European Journal of Cardiovascular Medicine

Optimal fluid management during surgery remains one of the most critical and challenging aspects of perioperative care. Approximately 50% of patients with haemodynamic instability do not respond sufficiently to fluid administration, highlighting the importance of accurately predicting fluid responsiveness before initiating therapy.[1] Inadequate fluid resuscitation can lead to organ hypoperfusion and dysfunction, while excessive fluid administration increases the risk of pulmonary oedema, tissue oedema, and prolonged mechanical ventilation.[2]

Recent evidence from multi-centre studies demonstrates that both restrictive and liberal fluid strategies, compared to goal-directed moderate fluid administration, result in significantly increased risk of acute kidney injury within 48 hours and 30-day mortality following surgery.[3] These findings underscore the critical need for reliable methods to assess fluid responsiveness and guide individualized fluid therapy.

Traditional static parameters such as central venous pressure (CVP) and pulmonary artery occlusion pressure have proven unreliable in predicting fluid responsiveness.[4] Dynamic parameters including stroke volume variation (SVV), pulse pressure variation (PPV), and passive leg raising test have demonstrated superior predictive value but require specific conditions or invasive monitoring.[5] The increasing availability of point-of-care ultrasonography has facilitated the development of non-invasive dynamic assessment tools for fluid status evaluation.

Changes in intrathoracic pressure and volume during positive pressure ventilation affect the extrathoracic venous system, making the internal jugular vein (IJV) an attractive target for assessing fluid responsiveness.[6] The IJV distensibility index (IJV-DI), calculated from respiratory variations in vein diameter, reflects changes in central venous pressure and right atrial filling. Previous studies have demonstrated that IJV-DI can predict fluid responsiveness in intensive care unit patients, including those post-cardiac surgery, on pressure support ventilation, and with sepsis.[7,8]

The IJV offers several advantages over the inferior vena cava (IVC) for ultrasound assessment during surgery. It is more easily accessible and visualized, particularly in obese patients or those with surgical drapes. The technique is simpler than comprehensive echocardiographic examination and does not require interruption of surgery. Studies in paediatric surgical patients have shown favourable correlations between IJV-DI and IVC distensibility index, suggesting potential utility in predicting fluid responsiveness.[9]

However, most existing research on IJV-DI has been conducted in critically ill patients in the intensive care setting. There is limited data on its effectiveness in adult patients during elective surgery, where standardized ventilation parameters and elimination of confounding factors may enhance the accuracy of the distensibility index in reflecting fluid status. Validation of IJV-DI in this specific population could provide clinicians with a practical, non-invasive tool for real-time fluid responsiveness assessment during surgery.

This study aimed to evaluate the accuracy of IJV-DI measurement compared with transthoracic echocardiography in predicting fluid responsiveness in adult patients undergoing elective surgery. The secondary objectives were to determine the optimal cut-off value for IJV-DI and to assess its sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for determining fluid responsiveness. We hypothesized that IJV-DI assessment using ultrasonography would demonstrate good diagnostic accuracy in predicting fluid responsiveness when compared with stroke volume changes measured by transthoracic echocardiography.

Study Population By convenience sampling, we recruited 33 patients undergoing elective surgery who met the following inclusion criteria: age 18-65 years, American Society of Anesthesiologists (ASA) physical status I-III, and body mass index (BMI) <30 kg/m². Exclusion criteria included signs of fluid overload, acute or chronic kidney dysfunction (serum creatinine >1.5 mg/dL), cardiovascular conditions (heart failure with ejection fraction <45%, cardiac arrhythmias, moderate-to-severe valvular heart disease, history of myocardial infarction within 6 months, pulmonary hypertension, peripheral artery disease), clinical signs of increased intra-abdominal pressure, anatomical anomalies of the neck or chest, jugular vein thrombosis, superior vena cava syndrome, and previous jugular vein catheterization within 4 weeks. Anaesthesia Protocol All patients underwent standard pre-anaesthetic evaluation. Following arrival in the operating room, standard monitoring was established including electrocardiography, non-invasive blood pressure, pulse oximetry, and capnography. Anaesthesia was induced with intravenous (IV) propofol 1.5-2 mg/kg and fentanyl 2 μg/kg. Tracheal intubation was facilitated with IV atracurium 0.5 mg/kg or rocuronium 0.6 mg/kg. Anaesthesia was maintained with sevoflurane (1-2% end-tidal concentration) in oxygen-air mixture. Mechanical ventilation was initiated in volume-controlled mode with the following standardized parameters: tidal volume 8 mL/kg predicted body weight, respiratory rate 12-14 breaths/min targeting end-tidal CO₂ of 35-40 mmHg, fraction of inspired oxygen (FiO₂) 0.5, and positive end-expiratory pressure (PEEP) 5 cmH₂O. These ventilation parameters were maintained constant throughout the measurement period. After initiation of mechanical ventilation and before surgical incision, baseline haemodynamic parameters (heart rate, systolic blood pressure, diastolic blood pressure, mean arterial pressure, oxygen saturation) were recorded. Internal Jugular Vein Distensibility Index Measurement IJV-DI measurements were performed by a single anaesthesiologist with advanced training in point-of-care ultrasonography who had completed at least 25 supervised IJV assessments. A portable ultrasound machine (SonoSite M-Turbo, FUJIFILM SonoSite Inc., Bothell, WA, USA) with a high-frequency linear transducer (6-13 MHz) was used for all measurements. Patients were positioned supine with the head elevated at 30° and rotated 30° to the left. The right IJV was identified at the level of the cricoid cartilage using B-mode ultrasonography in the short-axis view. Vessel identification was confirmed by compressibility and colour Doppler assessment. Adequate ultrasound gel was applied to minimize transducer pressure on the vein. Care was taken to avoid excessive compression that could alter vein diameter. M-mode scanning was used to record respiratory variations in IJV diameter over three complete respiratory cycles. The maximum anteroposterior diameter (Dmax) was measured at end-inspiration, and the minimum diameter (Dmin) was measured at end-expiration. Three measurements were obtained for each respiratory phase and averaged. The IJV distensibility index was calculated using the formula: IJV-DI = [(Dmax - Dmin) / Dmin] × 100%. Stroke Volume Measurement Stroke volume was measured using transthoracic echocardiography by the same anaesthesiologist trained in perioperative echocardiography. Using a phased-array transducer (2-5 MHz), the left ventricular outflow tract (LVOT) was visualized in the parasternal long-axis view. The LVOT diameter (D) was measured at the base of the aortic valve during systole. Three measurements were obtained and averaged. The cross-sectional area (CSA) was calculated as: CSA = π(D/2)². Subsequently, the apical five-chamber view was obtained, and pulsed-wave Doppler was placed at the LVOT just proximal to the aortic valve. The velocity-time integral (VTI) was measured by tracing the outline of the Doppler waveform. Three measurements were obtained and averaged. Stroke volume was calculated as: SV = LVOT CSA × LVOT VTI (mL). Fluid Challenge Protocol Following baseline measurements of IJV-DI and stroke volume, a standardized fluid challenge of 250 mL crystalloid solution (Ringer's lactate) was administered intravenously over 10 minutes using an infusion pump to ensure consistent delivery rate. No other fluid boluses or vasoactive medications were administered during the measurement period. Five minutes after completion of fluid administration, repeat measurements of IJV-DI and stroke volume were obtained using identical techniques and patient positioning. The change in stroke volume (ΔSV) was calculated as: ΔSV (%) = [(SV₁ - SV₀) / SV₀] × 100%, where SV₀ represents baseline stroke volume and SV₁ represents post-fluid challenge stroke volume. The change in IJV-DI (ΔIJV-DI) was calculated similarly. Based on previous literature defining fluid responsiveness as a 10-15% increase in stroke volume following crystalloid administration,10 patients were classified as fluid responders if ΔSV ≥10% and as non-responders if ΔSV <10%. Sample Size Calculation Sample size was calculated using the diagnostic study formula for area under the ROC curve (AUC) with the following assumptions: alpha error 5%, power 90%, expected AUC 0.87 (based on previous similar studies), precision 0.10, and expected ratio of responders to non-responders 1.5:1. This yielded a minimum required sample size of 30 patients. Anticipating a 10% dropout rate, we planned to enrol 33 patients. Statistical Analysis Data were analyzed using Statistical Package for the Social Sciences (SPSS) version 26.0 (IBM Corporation, Armonk, NY, USA). Normality of continuous variables was assessed using the Shapiro-Wilk test. Normally distributed data were presented as mean ± standard deviation (SD), while non-normally distributed data were presented as median (interquartile range [IQR]). Categorical variables were presented as frequencies and percentages. Baseline characteristics and haemodynamic parameters were compared between fluid responders and non-responders using independent samples t-test for normally distributed data and Mann-Whitney U test for non-normally distributed data. Paired measurements before and after fluid challenge were analyzed using paired t-test or Wilcoxon signed-rank test as appropriate. The diagnostic performance of IJV-DI in predicting fluid responsiveness was evaluated using receiver operating characteristic (ROC) curve analysis. The area under the curve (AUC) with 95% confidence interval (CI) was calculated to assess overall diagnostic accuracy. The optimal cut-off value for IJV-DI was determined using the Youden index (sensitivity + specificity - 1), which identifies the point on the ROC curve that maximizes both sensitivity and specificity. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (+LR), negative likelihood ratio (-LR), and odds ratio (OR) with 95% CI were calculated for the optimal cut-off value. The correlation between IJV-DI and change in stroke volume was assessed using Spearman's rank correlation coefficient for non-normally distributed data or Pearson's correlation coefficient for normally distributed data. Correlation strength was interpreted as: 0.00-0.19 (very weak), 0.20-0.39 (weak), 0.40-0.59 (moderate), 0.60-0.79 (strong), 0.80-1.00 (very strong). A two-tailed P-value <0.05 was considered statistically significant.

Patient Characteristics

A total of 33 patients were initially assessed for eligibility.

Table 1 presents the baseline characteristics of all study participants.

The mean age of participants was 41.3 ± 12.8 years, with 14 males (42.4%) and 19 females (57.6%). Mean BMI was 22.8 ± 3.2 kg/m². The distribution of ASA physical status was: ASA I - 13 patients (39.4%), ASA II - 17 patients (51.5%), ASA III - 3 patients (9.1%). Types of surgery included head and neck procedures (n=13, 39.4%), laparoscopic surgery (n=7, 21.2%), neurosurgery (n=5, 15.2%), laparotomy (n=4, 12.1%), and orthopaedic procedures (n=4, 12.1%). Pre-induction vital signs showed median values of systolic blood pressure 128 mmHg (IQR: 118-142), diastolic blood pressure 78 mmHg (IQR: 68-86), mean arterial pressure 94.7 mmHg (IQR: 85.3-104.7), and heart rate 82 beats/min (IQR: 72-91).

Fluid Responsiveness Classification

Based on the change in stroke volume following fluid challenge, 19 patients (57.6%) were classified as fluid responders (ΔSV ≥10%) and 14 patients (42.4%) as non-responders (ΔSV <10%). This proportion of responders is consistent with previous studies in surgical populations undergoing elective procedures.

Comparison Between Responders and Non-responders

Table 2 presents the comparison of haemodynamic parameters and IJV-DI between fluid responders and non-responders. There were no significant differences in baseline haemodynamic parameters between the two groups, indicating comparable initial cardiovascular status. However, significant differences were observed in IJV-DI measurements and their changes following fluid administration.

TABLE 1: Baseline Characteristics of Study Participants (n=33)

SD = Standard Deviation; IQR = Interquartile Range; ASA = American Society of Anesthesiologists; SBP = Systolic Blood Pressure; DBP = Diastolic Blood Pressure; MAP = Mean Arterial Pressure

At baseline (t₀), fluid responders had significantly higher IJV-DI compared to non-responders (median 20.3% vs 8.9%, P < 0.001), suggesting greater vascular compliance and volume responsiveness. Following fluid challenge (t₁), both groups showed reduction in IJV-DI, but responders demonstrated significantly greater decrease (ΔIJV-DI: -9.2% vs -1.1%, P < 0.001). This inverse relationship between fluid responsiveness and IJV-DI change reflects improved venous filling and decreased vein collapsibility after successful volume expansion.

Responders showed significant increases in systolic blood pressure (ΔSBP: 11 mmHg vs 5 mmHg, P = 0.006) and significant decreases in heart rate (ΔHR: -6 beats/min vs -2 beats/min, P < 0.001) compared to non-responders, consistent with improved cardiovascular performance following fluid administration. As expected by study design, stroke volume increased significantly in responders (ΔSV: 19.8% vs 3.6%, P < 0.001).

Diagnostic Performance of IJV-DI

ROC curve analysis demonstrated that IJV-DI had good discriminative ability for predicting fluid responsiveness, with an AUC of 0.863 (95% CI: 0.731, 0.995), P < 0.001 (Figure 1). An AUC value >0.8 indicates good diagnostic accuracy and suggests that IJV-DI is a reliable predictor of fluid responsiveness in this patient population.

Using the Youden index to determine the optimal balance between sensitivity and specificity, the best cut-off value for IJV-DI was identified as >13.45% (Youden index = 0.628). At this threshold, IJV-DI demonstrated sensitivity of 84.2% (95% CI: 60.4%, 96.6%) and specificity of 78.6% (95% CI: 49.2%, 95.3%) for predicting fluid responsiveness.

TABLE 2: Comparison of Haemodynamic Parameters and IJV-DI Between Fluid Responders and Non-responders

Data presented as median (interquartile range). *Mann-Whitney U test. SBP = Systolic Blood Pressure; DBP = Diastolic Blood Pressure; MAP = Mean Arterial Pressure; HR = Heart Rate; IJV = Internal Jugular Vein; Dmin = Minimum Diameter; Dmax = Maximum Diameter; DI = Distensibility Index; SV = Stroke Volume; t₀ = baseline; t₁ = post-fluid challenge

The positive predictive value at the optimal cut-off was 0.84 (95% CI: 0.64, 0.95), indicating that 84% of patients with IJV-DI >13.45% would be true fluid responders. The negative predictive value was 0.79 (95% CI: 0.54, 0.94), meaning that 79% of patients with IJV-DI ≤13.45% would truly not respond to fluid administration. These values suggest good clinical utility for both ruling in and ruling out fluid responsiveness.

The positive likelihood ratio was 3.93 (95% CI: 1.76, 8.77), indicating that patients with IJV-DI >13.45% are approximately 4 times more likely to be fluid responders. The negative likelihood ratio was 0.20 (95% CI: 0.08, 0.48), showing that patients with IJV-DI ≤13.45% are only one-fifth as likely to be fluid responders. The odds ratio was 19.6 (95% CI: 4.1, 93.8), demonstrating strong association between elevated IJV-DI and fluid responsiveness.

Table 3 presents the 2×2 contingency table showing the correspondence between IJV-DI classification (using the optimal cut-off of >13.45%) and actual fluid responsiveness determined by echocardiographic stroke volume measurement.

TABLE 3: Diagnostic Performance of IJV-DI (Cut-off >13.45%) Compared with Transthoracic Echocardiography for Predicting Fluid Responsiveness

IJV-DI = Internal Jugular Vein Distensibility Index; ΔSV = Change in Stroke Volume; CI = Confidence Interval

Correlation Between IJV-DI and Stroke Volume Change

Correlation analysis revealed a moderate positive correlation between baseline IJV-DI and percentage change in stroke volume following fluid challenge (Spearman's rho = 0.542, P < 0.001). This indicates that higher IJV-DI values at baseline are associated with greater increases in stroke volume after fluid administration, supporting the physiological basis of using IJV-DI as a predictor of fluid responsiveness.

The correlation coefficient of 0.542 suggests that IJV-DI accounts for approximately 29% of the variance in stroke volume response (r² = 0.294), indicating that while IJV-DI is a useful predictor, other factors also influence fluid responsiveness. These may include baseline ventricular function, compliance of the cardiovascular system, and individual variations in Frank-Starling curve position.

Principal Findings

This prospective cross-sectional study demonstrated that the internal jugular vein distensibility index (IJV-DI) is an accurate predictor of fluid responsiveness in adult patients undergoing elective surgery under general anaesthesia. With an area under the ROC curve of 0.863, IJV-DI showed good diagnostic accuracy comparable to transthoracic echocardiographic stroke volume measurement. The optimal cut-off value of >13.45% demonstrated sensitivity of 84.2% and specificity of 78.6%, with strong positive and negative likelihood ratios supporting its clinical utility. These findings validate IJV-DI as a practical, non-invasive bedside tool for guiding intraoperative fluid management.

Comparison with Previous Studies

Our results are consistent with several previous investigations of IJV-DI in different clinical settings. Guarracino et al.[8] studied 32 septic patients on mechanical ventilation and found IJV-DI >18% predicted fluid responsiveness with 80% sensitivity and 95% specificity (AUC 0.915). Ma et al.[11] examined 70 post-cardiac surgery patients in the intensive care unit and reported a cut-off of >12.99% with 91.43% sensitivity and 82.86% specificity (AUC 0.88). Aditianingsih et al.[12] evaluated 79 patients undergoing elective surgery and determined an optimal cut-off of >12.62% with 84.4% sensitivity and 79.4% specificity (AUC 0.871).

Our cut-off value of 13.45% falls between these previously reported thresholds, which likely reflects differences in patient populations, fluid challenge protocols, and definitions of fluid responsiveness. Guarracino et al.[8] used >15% increase in cardiac index to define responders, while Ma et al.11 used ≥15% increase in stroke volume. Our study used ≥10% increase in stroke volume based on the systematic review by Cecconi et al.,[10] which defined fluid responsiveness as 10-15% increase following crystalloid administration. This lower threshold for defining response may partially explain our slightly higher cut-off value compared to Aditianingsih et al.[12]

Despite these methodological variations, all studies consistently demonstrate that IJV-DI has good diagnostic accuracy for predicting fluid responsiveness, with AUC values ranging from 0.86 to 0.92. This consistency across different clinical contexts supports the robustness of IJV-DI as a fluid responsiveness predictor.

Physiological Basis

The physiological mechanism underlying IJV-DI as a predictor of fluid responsiveness relates to heart-lung interactions during positive pressure ventilation. During mechanical ventilation, intrathoracic pressure increases during inspiration, decreasing venous return and right atrial pressure. In hypovolaemic states, veins have high compliance and low pressure, allowing significant diameter variation with respiratory changes, resulting in high distensibility index values.[13,14]

Patients on the steep portion of the Frank-Starling curve (preload-responsive) demonstrate greater respiratory variation in venous diameter because small changes in venous return cause larger changes in ventricular filling. Conversely, patients on the flat portion of the curve (preload-independent) show minimal respiratory variation because their ventricles are operating near maximum filling capacity.[15] Thus, high IJV-DI indicates patients are preload-responsive and likely to benefit from fluid administration.

Following successful fluid resuscitation, venous pressure increases, compliance decreases, and respiratory-induced diameter variations diminish, leading to decreased IJV-DI. This inverse relationship between fluid responsiveness and IJV-DI reduction after fluid challenge was evident in our study, with responders showing significantly greater decrease in IJV-DI (-9.2% vs -1.1%, P < 0.001).

Advantages Over Alternative Methods

IJV-DI assessment offers several practical advantages over other methods of assessing fluid responsiveness. Compared with inferior vena cava (IVC) assessment, IJV visualization is easier, particularly in obese patients, those with increased intra-abdominal pressure, or during surgery when abdominal access is limited. The IJV is more superficial and consistently located, requiring less operator expertise for adequate visualization.[16]

Unlike pulse pressure variation (PPV) and stroke volume variation (SVV), which require arterial catheterization and are unreliable in patients with cardiac arrhythmias, spontaneous breathing efforts, or low tidal volume ventilation,[17] IJV-DI can be measured non-invasively using standard ultrasound equipment available in most operating rooms. While passive leg raising (PLR) test is non-invasive and reliable, it requires interruption of surgery and continuous cardiac output monitoring during the manoeuvre,[18] whereas IJV-DI can be assessed quickly without repositioning the patient or interrupting the procedure.

Compared with comprehensive transthoracic echocardiography, IJV ultrasound is simpler to perform, requires less training, and can be completed in under 2 minutes. While echocardiography provides valuable information about cardiac function, valvular pathology, and volume status, it requires significant operator expertise and may not be feasible during all surgical procedures. IJV-DI serves as a focused, goal-directed assessment that can complement rather than replace comprehensive haemodynamic evaluation.

Clinical Implications

The good diagnostic accuracy of IJV-DI has important implications for intraoperative fluid management. With 84% positive predictive value, clinicians can confidently administer fluid to patients with IJV-DI >13.45%, knowing they have high probability of responding with increased stroke volume and improved perfusion. Conversely, the 79% negative predictive value helps identify patients unlikely to benefit from fluid administration, potentially preventing unnecessary fluid loading and its associated complications such as tissue oedema, prolonged mechanical ventilation, and delayed recovery.[19]

The moderate positive correlation (r = 0.542) between IJV-DI and stroke volume increase suggests IJV-DI can help stratify patients by degree of fluid responsiveness. Patients with very high IJV-DI values (>20-25%) likely have significant hypovolaemia and may require larger volume resuscitation, while those with borderline values (13-16%) may benefit from smaller, carefully titrated fluid boluses with reassessment.

Integration of IJV-DI into goal-directed fluid therapy protocols could improve perioperative outcomes. Several studies have demonstrated that goal-directed therapy reduces postoperative complications, length of hospital stay, and mortality compared with standard fluid management.[20,21] IJV-DI assessment could facilitate implementation of such protocols in centres without access to advanced haemodynamic monitoring systems.

Limitations and Confounding Factors

Several limitations of this study merit consideration. First, the sample size of 33 patients, while adequate for primary analysis, limits the precision of sensitivity and specificity estimates, as reflected in the relatively wide confidence intervals. Larger multi-centre studies would provide more robust estimates and allow subgroup analyses by surgical type, ASA status, and other patient characteristics.

Second, this study excluded patients with cardiovascular dysfunction, arrhythmias, increased intra-abdominal pressure, and obesity. While this exclusion enhanced internal validity by eliminating confounding factors, it limits generalizability to more complex patient populations. Future studies should evaluate IJV-DI performance in patients with mild-to-moderate cardiac dysfunction, as these patients often pose the greatest clinical challenges in fluid management.

Third, sympathetic activation and vasoactive medications can affect venous compliance and distensibility.[22] Although we standardized anaesthetic technique and avoided vasoactive drugs during measurements, individual variations in autonomic tone and anaesthetic depth may have influenced results. The use of muscle relaxants in our protocol eliminated airway resistance and spontaneous breathing effects, potentially enhancing IJV-DI accuracy compared to spontaneously breathing or minimally sedated patients.

Fourth, we used a single fluid challenge volume (250 mL) administered over 10 minutes. Some studies have used larger volumes (500 mL) or different infusion rates, which may affect the magnitude of response. However, our protocol aligns with current recommendations for fluid challenge in haemodynamically stable surgical patients.[23]

Fifth, all measurements were performed by a single trained operator, which minimizes inter-observer variability but raises questions about reproducibility. Studies evaluating inter-observer and intra-observer reliability of IJV-DI measurements would strengthen evidence for its clinical implementation.

Finally, this study evaluated IJV-DI at a single time point before surgery. Serial measurements during surgery to track changing fluid status and guide ongoing resuscitation would provide valuable data on IJV-DI performance in dynamic clinical scenarios. Future research should investigate whether continuous or intermittent IJV-DI monitoring throughout surgery improves patient outcomes compared with standard care.

Future Research Directions

Several areas warrant further investigation. First, prospective randomized controlled trials comparing IJV-DI-guided fluid therapy with standard care or other goal-directed therapy approaches are needed to determine whether this technique improves clinical outcomes such as postoperative complications, length of stay, and mortality.

Second, studies combining IJV-DI with other dynamic parameters (e.g., pulse pressure variation in patients with arterial lines) may enhance predictive accuracy. Guarracino et al.[8] demonstrated that combining IJV-DI with PPV achieved 100% sensitivity and 95% specificity, suggesting potential synergistic benefit.

Third, investigation of IJV-DI in more complex patient populations including those with cardiac dysfunction, arrhythmias, obesity, and increased intra-abdominal pressure would expand clinical applicability. Understanding how comorbidities affect IJV-DI performance is essential for developing appropriate decision algorithms.

Fourth, development of automated IJV-DI measurement algorithms using machine learning and artificial intelligence could reduce operator dependence and improve measurement consistency. Real-time continuous monitoring using wearable ultrasound devices may eventually enable automated fluid responsiveness assessment throughout surgery.

Fifth, studies evaluating the learning curve for IJV-DI measurement and developing standardized training programs would facilitate broader clinical adoption. Understanding the minimum number of supervised procedures needed to achieve competence would inform training requirements.

This study demonstrates that internal jugular vein distensibility index (IJV-DI) measured by ultrasonography is an accurate predictor of fluid responsiveness in adult patients undergoing elective surgery under general anaesthesia. With an optimal cut-off value of >13.45%, IJV-DI showed sensitivity of 84.2% and specificity of 78.6%, with good overall diagnostic accuracy (AUC 0.863) comparable to transthoracic echocardiographic stroke volume measurement. IJV-DI assessment offers a practical, non-invasive bedside tool that can be performed quickly without interrupting surgery. Its ease of visualization, simple measurement technique, and good predictive performance make it suitable for guiding intraoperative fluid management, particularly in settings with limited access to advanced haemodynamic monitoring. By identifying patients likely to benefit from fluid administration and those at risk of fluid overload, IJV-DI may help optimize perioperative fluid therapy and improve patient outcomes. Further research through large multi-centre trials is needed to validate these findings across diverse patient populations and surgical procedures, and to determine whether IJV-DI-guided fluid therapy translates into improved clinical outcomes. Standardization of measurement techniques and development of training programs will facilitate broader clinical implementation of this promising haemodynamic assessment tool. ACKNOWLEDGEMENTS The authors thank the operating room staff for their cooperation during data collection and all patients who participated in this study. DECLARATIONS Funding: None Conflicts of Interest: The authors declare no conflicts of interest.

1.      Cherpanath TGV, Geerts BF, Lagrand WK, Schultz MJ, Groeneveld ABJ. Basic concepts of fluid responsiveness. Neth Heart J 2013;21:530-6.

2.      Myles PS, Bellomo R, Corcoran T, Forbes A, Peyton P, Story D, et al. Restrictive versus liberal fluid therapy for major abdominal surgery. N Engl J Med 2018;378:2263-74.

3.      Shin CH, Long DR, McLean D, Grabitz SD, Ladha K, Timm FP, et al. Effects of intraoperative fluid management on postoperative outcomes: a hospital registry study. Ann Surg 2018;267:1084-92.

4.      Marik PE, Cavallazzi R. Does the central venous pressure predict fluid responsiveness? An updated meta-analysis and a plea for some common sense. Crit Care Med 2013;41:1774-81.

5.      Michard F, Teboul JL. Predicting fluid responsiveness in ICU patients: a critical analysis of the evidence. Chest 2002;121:2000-8.

6.      Chua Chiaco JM, Parikh NI, Fergusson DJ. The jugular venous pressure revisited. Cleve Clin J Med 2013;80:638-44.

7.      Iizuka Y, Nomura T, Sanui M, Mochida Y, Aomatsu A, Lefor AK. Collapsibility of the right internal jugular vein predicts responsiveness to fluid administration in patients receiving pressure support ventilation: a prospective cohort study. J Clin Med Res 2020;12:150-6.

8.      Guarracino F, Ferro B, Forfori F, Bertini P, Magliacano L, Pinsky MR. Jugular vein distensibility predicts fluid responsiveness in septic patients. Crit Care 2014;18:647.

9.      Bilgili B, Haliloglu M, Tugtepe H, Umuroglu T. The assessment of intravascular volume with inferior vena cava and internal jugular vein distensibility indexes in children undergoing urologic surgery. J Invest Surg 2018;31:523-8.

10.   Cecconi M, Hofer C, Teboul JL, Pettila V, Wilkman E, Molnar Z, et al. Fluid challenges in intensive care: the FENICE study. Intensive Care Med 2015;41:1529-37.

11.   Ma GG, Hao GW, Yang XM, Zhu DM, Liu L, Liu H, et al. Internal jugular vein variability predicts fluid responsiveness in cardiac surgical patients with mechanical ventilation. Ann Intensive Care 2018;8:6.

12.   Aditianingsih D, Heriwardito A, Agusta LS, Leonard EN, Annabelle C. Internal jugular distensibility index as a predictor of fluid responsiveness in adult patients undergoing elective surgery - a prospective accuracy study. Indian J Anaesth 2025;69:206-13.

13.   Monnet X, Marik PE, Teboul JL. Prediction of fluid responsiveness: an update. Ann Intensive Care 2016;6:111.

14.   Marik PE, Lemson J. Fluid responsiveness: an evolution of our understanding. Br J Anaesth 2014;112:617-20.

15.   Kumar A, Anel R, Bunnell E, Habet K, Zanotti S, Marshall S, et al. Pulmonary artery occlusion pressure and central venous pressure fail to predict ventricular filling volume, cardiac performance, or the response to volume infusion in normal subjects. Crit Care Med 2004;32:691-9.

16.   Dipti A, Soucy Z, Surana A, Chandra S. Role of inferior vena cava diameter in assessment of volume status: a meta-analysis. Am J Emerg Med 2012;30:1414-9.

17.   De Backer D, Heenen S, Piagnerelli M, Koch M, Vincent JL. Pulse pressure variations to predict fluid responsiveness: influence of tidal volume. Intensive Care Med 2005;31:517-23.

18.   Monnet X, Teboul JL. Passive leg raising. Intensive Care Med 2008;34:659-63.

19.   Brandstrup B, Tonnesen H, Beier-Holgersen R, Hjortso E, Ording H, Lindorff-Larsen K, et al. Effects of intravenous fluid restriction on postoperative complications: comparison of two perioperative fluid regimens - a randomized assessor-blinded multicenter trial. Ann Surg 2003;238:641-8.

20.   Pearse RM, Harrison DA, MacDonald N, Gillies MA, Blunt M, Ackland G, et al. Effect of a perioperative, cardiac output-guided hemodynamic therapy algorithm on outcomes following major gastrointestinal surgery: a randomized clinical trial and systematic review. JAMA 2014;311:2181-90.

21.   Salzwedel C, Puig J, Carstens A, Bein B, Molnar Z, Kiss K, et al. Perioperative goal-directed hemodynamic therapy based on radial arterial pulse pressure variation and continuous cardiac index trending reduces postoperative complications after major abdominal surgery: a multi-center, prospective, randomized study. Crit Care 2013;17:R191.

22.   Fudim M, Kaye DM, Borlaug BA, Shah SJ, Rich S, Kapur NK, et al. Venous tone and stressed blood volume in heart failure: JACC review topic of the week. J Am Coll Cardiol 2022;79:1858-69.

23.   Vincent JL, Weil MH. Fluid challenge revisited. Crit Care Med 2006;34:1333-7.