out at the department of medicine and dialysis unit of Combined Military Hospital (CMH) Malir. A total of 45 participants were inducted in the study. The sample was predominantly male i.e. 62.20% (n=28) with 37.80% (n=17) being female. The mean age of the patients was 50.47 years (SD = 11.8). Comorbidities were prevalent, with hypertension present in 93.30% of patients, followed by diabetes (40.00%) and ischemic heart diseases (17.80%). Conclusion: Based on the research findings we concluded that ultrasound is a significantly reliable method for estimation of the fluid status in pre and post HD patients as compared to physical signs. Figures Figure 1 Figure 2 Figure 3 1. Introduction Cardiovascular complications are the leading cause of mortality and morbidity in End stage renal disease patients ( 1 , 2 ). Fluid overload over the course of progression of CKD serves as the major contributing factor to the development of congestive heart failure and other cardiovascular diseases, leading to inevitable adverse outcomes ( 3 ). Hence, accurate assessment of fluid status in hemodialysis dependent patients to achieve a euvolemic state remains the cornerstone of Chronic Kidney disease management. There are various clinical and physical examination parameters for optimal estimation of fluid status in CKD patients. However nonspecific clinical parameters such as heart rate, blood pressure, edema or venous congestion are largely unreliable. Bio-impedance spectroscopy, central venous pressure (CVP), lung ultrasonography, pulmonary artery catheterization, inferior vena cava diameter and biomarkers such (BNP, pro-BNP and ANP) are some of the tools used for technical assessment of fluid overload ( 4 ). These indices are used to assess fluid status and determine the effectiveness of dialysis in removing excess fluid from the body. This research focuses on studying the inferior vena cava diameter and compressibility index in pre and post dialysis patients for assessment of fluid status. By analyzing these indices, researchers aim to understand how they can be used as indicators for fluid management in dialysis patients. The findings of this research will potentially contribute to improving a practically reliable method for estimation of fluid status and help in effective fluid management of dialysis patients. 2. Materials and Methods 2.1 Study design: A cross sectional comparative study was conducted over the period of 03 months, between January 2024 and March 2024. 2.2 Study area and population: The research was carried out at the department of medicine and dialysis unit of Combined Military Hospital (CMH) Malir. A total of 45 participants were inducted in the study after taking informed consent before enrollment in the study. The participants were divided into two groups: 2.21. Group A Chronic kidney disease patients on hemodialysis 2.22. Group B Healthy individuals with no known disease All the participants were subjected to following inclusion and exclusion criteria: Inclusion criteria : Chronic kidney disease (CKD) patients undergoing regular hemodialysis and healthy individuals between 15 to 65 years of age were recruited in the study. Exclusion criteria : Healthy individuals under the age of 15 years or over the age of 65 years, patients undergoing hemodialysis for AKI, patients on peritoneal dialysis and those who refused to take part in the study were excluded from the research. 2.3 Data collection: The research was performed in accordance with the ethical principles outlined in the declarartion of Helsinki and its subsequent ammendments. Approval for the study was obtained from Ethical review committee Combined Military Hospital Malir Cantt reference no. 116/2023/Trg/ERC. Written informed consent was obtained from all participants (or their legal guardians, where applicable) prior to their inclusion in the study. All data were anonymized to ensure participant confidentiality and used solely for research purposes. Demographics and clinical characteristics including: age, gender, comorbidities, duration of CKD and duration on haemodialysis were obtained from all the participants. Inferior vena cava diameter (IVCD) measurement, before and after the hemodialysis sessions, was done by a classified radiologist. With the patient in the supine position, IVCD was measured 1.5 cm below the diaphragm at the junction of IVC and hepatic vein in the sub-xiphoid area, using 2 dimensional M-mode ultrasonography. Measurements were done during inspiration as well as expiration and calculation of mean value was done. IVC- Collapsibility index (CI) was calculated by the following formula: IVC-CI = [IVCD maximum (expiratory) – IVCD minimum (inspiratory)] / [IVCD maximum (expiratory)] X 100 2.4 Statistical analysis: Data analysis was performed by SPSS version 22. Numerical Data was presented as mean ± Standard deviation with comparison made by T-test. P value of < 0.05 was considered statistically significant. 2.5 Ethical considerations: An approval from Institutional review board (IRB) of CMH Malir was obtained prior to the conduction of study. Patients’ anonymity and confidentiality was maintained throughout the research. 2. Results A total of 45 participants were enrolled in the study. The sample was predominantly male i.e. 62.20% (n = 28) with 37.80% (n = 17) being female (Table 1 ). Age distribution revealed that 44.40% of patients were between 46–60 years, 31.10% were of 30–45 years, and 24.40% were over the age of 60 years. The mean age of the patients was 50.47 years (SD = 11.8). Comorbidities were prevalent, with hypertension present in 93.30% of patients, followed by diabetes (40.00%) and ischemic heart diseases (17.80%). Other comorbid conditions included Hepatitis C (8.90%), ADPKD (6.70%), asthma, TB, hyperthyroidism, and peptic ulcer disease, each at 4.40%. The mean systolic BP was 154 mmHg (SD = 27.4) with diastolic BP being 82.2 mmHg (SD = 16.3). The average pre-dialysis and post-dialysis weights were 62.2 kg (SD = 9.7) and 60.69 kg (SD = 9.7) respectively (Table 2 ). CKD duration averages 3.42 years (SD = 3.52), and duration on HD was 2.01 years (SD = 2.4). Pre-dialysis IVCD during inspiration was 1.2cm (SD = 0.35) and expiration was 0.97cm (SD = 0.29), with post-dialysis IVCD values slightly reduced to 1.03cm (SD = 0.33) and 0.8cm (SD = 0.27) respectively (Table 3 ). Table 1 : Demographic data and baseline factors: (n = 45) Table 1 Patient's demographics and baseline characteristics (n = 45) Characteristics N Percentage (%) Sex Male 28 62.20% Female 17 37.80% Age groups (years) 30–45 Years 14 31.10% 46–60 Years 20 44.40% > 60 Years 11 24.40% Comorbidities Hypertension 42 93.30% Diabetes 18 40.00% Ischemic Heart Diseases 8 17.80% Hepatitis C 4 8.90% ADPKD 3 6.70% Asthma 2 4.40% Pulmonary TB 2 4.40% Hyperthyroidism 2 4.40% Peptic Ulcer Disease 2 4.40% Characteristics Mean SD Age (years) 50.47 11.8 Pre-dialysis weight (kg) 62.2 9.7 Post-dialysis weight (kg) 60.69 9.7 CKD duration (years) 3.42 3.52 Duration on HD 2.01 2.4 BP Systolic (mmHg) 154 27.4 BP Diastolic (mmHg) 82.2 16.3 Pre dialysis IVCDi 1.2 0.35 Pre dialysis IVCDe 0.97 0.29 Post dialysis IVCDi 1.03 0.33 Post dialysis IVCDe 0.8 0.27 Description Table 1 represents the demographic and baseline characteristics. Table 2 : Weight (kg) before and after HD (n = 45) Table 2 Weight (kg) pre and post HD (n = 45) Characteristics Pre-HD Mean (SD) Post-HD Mean (SD) P-Value Weight (Kg) 62.2 (9.73) 60.7 (9.7) < .001 Description Table 2 presents the mean weight (kg) of 45 patients before and after hemodialysis (HD). The pre-HD mean weight is 62.2 kg (SD = 9.73), while the post-HD mean weight is slightly lower at 60.7 kg (SD = 9.7). The p-value for the difference in weight before and after HD is < 0.001, indicating a statistically significant reduction in weight following dialysis. Table 3 : IVC Parameters before and after HD (n = 45) Table 3 IVC Parameters pre and post HD (n = 45) Characteristics Pre-HD Mean (SD) Post-HD Mean (SD) P-Value IVC inspiratory 1.2024 (0.355) 1.0329 (0.331) < .001 IVC expiratory 0.9716 (0.299) 0.8129 (0.273) < .001 Collapsibility index 0.2619 (0.21) 0.2928 (0.268) < .001 IVC parameters are measured in cm Description : Table 3 presents the inferior vena cava (IVC) parameters before and after hemodialysis (HD) in 45 patients. The mean IVC inspiratory diameter decreased from 1.2024 cm (SD = 0.355) pre-HD to 1.0329 cm (SD = 0.331) post-HD, with a p-value of < 0.001. The IVC expiratory diameter also decreased from 0.9716 cm (SD = 0.299) pre-HD to 0.8129 cm (SD = 0.273) post-HD, with a p-value of < 0.001. The collapsibility index increased from 0.2619 (SD = 0.21) pre-HD to 0.2928 (SD = 0.268) post-HD, also showing statistical significance with a p-value of < 0.001 ROC Analysis- Comparing Physical signs with IVC Indices via Ultrasound To compare the effectiveness of physical examinations and IVC indices via ultrasound in evaluating fluid status among HD patients, we first computed composite scores using logistic regression models. For the handheld ultrasound examination, predictors included IVCD during Inspiration, Expiration, and the Collapsibility Index (C Index). For the physical signs examination, predictors were Weight and Auscultation findings. These composite scores were used to construct ROC curves, with pre- and post-HD conditions serving as the response variable. The ROC curves, shown in Fig. 1 , were generated to visualize the diagnostic performance of both tests, and the areas under the curves (AUCs) were calculated. The AUC for the IVC indices via ultrasound was 0.6543, while the AUC for the physical signs was 0.6188. Both AUCs are greater than 0.5, indicating that the diagnostic performance of both tests is better than random guessing. However, the AUC for the ultrasound examination (0.6543) is higher than that for the physical signs examination (0.6188), suggesting that the ultrasound examination has a better diagnostic performance. To statistically compare the two ROC curves, we employed DeLong's test, which is suitable for comparing the AUCs of correlated ROC curves. The results of DeLong's test showed a Z-value of 0.59793 and a p-value of 0.5499. The 95% confidence interval for the difference in AUCs ranged from − 0.0810 to 0.1521. Since the p-value was greater than the conventional threshold of 0.05, we conclude that there was no statistically significant difference in the diagnostic performance between the physical signs and ultrasound in distinguishing between pre- and post-HD conditions. Comparing both groups (Healthy with Patients) To evaluate the diagnostic performance of different parameters in distinguishing between treatment and control groups, we performed ROC curve analyses for weight, IVCi, IVCe, and the Collapsibility Index. The resulting ROC curves are presented in Fig. 2 . The key metrics, including the AUC, standard error, p-values, and 95% confidence intervals, are summarized in the provided table. The AUC for weight is 0.6614, with a standard error of 0.0498 and a p-value of 0.0012. This indicates that weight has a statistically significant ability to distinguish between the treatment and control groups, as the AUC is significantly greater than 0.5. The 95% confidence interval for weight ranges from 0.5477 to 0.7570, further supporting this finding. For IVCi, the AUC is 0.7498, with a standard error of 0.0456 and a p-value of less than 0.001. This suggests IVCi has a strong and statistically significant discriminative ability, as evidenced by the high AUC. The 95% confidence interval of 0.6462 to 0.8439, indicating a robust diagnostic performance. IVCe also shows a significant and good discriminative power, with an AUC of 0.7174, a standard error of 0.0474, and a p-value of less than 0.001. The 95% confidence interval for IVCe is 0.6056 to 0.8162, indicating its effectiveness in distinguishing between the two groups. In contrast, the AUC for the Collapsibility Index is 0.5358, with a standard error of 0.0525 and a p-value of 0.4954. This suggests that the Collapsibility Index does not have a statistically significant discriminative ability, as the AUC is not significantly greater than 0.5. The 95% confidence interval for the Collapsibility Index ranges from 0.4165 to 0.6505, including the value of 0.5, indicating that its diagnostic performance is not significantly different from chance. In conclusion, the ROC curve analyses indicate that weight, IVCi, and IVCe are significant predictors for distinguishing between the treatment and control groups. Among these parameters, IVCi has the highest AUC, suggesting it is the most effective parameter for this purpose. However, the Collapsibility Index does not show significant discriminative ability in this context. Test results of the ROC curve. Comparison between weight, IVCi, IVCe, and Collapsibility Index in both groups (Healthy and Patients) Test Result Variable(s) Area Standard Error P-value 95% Confidence Interval Lower Bound Upper Bound Weight 0.6614 0.0498 0.0012 0.5477 0.7570 Inspiration 0.7498 0.0456 < 0.001 0.6462 0.8439 Expiration 0.7174 0.0474 < 0.001 0.6056 0.8162 C Index 0.5358 0.0525 0.4954 0.4165 0.6505 Comparing the IVC parameters in pre and post dialysis conditions In our investigation of IVCD in both pre and post settings, ROC curve analysis was employed to evaluate the discriminatory ability of IVCi, IVCe and Collapsibility Index variables. The curves are provided in Fig. 3 . For IVCi, the obtained AUC was 0.6277, indicating a moderate discriminatory ability in distinguishing between pre and post settings. Similarly, the IVCe variable yielded an AUC of 0.6612, suggesting a slightly better discriminatory power compared to IVCi. Interestingly, the Collapsibility Index variable exhibited a lower AUC of 0.5244, indicating a limited ability to differentiate between pre and post dialysis settings. It's important to note that an AUC of 0.5 suggests performance no better than random chance. While IVCi and IVCe variables showed some ability to discriminate between pre and post settings, the Collapsibility Index variable appeared, comparatively, less effective in this regard. The p-values, given below, for IVCi and IVCe are less than 0.05 which indicates that these results are statistically significant from those obtained by chance. The p-value for Collapsibility index is greater than 0.05 which is not statistically significant at 5% level of significance. Test results of the ROC curve. Comparison between IVC parameters in pre and post settings Test Result Variable(s) Area Standard Error P-value 95% Confidence Interval Lower Bound Upper Bound IVCi 0.6334 0.0507 0.0086 0.5134 0.7390 IVCe 0.6500 0.0502 0.0028 0.5403 0.7587 Collapsibility Index 0.5279 0.0526 0.5955 0.4075 0.6404 3. Discussion Fluid overload is the most significant yet a very poor prognostic factor in end stage renal disease patients, ultimately leading to prolonged hospital stay, impaired oxygenation of vital organs and increased morbidity and mortality (a-d). Although several clinical evaluation methods and objective techniques have been introduced (e), accurate assessment of volume overload in management of CKD patients remains an unmet clinical need. In our study, we compared the physical examination parameters to inferior vena cava diameter measurement via ultrasound for the assessment of fluid overload. Based on the results, there was statistically no significant difference in the diagnostic performance between the physical signs and ultrasound in distinguishing between pre- and post-HD conditions. Weight, IVCi, and IVCe are significant predictors for distinguishing between the treatment and control groups. Among these parameters, IVCi is the most effective parameter for this purpose. Pre and Post Dialysis IVCi and IVCe were statistically significant. However, the Collapsibility Index did not show significant discriminative ability in treatment and control group as well as Pre and Post dialysis groups. There are various studies that correlate with our findings and have concluded superiority of IVC parameters over the physical examination indices in assessment of fluid status. In one of an interesting article by Millington, the author declared that although inferior vena cava diameter and collapsibility index are non-invasive means for fluid assessment, they are not very beneficial in majority of the patients( 5 ). Similarly another meta-analysis concluded that ultrasonographic measurement of inferior vena cava diameter or collapsibility index is not a very reliable index of fluid assessment ( 6 ). Likewise, Trivedi et al in his study revealed that IVC diameter and collapsibility index are not routinely useful for estimation of fluid status in hemodialysis patients ( 7 ). There are multiple factors that contribute to the uncertainty of IVC parameters. The effect of respiration, intra-thoracic or intra-abdominal pressure, blood volume, right heart function or operator dependency are noteworthy. Therefore, despite the non-invasive nature and good applicability of IVC parameters, their utility for assessment of volume status in hemodialysis dependent patients’ needs to be studied on a broader scale. However, contrary to the above mentioned findings, a recent study reported that measurements of inferior vena cava diameter and collapsibility index pre and post dialysis is very productive method for estimation of fluid status as compared to clinical parameters which are largely unreliable( 8 ). Moreover, some studies have compared IVC-CI to CVP and concluded it to be a low risk yet high sensitivity alternative to the CVP, favoring it to be an ideal tool in assessment of fluid overload and fluid responsiveness in critically ill patients ( 9 , 10 ). Hence, additional research is required to further investigate the efficacy of IVCD and IVC-CI for estimation of volume overload in the end stage renal patients. Meanwhile, clinical evaluation methods are equitably convenient in assessing the fluid status. 5. Conclusion Ultrasound measurement of IVCD is a good objective tool when compared with clinical parameters for assessment of fluid status. Integrating these measurements can lead to better assessment of patients’ volume status and subsequent improved outcomes. Declarations 6. Ethics Approval and consent to participate Approval for the study was obtained from Ethical review committee Combined Military Hospital Malir Cantt reference no. 116/2023/Trg/ERC. Written informed consent was obtained from all participants (or their legal guardians, where applicable) prior to their inclusion in the study. All data were anonymized to ensure participant confidentiality and used solely for research purposes. 7. Consent for publication Not Applicable 9. Conflict of interest The authors declare no conflict of interest regarding research study, publication or/and authorship. 10. Funding None. Author Contribution Naveed Ahmed Shah designed the studySundus Ali wrote the main manuscriptHarmla Hussain wrote the main manuscriptMuhammad Omer Amir collected the dataAli Bin Nasir collected the dataMuhammad Asim prepared the tables and analysed the data 12. Acknowledgements I acknowledge Dr Saima Afaq for her support in guiding us about this article. 8. Availability of Data and Materials The datasets generated and/or analysed during the current study are not publicly available due to confidentiality but are available from the corresponding author on reasonable request. References Matsushita K, Ballew SH, Wang AY, Kalyesubula R, Schaeffner E, Agarwal R. Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease. Nat Rev Nephrol. 2022;18(11):696–707. Jankowski J, Floege J, Fliser D, Böhm M, Marx N. Cardiovascular disease in chronic kidney disease: pathophysiological insights and therapeutic options. Circulation. 2021;143(11):1157–72. Loutradis C, Sarafidis PA, Ferro CJ, Zoccali C. Volume overload in hemodialysis: diagnosis, cardiovascular consequences, and management. Nephrol Dialysis Transplantation. 2021;36(12):2182–93. Ekinci C, Karabork M, Siriopol D, Dincer N, Covic A, Kanbay M. Effects of volume overload and current techniques for the assessment of fluid status in patients with renal disease. Blood Purif. 2018;46(1):34–47. Millington SJ. Ultrasound assessment of the inferior vena cava for fluid responsiveness: easy, fun, but unlikely to be helpful. Can J Anesthesia/Journal canadien d'anesthésie. 2019;66(6):633–8. Orso D, Paoli I, Piani T, Cilenti FL, Cristiani L, Guglielmo N. Accuracy of ultrasonographic measurements of inferior vena cava to determine fluid responsiveness: a systematic review and meta-analysis. J Intensive Care Med. 2020;35(4):354–63. Trivedi V, Prajapati M, Prajapati DJ, Bhosale G, Nayak J, Panchal H. Is Inferior vena cava diameter, a reliable indicator for fluid status in end-stage renal disease patients?-A prospective observational study. Indian J Transplantation. 2022;16(2):200–4. Hafiz MA, Mohamed EA, Mohamed MA, Ahmed MA. Inferior vena cava diameter and collapsibility index as a marker of fluid status in regular hemodialysis patients. Egypt J Intern Med. 2021;33:1–6. Saad SI, Behairymb AS, Mahdy EW. Role Of Lung Ultrasound, CVP And Inferior Vena Cava Diameter And Collapsibility Index In Assessment Of End Point Of Fluid Therapy In Critically ILL Patient With Sepsis. Benha J Appl Sci. 2022;7(10):33–40. Maghraby HM, Awad EA, Mohammed RA, Abdelmaniem MF, Sherif HM, Sabry R. Inferior Vena Cava Diameter and Collapsibility Index measurements by Ultrasound and its Correlation with Central Venous Pressure in Critically Ill Patients. Al-Azhar Int Med J. 2023;4(2):26. Magee G, Zbrozek A. Fluid overload is associated with increases in length of stay and hospital costs: pooled analysis of data from more than 600 US hospitals. ClinicoEconomics and Outcomes Research. 2013 Jun 26:289–96. Arikan AA, Zappitelli M, Goldstein SL, Naipaul A, Jefferson LS, Loftis LL. Fluid overload is associated with impaired oxygenation and morbidity in critically ill children. Pediatr Crit Care Med. 2012;13(3):253–8. Tsai YC, Chiu YW, Tsai JC, Kuo HT, Hung CC, Hwang SJ, Chen TH, Kuo MC, Chen HC. Association of fluid overload with cardiovascular morbidity and all-cause mortality in stages 4 and 5 CKD. Clin J Am Soc Nephrol. 2015;10(1):39–46. Zoccali C, Moissl U, Chazot C, Mallamaci F, Tripepi G, Arkossy O, Wabel P, Stuard S. Chronic fluid overload and mortality in ESRD. J Am Soc Nephrol. 2017;28(8):2491–7. La Porta E, Lanino L, Calatroni M, Caramella E, Avella A, Quinn C, Faragli A, Estienne L, Alogna A, Esposito P. Volume balance in chronic kidney disease: evaluation methodologies and innovation opportunities. Kidney Blood Press Res. 2021;46(4):396–410. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7874240","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":534548484,"identity":"4447a8ab-b4b2-4047-aae1-11389cb0c0ab","order_by":0,"name":"Naveed Ahmed 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3","display":"","copyAsset":false,"role":"figure","size":84180,"visible":true,"origin":"","legend":"\u003cp\u003eComparing IVC parameters in pre and post-settings\u003c/p\u003e","description":"","filename":"Picture3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7874240/v1/b27b8022fa659226043ed2d8.jpg"},{"id":94641106,"identity":"7a876f90-6ab2-4af3-a823-f822873b0a42","added_by":"auto","created_at":"2025-10-29 07:51:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1139404,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7874240/v1/ebb18d91-d18e-4d5a-a4b1-1a09e96e4602.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The role of inferior vena cava diameter and collapsibility index assessment of fluid status among hemodialysis dependent patients : A cross sectional comparative study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eCardiovascular complications are the leading cause of mortality and morbidity in End stage renal disease patients (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Fluid overload over the course of progression of CKD serves as the major contributing factor to the development of congestive heart failure and other cardiovascular diseases, leading to inevitable adverse outcomes (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Hence, accurate assessment of fluid status in hemodialysis dependent patients to achieve a euvolemic state remains the cornerstone of Chronic Kidney disease management. There are various clinical and physical examination parameters for optimal estimation of fluid status in CKD patients. However nonspecific clinical parameters such as heart rate, blood pressure, edema or venous congestion are largely unreliable. Bio-impedance spectroscopy, central venous pressure (CVP), lung ultrasonography, pulmonary artery catheterization, inferior vena cava diameter and biomarkers such (BNP, pro-BNP and ANP) are some of the tools used for technical assessment of fluid overload (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). These indices are used to assess fluid status and determine the effectiveness of dialysis in removing excess fluid from the body. This research focuses on studying the inferior vena cava diameter and compressibility index in pre and post dialysis patients for assessment of fluid status. By analyzing these indices, researchers aim to understand how they can be used as indicators for fluid management in dialysis patients. The findings of this research will potentially contribute to improving a practically reliable method for estimation of fluid status and help in effective fluid management of dialysis patients.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1 Study design:\u003c/h2\u003e\u003cp\u003eA cross sectional comparative study was conducted over the period of 03 months, between January 2024 and March 2024.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2 Study area and population:\u003c/h2\u003e\u003cp\u003eThe research was carried out at the department of medicine and dialysis unit of Combined Military Hospital (CMH) Malir. A total of 45 participants were inducted in the study after taking informed consent before enrollment in the study. The participants were divided into two groups:\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.21. Group A\u003c/h2\u003e\u003cp\u003eChronic kidney disease patients on hemodialysis\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.22. Group B\u003c/h2\u003e\u003cp\u003eHealthy individuals with no known disease\u003c/p\u003e\u003cp\u003eAll the participants were subjected to following inclusion and exclusion criteria:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eChronic kidney disease (CKD) patients undergoing regular hemodialysis and healthy individuals between 15 to 65 years of age were recruited in the study.\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eExclusion criteria\u003c/b\u003e:\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eHealthy individuals under the age of 15 years or over the age of 65 years, patients undergoing hemodialysis for AKI, patients on peritoneal dialysis and those who refused to take part in the study were excluded from the research.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.3 Data collection:\u003c/h2\u003e\u003cp\u003e The research was performed in accordance with the ethical principles outlined in the declarartion of Helsinki and its subsequent ammendments. Approval for the study was obtained from Ethical review committee Combined Military Hospital Malir Cantt reference no. 116/2023/Trg/ERC. Written informed consent was obtained from all participants (or their legal guardians, where applicable) prior to their inclusion in the study. All data were anonymized to ensure participant confidentiality and used solely for research purposes. Demographics and clinical characteristics including: age, gender, comorbidities, duration of CKD and duration on haemodialysis were obtained from all the participants. Inferior vena cava diameter (IVCD) measurement, before and after the hemodialysis sessions, was done by a classified radiologist. With the patient in the supine position, IVCD was measured 1.5 cm below the diaphragm at the junction of IVC and hepatic vein in the sub-xiphoid area, using 2 dimensional M-mode ultrasonography. Measurements were done during inspiration as well as expiration and calculation of mean value was done. IVC- Collapsibility index (CI) was calculated by the following formula:\u003c/p\u003e\u003cp\u003eIVC-CI = [IVCD maximum (expiratory) \u0026ndash; IVCD minimum (inspiratory)] / [IVCD maximum (expiratory)] X 100\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.4 Statistical analysis:\u003c/h2\u003e\u003cp\u003eData analysis was performed by SPSS version 22. Numerical Data was presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;Standard deviation with comparison made by T-test. P value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003e2.5 Ethical considerations:\u003c/h2\u003e\u003cp\u003eAn approval from Institutional review board (IRB) of CMH Malir was obtained prior to the conduction of study. Patients\u0026rsquo; anonymity and confidentiality was maintained throughout the research.\u003c/p\u003e\u003c/div\u003e"},{"header":"2. Results","content":"\u003cp\u003eA total of 45 participants were enrolled in the study. The sample was predominantly male i.e. 62.20% (n\u0026thinsp;=\u0026thinsp;28) with 37.80% (n\u0026thinsp;=\u0026thinsp;17) being female (Table\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Age distribution revealed that 44.40% of patients were between 46\u0026ndash;60 years, 31.10% were of 30\u0026ndash;45 years, and 24.40% were over the age of 60 years. The mean age of the patients was 50.47 years (SD\u0026thinsp;=\u0026thinsp;11.8). Comorbidities were prevalent, with hypertension present in 93.30% of patients, followed by diabetes (40.00%) and ischemic heart diseases (17.80%). Other comorbid conditions included Hepatitis C (8.90%), ADPKD (6.70%), asthma, TB, hyperthyroidism, and peptic ulcer disease, each at 4.40%. The mean systolic BP was 154 mmHg (SD\u0026thinsp;=\u0026thinsp;27.4) with diastolic BP being 82.2 mmHg (SD\u0026thinsp;=\u0026thinsp;16.3). The average pre-dialysis and post-dialysis weights were 62.2 kg (SD\u0026thinsp;=\u0026thinsp;9.7) and 60.69 kg (SD\u0026thinsp;=\u0026thinsp;9.7) respectively (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). CKD duration averages 3.42 years (SD\u0026thinsp;=\u0026thinsp;3.52), and duration on HD was 2.01 years (SD\u0026thinsp;=\u0026thinsp;2.4). Pre-dialysis IVCD during inspiration was 1.2cm (SD\u0026thinsp;=\u0026thinsp;0.35) and expiration was 0.97cm (SD\u0026thinsp;=\u0026thinsp;0.29), with post-dialysis IVCD values slightly reduced to 1.03cm (SD\u0026thinsp;=\u0026thinsp;0.33) and 0.8cm (SD\u0026thinsp;=\u0026thinsp;0.27) respectively (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e: \u003cb\u003eDemographic data and baseline factors: (n\u0026thinsp;=\u0026thinsp;45)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003ePatient's demographics and baseline characteristics (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003ePercentage (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62.20%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37.80%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge groups (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;45 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e31.10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e46\u0026ndash;60 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;60 Years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eComorbidities\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHypertension\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93.30%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDiabetes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIschemic Heart Diseases\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.80%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHepatitis C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.90%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eADPKD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAsthma\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePulmonary TB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHyperthyroidism\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePeptic Ulcer Disease\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.40%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e50.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre-dialysis weight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost-dialysis weight (kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60.69\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCKD duration (years)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDuration on HD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP Systolic (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e154\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBP Diastolic (mmHg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e82.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre dialysis IVCDi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePre dialysis IVCDe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost dialysis IVCDi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePost dialysis IVCDe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e represents the demographic and baseline characteristics.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e: \u003cb\u003eWeight (kg) before and after HD (n\u0026thinsp;=\u0026thinsp;45)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eWeight (kg) pre and post HD (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-HD\u003c/p\u003e\u003cp\u003e Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-HD\u003c/p\u003e\u003cp\u003e Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight (Kg)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e62.2 (9.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60.7 (9.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the mean weight (kg) of 45 patients before and after hemodialysis (HD). The pre-HD mean weight is 62.2 kg (SD\u0026thinsp;=\u0026thinsp;9.73), while the post-HD mean weight is slightly lower at 60.7 kg (SD\u0026thinsp;=\u0026thinsp;9.7). The p-value for the difference in weight before and after HD is \u0026lt;\u0026thinsp;0.001, indicating a statistically significant reduction in weight following dialysis.\u003c/p\u003e\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e: \u003cb\u003eIVC Parameters before and after HD (n\u0026thinsp;=\u0026thinsp;45)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eIVC Parameters pre and post HD (n\u0026thinsp;=\u0026thinsp;45)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePre-HD\u003c/p\u003e\u003cp\u003e Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003ePost-HD\u003c/p\u003e\u003cp\u003e Mean (SD)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eP-Value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIVC inspiratory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1.2024 (0.355)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.0329 (0.331)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIVC expiratory\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.9716 (0.299)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.8129 (0.273)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollapsibility index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.2619 (0.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.2928 (0.268)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003eIVC parameters are measured in cm\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eDescription\u003c/b\u003e: Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the inferior vena cava (IVC) parameters before and after hemodialysis (HD) in 45 patients. The mean IVC inspiratory diameter decreased from 1.2024 cm (SD\u0026thinsp;=\u0026thinsp;0.355) pre-HD to 1.0329 cm (SD\u0026thinsp;=\u0026thinsp;0.331) post-HD, with a p-value of \u0026lt;\u0026thinsp;0.001. The IVC expiratory diameter also decreased from 0.9716 cm (SD\u0026thinsp;=\u0026thinsp;0.299) pre-HD to 0.8129 cm (SD\u0026thinsp;=\u0026thinsp;0.273) post-HD, with a p-value of \u0026lt;\u0026thinsp;0.001. The collapsibility index increased from 0.2619 (SD\u0026thinsp;=\u0026thinsp;0.21) pre-HD to 0.2928 (SD\u0026thinsp;=\u0026thinsp;0.268) post-HD, also showing statistical significance with a p-value of \u0026lt;\u0026thinsp;0.001\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eROC Analysis- Comparing Physical signs with IVC Indices via Ultrasound\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo compare the effectiveness of physical examinations and IVC indices via ultrasound in evaluating fluid status among HD patients, we first computed composite scores using logistic regression models. For the handheld ultrasound examination, predictors included IVCD during Inspiration, Expiration, and the Collapsibility Index (C Index). For the physical signs examination, predictors were Weight and Auscultation findings. These composite scores were used to construct ROC curves, with pre- and post-HD conditions serving as the response variable.\u003c/p\u003e\u003cp\u003eThe ROC curves, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, were generated to visualize the diagnostic performance of both tests, and the areas under the curves (AUCs) were calculated. The AUC for the IVC indices via ultrasound was 0.6543, while the AUC for the physical signs was 0.6188. Both AUCs are greater than 0.5, indicating that the diagnostic performance of both tests is better than random guessing. However, the AUC for the ultrasound examination (0.6543) is higher than that for the physical signs examination (0.6188), suggesting that the ultrasound examination has a better diagnostic performance. To statistically compare the two ROC curves, we employed DeLong's test, which is suitable for comparing the AUCs of correlated ROC curves.\u003c/p\u003e\u003cp\u003eThe results of DeLong's test showed a Z-value of 0.59793 and a p-value of 0.5499. The 95% confidence interval for the difference in AUCs ranged from \u0026minus;\u0026thinsp;0.0810 to 0.1521. Since the p-value was greater than the conventional threshold of 0.05, we conclude that there was no statistically significant difference in the diagnostic performance between the physical signs and ultrasound in distinguishing between pre- and post-HD conditions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparing both groups (Healthy with Patients)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the diagnostic performance of different parameters in distinguishing between treatment and control groups, we performed ROC curve analyses for weight, IVCi, IVCe, and the Collapsibility Index. The resulting ROC curves are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The key metrics, including the AUC, standard error, p-values, and 95% confidence intervals, are summarized in the provided table.\u003c/p\u003e\u003cp\u003eThe AUC for weight is 0.6614, with a standard error of 0.0498 and a p-value of 0.0012. This indicates that weight has a statistically significant ability to distinguish between the treatment and control groups, as the AUC is significantly greater than 0.5. The 95% confidence interval for weight ranges from 0.5477 to 0.7570, further supporting this finding. For IVCi, the AUC is 0.7498, with a standard error of 0.0456 and a p-value of less than 0.001. This suggests IVCi has a strong and statistically significant discriminative ability, as evidenced by the high AUC. The 95% confidence interval of 0.6462 to 0.8439, indicating a robust diagnostic performance. IVCe also shows a significant and good discriminative power, with an AUC of 0.7174, a standard error of 0.0474, and a p-value of less than 0.001. The 95% confidence interval for IVCe is 0.6056 to 0.8162, indicating its effectiveness in distinguishing between the two groups. In contrast, the AUC for the Collapsibility Index is 0.5358, with a standard error of 0.0525 and a p-value of 0.4954. This suggests that the Collapsibility Index does not have a statistically significant discriminative ability, as the AUC is not significantly greater than 0.5. The 95% confidence interval for the Collapsibility Index ranges from 0.4165 to 0.6505, including the value of 0.5, indicating that its diagnostic performance is not significantly different from chance.\u003c/p\u003e\u003cp\u003eIn conclusion, the ROC curve analyses indicate that weight, IVCi, and IVCe are significant predictors for distinguishing between the treatment and control groups. Among these parameters, IVCi has the highest AUC, suggesting it is the most effective parameter for this purpose. However, the Collapsibility Index does not show significant discriminative ability in this context.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTest results of the ROC curve. Comparison between weight, IVCi, IVCe, and Collapsibility Index in both groups (Healthy and Patients)\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTest Result\u003c/p\u003e\u003cp\u003eVariable(s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eArea\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStandard Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLower Bound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUpper Bound\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWeight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.6614\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0012\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5477\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7570\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eInspiration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0456\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.8439\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eExpiration\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.7174\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.6056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.8162\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eC Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.5358\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0525\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.4954\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4165\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.6505\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eComparing the IVC parameters in pre and post dialysis conditions\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn our investigation of IVCD in both pre and post settings, ROC curve analysis was employed to evaluate the discriminatory ability of IVCi, IVCe and Collapsibility Index variables. The curves are provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eFor IVCi, the obtained AUC was 0.6277, indicating a moderate discriminatory ability in distinguishing between pre and post settings. Similarly, the IVCe variable yielded an AUC of 0.6612, suggesting a slightly better discriminatory power compared to IVCi. Interestingly, the Collapsibility Index variable exhibited a lower AUC of 0.5244, indicating a limited ability to differentiate between pre and post dialysis settings. It's important to note that an AUC of 0.5 suggests performance no better than random chance. While IVCi and IVCe variables showed some ability to discriminate between pre and post settings, the Collapsibility Index variable appeared, comparatively, less effective in this regard.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe p-values, given below, for IVCi and IVCe are less than 0.05 which indicates that these results are statistically significant from those obtained by chance. The p-value for Collapsibility index is greater than 0.05 which is not statistically significant at 5% level of significance.\u003c/p\u003e\u003cp\u003eTest results of the ROC curve. Comparison between IVC parameters in pre and post settings\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Tabb\" border=\"1\"\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTest Result\u003c/p\u003e\u003cp\u003eVariable(s)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eArea\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eStandard Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003e95% Confidence Interval\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eLower Bound\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eUpper Bound\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIVCi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.6334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0507\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7390\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIVCe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.6500\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0502\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.0028\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.5403\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.7587\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCollapsibility Index\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.5279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.0526\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.5955\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.4075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.6404\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eFluid overload is the most significant yet a very poor prognostic factor in end stage renal disease patients, ultimately leading to prolonged hospital stay, impaired oxygenation of vital organs and increased morbidity and mortality (a-d). Although several clinical evaluation methods and objective techniques have been introduced (e), accurate assessment of volume overload in management of CKD patients remains an unmet clinical need.\u003c/p\u003e\u003cp\u003eIn our study, we compared the physical examination parameters to inferior vena cava diameter measurement via ultrasound for the assessment of fluid overload. Based on the results, there was statistically no significant difference in the diagnostic performance between the physical signs and ultrasound in distinguishing between pre- and post-HD conditions. Weight, IVCi, and IVCe are significant predictors for distinguishing between the treatment and control groups. Among these parameters, IVCi is the most effective parameter for this purpose. Pre and Post Dialysis IVCi and IVCe were statistically significant. However, the Collapsibility Index did not show significant discriminative ability in treatment and control group as well as Pre and Post dialysis groups. There are various studies that correlate with our findings and have concluded superiority of IVC parameters over the physical examination indices in assessment of fluid status.\u003c/p\u003e\u003cp\u003eIn one of an interesting article by Millington, the author declared that although inferior vena cava diameter and collapsibility index are non-invasive means for fluid assessment, they are not very beneficial in majority of the patients(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Similarly another meta-analysis concluded that ultrasonographic measurement of inferior vena cava diameter or collapsibility index is not a very reliable index of fluid assessment (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Likewise, Trivedi et al in his study revealed that IVC diameter and collapsibility index are not routinely useful for estimation of fluid status in hemodialysis patients (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). There are multiple factors that contribute to the uncertainty of IVC parameters. The effect of respiration, intra-thoracic or intra-abdominal pressure, blood volume, right heart function or operator dependency are noteworthy. Therefore, despite the non-invasive nature and good applicability of IVC parameters, their utility for assessment of volume status in hemodialysis dependent patients\u0026rsquo; needs to be studied on a broader scale.\u003c/p\u003e\u003cp\u003eHowever, contrary to the above mentioned findings, a recent study reported that measurements of inferior vena cava diameter and collapsibility index pre and post dialysis is very productive method for estimation of fluid status as compared to clinical parameters which are largely unreliable(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Moreover, some studies have compared IVC-CI to CVP and concluded it to be a low risk yet high sensitivity alternative to the CVP, favoring it to be an ideal tool in assessment of fluid overload and fluid responsiveness in critically ill patients (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHence, additional research is required to further investigate the efficacy of IVCD and IVC-CI for estimation of volume overload in the end stage renal patients. Meanwhile, clinical evaluation methods are equitably convenient in assessing the fluid status.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eUltrasound measurement of IVCD is a good objective tool when compared with clinical parameters for assessment of fluid status. Integrating these measurements can lead to better assessment of patients\u0026rsquo; volume status and subsequent improved outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003ch2\u003e6. Ethics Approval and consent to participate\u003c/h2\u003e\u003cp\u003eApproval for the study was obtained from Ethical review committee Combined Military Hospital Malir Cantt reference no. 116/2023/Trg/ERC. Written informed consent was obtained from all participants (or their legal guardians, where applicable) prior to their inclusion in the study. All data were anonymized to ensure participant confidentiality and used solely for research purposes.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003e7. Consent for publication\u003c/strong\u003e\u003cp\u003eNot Applicable\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003e9. Conflict of interest\u003c/h2\u003e\u003cp\u003eThe authors declare no conflict of interest regarding research study, publication or/and authorship.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003e10. Funding\u003c/h2\u003e\u003cp\u003eNone.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eNaveed Ahmed Shah designed the studySundus Ali wrote the main manuscriptHarmla Hussain wrote the main manuscriptMuhammad Omer Amir collected the dataAli Bin Nasir collected the dataMuhammad Asim prepared the tables and analysed the data\u003c/p\u003e\u003ch2\u003e12. Acknowledgements\u003c/h2\u003e\u003cp\u003eI acknowledge Dr Saima Afaq for her support in guiding us about this article.\u003c/p\u003e\u003ch2\u003e8. Availability of Data and Materials\u003c/h2\u003e\u003cp\u003eThe datasets generated and/or analysed during the current study are not publicly available due to confidentiality but are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMatsushita K, Ballew SH, Wang AY, Kalyesubula R, Schaeffner E, Agarwal R. Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease. Nat Rev Nephrol. 2022;18(11):696\u0026ndash;707.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eJankowski J, Floege J, Fliser D, B\u0026ouml;hm M, Marx N. Cardiovascular disease in chronic kidney disease: pathophysiological insights and therapeutic options. Circulation. 2021;143(11):1157\u0026ndash;72.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLoutradis C, Sarafidis PA, Ferro CJ, Zoccali C. Volume overload in hemodialysis: diagnosis, cardiovascular consequences, and management. Nephrol Dialysis Transplantation. 2021;36(12):2182\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEkinci C, Karabork M, Siriopol D, Dincer N, Covic A, Kanbay M. Effects of volume overload and current techniques for the assessment of fluid status in patients with renal disease. Blood Purif. 2018;46(1):34\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMillington SJ. Ultrasound assessment of the inferior vena cava for fluid responsiveness: easy, fun, but unlikely to be helpful. Can J Anesthesia/Journal canadien d'anesth\u0026eacute;sie. 2019;66(6):633\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOrso D, Paoli I, Piani T, Cilenti FL, Cristiani L, Guglielmo N. Accuracy of ultrasonographic measurements of inferior vena cava to determine fluid responsiveness: a systematic review and meta-analysis. J Intensive Care Med. 2020;35(4):354\u0026ndash;63.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTrivedi V, Prajapati M, Prajapati DJ, Bhosale G, Nayak J, Panchal H. Is Inferior vena cava diameter, a reliable indicator for fluid status in end-stage renal disease patients?-A prospective observational study. Indian J Transplantation. 2022;16(2):200\u0026ndash;4.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eHafiz MA, Mohamed EA, Mohamed MA, Ahmed MA. Inferior vena cava diameter and collapsibility index as a marker of fluid status in regular hemodialysis patients. Egypt J Intern Med. 2021;33:1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSaad SI, Behairymb AS, Mahdy EW. Role Of Lung Ultrasound, CVP And Inferior Vena Cava Diameter And Collapsibility Index In Assessment Of End Point Of Fluid Therapy In Critically ILL Patient With Sepsis. Benha J Appl Sci. 2022;7(10):33\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMaghraby HM, Awad EA, Mohammed RA, Abdelmaniem MF, Sherif HM, Sabry R. Inferior Vena Cava Diameter and Collapsibility Index measurements by Ultrasound and its Correlation with Central Venous Pressure in Critically Ill Patients. Al-Azhar Int Med J. 2023;4(2):26.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMagee G, Zbrozek A. Fluid overload is associated with increases in length of stay and hospital costs: pooled analysis of data from more than 600 US hospitals. ClinicoEconomics and Outcomes Research. 2013 Jun 26:289\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eArikan AA, Zappitelli M, Goldstein SL, Naipaul A, Jefferson LS, Loftis LL. Fluid overload is associated with impaired oxygenation and morbidity in critically ill children. Pediatr Crit Care Med. 2012;13(3):253\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTsai YC, Chiu YW, Tsai JC, Kuo HT, Hung CC, Hwang SJ, Chen TH, Kuo MC, Chen HC. Association of fluid overload with cardiovascular morbidity and all-cause mortality in stages 4 and 5 CKD. Clin J Am Soc Nephrol. 2015;10(1):39\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eZoccali C, Moissl U, Chazot C, Mallamaci F, Tripepi G, Arkossy O, Wabel P, Stuard S. Chronic fluid overload and mortality in ESRD. J Am Soc Nephrol. 2017;28(8):2491\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLa Porta E, Lanino L, Calatroni M, Caramella E, Avella A, Quinn C, Faragli A, Estienne L, Alogna A, Esposito P. Volume balance in chronic kidney disease: evaluation methodologies and innovation opportunities. Kidney Blood Press Res. 2021;46(4):396\u0026ndash;410.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7874240/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7874240/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003e Accurate assessment of fluid status in hemodialysis dependent patients to achieve a euvolumic state remains the cornerstone of Chronic Kidney disease management. There are various clinical and physical examination parameters for optimal estimation of fluid status in CKD patients. This research focuses on studying the comparison between inferior vena cava diameter and compressibility index with physical signs for fluid manage in pre and post dialysis patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods and results:\u003c/strong\u003e A cross sectional comparative study was conducted out at the department of medicine and dialysis unit of Combined Military Hospital (CMH) Malir. A total of 45 participants were inducted in the study. The sample was predominantly male i.e. 62.20% (n=28) with 37.80% (n=17) being female. The mean age of the patients was 50.47 years (SD = 11.8). Comorbidities were prevalent, with hypertension present in 93.30% of patients, followed by diabetes (40.00%) and ischemic heart diseases (17.80%).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eBased on the research findings we concluded that ultrasound is a significantly reliable method for estimation of the fluid status in pre and post HD patients as compared to physical signs.\u003c/p\u003e","manuscriptTitle":"The role of inferior vena cava diameter and collapsibility index assessment of fluid status among hemodialysis dependent patients : A cross sectional comparative study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-29 06:27:01","doi":"10.21203/rs.3.rs-7874240/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6cff0c1e-ae62-4bbe-9284-7f20b8a0e914","owner":[],"postedDate":"October 29th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-29T06:27:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-29 06:27:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7874240","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7874240","identity":"rs-7874240","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}