The Doppler blood flow parameters of the superior mesenteric artery in the progression from sepsis to refractory shock and its diagnostic value

The Doppler blood flow parameters of the superior mesenteric artery in the progression from sepsis to refractory shock and its diagnostic value | 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 Doppler blood flow parameters of the superior mesenteric artery in the progression from sepsis to refractory shock and its diagnostic value Shujun Zhou, Xinyi Liu, Tao Zeng, Wanru Li, Feng Ping, Siwei Wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9619615/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 Background Early identification of refractory septic shock and mesenteric hypoperfusion remains a significant clinical challenge due to the loss of hemodynamic coherence. This study aimed to characterize the dynamic evolution of superior mesenteric artery (SMA) Doppler parameters across the sepsis-severity spectrum and evaluate their performance in predicting refractory septic shock and mesenteric vasoplegia. Methods This study included five groups: healthy controls, sepsis, septic shock, refractory septic shock, and resuscitation-responsive septic shock. SMA Doppler parameters were measured, including peak systolic velocity (PSV), end-diastolic velocity (EDV), time-averaged mean velocity (TAMV), resistive index (RI), and pulsatility index (PI). Between-group comparisons, receiver operating characteristic (ROC) analysis, correlation analysis, and logistic regression were performed. Results A total of 116 participants were analyzed. The SMA hemodynamic profile exhibited a distinct biphasic evolutionary trajectory across the sepsis spectrum. During the initial sepsis stage, SMA Doppler indices exhibited a compensatory surge compared to controls, characterized by higher flow velocities (PSV: 188.20 vs. 115.40 cm/s) and increased vascular resistance (RI: 0.88 vs. 0.83). However, as illness severity intensified from septic shock to refractory septic shock, a paradoxical and progressive decline was observed: the resistance indices significantly decreased (RI: 0.88 to 0.72; PI: 2.97 to 1.50; both p < 0.001), while flow velocity and flow parameters followed a similar downtrend (PSV: 188.20 cm/s to 69.00 cm/s; TAMV: 24.60 cm/s to 13.55 cm/s;BF:450.24ml/min to 264.00ml/min ;both p < 0.001). Correlation analysis revealed that SMA hemodynamic parameters (RI, PI, PSV) were significantly negatively correlated with SOFA scores, serum lactate and Creatinine levels (all p < 0.05). For the identification of refractory septic shock, PSV demonstrated high discriminative capacity (AUC: 0.922, cutoff: 82.30 cm/s), outperforming RI (AUC: 0.874, cutoff: 0.745). Notably, the combined multivariable model of PSV and RI achieved superior diagnostic accuracy, with an AUC of 0.966 (95% CI: 0.946–0.989), a sensitivity of 87.5%, and a specificity of 95.3%. Conclusion Bedside SMA Doppler parameters effectively capture the transition from compensatory hyperdynamics to terminal hypodynamics and mesenteric vasoplegia. A low SMA RI and PSV, serves as a hallmark of refractory septic shock. Sepsis Septic shock Refractory shock Superior mesenteric artery Doppler ultrasonography Figures Figure 1 Figure 2 Figure 3 Introduction Sepsis shock remains a predominant cause of mortality in intensive care units worldwide, characterized by a dysregulated host response to infection and subsequent life-threatening multi-organ dysfunction( 1 ). Within this pathophysiological cascade, the gastrointestinal (GI) tract is widely recognized as the "motor" of multiple organ dysfunction syndrome (MODS)( 2 , 3 ). Despite the optimization of early resuscitation bundles, a significant subset of patients inevitably progresses toward refractory septic shock—a state defined by profound circulatory collapse, escalating vasopressor requirements, and an unacceptably high mortality rate( 4 , 5 ). A fundamental challenge in current clinical practice is "hemodynamic incoherence," wherein stabilized macro-hemodynamic targets, such as mean arterial pressure (MAP), fail to reflect the persistent deterioration of regional tissue perfusion( 6 ). Conventional systemic markers, including blood lactate clearance and central venous oxygen saturation (ScvO 2 ), represent global metabolic status and frequently lag behind the microvascular failure of specific organ beds( 7 , 8 ). By the time these systemic indicators manifest as refractory shock, irreversible ischemic injury and the breakdown of the intestinal mucosal barrier may have already occurred( 9 ). Consequently, identifying a real-time, non-invasive biomarker that reflects the dynamic alterations in splanchnic Perfusion state represents a critical unmet clinical need. Bedside Doppler ultrasonography of the superior mesenteric artery (SMA) provides a reliable modality for the direct assessment of visceral perfusion. While abnormal SMA flow patterns, such as an increased resistive index (RI) and reduced flow velocities, have been associated with impaired mesenteric perfusion in critically ill patients, the sequential evolution of these parameters across the full clinical spectrum—from initial sepsis to refractory septic shock—remains inadequately characterized( 10 , 11 ). Specifically, we sought to elucidate whether the mesenteric vasculature undergoes a 'paradoxical' pathophysiological transition, evolving from an initial compensatory state of hyperdynamic vasoconstriction to a terminal stage of profound vasoplegia during refractory shock( 12 , 13 ). We hypothesized that alterations in the SMA Doppler blood flow parameters accurately reflect the onset of mesenteric Perfusion state and vascular tone loss, thereby serving as early predictors of refractory septic shock development. Consequently, this prospective study aimed to map the hemodynamic trajectory of the SMA across five distinct clinical stages—healthy control, sepsis, septic shock, refractory shock, and successful resuscitation—and to evaluate the diagnostic performance of SMA Doppler parameters in identifying patients with refractory septic shock. Methods Study design and population This was a single-center, Retrospective study conducted in the Department of Critical Care Medicine at the Third Affiliated Hospital of Soochow University from January 2023 to January 2024. The study protocol was designed in accordance with the Declaration of Helsinki and received formal approval from the Institutional Review Board (Approval No. 2023E065). Written informed consent was obtained from all patients or their legally authorized representatives. Participant Selection and Group Definitions A total of 116 participants were consecutively enrolled and stratified into five groups based on international consensus criteria and clinical trajectories: Healthy Control (n = 22) : Patients admitted to the Intensive Care Unit (ICU) for non-septic conditions (e.g., postoperative monitoring or non-infectious trauma) who exhibited hemodynamic stability. Sepsis (n = 29) : Defined according to the Sepsis-3 criteria as infection-induced organ dysfunction, characterized by an acute increase in the Sequential Organ Failure Assessment (SOFA) score of ≥ 2 points( 1 ). Septic Shock (n = 22) : Defined as sepsis requiring vasopressors to maintain a mean arterial pressure (MAP) ≥ 65mmHg and a serum lactate level > 2 mmol/L despite adequate fluid resuscitation( 1 ). Refractory Septic Shock (n = 23) : Defined as persistent hypotension and deteriorating tissue hypoperfusion (e.g., rising lactate) despite adequate fluid resuscitation, necessitating high-dose norepinephrine (≥ 0.5ug/kg/min)( 14 ). Successful Resuscitation (n = 20) : Patients who achieved achieving hemodynamic stability (MAP ≥ 65mmHg with minimal or no vasopressor support), metabolic restoration (lactate ≤ mmol/L or significant clearance), and evidence of multi-organ functional recovery after comprehensive treatment. Exclusion Criteria Age < 18 years; pregnancy; primary gastrointestinal disease (e.g., bowel obstruction, mesenteric ischemia); severe intra-abdominal hypertension (IAH); or poor acoustic windows for SMA visualization. SMA Doppler ultrasonography measurement Bedside point-of-care ultrasound (POCUS) was performed by two experienced intensivists using a [KONICA SONIMAGE-HS1] ultrasound system with a 1–5 MHz convex transducer. With patients in a neutral supine position, the superior mesenteric artery (SMA) was visualized in the longitudinal sagittal plane, 1–2 cm distal to its aortic origin. The Doppler sample volume was centered within the lumen, maintaining an insonation angle < 60°with automated angle correction. Peak systolic velocity (PSV) and end-diastolic velocity (EDV) were averaged over at least three consecutive stable cardiac cycles. The resistive index (RI) was calculated as (PSV - EDV) / PSV. Superior mesenteric blood flow (BF) was derived using the formula: BF (mL/min) = Cross sectional area (CSA) ×time-averaged mean velocity (TAMV) ×60. Clinical data collection Baseline characteristics, including age, sex, and body mass index (BMI), were documented upon enrollment. Disease severity was assessed within the first 6 hours of inclusion using the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. Concomitantly with the superior mesenteric artery (SMA) ultrasound, real-time macro-hemodynamic parameters and systemic perfusion markers—comprising heart rate (HR), mean arterial pressure (MAP), norepinephrine (NE) dosage, arterial blood lactate (Lac), and venous-to-arterial carbon dioxide tension difference (Pv-aCO2)—were recorded to ensure hemodynamic coherence. Additionally, a comprehensive biochemical panel was analyzed to evaluate inflammatory response and organ function, including white blood cell (WBC) count, C-reactive protein (CRP), procalcitonin (PCT), total bilirubin, serum creatinine (Scr), and cardiac troponin I (cTnI). Statistical analysis The normality of data distribution was assessed visually. Normally distributed continuous variables were presented as mean±standard deviation, whereas nonnormally distributed data were reported as medians with interquartile ranges (IQRs, 25th-75th percentiles). Categorical variables were expressed as counts (n) and percentages (%). Continuous variables across the five clinical groups were compared using the Kruskal-Wallis H test, followed by post-hoc pairwise comparisons with Bonferroni correction. Correlations between SMA Doppler parameters (PSV, TAMV, RI, PI, BF) and clinical severity indices (e.g., SOFA score, arterial lactate, and norepinephrine dosage) were examined using the pearson correlation coefficient and visualized via a correlation matrix. To identify independent risk factors for refractory septic shock, SMA Doppler parameters were first screened using univariate Logistic regression. Variables with P < 0.05 were subsequently entered into a multivariable Logistic regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). Receiver operating characteristic (ROC) curves were constructed based on the predicted probabilities from the multivariable model. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the discriminative ability of the combined SMA parameter model for refractory shock. All statistical analyses were performed using SPSS software (version 26.0; IBM Corp, Armonk, NY). A two-sided P < 0.05 was considered statistically significant. Results Baseline characteristics A total of 116 patients were included (Table 1 ). No significant differences were observed among the five groups regarding age, sex, or BMI ( p > 0.05). Illness severity scores showed a progressive increase from the control to the refractory septic shock group (APACHE II: 20.0 to 30.0; SOFA: 2.0 to 12.0; both p < 0.001). Laboratory findings mirrored this clinical gradient, with significant elevations in inflammatory markers (WBC and PCT) and organ dysfunction indicators (creatinine and cardiac troponin I) as the disease severity intensified ( p < 0.001). Notably, perfusion markers such as serum lactate and Pv-aCO 2 peaked in the refractory septic shock group (6.05mmol/L and 10.0 mmHg, respectively). While MAP was maintained across groups ( p = 0.175), the norepinephrine requirement increased significantly with shock severity ( p < 0.001). Compared with the refractory group, patients in the successful resuscitation group exhibited a marked restoration of metabolic parameters and a reduction in vasopressor demand. Table 1 Baseline characteristics of the study population Characteristic Control (n = 22) Sepsis (n = 29) Septic shock (n = 22) Refractory septic shock (n = 23) Successful resuscitation (n = 20) p -Value Age (years) 71.00(52.00–78.00) 76.00(67.00–84.00) 75.00(65.000–82.00) 75.00(63.00–81.00) 74.00(64.00–82.00) 0.328 Male Sex(%) 12(54.54) 15(51.72) 12(63.64) 13(52.17) 10.00(50.00) 0.157 BMI 22.49(20.76–25.53) 22.14(19.37–24.91) 22.88(19.38–25.95) 22.38(19.11–25.46) 22.38(19.29–25.69) 0.851 APACHE II 20.00(15.00–26.00) 23.00(18.00–27.00) 29.00(23.00–33.00) 30.00(27.00–34.00) 30.00(26.00–33.00) < 0.001 SOFA score 2.00(1.00–3.00) 5.00(4.00–7.00) 8.00(6.00–10.00) 12.00(10.00–15.00) 9.00(7.00–11.00) < 0.001 WBC (×10 9 /L) 11.84(8.60–13.10) 12.24(7.59–16.17) 17.68(14.75-28.00) 18.93(15.44-30.00) 18.49(15.10–30.00) < 0.001 Hemoglobin (g/L) 111.00(99.00-122.00) 101.00(82.00-113.00) 102.00(91.00-115.00) 100.00(74.00-120.00) 101.00(82.00–11.00) 0.239 Albumin (g/L) 32.00(29.00-35.10) 33.35(27.70–36.50) 31.90(29.25–34.05) 30.10(26.20–34.20) 32.60(28.67–35.05) 0.245 TB (ummol/L) 15.45(11.70–26.10) 17.30(10.65–27.75) 22.10(12.30-30.87) 24.10(15.37–37.95) 22.65(12.30-16.32.32) 0.565 Cr (ummol/L) 72.00(52.00-113.00) 86.00(55.00-128.00) 149.00(107.00-206.00) 156.00(120.00-238.00) 153.00(114.50–209.00) < 0.001 CRP (mg/L) 55.00(19.00-109.00) 117.00(69.00-185.00) 121.85(51.00-163.00) 152.00(105.00-208.00) 179.60(123.15-233.68) 0.004 PCT (ng/L) 0.30(0.25–0.60) 1.50(0.29–9.25) 16.54(2.69–55.36) 21.92(6.10-87.85) 21.54(4.20–66.00) < 0.001 cTnI (ng/ml) 0.03(0.01–0.20) 0.04(0.15–0.53) 0.46(0.09–0.88) 0.94(0.42–2.60) 0.67(0.18–1.53) < 0.001 Lactate (mmol/L) 1.05(1.00-1.30) 2.20(1.20–2.80) 4.25(2.70–7.10) 6.05(4.45-11.00) 1.8(1.2–2.10) < 0.001 Pv-aCO 2 (mmHg) 5.00(4.00–6.00) 6.00(4.00–6.00) 8.00(6.00–9.00) 10.00(7.00–12.00) 5.00(4.00–6.00) < 0.001 MAP (mmHg) 88.00(80.00–98.00) 87.00(79.00–94.00) 82.00(68.00–96.00) 80.00(63.00–93.00) 82.00(67.00–93.00) 0.175 HR (bpm) 86.00(70.00–95.00) 96.00(83.00-114.00) 106.00(92.00-118.00) 110.00(88.00-127.00) 106.00(83.00-123.00) 0.002 NE (ug/kg/min) 00.00(0.00–0.00) 0.25(0.10–0.50) 0.50(0.30–0.85) 0.75(0.50–1.30) 0.1(0.00-0.20) < 0.001 CRRT use (%) 1(4.5) 3(10.34) 10(45.45) 18(75) 8(40) < 0.001 28 d mortality 3(10.34) 7(24.14) 10(40.91) 15(65.22) 4( 20 ) < 0.001 Data are presented as median (interquartile range) or n (%). APACHE II, Acute Physiology and Chronic Health Evaluation II; SOFA, Sequential Organ Failure Assessment; BMI, body mass index; WBC, white blood cell; TB, total bilirubin; Cr, Creatinine; CRP, C-reactive protein; PCT, procalcitonin; cTnI, cardiac troponin I; Pv-aCO 2 , central venous-to-arterial carbon dioxide difference; MAP, mean arterial pressure; HR, heart rate; NE, norepinephrine; CRRT, continuous renal replacement therapy. Comparisons of SMA Doppler parameters among groups The hemodynamic profiles of the SMA varied significantly across the clinical severity spectrum (Table 2 , Figure. 1 ; all p < 0.001). In the sepsis group, a hyperdynamic mesenteric circulation was evident, characterized by significantly higher flow velocities and blood flow compared to controls (PSV: 188.20 cm/s vs. 115.40cm/s; BF: 450.24 mL/min vs. 368.16 mL/min; p < 0.05). As the disease severity progressed to septic shock and refractory septic shock, a profound decline in mesenteric perfusion was observed. PSV, TAMV, and BF reached their lowest levels in the refractory shock group (PSV: 69.00 [63.22-88.00] cm/s; BF: 264.00 [201.55-318.54] mL/min). Crucially, resistance indices (RI, PI), which were highest in the sepsis phase, exhibited a paradoxical and significant reduction as shock intensified, reflecting a transition toward mesenteric vasoplegia (RI: 0.72 in refractory shock vs. 0.88 in sepsis; p < 0.001). Following successful resuscitation, all Doppler parameters showed a restorative trend, with RI and PI returning to levels comparable to the control group (0.84 vs. 0.83). Table 2 Comparison of superior mesenteric artery Doppler parameters among five groups PSV Control Sepsis Septic Shock Refractory septic shock Successful resuscitation p -Value 115.40(98.90-136.90) 188.20(173.70-210.55) 111.70(100.84-128.63) 69.00(63.22-88.00) 127.80(105.32-143.55) < 0.001 EDV 19.90(16.37–21.05) 21.40(15.75–25.85) 27.00(22.7-30.15) 19.65(16.03–25.02) 20.30(18.25–23.27) < 0.001 RI 0.83(0.82–0.85) 0.88(0.86–0.92) 0.77(0.73–0.79) 0.72(0.63–0.76) 0.84(0.82–0.86) < 0.001 PI 2.39(2.09–2.68) 2.97(2.52–3.51) 1.77(1.60–1.94) 1.50(1.11–1.79) 2.20(2.07–2.64) < 0.001 TAMV 17.65(15.42–19.95) 24.60(19.75–29.10) 20.15(17.32–22.80) 13.55(11.10-17.05) 19.20(16.05–22.62) < 0.001 BF 368.16(306.60-473.13) 450.24(321.12-588.96) 375.69(303.39-443.58) 264.00(201.55-318.54) 382.35(320.44-436.15) < 0.001 PSV, peak systolic velocity; TAMV, time-averaged mean velocity; BF, blood flow; RI, resistive index; PI, pulsatility index. Correlations between SMA Doppler indices and clinical severity markers Correlations between SMA Doppler parameters and clinical markers are summarized in Table 3 . Hemodynamic parameters, particularly PSV, RI, and PI, demonstrated significant inverse correlations with markers of clinical severity. Specifically, both RI and PI were negatively correlated with SOFA score (r = -0.64 and − 0.59, respectively; both p < 0.001) and lactate levels (r = -0.53 and − 0.52, respectively; both p < 0.001). Similarly, higher norepinephrine requirements were associated with lower RI (r = -0.59, p < 0.001) and PI (r = -0.51, p < 0.001). Furthermore, PSV showed a strong negative correlation with SOFA score (r = -0.61, p < 0.001) and creatinine (r = -0.40, p < 0.05). In contrast, EDV and TAMV displayed negligible correlations with most clinical severity markers. Interestingly, MAP exhibited a weak but significant positive correlation with PI (r = 0.33, p < 0.01) and RI (r = 0.24, p < 0.05). Overall, the heatmap analysis ( Figure. 2 ) confirmed that a decrease in SMA resistance indices (RI and PI) was closely aligned with increasing organ dysfunction and intensified norepinephrine support. Table 3 Correlations between SMA Doppler parameters and markers of clinical severity. Variables Lactate Pv-aCO 2 MAP Norepinephrine SOFA Creatinine R R r r r r PSV -0.49 -0.42 0.12 -0.44 -0.61 -0.4 EDV 0.033 0.12 -0.2 0.17 0.12 0.043 TAMV -0.28 -0.098 -0.21 -0.11 -0.29 -0.26 RI -0.53 -0.41 0.24 -0.59 -0.64 -0.40 PI -0.52 -0.40 0.33 -0.51 -0.59 -0.38 BF -0.28 -0.095 -0.21 -0.15 -0.26 -0.27 PSV, peak systolic velocity; EDV, end diastolic velocity; TAMV, time-averaged mean velocity; RI, resistive index; PI, pulsatility index; BF, blood flow; Pv-aCO 2 , venous-to-arterial carbon dioxide difference; MAP, mean arterial pressure; SOFA, Sequential Organ Failure Assessment; Cr, creatinine. Independent predictors of refractory septic shock In univariable logistic regression, PSV, TAMV, RI, PI, and BF were all significantly associated with refractory septic shock, whereas EDV was not. After adjustment in the multivariable model, only PSV and RI remained independently associated with refractory septic shock, with PSV showing a protective association and RI retaining a significant inverse association with the outcome (Table 4 ). Table 4 Univariate and multivariate logistic regression analysis for refractory septic shock Variables Univariate Mulvariate Β S.E Z P OR (95%CI) Β S.E Z P OR (95%CI) PSV -0.10 0.02 -4.07 < .001 0.91 (0.87 ~ 0.95) -0.34 0.16 -2.14 0.033 0.71 (0.52 ~ 0.97) EDV -0.01 0.04 -0.37 0.415 0.99 (0.92 ~ 1.06) TAMV -0.18 0.06 -2.83 < .001 0.82 (0.73 ~ 0.91) RI*10 -2.78 0.74 -3.75 < .001 0.06 (0.02 ~ 0.27) -2.73 1.27 -2.15 0.041 0.14 (0.02 ~ 0.78) PI -2.83 0.84 -3.37 < .001 0.14 (0.02 ~ 0.32) BF -0.01 0.00 -3.32 < .001 0.99 (0.98 ~ 0.99) PSV, peak systolic velocity; EDV, end diastolic velocity; TAMV, time-averaged mean velocity; RI, resistive index; PI, pulsatility index; BF, blood flow; OR, odds ratio; CI, confidence interval.; OR: Odds Ratio, CI: Confidence Interval. Diagnostic performance of SMA Blood flow parameters for refractory septic shock ROC curve analysis demonstrated excellent discriminative performance of SMA Doppler parameters for identifying refractory septic shock. PSV showed the highest AUC of 0.922 (95% CI 0.864–0.979; p < 0.001), with an optimal cutoff of 82.30 cm/s providing 81.2% sensitivity and 92.9% specificity. RI also exhibited strong performance (AUC 0.874, 95% CI 0.791–0.958; p < 0.001), with a cutoff of 0.745 yielding 83.3% sensitivity and 78.6% specificity. The combined multivariable model achieved superior discrimination, with an AUC of 0.966 (95% CI 0.946–0.989, p < 0.001), with a sensitivity of 87.5% and a specificity of 95.3% (Table 5 , Figure. 3 ). Table 5 Comparison of the areas under the ROC curves for refractory septic shock Varibles AUC 95%CI P Value Cut-off Value Sensitivity Specificity PSV 0.922 0.864–0.979 < 0.001 82.30 0.812 0.929 RI 0.874 0.791–0.958 < 0.001 0.745 0.833 0.786 Model 0.966 0.946–0.989 < 0.001 - 0.875 0.952 PSV, peak systolic velocity; RI, resistive index. Discussion Our study systematically delineates the hemodynamic trajectory of the SMA across the clinical spectrum of sepsis. The principal finding is that SMA Doppler parameters exhibit a distinct, non-linear evolutionary pattern as the disease progresses. Specifically, while early sepsis is characterized by a hyperdynamic mesenteric circulation, the progression to refractory septic shock is marked by a profound decline in both flow velocities (PSV, TAMV) and resistance indices (RI, PI). Furthermore, we demonstrated that the combination of SMA PSV and RI offers exceptional discriminative capacity (AUC 0.957) for predicting refractory septic shock, providing a powerful, non-invasive tool for early bedside risk stratification. A defining finding of this study is the paradoxical reduction in SMA resistance indices (RI decreasing from 0.88 to 0.72; PI from 2.97 to 1.50) as patients transitioned into refractory shock. While early sepsis is characterized by catecholamine-mediated compensatory vasoconstriction to prioritize vital organ perfusion, our data identify a critical "tipping point" where this mechanism fails. In the most critically ill patients—despite escalating doses of norepinephrine—RI and PI reached their lowest values. This suggests that a low-resistance state, rather than a high one, serves as the definitive hallmark of terminal vascular failure. The significant negative correlation between SMA resistance indices and clinical severity markers (lactate, SOFA scores, and creatinine) underscores the pathophysiological shift toward terminal vasoplegia. This state is primarily driven by an overwhelming inflammatory cascade. Beyond the excessive production of nitric oxide (NO) and pathological activation of ATP-sensitive potassium (K-ATP) channels, a complex interplay of endogenous vasodilators—including acetylcholine, histamine, leukotrienes, and glucagon—contributes to the progressive loss of vascular tone( 15 , 16 ). Furthermore, the secretion of various gastrointestinal hormones and thromboxane analogues acts in concert with catecholamine receptor downregulation to induce a refractory paralysis of the vascular smooth muscle( 17 ). Collectively, this multifaceted biochemical milieu results in the profound mesenteric vasoplegia observed in our refractory shock cohort. Consequently, a declining SMA-RI in refractory shock does not signify improved flow; instead, it represents a catastrophic loss of vascular tone. This corrects the clinical misconception that higher RI always correlates with severity, identifying the collapse of mesenteric resistance as a primary indicator of global circulatory collapse. Furthermore, we observed a paradoxical elevation in SMA-RI and PI among patients who were successfully resuscitated. This increase suggests a restoration of mesenteric vascular tone, marking the transition from a paralytic vasodilatory state back to a regulated hemodynamic environment. This recovery of resistance in successful resuscitation group, contrasted with its collapse in the refractory cohort, underscores that SMA-RI and PI are not merely static markers of resistance, but dynamic indicators of vasomotor reactivity. Consequently, these indices emerge as potential bedside tools for evaluating resuscitation responsiveness, offering a unique window into the functional recovery of the splanchnic circulation that global macro-hemodynamic targets may overlook. The observed negative correlation between SMA-RI and serum creatinine presents an intriguing contrast to the well-established pathophysiology of the renal resistive index (RRI). In the renal bed, a higher RRI typically correlates with worsening renal function and acute kidney injury (AKI), as the kidney is highly sensitive to intra-organ pressure and venous congestion( 18 , 19 ). A recent study that emphasize a synergistic increase in organ resistance indices—such as the positive correlation between RRI and renal dysfunction in 'Intestinal-Renal Syndrome( 11 ). However, our findings suggest that the mesenteric circulation follows a different trajectory during the transition to refractory shock. While the kidney may maintain a high-resistance state during injury, the mesenteric bed enters a "paralytic" low-resistance state. This splanchnic-renal heterogeneity underscores that regional organ systems do not respond uniformly to septic insult. The SMA’s transition to a low-resistance state may precede or parallel the peak of systemic organ dysfunction, providing a unique, stage-specific marker of terminal circulatory failure that global metrics or renal indices might overlook. In the present study, SMA flow parameters (PSV, TAMV, and BF) exhibited a compensatory increase during the early phase of sepsis, followed by a progressive and severe decline as the disease evolved toward septic shock and, ultimately, refractory shock. Previous physiological research has established that regional mesenteric blood flow maintains a robust linear relationship with cardiac output (CO), with flow velocity indices being tightly coupled with the cardiac index (CI)( 10 , 20 ). As sepsis progresses, myocardial contractility is frequently compromised by an overwhelming surge of inflammatory mediators, mitochondrial dysfunction, and the downregulation of adrenergic receptors—a clinical entity recognized as sepsis-induced cardiomyopathy (SIC)( 21 ). The precipitous collapse in flow velocity and volume observed in our cohort reflects more than localized vasoplegia; it underscores the profound impact of SIC on regional organ perfusion. This tight coupling between SMA flow and cardiac performance carries significant clinical weight. Consequently, SMA Doppler monitoring serves as more than a tool for assessing intestinal perfusion; it acts as a sensitive bedside indicator for identifying cardiac pump failure, providing a physiological basis for optimizing inotropic support and refining resuscitation strategies. We acknowledge several limitations in the present study. First, as a single-center observational study with a relatively small sample size (n = 116), external validation in larger, multi-center cohorts is requisite to confirm the robustness of the optimal cutoff values for PSV and RI. Second, bedside Doppler ultrasonography is inherently operator-dependent, and the acquisition of high-quality SMA signals can be challenging in patients with severe abdominal distension or excessive bowel gas, potentially limiting its universal applicability. Finally, our study provides a cross-sectional comparison across discrete clinical stages; continuous hemodynamic monitoring of the SMA over time would provide a more granular understanding of the precise moment microcirculatory failure occurs. Conclusion In conclusion, bedside SMA Doppler ultrasonography effectively captures the critical transition from a compensatory hyperdynamic state to terminal mesenteric vasoplegia in patients with septic shock. The paradoxical decline of the SMA resistance index, coupled with diminished peak systolic velocity, serves as a powerful independent predictor of refractory septic shock. Integrating these dynamic vascular parameters into routine intensive care monitoring could facilitate the early recognition of vasoplegia, prompting timely and more personalized resuscitation strategies. Abbreviations APACHE II Acute Physiology and Chronic Health Evaluation II PSV Peak systolic velocity; RI,; PI,; BF, EDV End diastolic velocity RI Resistive index PI Pulsatility index TAMV Time-averaged mean velocity BF Blood flow SOFA Sequential Organ Failure Assessment Pv-aCO 2 Central venous-to-arterial carbon dioxide difference SIC sepsis-induced cardiomyopathy CRRT Continuous renal replacement therapy Declarations Acknowledgements This work was completed with thanks to the patients, families, and all staff who contributed to the care of patients. Author contributions Hao Pu and Shujun Zhou had the idea of the study and conceptualized the research aims; Hao Pu and Shujun Zhou designed the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Hao Pu and Wanru Li implemented the study and collected the data; Hao Pu, Tao Zeng, Xinyi Liu and Siwei Wang did the statistical analysis and wrote the first version of the paper; Hao Pu, Shujun Zhou, Tao Zeng, Xinyi Liu, Feng Ping and Siwei Wang contributed substantially to the acquisition of data. Hao Pu, Xinyi Liu and Tao Zeng revised the first draft. All the authors approved the final manuscript. Funding None. Data availability The datasets used and/or analysed during the present study are available from the corresponding author on reasonable request. Ethics approval and consent to participate The Third Affiliated Hospital of Soochow University Ethics Committee approved the study (No. 2023E065), and all patients were involved in the study based on the voluntary principle and had signed informed consent form. Informed consent was obtained from all patients. We would maximize the protection of the interests of patients and would not cause harm to any patients. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Author details 1 Department of Critical Care Medicine, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610041, China. 2 Department of Thoracic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610041, China 3 Department of Critical Care Medicine, The Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu Province, China. References Singer M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801–10. Klingensmith NJ, Coopersmith CM. The Gut as the Motor of Multiple Organ Dysfunction in Critical Illness. Crit Care Clin. 2016;32(2):203–12. Meng M, Klingensmith NJ, Coopersmith CM. New insights into the gut as the driver of critical illness and organ failure. Curr Opin Crit Care. 2017;23(2):143–8. Nacul FE, Bezerra MB, Gomes BC, Hohmann FB, Treml RE, Caldonazo T, et al. Current and emerging therapeutic options for refractory septic shock: A systematic review. World J Crit Care Med. 2025;14(4):111164. Weiss SL, Peters MJ, Oczkowski SJW, Belley-Cote E, Buysse C, Choong KLM, et al. Surviving Sepsis Campaign International Guidelines for the Management of Sepsis and Septic Shock in Children 2026. Pediatr Crit Care Med. 2026;27(4):379–434. Ince C. Hemodynamic coherence and the rationale for monitoring the microcirculation. Crit Care. 2015;19(Suppl 3):S8. Hariri G, Joffre J, Leblanc G, Bonsey M, Lavillegrand J-R, Urbina T, et al. Narrative review: clinical assessment of peripheral tissue perfusion in septic shock. Ann Intensive Care. 2019;9(1):37. Huber W, Zanner R, Schneider G, Schmid R, Lahmer T. Assessment of Regional Perfusion and Organ Function: Less and Non-invasive Techniques. Front Med (Lausanne). 2019;6:50. Soranno DE, Coopersmith CM, Brinkworth JF, Factora FNF, Muntean JH, Mythen MG, et al. A review of gut failure as a cause and consequence of critical illness. Crit Care. 2025;29(1):91. Pu H, Li W, Wang G, Zhou S. Effect of different shock conditions on mesenteric hemodynamics. Am J Med Sci. 2024;369(2):208–17. Zheng Q, Kang D, Chen Y, Huang B, Lin P. The significance of joint evaluation of gastrointestinal ultrasound results and renal artery resistance index for assessing intestinal-renal syndrome in sepsis patients: a retrospective study. Quant Imaging Med Surg. 2025;15(11):11488–98. Landry DW, Oliver JA. The pathogenesis of vasodilatory shock. N Engl J Med. 2001;345(8):588–95. Reilly PM, Wilkins KB, Fuh KC, Haglund U, Bulkley GB. The mesenteric hemodynamic response to circulatory shock: an overview. Shock. 2001;15(5):329–43. Leone M, Myatra SN, Dugar S, Wieruszewski PM, Russell L, Evans L et al. Clinical Criteria for the Definition of Refractory Septic Shock: A Joint Delphi Consensus from the Society of Critical Care Medicine (SCCM) and European Society of Intensive Care Medicine (ESICM). Crit Care Med. 2026. Balligand JL, Feron O, Dessy C. eNOS activation by physical forces: from short-term regulation of contraction to chronic remodeling of cardiovascular tissues. Physiol Rev. 2009;89(2):481–534. Matheson PJ, Wilson MA, Garrison RN. Regulation of intestinal blood flow. J Surg Res. 2000;93(1):182–96. Oldenburg WA, Lau LL, Rodenberg TJ, Edmonds HJ, Burger CD. Acute mesenteric ischemia: a clinical review. Arch Intern Med. 2004;164(10):1054–62. Beloncle F, Rousseau N, Hamel J-F, Donzeau A, Foucher A-L, Custaud M-A, et al. Determinants of Doppler-based renal resistive index in patients with septic shock: impact of hemodynamic parameters, acute kidney injury and predisposing factors. Ann Intensive Care. 2019;9(1):51. Fujii K, Nakayama I, Izawa J, Iida N, Seo Y, Yamamoto M, et al. Association between intrarenal venous flow from Doppler ultrasonography and acute kidney injury in patients with sepsis in critical care: a prospective, exploratory observational study. Crit Care. 2023;27(1):278. Sandek A, Swidsinski A, Schroedl W, Watson A, Valentova M, Herrmann R, et al. Intestinal blood flow in patients with chronic heart failure: a link with bacterial growth, gastrointestinal symptoms, and cachexia. J Am Coll Cardiol. 2014;64(11):1092–102. Hollenberg SM, Singer M. Pathophysiology of sepsis-induced cardiomyopathy. Nat Rev Cardiol. 2021;18(6):424–34. 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9619615","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":641646259,"identity":"7d392edb-6b40-47ff-b029-2a78a4f2ac1c","order_by":0,"name":"Shujun Zhou","email":"","orcid":"","institution":"The Third Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Shujun","middleName":"","lastName":"Zhou","suffix":""},{"id":641646271,"identity":"c7ec3a41-8e96-4518-bb66-873118a5e4e9","order_by":1,"name":"Xinyi Liu","email":"","orcid":"","institution":"Sichuan Cancer Hospital \u0026 Institute, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Xinyi","middleName":"","lastName":"Liu","suffix":""},{"id":641646279,"identity":"d2d201f0-6188-4dfc-8e33-3d36b38a8886","order_by":2,"name":"Tao Zeng","email":"","orcid":"","institution":"Sichuan Cancer Hospital \u0026 Institute, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Zeng","suffix":""},{"id":641646282,"identity":"739cb46a-c288-43a5-8efa-84fb1f176b98","order_by":3,"name":"Wanru Li","email":"","orcid":"","institution":"The Third Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Wanru","middleName":"","lastName":"Li","suffix":""},{"id":641646284,"identity":"086ca8d4-b999-4846-b12a-313e7c94a7fd","order_by":4,"name":"Feng Ping","email":"","orcid":"","institution":"Sichuan Cancer Hospital \u0026 Institute, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Feng","middleName":"","lastName":"Ping","suffix":""},{"id":641646293,"identity":"b1d336db-9e67-40a6-8fe2-dee5f3bfacf0","order_by":5,"name":"Siwei Wang","email":"","orcid":"","institution":"Sichuan Cancer Hospital \u0026 Institute, University of Electronic Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Siwei","middleName":"","lastName":"Wang","suffix":""},{"id":641646300,"identity":"71af1e88-fc3e-45c6-a4e6-c2398a0235a8","order_by":6,"name":"Hao Pu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzElEQVRIiWNgGAWjYFACHiAuYGCQYGA+cODDD6K1GIC0sCUenNlDmhYe48McbERoMJfIPfjhg8FheckZOR8OA/XL84sdwK/FckZesuQMg8OGsyVyNxwusGAwnDk7Ab8Wgxs5BtI8BocT5EBaZvAwJBjcJqzF+DdES86DwzxsxGkxA9siLZHDQJwWy543ZpYzDNINZ/Y8MwAGsgRhv5iz5xjf+FBhLS9xPPnxhw8/bOT5pQk5DM4SAKuUwK8cVQv/AcKqR8EoGAWjYGQCAPwuQ4JyKnQUAAAAAElFTkSuQmCC","orcid":"","institution":"Sichuan Cancer Hospital \u0026 Institute, University of Electronic Science and Technology of China","correspondingAuthor":true,"prefix":"","firstName":"Hao","middleName":"","lastName":"Pu","suffix":""}],"badges":[],"createdAt":"2026-05-05 14:08:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9619615/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9619615/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109444625,"identity":"bfb8082a-3155-4523-a801-247ff490b5c8","added_by":"auto","created_at":"2026-05-18 08:02:02","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":110328,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of SMA Doppler parameters among five study groups. Box-and-whisker plots illustrating (a) SMA peak systolic velocity, (b) end-diastolic velocity, (c) time-averaged mean velocity, (d) SMA resistive index, (e) SMA pulsatility index,and (f) SMA blood flow in healthy controls, sepsis, septic shock, refractory septic shock, and Successful-resuscitation septic shock groups. \u003cem\u003eP\u003c/em\u003e-values were derived from Kruskal–Wallis testing with post-hoc correction for multiple comparisons. *: \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.05; **: \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01; ***: \u003cem\u003ep \u003c/em\u003e\u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-9619615/v1/73ad13cbe81ca02d329f8053.png"},{"id":109444627,"identity":"986995dc-8ca9-4f2f-88c1-f8360c2ba51d","added_by":"auto","created_at":"2026-05-18 08:02:03","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":57125,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation heatmap between superior mesenteric artery (SMA) Doppler parameters and markers of clinical severity. The pearson correlation coefficients (r) are visualized by both circle size and color intensity. The color scale on the right indicates the strength and direction of the correlation: blue represents a negative correlation (r \u0026lt; 0), while red represents a positive correlation (r \u0026gt; 0). Asterisks denote statistical significance: * \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026lt; 0.01, and *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-9619615/v1/8e2d3acef4df75dca7b47bdf.png"},{"id":109444626,"identity":"6c10ea84-1a8f-44ea-8d6b-ef4b03175665","added_by":"auto","created_at":"2026-05-18 08:02:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":100727,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis of RI and PSV for predicting refractory septic shock.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-9619615/v1/39fec7507a430e03d0ec2195.png"},{"id":109799702,"identity":"4d3356b5-3d79-4403-8ca7-e7eaa1ca345e","added_by":"auto","created_at":"2026-05-22 15:33:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":609464,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9619615/v1/4e1d0aa5-3e14-43db-b3d5-12a9a29d2799.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Doppler blood flow parameters of the superior mesenteric artery in the progression from sepsis to refractory shock and its diagnostic value","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSepsis shock remains a predominant cause of mortality in intensive care units worldwide, characterized by a dysregulated host response to infection and subsequent life-threatening multi-organ dysfunction(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Within this pathophysiological cascade, the gastrointestinal (GI) tract is widely recognized as the \"motor\" of multiple organ dysfunction syndrome (MODS)(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Despite the optimization of early resuscitation bundles, a significant subset of patients inevitably progresses toward refractory septic shock\u0026mdash;a state defined by profound circulatory collapse, escalating vasopressor requirements, and an unacceptably high mortality rate(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA fundamental challenge in current clinical practice is \"hemodynamic incoherence,\" wherein stabilized macro-hemodynamic targets, such as mean arterial pressure (MAP), fail to reflect the persistent deterioration of regional tissue perfusion(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Conventional systemic markers, including blood lactate clearance and central venous oxygen saturation (ScvO\u003csub\u003e2\u003c/sub\u003e), represent global metabolic status and frequently lag behind the microvascular failure of specific organ beds(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). By the time these systemic indicators manifest as refractory shock, irreversible ischemic injury and the breakdown of the intestinal mucosal barrier may have already occurred(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Consequently, identifying a real-time, non-invasive biomarker that reflects the dynamic alterations in splanchnic Perfusion state represents a critical unmet clinical need.\u003c/p\u003e \u003cp\u003eBedside Doppler ultrasonography of the superior mesenteric artery (SMA) provides a reliable modality for the direct assessment of visceral perfusion. While abnormal SMA flow patterns, such as an increased resistive index (RI) and reduced flow velocities, have been associated with impaired mesenteric perfusion in critically ill patients, the sequential evolution of these parameters across the full clinical spectrum\u0026mdash;from initial sepsis to refractory septic shock\u0026mdash;remains inadequately characterized(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Specifically, we sought to elucidate whether the mesenteric vasculature undergoes a 'paradoxical' pathophysiological transition, evolving from an initial compensatory state of hyperdynamic vasoconstriction to a terminal stage of profound vasoplegia during refractory shock(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe hypothesized that alterations in the SMA Doppler blood flow parameters accurately reflect the onset of mesenteric Perfusion state and vascular tone loss, thereby serving as early predictors of refractory septic shock development. Consequently, this prospective study aimed to map the hemodynamic trajectory of the SMA across five distinct clinical stages\u0026mdash;healthy control, sepsis, septic shock, refractory shock, and successful resuscitation\u0026mdash;and to evaluate the diagnostic performance of SMA Doppler parameters in identifying patients with refractory septic shock.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and population\u003c/h2\u003e \u003cp\u003e This was a single-center, Retrospective study conducted in the Department of Critical Care Medicine at the Third Affiliated Hospital of Soochow University from January 2023 to January 2024. The study protocol was designed in accordance with the Declaration of Helsinki and received formal approval from the Institutional Review Board (Approval No. 2023E065). Written informed consent was obtained from all patients or their legally authorized representatives.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipant Selection and Group Definitions\u003c/h3\u003e\n\u003cp\u003eA total of 116 participants were consecutively enrolled and stratified into five groups based on international consensus criteria and clinical trajectories:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHealthy Control (n\u0026thinsp;=\u0026thinsp;22)\u003c/b\u003e: Patients admitted to the Intensive Care Unit (ICU) for non-septic conditions (e.g., postoperative monitoring or non-infectious trauma) who exhibited hemodynamic stability.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSepsis (n\u0026thinsp;=\u0026thinsp;29)\u003c/b\u003e: Defined according to the Sepsis-3 criteria as infection-induced organ dysfunction, characterized by an acute increase in the Sequential Organ Failure Assessment (SOFA) score of \u0026ge;\u0026thinsp;2 points(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSeptic Shock (n\u0026thinsp;=\u0026thinsp;22)\u003c/b\u003e: Defined as sepsis requiring vasopressors to maintain a mean arterial pressure (MAP) \u0026ge; 65mmHg and a serum lactate level\u0026thinsp;\u0026gt;\u0026thinsp;2 mmol/L despite adequate fluid resuscitation(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRefractory Septic Shock (n\u0026thinsp;=\u0026thinsp;23)\u003c/b\u003e: Defined as persistent hypotension and deteriorating tissue hypoperfusion (e.g., rising lactate) despite adequate fluid resuscitation, necessitating high-dose norepinephrine (\u0026ge;\u0026thinsp;0.5ug/kg/min)(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eSuccessful Resuscitation (n\u0026thinsp;=\u0026thinsp;20)\u003c/b\u003e: Patients who achieved achieving hemodynamic stability (MAP\u0026thinsp;\u0026ge;\u0026thinsp;65mmHg with minimal or no vasopressor support), metabolic restoration (lactate\u0026thinsp;\u0026le;\u0026thinsp;mmol/L or significant clearance), and evidence of multi-organ functional recovery after comprehensive treatment.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eExclusion Criteria\u003c/strong\u003e \u003cp\u003eAge\u0026thinsp;\u0026lt;\u0026thinsp;18 years; pregnancy; primary gastrointestinal disease (e.g., bowel obstruction, mesenteric ischemia); severe intra-abdominal hypertension (IAH); or poor acoustic windows for SMA visualization.\u003c/p\u003e \u003c/p\u003e\n\u003ch3\u003eSMA Doppler ultrasonography measurement\u003c/h3\u003e\n\u003cp\u003eBedside point-of-care ultrasound (POCUS) was performed by two experienced intensivists using a [KONICA SONIMAGE-HS1] ultrasound system with a 1\u0026ndash;5 MHz convex transducer. With patients in a neutral supine position, the superior mesenteric artery (SMA) was visualized in the longitudinal sagittal plane, 1\u0026ndash;2 cm distal to its aortic origin. The Doppler sample volume was centered within the lumen, maintaining an insonation angle\u0026thinsp;\u0026lt;\u0026thinsp;60\u0026deg;with automated angle correction. Peak systolic velocity (PSV) and end-diastolic velocity (EDV) were averaged over at least three consecutive stable cardiac cycles. The resistive index (RI) was calculated as (PSV - EDV) / PSV. Superior mesenteric blood flow (BF) was derived using the formula: BF (mL/min) = Cross sectional area (CSA) \u0026times;time-averaged mean velocity (TAMV) \u0026times;60.\u003c/p\u003e\n\u003ch3\u003eClinical data collection\u003c/h3\u003e\n\u003cp\u003eBaseline characteristics, including age, sex, and body mass index (BMI), were documented upon enrollment. Disease severity was assessed within the first 6 hours of inclusion using the Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. Concomitantly with the superior mesenteric artery (SMA) ultrasound, real-time macro-hemodynamic parameters and systemic perfusion markers\u0026mdash;comprising heart rate (HR), mean arterial pressure (MAP), norepinephrine (NE) dosage, arterial blood lactate (Lac), and venous-to-arterial carbon dioxide tension difference (Pv-aCO2)\u0026mdash;were recorded to ensure hemodynamic coherence. Additionally, a comprehensive biochemical panel was analyzed to evaluate inflammatory response and organ function, including white blood cell (WBC) count, C-reactive protein (CRP), procalcitonin (PCT), total bilirubin, serum creatinine (Scr), and cardiac troponin I (cTnI).\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe normality of data distribution was assessed visually. Normally distributed continuous variables were presented as mean\u0026plusmn;standard deviation, whereas nonnormally distributed data were reported as medians with interquartile ranges (IQRs, 25th-75th percentiles). Categorical variables were expressed as counts (n) and percentages (%). Continuous variables across the five clinical groups were compared using the Kruskal-Wallis \u003cem\u003eH\u003c/em\u003e test, followed by \u003cem\u003epost-hoc\u003c/em\u003e pairwise comparisons with Bonferroni correction. Correlations between SMA Doppler parameters (PSV, TAMV, RI, PI, BF) and clinical severity indices (e.g., SOFA score, arterial lactate, and norepinephrine dosage) were examined using the pearson correlation coefficient and visualized via a correlation matrix. To identify independent risk factors for refractory septic shock, SMA Doppler parameters were first screened using univariate Logistic regression. Variables with \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were subsequently entered into a multivariable Logistic regression model. Results are presented as odds ratios (OR) with 95% confidence intervals (CI). Receiver operating characteristic (ROC) curves were constructed based on the predicted probabilities from the multivariable model. The area under the curve (AUC), sensitivity, and specificity were calculated to evaluate the discriminative ability of the combined SMA parameter model for refractory shock. All statistical analyses were performed using SPSS software (version 26.0; IBM Corp, Armonk, NY). A two-sided \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 116 patients were included (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). No significant differences were observed among the five groups regarding age, sex, or BMI (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Illness severity scores showed a progressive increase from the control to the refractory septic shock group (APACHE II: 20.0 to 30.0; SOFA: 2.0 to 12.0; both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Laboratory findings mirrored this clinical gradient, with significant elevations in inflammatory markers (WBC and PCT) and organ dysfunction indicators (creatinine and cardiac troponin I) as the disease severity intensified (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Notably, perfusion markers such as serum lactate and Pv-aCO\u003csub\u003e2\u003c/sub\u003e peaked in the refractory septic shock group (6.05mmol/L and 10.0 mmHg, respectively). While MAP was maintained across groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.175), the norepinephrine requirement increased significantly with shock severity (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared with the refractory group, patients in the successful resuscitation group exhibited a marked restoration of metabolic parameters and a reduction in vasopressor demand.\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\u003eBaseline characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;29)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeptic shock\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;22)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eRefractory septic shock\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;23)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSuccessful resuscitation\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;20)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\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\u003e71.00(52.00\u0026ndash;78.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76.00(67.00\u0026ndash;84.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.00(65.000\u0026ndash;82.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75.00(63.00\u0026ndash;81.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e74.00(64.00\u0026ndash;82.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.328\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale Sex(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12(54.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(51.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12(63.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13(52.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.00(50.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.157\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.49(20.76\u0026ndash;25.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.14(19.37\u0026ndash;24.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.88(19.38\u0026ndash;25.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.38(19.11\u0026ndash;25.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.38(19.29\u0026ndash;25.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.851\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAPACHE II\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.00(15.00\u0026ndash;26.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.00(18.00\u0026ndash;27.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.00(23.00\u0026ndash;33.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.00(27.00\u0026ndash;34.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30.00(26.00\u0026ndash;33.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSOFA score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.00(1.00\u0026ndash;3.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.00(4.00\u0026ndash;7.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.00(6.00\u0026ndash;10.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.00(10.00\u0026ndash;15.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.00(7.00\u0026ndash;11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWBC (\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.84(8.60\u0026ndash;13.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.24(7.59\u0026ndash;16.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.68(14.75-28.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18.93(15.44-30.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e18.49(15.10\u0026ndash;30.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e111.00(99.00-122.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e101.00(82.00-113.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e102.00(91.00-115.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100.00(74.00-120.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e101.00(82.00\u0026ndash;11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlbumin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32.00(29.00-35.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33.35(27.70\u0026ndash;36.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.90(29.25\u0026ndash;34.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30.10(26.20\u0026ndash;34.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32.60(28.67\u0026ndash;35.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.245\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTB (ummol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15.45(11.70\u0026ndash;26.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.30(10.65\u0026ndash;27.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.10(12.30-30.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e24.10(15.37\u0026ndash;37.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e22.65(12.30-16.32.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCr (ummol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e72.00(52.00-113.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e86.00(55.00-128.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149.00(107.00-206.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e156.00(120.00-238.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e153.00(114.50\u0026ndash;209.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP (mg/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55.00(19.00-109.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117.00(69.00-185.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121.85(51.00-163.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e152.00(105.00-208.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e179.60(123.15-233.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePCT (ng/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30(0.25\u0026ndash;0.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.50(0.29\u0026ndash;9.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.54(2.69\u0026ndash;55.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21.92(6.10-87.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.54(4.20\u0026ndash;66.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecTnI (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.03(0.01\u0026ndash;0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04(0.15\u0026ndash;0.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.46(0.09\u0026ndash;0.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.94(0.42\u0026ndash;2.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.67(0.18\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.05(1.00-1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.20(1.20\u0026ndash;2.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.25(2.70\u0026ndash;7.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.05(4.45-11.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.8(1.2\u0026ndash;2.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePv-aCO\u003csub\u003e2\u003c/sub\u003e(mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5.00(4.00\u0026ndash;6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.00(4.00\u0026ndash;6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.00(6.00\u0026ndash;9.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.00(7.00\u0026ndash;12.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.00(4.00\u0026ndash;6.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMAP (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88.00(80.00\u0026ndash;98.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87.00(79.00\u0026ndash;94.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82.00(68.00\u0026ndash;96.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80.00(63.00\u0026ndash;93.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e82.00(67.00\u0026ndash;93.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.175\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHR (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86.00(70.00\u0026ndash;95.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96.00(83.00-114.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e106.00(92.00-118.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e110.00(88.00-127.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e106.00(83.00-123.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNE (ug/kg/min)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e00.00(0.00\u0026ndash;0.00)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.25(0.10\u0026ndash;0.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.50(0.30\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.75(0.50\u0026ndash;1.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.1(0.00-0.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRRT use (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(4.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3(10.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(45.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18(75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8(40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e28 d mortality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(10.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(24.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10(40.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15(65.22)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eData are presented as median (interquartile range) or n (%). APACHE II, Acute Physiology and Chronic Health Evaluation II; SOFA, Sequential Organ Failure Assessment; BMI, body mass index; WBC, white blood cell; TB, total bilirubin; Cr, Creatinine; CRP, C-reactive protein; PCT, procalcitonin; cTnI, cardiac troponin I; Pv-aCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003ecentral venous-to-arterial carbon dioxide difference; MAP, mean arterial pressure; HR, heart rate; NE, norepinephrine; CRRT, continuous renal replacement therapy.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eComparisons of SMA Doppler parameters among groups\u003c/h3\u003e\n\u003cp\u003eThe hemodynamic profiles of the SMA varied significantly across the clinical severity spectrum (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cb\u003eFigure. 1\u003c/b\u003e; all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In the sepsis group, a hyperdynamic mesenteric circulation was evident, characterized by significantly higher flow velocities and blood flow compared to controls (PSV: 188.20 cm/s vs. 115.40cm/s; BF: 450.24 mL/min vs. 368.16 mL/min; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As the disease severity progressed to septic shock and refractory septic shock, a profound decline in mesenteric perfusion was observed. PSV, TAMV, and BF reached their lowest levels in the refractory shock group (PSV: 69.00 [63.22-88.00] cm/s; BF: 264.00 [201.55-318.54] mL/min). Crucially, resistance indices (RI, PI), which were highest in the sepsis phase, exhibited a paradoxical and significant reduction as shock intensified, reflecting a transition toward mesenteric vasoplegia (RI: 0.72 in refractory shock vs. 0.88 in sepsis; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Following successful resuscitation, all Doppler parameters showed a restorative trend, with RI and PI returning to levels comparable to the control group (0.84 vs. 0.83).\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\u003eComparison of superior mesenteric artery Doppler parameters among five groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePSV\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSepsis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSeptic Shock\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e \u003cp\u003eRefractory septic shock\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSuccessful resuscitation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e-Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115.40(98.90-136.90)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e188.20(173.70-210.55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e111.70(100.84-128.63)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e69.00(63.22-88.00)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e127.80(105.32-143.55)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19.90(16.37\u0026ndash;21.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.40(15.75\u0026ndash;25.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e27.00(22.7-30.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e19.65(16.03\u0026ndash;25.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e20.30(18.25\u0026ndash;23.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83(0.82\u0026ndash;0.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.88(0.86\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.77(0.73\u0026ndash;0.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72(0.63\u0026ndash;0.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.84(0.82\u0026ndash;0.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.39(2.09\u0026ndash;2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.97(2.52\u0026ndash;3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.77(1.60\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.50(1.11\u0026ndash;1.79)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.20(2.07\u0026ndash;2.64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.65(15.42\u0026ndash;19.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.60(19.75\u0026ndash;29.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e20.15(17.32\u0026ndash;22.80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.55(11.10-17.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e19.20(16.05\u0026ndash;22.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e368.16(306.60-473.13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e450.24(321.12-588.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e375.69(303.39-443.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e264.00(201.55-318.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e382.35(320.44-436.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"8\" nameend=\"c8\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSV, peak systolic velocity; TAMV, time-averaged mean velocity; BF, blood flow; RI, resistive index; PI, pulsatility index.\u003c/b\u003e\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 \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eCorrelations between SMA Doppler indices and clinical severity markers\u003c/h2\u003e \u003cp\u003eCorrelations between SMA Doppler parameters and clinical markers are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Hemodynamic parameters, particularly PSV, RI, and PI, demonstrated significant inverse correlations with markers of clinical severity. Specifically, both RI and PI were negatively correlated with SOFA score (r = -0.64 and \u0026minus;\u0026thinsp;0.59, respectively; both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and lactate levels (r = -0.53 and \u0026minus;\u0026thinsp;0.52, respectively; both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, higher norepinephrine requirements were associated with lower RI (r = -0.59, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and PI (r = -0.51, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, PSV showed a strong negative correlation with SOFA score (r = -0.61, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and creatinine (r = -0.40, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). In contrast, EDV and TAMV displayed negligible correlations with most clinical severity markers. Interestingly, MAP exhibited a weak but significant positive correlation with PI (r\u0026thinsp;=\u0026thinsp;0.33, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01) and RI (r\u0026thinsp;=\u0026thinsp;0.24, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Overall, the heatmap analysis (\u003cb\u003eFigure. 2\u003c/b\u003e) confirmed that a decrease in SMA resistance indices (RI and PI) was closely aligned with increasing organ dysfunction and intensified norepinephrine support.\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\u003eCorrelations between SMA Doppler parameters and markers of clinical severity.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLactate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePv-aCO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMAP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNorepinephrine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSOFA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003er\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.043\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.098\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.095\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePSV, peak systolic velocity; EDV, end diastolic velocity; TAMV, time-averaged mean velocity; RI, resistive index; PI, pulsatility index; BF, blood flow; Pv-aCO\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e, \u003cb\u003evenous-to-arterial carbon dioxide difference; MAP, mean arterial pressure; SOFA, Sequential Organ Failure Assessment; Cr, creatinine.\u003c/b\u003e\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 \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eIndependent predictors of refractory septic shock\u003c/h2\u003e \u003cp\u003eIn univariable logistic regression, PSV, TAMV, RI, PI, and BF were all significantly associated with refractory septic shock, whereas EDV was not. After adjustment in the multivariable model, only PSV and RI remained independently associated with refractory septic shock, with PSV showing a protective association and RI retaining a significant inverse association with the outcome (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariate and multivariate logistic regression analysis for refractory septic shock\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c6\" namest=\"c2\"\u003e \u003cp\u003eUnivariate\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c12\" namest=\"c8\"\u003e \u003cp\u003eMulvariate\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eΒ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eΒ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eS.E\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eZ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c12\"\u003e \u003cp\u003eOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-4.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.91 (0.87\u0026thinsp;~\u0026thinsp;0.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.033\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.71 (0.52\u0026thinsp;~\u0026thinsp;0.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEDV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.415\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.92\u0026thinsp;~\u0026thinsp;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTAMV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.82 (0.73\u0026thinsp;~\u0026thinsp;0.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRI*10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.06 (0.02\u0026thinsp;~\u0026thinsp;0.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-2.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-2.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.041\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003e0.14 (0.02\u0026thinsp;~\u0026thinsp;0.78)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-2.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.14 (0.02\u0026thinsp;~\u0026thinsp;0.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-3.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.99 (0.98\u0026thinsp;~\u0026thinsp;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cb\u003ePSV, peak systolic velocity; EDV, end diastolic velocity; TAMV, time-averaged mean velocity; RI, resistive index; PI, pulsatility index; BF, blood flow; OR, odds ratio; CI, confidence interval.; OR: Odds Ratio, CI: Confidence Interval.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDiagnostic performance of SMA Blood flow parameters for refractory septic shock\u003c/h2\u003e \u003cp\u003eROC curve analysis demonstrated excellent discriminative performance of SMA Doppler parameters for identifying refractory septic shock. PSV showed the highest AUC of 0.922 (95% CI 0.864\u0026ndash;0.979; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with an optimal cutoff of 82.30 cm/s providing 81.2% sensitivity and 92.9% specificity. RI also exhibited strong performance (AUC 0.874, 95% CI 0.791\u0026ndash;0.958; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a cutoff of 0.745 yielding 83.3% sensitivity and 78.6% specificity. The combined multivariable model achieved superior discrimination, with an AUC of 0.966 (95% CI 0.946\u0026ndash;0.989, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with a sensitivity of 87.5% and a specificity of 95.3% (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, \u003cb\u003eFigure. 3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of the areas under the ROC curves for refractory septic shock\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVaribles\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%CI\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCut-off Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSensitivity\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSpecificity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePSV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.922\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.864\u0026ndash;0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.812\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.929\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.874\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.791\u0026ndash;0.958\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.745\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.833\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.786\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.966\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.946\u0026ndash;0.989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.952\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cb\u003ePSV, peak systolic velocity; RI, resistive index.\u003c/b\u003e\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study systematically delineates the hemodynamic trajectory of the SMA across the clinical spectrum of sepsis. The principal finding is that SMA Doppler parameters exhibit a distinct, non-linear evolutionary pattern as the disease progresses. Specifically, while early sepsis is characterized by a hyperdynamic mesenteric circulation, the progression to refractory septic shock is marked by a profound decline in both flow velocities (PSV, TAMV) and resistance indices (RI, PI). Furthermore, we demonstrated that the combination of SMA PSV and RI offers exceptional discriminative capacity (AUC 0.957) for predicting refractory septic shock, providing a powerful, non-invasive tool for early bedside risk stratification.\u003c/p\u003e \u003cp\u003eA defining finding of this study is the paradoxical reduction in SMA resistance indices (RI decreasing from 0.88 to 0.72; PI from 2.97 to 1.50) as patients transitioned into refractory shock. While early sepsis is characterized by catecholamine-mediated compensatory vasoconstriction to prioritize vital organ perfusion, our data identify a critical \"tipping point\" where this mechanism fails. In the most critically ill patients\u0026mdash;despite escalating doses of norepinephrine\u0026mdash;RI and PI reached their lowest values. This suggests that a low-resistance state, rather than a high one, serves as the definitive hallmark of terminal vascular failure.\u003c/p\u003e \u003cp\u003eThe significant negative correlation between SMA resistance indices and clinical severity markers (lactate, SOFA scores, and creatinine) underscores the pathophysiological shift toward terminal vasoplegia. This state is primarily driven by an overwhelming inflammatory cascade. Beyond the excessive production of nitric oxide (NO) and pathological activation of ATP-sensitive potassium (K-ATP) channels, a complex interplay of endogenous vasodilators\u0026mdash;including acetylcholine, histamine, leukotrienes, and glucagon\u0026mdash;contributes to the progressive loss of vascular tone(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Furthermore, the secretion of various gastrointestinal hormones and thromboxane analogues acts in concert with catecholamine receptor downregulation to induce a refractory paralysis of the vascular smooth muscle(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Collectively, this multifaceted biochemical milieu results in the profound mesenteric vasoplegia observed in our refractory shock cohort. Consequently, a declining SMA-RI in refractory shock does not signify improved flow; instead, it represents a catastrophic loss of vascular tone. This corrects the clinical misconception that higher RI always correlates with severity, identifying the collapse of mesenteric resistance as a primary indicator of global circulatory collapse.\u003c/p\u003e \u003cp\u003eFurthermore, we observed a paradoxical elevation in SMA-RI and PI among patients who were successfully resuscitated. This increase suggests a restoration of mesenteric vascular tone, marking the transition from a paralytic vasodilatory state back to a regulated hemodynamic environment. This recovery of resistance in successful resuscitation group, contrasted with its collapse in the refractory cohort, underscores that SMA-RI and PI are not merely static markers of resistance, but dynamic indicators of vasomotor reactivity. Consequently, these indices emerge as potential bedside tools for evaluating resuscitation responsiveness, offering a unique window into the functional recovery of the splanchnic circulation that global macro-hemodynamic targets may overlook.\u003c/p\u003e \u003cp\u003eThe observed negative correlation between SMA-RI and serum creatinine presents an intriguing contrast to the well-established pathophysiology of the renal resistive index (RRI). In the renal bed, a higher RRI typically correlates with worsening renal function and acute kidney injury (AKI), as the kidney is highly sensitive to intra-organ pressure and venous congestion(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). A recent study that emphasize a synergistic increase in organ resistance indices\u0026mdash;such as the positive correlation between RRI and renal dysfunction in 'Intestinal-Renal Syndrome(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). However, our findings suggest that the mesenteric circulation follows a different trajectory during the transition to refractory shock. While the kidney may maintain a high-resistance state during injury, the mesenteric bed enters a \"paralytic\" low-resistance state. This splanchnic-renal heterogeneity underscores that regional organ systems do not respond uniformly to septic insult. The SMA\u0026rsquo;s transition to a low-resistance state may precede or parallel the peak of systemic organ dysfunction, providing a unique, stage-specific marker of terminal circulatory failure that global metrics or renal indices might overlook.\u003c/p\u003e \u003cp\u003eIn the present study, SMA flow parameters (PSV, TAMV, and BF) exhibited a compensatory increase during the early phase of sepsis, followed by a progressive and severe decline as the disease evolved toward septic shock and, ultimately, refractory shock. Previous physiological research has established that regional mesenteric blood flow maintains a robust linear relationship with cardiac output (CO), with flow velocity indices being tightly coupled with the cardiac index (CI)(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). As sepsis progresses, myocardial contractility is frequently compromised by an overwhelming surge of inflammatory mediators, mitochondrial dysfunction, and the downregulation of adrenergic receptors\u0026mdash;a clinical entity recognized as sepsis-induced cardiomyopathy (SIC)(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe precipitous collapse in flow velocity and volume observed in our cohort reflects more than localized vasoplegia; it underscores the profound impact of SIC on regional organ perfusion. This tight coupling between SMA flow and cardiac performance carries significant clinical weight. Consequently, SMA Doppler monitoring serves as more than a tool for assessing intestinal perfusion; it acts as a sensitive bedside indicator for identifying cardiac pump failure, providing a physiological basis for optimizing inotropic support and refining resuscitation strategies.\u003c/p\u003e \u003cp\u003eWe acknowledge several limitations in the present study. First, as a single-center observational study with a relatively small sample size (n\u0026thinsp;=\u0026thinsp;116), external validation in larger, multi-center cohorts is requisite to confirm the robustness of the optimal cutoff values for PSV and RI. Second, bedside Doppler ultrasonography is inherently operator-dependent, and the acquisition of high-quality SMA signals can be challenging in patients with severe abdominal distension or excessive bowel gas, potentially limiting its universal applicability. Finally, our study provides a cross-sectional comparison across discrete clinical stages; continuous hemodynamic monitoring of the SMA over time would provide a more granular understanding of the precise moment microcirculatory failure occurs.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, bedside SMA Doppler ultrasonography effectively captures the critical transition from a compensatory hyperdynamic state to terminal mesenteric vasoplegia in patients with septic shock. The paradoxical decline of the SMA resistance index, coupled with diminished peak systolic velocity, serves as a powerful independent predictor of refractory septic shock. Integrating these dynamic vascular parameters into routine intensive care monitoring could facilitate the early recognition of vasoplegia, prompting timely and more personalized resuscitation strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAPACHE II\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Physiology and Chronic Health Evaluation II\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePSV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeak systolic velocity; RI,; PI,; BF,\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEDV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEnd diastolic velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eResistive index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePulsatility index\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTAMV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTime-averaged mean velocity\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eBF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBlood flow\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSOFA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSequential Organ Failure Assessment\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePv-aCO\u003csub\u003e2\u003c/sub\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCentral venous-to-arterial carbon dioxide difference\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSIC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esepsis-induced cardiomyopathy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eContinuous renal replacement therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was completed with thanks to the patients, families, and all staff who contributed to the care of patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHao Pu and Shujun Zhou had the idea of the study and conceptualized the research aims; Hao Pu and Shujun Zhou designed the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Hao Pu and Wanru Li implemented the study and collected the data; Hao Pu, Tao Zeng, Xinyi Liu and Siwei Wang did the statistical analysis and wrote the first version of the paper; Hao Pu, Shujun Zhou, Tao Zeng, Xinyi Liu, Feng Ping and Siwei Wang contributed substantially to the acquisition of data. Hao Pu, Xinyi Liu and Tao Zeng revised the first draft. All the authors approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNone.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and/or analysed during the present study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Third Affiliated Hospital of Soochow University Ethics Committee approved the study (No. 2023E065), and all patients were involved in the study based on the voluntary principle and had signed informed consent form. Informed consent was obtained from all patients. We would maximize the protection of the interests of patients and would not cause harm to any patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eDepartment of Critical Care Medicine, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital \u0026amp; Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610041, China.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eDepartment of Thoracic Oncology, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital \u0026amp; Institute, Sichuan Cancer Center, School of Medicine, University of Electronic Science and Technology of China, Chengdu, 610041, China\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDepartment of Critical Care Medicine, The Third Affiliated Hospital of Soochow University, Changzhou 213003, Jiangsu Province, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSinger M, Deutschman CS, Seymour CW, Shankar-Hari M, Annane D, Bauer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKlingensmith NJ, Coopersmith CM. The Gut as the Motor of Multiple Organ Dysfunction in Critical Illness. Crit Care Clin. 2016;32(2):203\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeng M, Klingensmith NJ, Coopersmith CM. New insights into the gut as the driver of critical illness and organ failure. Curr Opin Crit Care. 2017;23(2):143\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNacul FE, Bezerra MB, Gomes BC, Hohmann FB, Treml RE, Caldonazo T, et al. Current and emerging therapeutic options for refractory septic shock: A systematic review. World J Crit Care Med. 2025;14(4):111164.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeiss SL, Peters MJ, Oczkowski SJW, Belley-Cote E, Buysse C, Choong KLM, et al. Surviving Sepsis Campaign International Guidelines for the Management of Sepsis and Septic Shock in Children 2026. Pediatr Crit Care Med. 2026;27(4):379\u0026ndash;434.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eInce C. Hemodynamic coherence and the rationale for monitoring the microcirculation. Crit Care. 2015;19(Suppl 3):S8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHariri G, Joffre J, Leblanc G, Bonsey M, Lavillegrand J-R, Urbina T, et al. Narrative review: clinical assessment of peripheral tissue perfusion in septic shock. Ann Intensive Care. 2019;9(1):37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuber W, Zanner R, Schneider G, Schmid R, Lahmer T. Assessment of Regional Perfusion and Organ Function: Less and Non-invasive Techniques. Front Med (Lausanne). 2019;6:50.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSoranno DE, Coopersmith CM, Brinkworth JF, Factora FNF, Muntean JH, Mythen MG, et al. A review of gut failure as a cause and consequence of critical illness. Crit Care. 2025;29(1):91.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePu H, Li W, Wang G, Zhou S. Effect of different shock conditions on mesenteric hemodynamics. Am J Med Sci. 2024;369(2):208\u0026ndash;17.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng Q, Kang D, Chen Y, Huang B, Lin P. The significance of joint evaluation of gastrointestinal ultrasound results and renal artery resistance index for assessing intestinal-renal syndrome in sepsis patients: a retrospective study. Quant Imaging Med Surg. 2025;15(11):11488\u0026ndash;98.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLandry DW, Oliver JA. The pathogenesis of vasodilatory shock. N Engl J Med. 2001;345(8):588\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eReilly PM, Wilkins KB, Fuh KC, Haglund U, Bulkley GB. The mesenteric hemodynamic response to circulatory shock: an overview. Shock. 2001;15(5):329\u0026ndash;43.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeone M, Myatra SN, Dugar S, Wieruszewski PM, Russell L, Evans L et al. Clinical Criteria for the Definition of Refractory Septic Shock: A Joint Delphi Consensus from the Society of Critical Care Medicine (SCCM) and European Society of Intensive Care Medicine (ESICM). Crit Care Med. 2026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBalligand JL, Feron O, Dessy C. eNOS activation by physical forces: from short-term regulation of contraction to chronic remodeling of cardiovascular tissues. Physiol Rev. 2009;89(2):481\u0026ndash;534.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMatheson PJ, Wilson MA, Garrison RN. Regulation of intestinal blood flow. J Surg Res. 2000;93(1):182\u0026ndash;96.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOldenburg WA, Lau LL, Rodenberg TJ, Edmonds HJ, Burger CD. Acute mesenteric ischemia: a clinical review. Arch Intern Med. 2004;164(10):1054\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeloncle F, Rousseau N, Hamel J-F, Donzeau A, Foucher A-L, Custaud M-A, et al. Determinants of Doppler-based renal resistive index in patients with septic shock: impact of hemodynamic parameters, acute kidney injury and predisposing factors. Ann Intensive Care. 2019;9(1):51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFujii K, Nakayama I, Izawa J, Iida N, Seo Y, Yamamoto M, et al. Association between intrarenal venous flow from Doppler ultrasonography and acute kidney injury in patients with sepsis in critical care: a prospective, exploratory observational study. Crit Care. 2023;27(1):278.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSandek A, Swidsinski A, Schroedl W, Watson A, Valentova M, Herrmann R, et al. Intestinal blood flow in patients with chronic heart failure: a link with bacterial growth, gastrointestinal symptoms, and cachexia. J Am Coll Cardiol. 2014;64(11):1092\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHollenberg SM, Singer M. Pathophysiology of sepsis-induced cardiomyopathy. Nat Rev Cardiol. 2021;18(6):424\u0026ndash;34.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Sepsis, Septic shock, Refractory shock, Superior mesenteric artery, Doppler ultrasonography","lastPublishedDoi":"10.21203/rs.3.rs-9619615/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9619615/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eEarly identification of refractory septic shock and mesenteric hypoperfusion remains a significant clinical challenge due to the loss of hemodynamic coherence. This study aimed to characterize the dynamic evolution of superior mesenteric artery (SMA) Doppler parameters across the sepsis-severity spectrum and evaluate their performance in predicting refractory septic shock and mesenteric vasoplegia.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis study included five groups: healthy controls, sepsis, septic shock, refractory septic shock, and resuscitation-responsive septic shock. SMA Doppler parameters were measured, including peak systolic velocity (PSV), end-diastolic velocity (EDV), time-averaged mean velocity (TAMV), resistive index (RI), and pulsatility index (PI). Between-group comparisons, receiver operating characteristic (ROC) analysis, correlation analysis, and logistic regression were performed.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 116 participants were analyzed. The SMA hemodynamic profile exhibited a distinct biphasic evolutionary trajectory across the sepsis spectrum. During the initial sepsis stage, SMA Doppler indices exhibited a compensatory surge compared to controls, characterized by higher flow velocities (PSV: 188.20 vs. 115.40 cm/s) and increased vascular resistance (RI: 0.88 vs. 0.83). However, as illness severity intensified from septic shock to refractory septic shock, a paradoxical and progressive decline was observed: the resistance indices significantly decreased (RI: 0.88 to 0.72; PI: 2.97 to 1.50; both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while flow velocity and flow parameters followed a similar downtrend (PSV: 188.20 cm/s to 69.00 cm/s; TAMV: 24.60 cm/s to 13.55 cm/s;BF:450.24ml/min to 264.00ml/min ;both \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Correlation analysis revealed that SMA hemodynamic parameters (RI, PI, PSV) were significantly negatively correlated with SOFA scores, serum lactate and Creatinine levels (all \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). For the identification of refractory septic shock, PSV demonstrated high discriminative capacity (AUC: 0.922, cutoff: 82.30 cm/s), outperforming RI (AUC: 0.874, cutoff: 0.745). Notably, the combined multivariable model of PSV and RI achieved superior diagnostic accuracy, with an AUC of 0.966 (95% CI: 0.946\u0026ndash;0.989), a sensitivity of 87.5%, and a specificity of 95.3%.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eBedside SMA Doppler parameters effectively capture the transition from compensatory hyperdynamics to terminal hypodynamics and mesenteric vasoplegia. A low SMA RI and PSV, serves as a hallmark of refractory septic shock.\u003c/p\u003e","manuscriptTitle":"The Doppler blood flow parameters of the superior mesenteric artery in the progression from sepsis to refractory shock and its diagnostic value","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-18 08:01:54","doi":"10.21203/rs.3.rs-9619615/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":"d40ca95f-bde3-48d2-8203-25cb171d8ae1","owner":[],"postedDate":"May 18th, 2026","published":true,"recentEditorialEvents":[{"type":"decision","content":"Rejected","date":"2026-05-20T08:17:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-19T12:03:54+00:00","index":37,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-11T08:11:12+00:00","index":34,"fulltext":""},{"type":"reviewerAgreed","content":"335374467304057137968924461689891972713","date":"2026-05-11T04:01:05+00:00","index":32,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-08T19:13:15+00:00","index":24,"fulltext":""},{"type":"reviewerAgreed","content":"128487556800631596943767097773328079993","date":"2026-05-08T12:00:28+00:00","index":22,"fulltext":""},{"type":"reviewerAgreed","content":"113962206745549995902031614721015451201","date":"2026-05-07T21:48:27+00:00","index":10,"fulltext":""},{"type":"reviewersInvited","content":"18","date":"2026-05-07T21:46:32+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-07T00:24:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-05-07T00:24:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Critical Care","date":"2026-05-05T13:53:36+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T08:25:48+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-18 08:01:54","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9619615","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9619615","identity":"rs-9619615","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}